Download Towards a paradigm shift in chronic low back pain?

Towards a paradigm shift in
chronic low back pain?
Identification of patient profiles
to guide treatment
Miranda van Hooff
Towards a paradigm shift in
chronic low back pain?
Identification of patient profiles
to guide treatment
Miranda L. van Hooff
2
Colofon
Towards a paradigm shift in chronic low back pain?
Identification of patient profiles to guide treatment
Beoordelingscommissie:
Prof. dr. R.H.M.A. Bartels
Dr. J. van Limbeek
Prof. dr. J. Nijs
Prof. dr. B.J. van Royen
Prof. dr. M.W. van Tulder
This thesis was prepared within the Department of Orthopaedics and the Department
Research of Sint Maartenskliniek, Nijmegen, The Netherlands
The publication of this thesis was financially supported by Sint Maartenskliniek, Nijmegen,
The Netherlands, the Nederlandse Orthopaedische Vereniging and the Dutch Spine Society
Cover design and layout by: burorub grafisch ontwerp, Nijmegen
Printed by: Koninklijke Van der Most BV, Heerde
ISBN: 978 90 9030218 8 (paperback version)
ISBN: 978 90 826698 0 0 (digital version)
© 2017 Miranda L. van Hooff, Deventer, The Netherlands ([email protected])
Except Chapter 07 © 2015 Wolters Kluwer Health Inc; Chapter 08 © 2016 Elsevier Inc.
Open Access: Chapters 02-06 and 09 are distributed under the terms of Creative Commons
Attribution Licence, which permits any use, distribution, and reproduction in any medium
provided the original author(s) and the source are credited.
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system of
any nature, or transmitted in any form or by any means, electronic, mechanical, photocopying,
recording or otherwise without the prior written permission of the holder of the copyright.
3
VRIJE UNIVERSITEIT
Towards a paradigm shift in chronic low back pain?
Identification of patient profiles to guide treatment
ACADEMISCH PROEFSCHRIFT
ter verkrijging van de graad Doctor aan
de Vrije Universiteit Amsterdam,
op gezag van de rector magnificus
prof.dr. V. Subramaniam,
in het openbaar te verdedigen
ten overstaan van de promotiecommissie
van de Faculteit der Geneeskunde
op vrijdag 21 april 2017 om 11.45 uur
in de aula van de universiteit,
De Boelelaan 1105
door
Miranda Lisette van Hooff
geboren te Diepenveen
4
promotoren:
prof.dr. M. de Kleuver
prof.dr. R.W.J.G. Ostelo
copromotor:
dr. M. Spruit
5
Table of contents
Chapter 01
General introduction
1.1 Chronic low back pain
1.2 Interventions for chronic low back pain
1.3 Outcomes of interventions for chronic low back pain
1.4 Aims and Outline of this thesis
9
9
11
12
16
Theme A: Introduction of a combined physical and psychological programme
25
Chapter 02
Daily functioning and self-management in patients with chronic low
back pain after an intensive cognitive behavioural programme for
pain management. European Spine Journal 2010; 19(9):1517-26
27
Chapter 03
A short, intensive cognitive behavioral program for pain
management improves long term daily functioning, quality of life
and reduces healthcare use in patients with Chronic Low Back Pain.
European Spine Journal 2012; 21(7): 1257-64
43
Chapter 04
Predictive factors for successful clinical outcome one year after an
intensive pain management programme for chronic low back pain.
European Spine Journal 2014; 23(1):102-12
57
Theme B: Outcomes assessment
75
Chapter 05 Evidence and practice of spine registries – A systematic review and
recommendations for future design of registries. Acta Orthopaedica
2015; 86(5): 534-44
77
Chapter 06
A proposed set of metrics for standardized outcome reporting in the
management of low back pain. Acta Orthopaedica 2015; 86(5): 523-33
111
6.5 Appendix to Chapter 5 and 6. Guest editorial: Spinal disorders,
quality based healthcare and spinal registers. Acta Orthopaedica
2015; 86(5): 521-32
130
Chapter 07
Validation of the Dutch Oswestry Disability Index version 2.1a:
validation of a Dutch language version. Spine 2015; 40(2): E83-90
135
Chapter 08
Determination of the Oswestry Disability Index equivalent to a
‘satisfactory symptom state’ in patients undergoing surgery for
degenerative disorders of the lumbar spine – A Spine Tango registrybased study. Spine J. 2016;16(10):1221-1230.
151
6
Theme C: Prediction of outcomes
167
Chapter 09
The Nijmegen decision tool for chronic low back pain. Development
of a clinical decision tool for secondary or tertiary back care
specialists. PLoS One 2014; 19(8): e104226
169
Chapter 10
Patient-reported factors partly predicted referral to spinal surgery in
a consecutive cohort of 4,987 chronic low back pain patients.
[Under review]
193
Chapter 11
Prognostic patient-reported profiles for referral to secondary or
tertiary spine specialists – The Nijmegen Decision Tool for Chronic
Low Back Pain. [Submitted]
215
Chapter 12
Summary & General discussion
247
Key points thesis
271
Dutch summary | Nederlandse samenvatting
Acknowledgements | Dankwoord
Curriculum Vitae
Publications
Theses Sint Maartenskliniek
277
285
291
295
303
7
Chapter 01
General introduction
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02
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08
09
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12
8
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Content
1.1
1.2
1.3
1.4
Chronic low back pain
Interventions for chronic low back pain
Outcomes of interventions for chronic low back pain
Aims and Outline of this thesis
General introduction
1.1 Chronic low back pain
Prevalence and incidence
Low back pain is a highly prevalent health condition globally and leads to individual suffering
and a considerable burden for society. Recent research shows that, worldwide, low back pain
is responsible for more years lived with disability than any other health condition [1,2]. Many
people with low back pain have ongoing and recurrent complaints [3,4], and at a societal
level there are substantial costs related to low back pain as a consequence of healthcare
expenditure, disability insurance, and productivity loss caused by work absenteeism and work
loss [5,6].
The mean global one-year point prevalence of low back pain is estimated to be 38.0% (±19.4)
[7]. In the Netherlands, approximately 44% of the adult population experiences at least one
episode of low back pain, and one in five (21%) report persistent back pain resulting in chronic
low back pain (CLBP)[8,9], defined as low back pain lasting for more than three months [10]
with substantial limitations in functional activities after one year [8,11]. Approximately 14%
of the Dutch adult CLBP population is incapable of work [9]. Due to ageing and population
growth, it is expected that the total number of CLBP-patients will increase.
In the Netherlands in 2007 the total cost of back pain to Dutch society was estimated to be €3.5
billion, which equates to 0.6% of the gross national product. This amount includes indirect
costs such as productivity loss and costs incurred by society due to morbidity and mortality,
which represent the majority of these total costs [5]. In 2007, more than 500,000 patients with
back pain were referred to secondary or tertiary spine care and more than 30,000 underwent
a surgical intervention for which the related costs were estimated to be 23 million euro.
However, these numbers are likely to be underestimates, because research shows that despite
initiatives to try to discourage the use of expensive diagnostic imaging in early stages, there
has been no change in the amount of ineffective referrals to secondary care [5,12].
Symptom or diagnosis?
The CLBP population is heterogeneous and the term CLBP lacks diagnostic clarity. CLBP is an
umbrella term, covering two main categories of lumbar spine disorders: degenerative and nondegenerative [13]. In clinical practice, an accurate patho-anatomical diagnosis of the cause of
CLBP based on biomedical indicators can be made in only 10% of the patients (e.g. isthmic
spondylolisthesis, lumbar spinal stenosis, lumbar disc herniation, scoliosis, spinal fracture,
axial spondylarthropathy, neoplasm, Morbus Scheuermann) [14]. Hence, in the majority of
patients, low back pain is a symptom referring to the location rather than reflecting a specific
diagnosis [15,16]. Because in the vast majority of patients (90%) the aetiology is unknown [14],
these patients are diagnosed as having degenerative low back pain and are often labelled as
‘non-specific’. However, the term ‘non-specific’ is thought to be meaningless [17] and therefore
the term ‘degenerative lumbar spine disorder’ seems more appropriate (Figure 1.1).
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General introduction
Figure 1.1 Representation of the lumbar spine (A-B) and of a degenerative lumbar spine disorder
(i.e. chronic low back pain; C)
(A)
(B)(C)
Schematic representation of the lumbar spine (A); ‘normal’ lumbar spine (MRI; B); ‘degenerative’ lumbar spine (MRI; C)
Aetiology and prognosis
The traditional model of clinical practice incorporates diagnosis based on aetiology, prognosis,
and treatment of the condition or disease [18]. Aetiology refers to the study of causality of
diseases [19]: the relationship between cause and effect. To describe aetiology in CLBP, in
Western medicine the biomedical model, derived from Louis Pasteur's germ theory of disease,
has been the dominant force. Following this model, it is assumed that CLBP is fully accounted for
by deviations from the norm of measurable biological (i.e. somatic or patho-anatomic) factors.
However, in the vast majority of CLBP cases no patho-anatomical diagnosis can be made. The
model is also exclusive, since any symptoms that cannot be explained in biological terms are
excluded from consideration, and thereby it leaves no room for the social, psychological, and
behavioural dimensions. Yet, these aspects are important in chronic diseases and have led to
a paradigm shift from purely biological to the bio-psychosocial model, which was introduced
by Engel in 1977. Its scope is determined by the historic function of the physician to establish
whether the person soliciting help is "sick" or "well" — and if sick, why sick and in which ways
sick — and then to develop a rational programme to treat the illness and restore and maintain
health [20].
Studies on the prognosis of CLBP show frequent persistence of complaints [21] whilst an
inverse relationship for the prognosis of a satisfactory outcome with symptom duration
has been shown [22]. It is estimated that one to two years after the initial onset, 60-80% of
patients consulting healthcare professionals still have pain and have not fully recovered
[23,24]. Amongst patients with back complaints for more than three years, the chances
of recovery are even smaller [22]. The literature demonstrates that persistence of CLBP is
associated with pain, disability and psychological status at onset [22,25-27]. Many authors
have emphasised bio-psychosocial influences on the development and persistence of CLBP
[21,22,28,29]. However, the aetiology of CLBP remains largely unknown and the prognosis
detrimental. Owing to this lack of diagnostic clarity, targeted interventions with successful
outcomes remain a challenge.
General introduction
1.2 Interventions for chronic low back pain
The failure to identify underlying causes is one of the reasons why a plethora of invasive and
non-invasive interventions exist for the same symptom [30]. Therefore, practice variation
exists amongst healthcare providers, and considerable uncertainty exists amongst major
stakeholders as to which interventions are (cost) effective. For example, the rates of lumbar
spine surgery vary largely within and between countries [31-34]. Despite decades of research
and improved quality of clinical trials, the treatments offered to patients produce inconsistent
results [35-41] and rarely show more than a small to moderate overall benefit [6,35,40,42-44].
Table 1.1 shows an overview of recently published systematic reviews and showing effect sizes
for the main surgical and non-surgical interventions underlining these facts.
Surgical interventions
Various surgical interventions exist for CLBP. In the context of this thesis the focus is on
most commonly performed surgeries for CLBP. These are spinal fusion surgery (two or more
vertebrae are permanently ‘fused’ together [spondylodesis]) with or without decompression
(relief of a compressed spinal nerve root), discectomy (removal of a part of the intervertebral
disc), and disc replacement (replacement of the intervertebral disc by an artificial spinal
implant). Figure 1.2 shows an example of a commonly performed procedure for spinal fusion
surgery. Fusion surgery with or without decompression could be beneficial for a selected
group of patients with CLBP, i.e. those with a specific diagnosis with an underlying ‘biological
cause’ and who previously failed non-operative treatment (e.g. lumbar spinal stenosis, isthmic
spondylolisthesis) [40,50,51]. However, for fusion surgery with or without decompression the
effect sizes are not large and the overall quality of evidence is low. Current scientific evidence
does not support superiority of surgery for CLBP compared to high-intensity conservative
interventions to reduce pain intensity and restore functional ability [52]. Therefore, it is
debatable whether any surgical, invasive intervention such as disc replacement or fusion
surgery should be performed in patients without a clear diagnosis of the cause of their
CLBP [53]. A nationwide survey amongst Dutch spine surgeons showed that no professional
consensus could be identified in decision making on the treatment strategy for chronic low
back pain, even in the group ‘with presumed biological causes’ [54]. To improve outcomes it
has been recommended to identify subgroups of patients for whom spinal fusion surgery is an
effective treatment [53-55]. Indeed, in a recently released draft version of the Dutch national
guideline for instrumented lumbar spine surgery [56], this is regarded as an important
recommendation to improve surgical outcomes, which is the subject of the third part of this
thesis (Theme C; Chapter 9-11).
Non-surgical interventions
Various non-surgical interventions for CLBP in secondary care exist (e.g. invasive pain
treatment [injections], functional restoration programmes, back schools, cognitive
behavioural therapy, multidisciplinary bio-psychosocial pain management programme). In
the context of this thesis the focus is on multidisciplinary bio-psychosocial pain management
programmes. These multidisciplinary programmes may have benefits comparable to surgery
for back pain caused by degenerative spine disorder, as demonstrated in a recent 11-year
follow-up study of surgical trials [41]. A recent Cochrane review of 42 randomised controlled
trials (RCTs) including 6,858 patients with CLBP showed that the effects of multidisciplinary
bio-psychosocial programmes were of modest magnitude compared to usual care (moderate
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General introduction
Figure 1.2 An example of lumbar spine surgery; decompression and posterior lumbar interbody fusion
(PLIF): a female patient, 63 years of age, with degenerative spondylolisthesis L4-L5 who underwent
lumbar spine surgery; decompression and fusion (PLIF procedure).
(A)
(B)(C)
(A) Preoperative MRI: degenerative spondylolisthesis L4-L5 with severe spinal stenosis; (B) Pre-operative X-ray lateral view; (C) Post-operative
X-ray lateral and anterior-posterior view: spondylolithetic slippage reduction, decompression and fusion with pedicle screws and PLIF cages.
quality evidence) and physical treatments (low quality evidence) in reducing pain and
disability in people with CLBP. For work outcomes, multidisciplinary programmes seem to
be more effective than physical treatment but not more effective than usual care [44]. Very
recently, the cost-effectiveness of a multidisciplinary bio-psychosocial pain management
programme including minimal interventional procedures (e.g. radiofrequency denervation)
for patients with CLBP was compared to the multidisciplinary programme alone (i.e. MinT
study [57]). The preliminary 12-month results of the MinT study show that adding minimal
interventional procedures is not more cost-effective [58]. At the Sint Maartenskliniek a new
combined physical and psychological (CPP) pain management programme was introduced
in October 2006 for patients with CLBP (Figure 1.3). The two-week intensive programme is
provided outside the clinic in a hotel setting, and three main components can be distinguished:
physical training, cognitive behavioural training including graded activity and graded
exposure, and education. To monitor the individual progress and to evaluate the programme
on a group level over time, participants are systematically followed for one year on patientrelevant indicators (i.e. routine outcome monitoring). More detailed information on the CPP
programme is provided through the Internet [59]. A description of the treatment, including
who might benefit, has been reported in several published articles [60-62] that belong to
the first theme of this thesis (Theme A; Chapters 2-4). These results gave us the motivation
to further study and to determine which patients from the larger population of people with
CLBP should be referred to these multidisciplinary bio-psychosocial programmes, which is
in line with the recommendations in international guidelines [55,63,64] and in the previously
mentioned Cochrane review [44]. This is the subject of the third part of this thesis (Theme C;
Chapter 9-11).
1.3 Outcomes of interventions for chronic low back pain
An important mechanism to improve interventions and with that the delivery of healthcare,
is to learn from practices proven to have the best outcomes in order to improve the overall
‘quality of care’ (i.e. benchmarking). The desired outcomes of interventions are the result of
a high-quality (infra) structure and process [65], reflecting the end result of care [66], and
are thought to matter most to patients and reflect all aspects of care [67,68]. The outcomes
General introduction
Figure 1.3 Non-surgical intervention; CPP programme as provided by RealHealth NL
of (spine) interventions could be regarded as a proxy for quality of care. Routine outcome
measurement by means of well-designed outcome registries is challenging, but has
well-documented benefits. For example, asking providers to systematically measure and
report their outcomes has been shown to improve performance of the care delivered [67].
Furthermore, understanding and comparing outcomes facilitates continuous learning and
improvement of the provider’s own strategies through benchmarking and learning from best
practices. This type of continuous improvement and informed decision-making could be an
important driving force for improving healthcare delivery by refocusing the system on ‘value’
(i.e. patient-related outcomes relative to costs [67,68]), especially in the area of low back
pain where the current global burden of the condition, the practice variation, and growth in
associated healthcare costs are unsustainable. The ability to define real-world ‘effectiveness’
(i.e. outcomes) of healthcare delivery is of utmost importance and gives the opportunity to
assess the value of delivered healthcare, which is gaining in importance particularly within
the realm of spine care [69,70].
Measuring outcomes
Human functioning and disability are central aspects of human life, and are key concerns
in health and medicine. In numerous conditions, including CLBP, functioning or functional
ability is not part of the disease process but is both a target and an outcome of health
interventions. Therefore, the main health-related outcome domain used in the empirical
and methodological studies of this thesis is functional ability. In CLBP, functional disability
(i.e. disability) is characterised by pain of variable duration and by various activity limitations
of daily life and participation restrictions. The health-related outcome domains that are
relevant for patients with CLBP and clinicians include pain, functional ability, health-related
quality of life [71-74], complications (including number of deaths) [73,74], repeat surgery (in
spine surgery), work status, and analgesic use [74]. To evaluate these outcome domains over
time and to achieve patient-centred care, patient-related outcomes such as patient-reported
outcome measures (PROMs) are used. PROMs are used alongside the clinician-based measures
(e.g. radiologic imaging, physical function tests) and aim to provide an objective measure
of a subjective construct: that is, from the individual patient’s perspective and concerns in
relationship to their health, healthcare and quality of life [75-77]. Well-designed PROMs have
undergone rigorous testing and may be better validated, and as a result PROMs have greater
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General introduction
reproducibility than the so-called objective clinician-based measures [78,79]. PROMs provide
a powerful, quantifiable and standardised research tool against which the effectiveness
of healthcare interventions can be judged [77,80]. They facilitate comparison of results of
different studies and also facilitate subsequent meta-analysis [79,81]. To evaluate individual
patient care, PROMs can be used to support shared decision-making, communication and
appropriate evaluation of individual treatment success [80].
To evaluate outcomes of interventions, generic or condition-specific PROMs can be used.
Generic measures contain multiple concepts of health relevant to both patients and the
general population, such as the MOS short-form 36 (SF-36) and the utility measure EuroQol 5
Dimensions (EQ5D) for CLBP. These measures support comparison of health between different
patient groups, and between patient groups and the general population. Condition-specific
measures are developed to evaluate the well-being of patients with a particular condition or
disease. For example, in CLBP, functional ability is measured with condition-specific measures
such as the Oswestry Disability Index and the Roland and Morris Disability Questionnaire [82].
However, limitations to the use of PROMs and the challenge to obtain sufficient follow-up
responses are acknowledged. Some of these may be related to lack of data or lack of knowledge,
and need further research. Such challenges include the myriad of (overlapping) PROMs used
in evaluating interventions for CLBP [71], challenges of validation and understanding the
association with long-term outcomes, and with that the predictive capacities of PROMs [83].
In this thesis, part B is dedicated to these challenges (Theme B; Chapter 5-7).
Patient-related outcome measures (both PROMs and clinician-based) need to be
methodologically sound, that is they need to be based on good quality criteria (i.e. clinimetric
properties). These criteria include: content validity, internal consistency, criterion validity,
construct validity, reproducibility (agreement and reliability), responsiveness, floor and
ceiling effects, and interpretability [84]. Score interpretation is a major challenge to the
incorporation of PROMs into all settings; a challenge which is further confounded by growing
evidence that patients and clinicians differ in their judgment of important change [85,86]. A
patient’s interpretation of beneficial change or acceptable symptom state will be informed
by his or her own definition of a ‘good outcome’. The tradition of reporting the statistical
significance of score change does not necessarily translate into clinically meaningful change
by the patient, the healthcare professional or other stakeholder. In fact, treatment success
can be conceptualised in two ways: 1) relevant change or improvement, and 2) reaching an
acceptable state. With the first concept, the emphasis is on whether or not an individual has
relatively improved after an intervention, often expressed as reaching a minimal clinically
important change, whereas with the second, the emphasis is on whether or not the achieved
outcome is acceptable from the patient’s perspective [87], often expressed as reaching an
absolute value. In this thesis, a chapter is dedicated to these concepts (Theme B; Chapter 8).
Collecting outcomes - Outcome registries
In systematic reviews, results of RCTs are pooled, analysed, and interpreted. In evidence-based
medicine, RCTs are considered the gold standard for assessing the efficacy of interventions.
However, some barriers for RCTs in spinal disorders are acknowledged, specifically when
surgical procedures are involved. Examples are surgeon preferences, patients’ reluctance
to randomisation, difficulties in blinding, high cost, the need for long-term follow-up and
consequently the often high losses to follow-up, as well as the problem with cross-over [88].
General introduction
Well-designed observational cohort studies, reflecting daily clinical practice, can reliably
produce results similar to those of RCTs [89-91]. Such studies could be performed by means
of an outcome registry. An outcome registry is an organised system that uses observational
study methods to collect uniform data (clinical and other) to evaluate specified outcomes
for a population defined by a particular disease, condition, or exposure, and that serves a
predetermined scientific, clinical, or policy purpose(s) [92]. In spine care, various national
registries exist, such as the recently started Dutch Spine Surgery Registry in the Netherlands.
Examples of large spine registries are the Swedish Spine Register (SweSpine) [93], the Spine
Tango Spine Surgery Registry of Eurospine (the Spine Society of Europe) [94,95], and the
multicentre adult spinal deformity database in the United States [96]. Recently published
studies showed that the results of spine registries seem to be in concordance with those of
the published RCTs [91,97-99]. When well designed, registry data can be used to reliably
identify optimal treatments, to understand variations in treatment, and to describe care
patterns, including identifying appropriateness of care and disparities in the delivery of care.
Furthermore, when introducing new health interventions in healthcare, outcome registries
are needed to continuously monitor the quality of the healthcare delivered to improve health
outcomes [100,101] and, ultimately, to increase the value of the care delivered (i.e. outcome per
unit cost [67]) [67,68,70,101,102]. In this thesis the impact and methodology of spine outcome
registries are studied (Theme B; Chapter 5).
Predicting outcomes
It is assumed that with more precise targeting of interventions, patient outcomes improve
and so too the efficiency of the healthcare. Classifying the heterogeneous CLBP-population
into more homogeneous subgroups, based on their profiles, would support patient triage
and guide treatment, as much as any classification system in healthcare aims to do. To
distinguish patient profiles, several outcome-based classifications for decision making exist
and some aim to identify profiles based on patho-anatomy and biomedical indicators [103].
Some classifications are based on the prognostic course of back pain, e.g. those aimed at the
risk of chronicity [104], whilst others aim to identify patients likely to respond favourably
to particular interventions [105]. All of them have been developed and studied as a guide
for non-surgical interventions applied in primary care [106]. Although these attempts have
been made, and some of them seem to be successful [104], the optimal classification system
still remains elusive and large numbers of patients consult secondary or tertiary spine care
medical specialists to help them solve their CLBP-problem. Different patient profiles might
be identified which are likely to benefit from different recommended interventions [39,
44,50,55,63,106]. Ideally, these profiles are based on aetiological and prognostic evidence and
on evidence of indicators modifying the effects of interventions. As a challenge, the major
recommendation for future research has been to focus on classification systems, which guide
the right patient to appropriate surgical or nonsurgical interventions. The rationale is that this
has the greatest potential for improving outcomes [106]. A research programme of the spine
unit in Sint Maartenskliniek has focussed on the development of such a classification system,
and the third theme of this thesis is dedicated to this challenge (Theme C; Chapter 9-11).
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General introduction
1.4 Aims and Outline
The ultimate aim of this thesis is to contribute to the body of knowledge on outcomes of
interventions for CLBP and to identify outcome-based subgroups characterised by different
patient profiles within the heterogeneous CLBP population.
Outline of this thesis
The thesis consists of three related themes (A-C) with a total of twelve chapters, including
the General introduction and the Summary and General discussion. In Chapter 1, the General
introduction, an overview of CLBP as the topic of this thesis is given and this sets the scene
for the studies described in themes A-C, including (systematic) literature reviews, empirical,
and methodological studies. The thesis follows the chronological framework of the research
programme, which is the basis for this thesis. First, a combined physical and psychological
(CPP) programme was evaluated and a subgroup of patients benefitting from this programme
was identified (Theme A). Subsequently, methodological considerations were studied
regarding outcomes and outcomes assessment (Theme B). Finally, through a literature search
and a formal consensus procedure, indicators contributing to treatment outcome were
identified. These indicators were used to develop a classification system for patient triage to
surgical and non-surgical interventions (Theme C).
THEME A: Introduction of a combined physical and psychological programme (Chapter 2-4)
This theme includes empirical studies in which, amongst others, continuous outcome
monitoring is performed after introduction of a new intervention for patients with CLBP —the
intensive combined physical and psychological (CPP) programme as provided by RealHealth
NL.
The overall research question of this part is twofold:
1. Does the novel CPP programme for CLBP improve patient outcomes and reduce healthcare
consumption?
2. Is it possible to identify a subgroup of patients that benefits most from the novel CPP
programme so that selection criteria can be optimised?
The specific study aims:
• To evaluate the outcomes of a new intensive CPP pain management programme for CLBP
patients and whether this is reflected in the use of healthcare services (Chapter 2).
• To evaluate the stability of the two-year follow-up results of a short, intensive cognitive
behavioural pain management programme. The emphasis is on evaluating daily
functioning, the use of healthcare services, and the use of pain medication two years after
the intervention (Chapter 3).
• To determine the factors which predict a successful 1-year outcome from this new
intervention with the goal of refining the selection criteria (Chapter 4).
THEME B: Outcomes assessment (Chapter 5-8)
This theme includes a literature study with a qualitative survey, and empirical and
methodological studies to clarify the ambiguity of and recommendations to standardise
outcomes assessment in secondary or tertiary level spine care.
General introduction
The overall research question of this part is threefold:
1. What is the current value and methodology of spine outcome registries in clinical practice?
2. Which patient-related outcome measures should be used for outcomes assessment for
degenerative lumbar spine disorders?
3. Which criterion can be used to define a successful outcome of interventions for patients
with degenerative lumbar spine disorders?
The specific study aims:
• To evaluate the available evidence for the effects of introducing and using spine registries
on patient-related outcomes, and to provide a set of methodological recommendations to
improve spine registries (Chapter 5).
• To propose a set of patient-related outcomes for use in daily spine care and for research
purposes (Chapter 6).
• To translate and adapt a patient-reported outcome measure in the functional outcome
domain, the Oswestry Disability Index (ODI; version 2.1a), into the Dutch language and to
investigate the validity and internal consistency of the translation (Chapter 7).
• To estimate the score on the ODI version 2.1a corresponding to a ‘patient acceptable
symptom state’ (PASS) in patients undergoing surgery for degenerative disorders of the
lumbar spine (Chapter 8).
THEME C: Prediction of outcomes (Chapter 9-11)
This theme includes a literature study and empirical studies in which the development and
validation of a new triage tool is studied for secondary or tertiary spine care specialists.
The overall research question of this theme:
1. Is it possible to develop a triage tool for CLBP, which enables valid and reliable identification
of patient profiles that supports triage of the patients to a spine surgeon or to non-surgical
specialists?
The specific study aims:
• To develop a decision tool for secondary or tertiary spine care specialists to decide which
patients with CLBP should be seen by a spine surgeon or by non-surgical medical specialists
(Chapter 9).
• To provide preliminary insight into the factors considered by CLBP-experts when deciding
whether or not to refer a patient to spinal surgery (Chapter 10).
• To identify patient profiles which are associated with and predictive for treatment
‘response’ or ‘non-response’ when referred to either a surgical intervention or a nonsurgical intervention (Chapter 11).
In the Summary & General discussion, Chapter 12, the results of the studies performed and
described in the previous chapters are discussed and their implications for generalisability of
the study results, for research, and for clinical practice are considered. In Key points thesis an
overview of this thesis is shown by summarising per the themes ‘What is already known on
this topic’ and ‘What this thesis adds’.
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Degenerative spinal stenosis
Zaina (2016) [49]
(neck, thoracic, low back,
or pelvic)
Chronic spinal pain
CLBP
0.09
Progression
1.93
Patient satisfaction at 2 yr
prgm. vs Physical treatment
Multidisc biopsychosocial
prgm. vs Usual care
Disability
0.25
0.46
1.04
Return to work
Pain
-0.23
Disability
-0.21
Return to work
Pain
1.87
Disability
Multidisc biopsychosocial
-0.68
Pain
-0.51
-4.43
prgm. vs Phsyical treatment
Improved ODI at 2 yr
-6.16
4.27
improved ODI at 2 yr
Improved ODI at 1 yr
6.22
Improved Back pain at 2 yr
-1.57
4.69
Reoperation at 2 yr
Improved ODI at 2 yr
4.41
0.44
Good result at 1.5 - 2 yr
(surgeon-rated)
Poor outcome at 1.5 - 2 yr
(patient-reported)
Failure at 2 yrs
0.76
0.28
Unchanged / worse at 2 yr
(patient-reported)
0.26
2.43
0.09
Effect size
(SMD)
Not back to work at 2 yr
Bad result at 10 yr
Repeat surgery after 4 yr
Outcome
Multidisc biopsychosocial
non-operative care
Surgery vs Usual
Disc replacement vs Fusion
Surgery vs Conservative
Fusion vs Decompression
Decompression &
Cognitive excercises
Fusion vs
Fusion vs Conservative
Conservative (PT)
Decompression vs
Comparison
0.07 - 0.43
0.09 - 0.83
n.s. 0.73 - 1.47
-0.40 - -0.06
-0.37 - -0.04
1.39 - 2.53
-1.19 - -0.16
-1.04 - 0.01
-7.91 - -0.90
n.s. -15.02 - 2.67
1.36 - 2.76
1.85 - 6.68
0.18 - 10.26
n.s. -4.65 - 1.51
0.00 - 2.07
0.51 - 42.83
1.09 - 17.76
0.13 - 1.48
0.25 - 2.25
0.15 - 0.53
0.10 - 0.64
0.09 - 67.57
0.01 - 0.89
95% CI
- small effect sizes
Favours multidisc. prgm.
Outcome: long term (≥ 1 yr)
- moderate quality evidence
- heterogeniety
- small effect sizes
Favours in both reviews: multidisc. prgm.
Outcome: long term (≥ 1 yr)
- low quality evidence
Favours surgery (decompression & fusion)
No firm conclusions drawn
- not clinically relevant
Favours disc replacement
Favours surgery
- effect sizes mostly n.s. or imprecise
- small effect sizes
Favours decompression & fusion
- not clinically relevant
Favours surgery
- low quality evidence
- heterogeniety
- small effect sizes
Favours surgery
Remark
CLBP, chronic low back pain; SMD, standardised mean difference; CI, confidence interval; PT, physical therapy; multidisc., multidisciplinary; prgm., programme; yr, year; ODI, Oswestry Disability Index
O'Keefe (2016) [48]
Kamper (2015) [44]
CLBP
CLBP with degenerative disc
Jacobs (2012) [47]
Non-surgical intervention
Degenerative spinal stenosis
Degenerative spinal stenosis
Degenerative disc
Lumbar spondylosis
Diagnosis
Kovacs (2011) [46]
Gibson (2005) [45]
Surgical intervention
Author (year)
18
General introduction
Table 1.1 Overview of effect sized for the surgical main surgical and non-surgical interventions
01
General introduction
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23
01
24
01
25
THEME A:
Introduction of a combined physical and
psychological programme
26
01
27
Chapter 02
Daily functioning and
self-management in patients with
chronic low back pain
after an intensive cognitive
behavioural programme
for pain management
van Hooff ML
van der Merwe JD
O’Dowd J
Pavlov PW
Spruit M
de Kleuver M
van Limbeek J
Published in: Eur Spine J. 2010;19(9):1517-26
28
Abstract
Purpose: Chronic low back pain (CLBP) is associated with persistent or recurrent disability,
which results in high costs for society. Cognitive behavioral treatments produce clinically
relevant benefits for patients with CLBP. Nevertheless, no clear evidence for the most
appropriate intervention is yet available. The purpose of this study is to evaluate the midterm effects in a cohort of patients with CLBP participating in an intensive pain management
programme.
Methods: The programme provided by RealHealth-Netherlands is based on cognitive
behavioral principles and executed in collaboration with orthopedic surgeons. Main outcome
parameters were daily functioning (Roland and Morris Disability Questionnaire and Oswestry
Disability Questionnaire), self-efficacy (Pain Self-Efficacy Questionnaire) and quality of life
(Short Form 36 Physical Component Score). All parameters were measured at baseline, last
day of residential programme and at 1 and 12 months follow up. Repeated measures analysis
was applied to examine changes over time. Clinical relevance was examined using minimal
clinical important differences (MCID) estimates for main outcomes. To compare results with
literature effect sizes (Cohens’ d) and Standardized Morbidity Ratios (SMR) were determined.
Results: 107 patients with CLBP participated in this programme. Mean scores on outcome
measures showed a similar pattern: improvement after residential programme and
maintenance of results over time. Effect sizes were 0.9 for functioning, 0.8 for self-efficacy
and 1.3 for physical functioning related quality of life. Clinical relevancy: 79% reached MCID
on functioning, 53% on self-efficacy, and 80% on quality of life. Study results on functioning
were found to be 36% better and 2% worse when related to previous research on, respectively,
rehabilitation programmes and spinal surgery for similar conditions (SMRs 136% and 98%,
respectively).
Conclusions: The participants of this evidence-based programme learned to manage CLBP,
improved in daily functioning and quality of life. The study results are meaningful and
comparable with results for spinal surgery and even better than results from less intensive
rehabilitation programmes.
Daily functioning after a pain management programme
29
Introduction
Chronic low back pain (CLBP) is a major health and economic problem in western industrialized
countries and it is associated with persistent or recurrent disability, resulting in high costs for
society [1-3]. In the Netherlands in 2003, the 1 year prevalence in the general population was
estimated to be 44%, and caused 24.4% of all sick leave in the employed population [4].
Annually, 22,000 new orthopedic patients visit the orthopedic surgery department at the Sint
Maartenskliniek Nijmegen, in The Netherlands. Around 27% (6,000) are patients with low
back pain complaints. Ten percent have an indication for surgery and another 10% for invasive
pain treatment (epidural block, nerve root block, or spinal cord stimulation). Therefore,
approximately 80% (4,500) of the CLBP sufferers do not need invasive treatment.
In literature there is no clear evidence that primary spinal fusion in patients with CLBP was
any more beneficial than intensive rehabilitation [5,6]. Fairbank et al. [5] came this conclusion
after they performed the MRC spine stabilization trial in which 349 patients were randomized
to either a surgical stabilization (spinal fusion) or an intensive outpatient rehabilitation group
(approximately 75h of exercises, supported by cognitive behavioral elements for 3 weeks).
The conclusions have been sustained by Mirza and Deyo [7] , who conducted a systematic
literature review of four randomized trials comparing lumbar fusion surgery to non-operative
care for treatment in CLBP.
Several non-surgical interventions are available for patients with CLBP [1,2,8,9]. The guidelines
of the National Institute for Health and Clinical Excellence (NICE) [10] recommend cognitive
behavioral therapy, exercise therapy, brief educational interventions, and multidisciplinary
(bio-psycho-social) treatment. Recently the American Pain Society [11] published an
evidence-based clinical practice guideline strongly recommending intensive interdisciplinary
rehabilitation with a cognitive behavioral emphasis for patients with non-radicular, low back
pain. Although such treatments can be effective, it is not yet known which type of patients
benefits most from them [2,9,12].
In The Netherlands, Smeets et al. [9,13] recently performed a multicenter, randomized clinical
trial among 172 patients with non-specific CLBP to determine the effectiveness of three often
used approaches in non-surgical treatment. These outpatient treatments were based upon
different theoretical models in CLBP: the active physical model, the cognitive behavioral
model, and a combination of both; they were delivered three times a week during 10 weeks.
He then compared these therapeutic modalities to a group of patients on the waiting list. Sixmonth and 1-year post-treatment results showed that all three active treatments were more
effective than no treatment, but no treatment group was more clinically relevant than the
other two [9]. The authors concluded that these results could, at least partially, be ascribed
to the fact that exposure to the cognitive behavioral treatment components was only 78h,
and not the 100h originally recommended in a Cochrane review by Guzman et al. [8]. In the
Cochrane review, the authors concluded that intensive multidisciplinary, bio-psycho-social
rehabilitation, improves CLBP and physical functioning whereas interventions of less than
100h do not yield an additional effect compared to non-multidisciplinary treatment or usual
care.
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Daily functioning after a pain management programme
The intensive pain management programme provided by RealHealth NL is based upon
cognitive behavioral principles, using a multidisciplinary bio-psycho-social approach, and is
of a 100h duration. The programme follows the NICE guidelines [10] as well as the American
Pain Society recommendations [11]. It is indicated for patients with CLBP for whom surgical or
anaesthesiological pain intervention is not an option.
The aim of this article is to evaluate the 1-year follow-up results of a programme based on
the cognitive behavioral approach in patients with CLBP. We conducted a prospective cohort
study and compared the results to outcomes of published research on interventions for CLBP.
Materials and Methods
Study design and Setting
This is a prospective cohort study with a repeated measures structure to ensure a sufficient
degree of internal control. Assessments were made pre-treatment, immediately posttreatment, and to assess whether the effect was sustained, 1 and 12 months after the
treatment period. The results of this programme are compared to the outcomes of published
research of Fairbank et al. [5] and Smeets et al. [9], on interventions for similar conditions. The
pain management programme is part of the Sint Maartenskliniek Nijmegen, but is provided in
a hotel facility outside the clinic.
Patients
Patients entered into the programme consecutively, after a multisciplinary team of RealHealth
(consisting of a psychologist, a physiotherapist and an occupational therapist) screened the
patients. These patients had no indication for invasive or anaesthesiological intervention, as
confirmed by orthopedic surgeons of the outpatient department of Sint Maartenskliniek, and
they were motivated to learn to change their pain behavior. The patients met the following
criteria: low back pain for at least 6 months, no indication for surgical or pain treatment, had
no intention of asking for medical treatment for the year following the 2-week programme,
age between 20 and 65 years, absence from work for less than 2 years, were motivated to
change behavior, were willing to follow the programme and to reside for 2 weeks in the hotel,
were able to speak and read Dutch. Exclusion criteria were severe psychiatric disorders and
poor physical condition.
Treatment
The cognitive behavioral programme has been developed by the RealHealth Institute in the
United Kingdom and it is a specific pain management programme for patients suffering from
CLBP. All sessions in the programme are delivered by the trainers of the multidisciplinary team
of RealHealth; the same professionals who did the screening. The full programme comprises
an assessment day for intake, the 10-day residential programme with 2 days of follow up,
at 1 and 12 months post-treatment. It is based upon cognitive behavioral principles and
involves a 100h of participant contact time delivered in a 2-week group-orientated residential
setting; around 50h of cognitive behavioral training, 35h of physical activities, and a 15h
of education. The main goal of the programme is to increase the patients’ ability for selfmanagement and self-efficacy, and with that to address the psychological impact of pain. The
perspective is to give people with persistent pain the opportunity to develop techniques and
Daily functioning after a pain management programme
strategies which allows them to minimize the impact of their pain on their daily activities.
This is achieved through a combination of a psychological emphasis and physical activities.
In general this comprises: a stretch and exercise programme, education to define the cause
and nature of chronic pain with particular emphasis on the distinction between pain and
damage. Patients work on goals to enable them to return to an active lifestyle, using planning
and pacing techniques. Cognitive behavioral therapy is given to promote understanding
in the link between beliefs, fears, thoughts, and subsequently mood and pain, and to learn
techniques to identify unhelpful patterns of thinking and to develop effective responses
to challenges. Patients learn to develop a range of relaxation techniques to reduce pain, to
aid sleep, and to increase their range and style of strategies to manage increases in pain
(www.realhealth.org.uk/what-we-do/pmp).
Outcome assessment: Procedure
Participants provide information about medical history, pain (history, intensity, and duration),
medication, general health status, sick leave from work, and disability compensation.
Standardized and validated self-assessment questionnaires measuring low back pain-related
disability, mood, self-management, pain catastrophizing, pain-related fear, and quality of life
were also filled out; as described in the next paragraph. These questionnaires were completed
on four occasions: at baseline, (intake within 1 week before start of programme), at the end
of 2-week programme, and at 1 and 12 months post-treatment. The participants received no
assistance in completing the assessment measures. For intake they were asked to bring the
completed questionnaires with them; on the other occasions the participants completed the
questionnaires at the treatment location.
Outcome Measures
I. Roland and Morris Disability Questionnaire (RMDQ)
The RMDQ [14] is a valid, reliable, and responsive outcome measure for functional
disability in patients with LBP [9,15,16]. This measure is generally used in studies evaluating
conservative treatments on patients suffering from CLBP. The total (sum) score ranges
between 0 (no disability) and 24 (maximal disability). The minimal clinical important
difference (MCID) for clinical relevance is considered to be 5 points [17], although Smeets et
al. [9,13] based their study results on a MCID of 2 points.
II. Oswestry Disability Index (ODI)
The ODI [18] is a questionnaire to detect the extent of disability in patients with LBP; it is
often used in studies in which orthopedic interventions are evaluated. The widely used
measure has been shown to be valid, reliable, and responsive in patients with CLBP [15].
It measures the impact of LBP on daily functioning in ten domains. The total (sum) score
ranges between 0 and 100, the higher the score the higher the disability. In literature the
MCID varied from 4 to 22.1 points when fusion surgery was evaluated [17,19-22]. The MCID
for clinical relevance in this study is considered to be 10 points [17,20].
III.Pain Self-Efficacy Questionnaire (PSEQ)
The PSEQ is a 10-item inventory which measures the patient’s belief about his/her ability to
accomplish a range of activities despite his/her pain [23]. Belief in self-efficacy influences
the possibility of effectively using pain-coping strategies. It also measures physical and
psychological function and rehabilitation outcome in patients with chronic pain. The
measure is used to evaluate the participants’ ability to self-manage his/her pain complaints.
Scores range from 0 to 60, with the higher scores indicating stronger self-efficacy beliefs.
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Validity and reliability has been shown, but no MCID for PSEQ was found in literature. The
generally accepted MCID of 25% improvement above mean baseline score has been used
for this study.
IV. MOS Short Form–36 Health Survey Questionnaire (SF36)
The SF36 [24] is a generic instrument to measure the health-related quality of life. The SF36
consists of two component scores: a physical and a mental score, each of which is made up
of subscales. The 8 subscales of the SF36 represent generic health concepts, considered to
be universal and to represent basic human functions and well-being. In this study we only
used the SF36 Physical Component Score (SF36 PCS); it is has been used in several studies
among patients with chronic pain and has been found valid, reliable, and responsive [24].
The total score ranges from 0 to 100. On the SF36 PCS, a higher score indicates better health.
The MCID of the SF36 PCS is reported to be 5.4 [22].
Statistical Analysis
Descriptive statistics were used to present frequencies. A General Linear Model (GLM) repeated
measures multivariate analysis of variance was used to identify changes over time using
variables measured on at least an interval scale. To show the strength of the within-subject
factor Time in the multivariate models of primary outcome measures, R2 has been computed.
This descriptive statistic indicates the proportion of the variability in the observed data that
can be attributed to the treatment. In other words, it is a way to measure treatment effect.
Because of the use of questionnaires we anticipated missing data on items. We assumed that
these missing data are randomly divided over the different outcome measures. Imputation
techniques were used to compensate for these item-missing data. With this, sensitivity
analyses are performed to determine the robustness of the outcomes and to estimate the
degree and direction of potential confounding. The level of statistical significance was set at
0.05. All statistical analyses were performed using SPSS, version 12.0.1 for Windows.
Sensitivity analysis. Two methods were used for imputation: carrying the last observation
forward (CLOF) and imputation of the baseline values for each missing data point (worstcase scenario). We considered the CLOF data the most realistic scenario since one assumes
no change over time in the specific item that was substituted and the imputation of baseline
values to be the worst-case scenarios, since every effect of the programme was considered to
have vanished for that item. We completed the analysis by comparing the patterns of each
method with the analysis for those cases with complete data (best-case scenario). When
patterns are similar in direction and in the magnitude of estimation of effect size as well, CLOF
is considered to be the approach of choice.
Clinical relevance. Clinical outcome was defined as mean net change with time in outcome
scores as well as the percentage of participants reaching a preset minimal clinical important
difference (MCID) for each outcome. The MCID is the threshold for meaningful change; it
is defined as the smallest difference that can be considered to be beneficial for the patient
and that would result in a change in management by the patient, assuming an absence of
excessive side effects or costs [25]. The MCID is often reported as minimal clinical important
change (MCIC) [17,20]. Effect sizes were calculated for all outcome measures for the RealHealth
programme as well as for the same measures used in published research to indicate the
magnitude of treatment effect. It is measured as the standardized difference between the
mean post– and pre-treatment score and it takes group variability into account. We used
Daily functioning after a pain management programme
Cohen’s d for effect size; it is defined as the difference between means (baseline and follow
up) divided by the pooled standard deviation [26]. An effect size of 1 is equivalent to a change
of 1 standard deviation (SD) in the sample. The effect sizes are translated into benchmarks for
assessing the relative size of change. An effect size (d) of 0.2 is considered small, 0.5 moderate,
while 0.8 is a large effect.
To compare results of this cohort study with published research we used Standardized
Morbidity Ratios (SMR) to estimate the relative rates of treatment improvement. In this study
the SMR is the observed/expected ratio. The expected values have been computed using data
from an external reference population [27]. Our reference population came from literature for
spinal surgery and rehabilitation programmes for patients treated for CLBP. The percentages
in this formula indicate the number of participants improved. The standard deviation of the
difference in the reference data of Fairbank et al. [5] was not reported; therefore, we calculated
the variance of the difference using the following formula: σ2X-Y = σ2X + σ2Y - 2ρσX σY, where ρ is the
correlation between the variances of the differences of the variables X and Y in the reference;
for this calculation it is assumed to be 0.50. With the normalized data, a z-value is calculated
and the percentage patients improved by the intervention can be determined.
Results
Response
One hundred fifty-five patients were referred for the RealHealth programme between October
2006 and July 2007; 107 (69%) were admitted according to the inclusion and exclusion criteria.
The 48 excluded patients were referred back to the orthopedic surgeon. Nineteen (12%) of the
107 failed to meet the inclusion criteria, 17 (11%) were included but decided not to join the
programme, and 12 (8%) were included but wished to postpone their participation until a later
time.
In August 2008, all participants had completed the 1-year follow up. Four of the 107 participants
left during the 2-week residential programme: two due to lack of motivation, one because of
inappropriate behavior during group sessions, and one due to acute illness of the partner.
The scores for 77% (n= 82) of all possible items for each participant at each assessment were
available for analysis: the best-case scenario. Some data were missing for 21 participants;
these missing values were randomly divided among the four assessment moments and the
items to be scored. In total 446 of the 5,592 data points were missing (7.4%) in the database.
For RMDQ 45 data points were missing (0.7%); for ODI 43 (0.7%); for PSEQ 44 (0.7%), and for
SF36 PCS 184 data points (3.1%). Imputation techniques were applied to assign a value for the
missing data.
Post hoc power analyses, to determine the minimal sample size needed to find a significant
effect on the main outcome parameters, showed that a minimum of 26 complete data sets
was needed to show clinical relevant (α= 0.05, β= 0.90) change on each outcome measure.
Since we included the data of all 107 participants for analysis, and compared these results
with the best-case scenario (complete cases only), sufficient power was achieved.
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Baseline characteristics
The baseline characteristics for the 107 patients who participated in the RealHealth
programme are shown in Table 2.1. The mean age was 44 (± 8.4) years; the mean duration of
LBP was 12 years, with one 63-year-old patient reporting 52 years of complaints. Females were
in the majority (57%), while 70% of the participants were currently at work, and one-third had
previously undergone surgery for their LBP.
Table 2.1 Baseline characteristics reported by participants in RealHealth NL programme with chronic low
back pain (CLBP; n= 107)
Baseline characteristics
Total (n=107)
Sociodemographic
Age, mean (SD, range min-max) in years
44.1 (± 8.4, 23-60)
Gender n (%), Male : Female
46 (43%) : 61 (57%)
Employement status, n (%)
Yes : no
75 (70.1%) : 32 (29.9%)
Working – Full time
43 (40.2%)
Working – Part time
32 (29.9%)
Unemployed because of CLBP
15 (14%)
Unemployed because of other causes
2 (1.9%)
Disability pension
15 (14%)
CLBP History
Duration of LBP, mean (SD, range min-max) in years
12.3 (±10.9, 1-52)
Pain medication n (%), yes : no
91 (85%) : 16 (15%)
Previous surgery n (%), yes : no
34 (32%) : 73 (68%)
Baseline values factors related to CLBP
PCS Pain Catastrophizing Scale, mean (SD)
22.6 (± 9.2)
ZSDS Zung Self-Rating Depression Scale, mean (SD)
24.8 (± 10.4)
TSK Tampa Scale for Kinesiophobia, mean (SD)
41.0 (± 6.5)
Clinical outcome
Table 2.2 shows means and standard deviations (SD) for all outcome measures. Mean outcome
scores improved greatly between baseline and directly post-treatment as seen in Table 2.2.
During the following 12 months a continuous, slight improvement in mean scores is seen.
Mean improvements between baseline and 12 months follow up are: 5 points on the RMDQ (±
6.3), 12 points on the ODI (± 15.2), 10 points on the PSEQ (± 12.8), and 21 points on the SF36 PCS
(± 17.6).
Daily functioning after a pain management programme
The R2 for the factor time, a measure for treatment effect, for each outcome measure is also
presented in Table 2.2 It is significant for each of the four outcome variables. For both physical
functioning scores (ODI and RMDQ), the effects are of similar magnitude as it is for pain selfefficacy (PSEQ). The strongest effect was found for physical functioning-related quality of life
(SF36 PCS); it was almost one and a half times greater: R2 = 0.59 than the 0.40 found for the
other three outcomes.
To verify that using the CLOF (carrying the last observation forward) method to compensate
for missing data could be applied, the mean scores for each outcome variable were graphically
compared as presented in Figures 2.1-4. Each figure presents three scenarios: the best-case
scenario (n= 82) in which only the patients with no missing values have been included, the
worst-case scenario (n= 107) in which the baseline value has been inserted for any missing
value, and the CLOF method (n= 107). In each figure all three curves show the same tendency,
which supports our assumption that the results are robust, independent of which imputation
method was used. They all improve with time, and the curve for the best-case scenario stayed
within the confidence intervals of the CLOF curve. Hence, the results obtained using CLOF can
be considered as reasonably realistic and can be used to evaluate the RealHealth programme.
Table 2.2 Mean (SD) for functional disability, self-efficacy and quality of life in CLBP
Baseline
Last day of 2-week
programme
1 month
follow up
12 months
follow up
R2
ODI
41.2 (14.5)
35.4 (16.6)
31.7 (16.0)
29.0 (17.9)
0.40
RMDQ
13.9 ( 4.0)
10.1 ( 5.2)
9.2 ( 5.7)
8.9 (6.5)
0.39
PSEQ
33.9 (11.5)
42.8 (11.0)
42.3 (11.2)
43.8 (11.3)
0.38
SF36 PCS
40.2 (12.6)
49.6 (15.4)
60.9 (20.5)
61.3 (18.8)
0.59
Outcome measures
R variability attributed to treatment (within-subject factor time), a measure for treatment effect, was analyzed with Repeated Measures
multivariate analyses of variance. CLOF scenario (n= 107) was used.
CLOF carrying last observation forward, as described in the text
Repeated Measures MANOVA are the following: ODI Oswestry Disability Index: df (1, 106), F= 69.20, p<0.001; RMDQ Roland and Morris Disability
Questionnaire: df (1, 106), F= 67.71, p<0.001; PSEQ Pain Self-Efficacy Questionnaire: df (1, 106), F= 65.14, p<0.001; SF36 PCS MOS Short Form 36
Physical Component Scale: df (1, 106), F=152.08, p<0.001
2
The effect sizes for the functional scales, those to assess self-management and quality of life
scales, are given in Table 3: these range between 0.8 and 1.3. For our study, all the effect sizes
can be classified as large. The clinical relevancy is further supported by the percentage of
participants who reached the preset minimal clinical important difference (MCID) for each
outcome measure. At least 50% of the participants showed improvement greater than the
reference MCID for all 4 measurements. For a reduction of 5 points on RMDQ [17], 49% showed
a relevant improvement in daily functioning 12 months after the treatment. A clinical relevant
improvement of 10 points or more on ODI [17,20] was seen in 56% of the participants. The MCID
for self-management of pain (PSEQ) was set a 25% (8.5 points) of the mean baseline score; 57
participants (53%) showed a relevant improvement. For the quality of life related to physical
functioning (SF36 PCS) 86 participants (80%) showed a meaningful improvement of 5.4 points
[22] or more.
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In order to be able to compare the results of the RealHealth programme with those found in the
literature, both the effect sizes and Standardized Morbidity Ratios (SMR), based on the data
provided in the article, needed to be calculated (Table 3). No one study used all of our outcome
variables. For the cognitive behavioral treatment group reported by Smeets et al. [9] the effect
size is small (d= 0.2). To compare with the results of the UK MRC spine stabilization trial [5], we
calculated the Cohen’s d for the fusion group and the rehabilitation group separately. As can
be seen in Table 2.3, the effect sizes for both interventions for the ODI are moderate (surgery
d= 0.7 and rehabilitation d= 0.5) as is that for the SF36 PCS (rehabilitation d= 0.6). Only the
Cohen’s d for the SF36 PCS for the group, which had had a surgical intervention, is considered
large (d= 0.8).
For the SMR: first the literature studies the percentage of patients who improved was
determined for the literature studies and for the RealHealth study. Subsequently, the SMR
was calculated, as shown in Table 2.3. To compare with the cognitive behavioral treatment
of Smeets et al. [9] a 2-point MCID was used, as reported in that study. The calculated SMR
of 136% indicates that 36% more of the participants of the RealHealth programme showed
improvement on the RMDQ. In comparison to the rehabilitation treatment of Fairbank et al.
[5], the SMR of 107% indicates that a slightly larger percentage of the RealHealth participants
showed improvement on the ODI. The SMR of 98% for the comparison between surgical
treatment [5] and the RealHealth programme indicate that a slightly larger percentage of
the surgical intervention group showed improvement on the ODI. More participants of the
RealHealth programme (10% when compared with surgical intervention group; 18% for the
rehabilitation group) showed improvement on the SF36 PCS. No comparative literature study
could be found for the PSEQ.
Table 2.3 Clinical relevancy after 12 months
RMDQ
(0 – 24)
ODI
(0 - 100)
PSEQ
(0 - 60)
SF36 PCS
(0 - 100)
Effect Size
RealHealth NL
0.9
0.8
0.8
1.3
Cohen’s d
Smeets et al. [9]
0.2
-
-
-
MCID (%)
Surgery
Rehab
0.5
Fairbank et al. [5]
-
0.7
RealHealth NL
79%
56%
SMR (%)
Surgery
Rehab
136% [9]
98% [5]
107% [5]
(79/58)
(77/79)
(77/72)
Surgery
Rehab
-
0.8
0.6
53%
80%
-
Surgery
Rehab
110% [5]
118% [5]
(85/77)
(85/72)
Calculated percentages of the RealHealth programme participants who reached the MCID. Effect sizes and SMR as relative rate for treatment
improvement were calculated for the RealHealth programme as well as for the external reference populations found in literature [5,9] .
MCID, minimal clinical important difference: MCID for RMDQ = 2 points [9]; MCID for ODI = 10 points [17,20]; MCID for PSEQ = 8.5 (based on 25%
of the mean baseline score); MCID for SF36 PCS = 5.4 point [22]
SMR, standardized morbibidity ratio
Daily functioning after a pain management programme
37
Figures 2.1-4. Graphic trends of three scenarios: the worst case (imputation of baseline value, n=107),
CLOF (carrying the last observation forward, n=107), and the best case scenario (completed cases only,
n=82)
02
Figure 2.1
Oswestry Disability Index (ODI)
Figure 2.2
Roland & Morris Disability Questionnaire
(RMDQ)
Figure 2.3
Pain Self Efficacy Questionnaire (PSEQ)
Figure 2.4
SF36 Physical Component Score (SF36 PCS)
38
Daily functioning after a pain management programme
Discussion
02
The aim of this article was to evaluate the 1-year follow-up results in patients with CLBP
after a cognitive behavior based programme provided by RealHealth-Netherlands. This
programme follows the international guidelines [10], and is indicated for patients for whom
surgery or anaesthesiology is not an option. These results were compared to the outcomes
for interventions for patients with CLBP found in published research. More than half of the
prospective cohort of RealHealth participants showed improvement in daily functioning,
learned to manage their chronic disabling low back pain, and for a tremendous amount of
the cohort (80%) their quality of life improved significantly. All these clinically relevant results
were sustained at 1-year follow up, and were meaningful to patients. These improvements
were greater than the reference MCID for all outcome measures. The effect of the treatment is
further established by the large effect sizes (Cohen’s d ranging from 0.8 to 1.3) found for the four
outcome measures, which indicate a treatment effect and by the SMRs used to compare the
RealHealth results to two other studies in which patients were treated for CLBP; these ranged
from 98% to 136%. When compared to other multidisciplinary rehabilitation programmes, the
results for daily functioning favor the RealHealth programme, and were comparable to those
achieved after fusion surgery.
Comparison with related research: multidisciplinary rehabilitation programmes
We compared the results of the RealHealth programme to the interventions recently conducted
in The Netherlands by Smeets et al.[9,13], in which the patients were randomized among three
treatment groups (the active physical, the cognitive behavioral, and a combination of both)
was also compared to a group of patients on the waiting list. One-year post-treatment results
showed that all three active treatments were more effective than no treatment; however, no
treatment group had greater clinical relevant improvement than the other two. The cognitive
behavioral arm is most similar to the RealHealth programme; therefore, those results were
compared to those obtained in the present study. The baseline level of functional disability,
measured by the RMDQ, is comparable to that of our study population (both 14 ±4). Depending
on the therapy given, the Smeets et al. study reported at 1-year follow up a mean improvement
of 2-4 points on the RMDQ; this is lower than the 5 points improvement reported in the
RealHealth study. When a 2-point reduction on RMDQ was used to show clinical relevancy,
58% of those patients reached this threshold 1-year post-treatment. When we applied the
same criterion, 79% of our patients showed a clinically relevant improvement.
An extremely small effect size was calculated for the cognitive behavioral group of Smeets
et al. for functional disability (d= 0.2) versus the large effect size (d= 0.9) of the programme
of RealHealth, which is favorably sustained by the SMR of 136%. The small effect size found
is possibly due to the heterogeneous patients, as shown in the relatively large standard
deviation of 4 points. The authors of that study also mentioned the limited exposure to
cognitive treatment (78h). The results of the RealHealth programme seems to validate the
guideline value of 100h exposure to cognitive behavioral techniques [8].
Comparison with related research: fusion surgery
We also compared the results of the RealHealth programme to those reported in the MRC
spine stabilization trial by Fairbank et al.[5]. They randomized patients to either a surgical
stabilization (spinal fusion) or an intensive rehabilitation. Those authors concluded there is
Daily functioning after a pain management programme
no clear evidence that primary spinal fusion surgery was any more beneficial than intensive
rehabilitation. We chose that study to determine whether an intensive cognitive behavioral
pain management programme could be an alternative for patients with longstanding CLBP.
In studies in which evaluations of surgical interventions, such as spinal fusion were reported,
the primary disability outcome measure usually is the ODI. When comparing the baseline
characteristics for disability, we found that the surgical group had a score of 47, whereas
the mean score in the rehabilitation group was 45, which are reasonably comparable to the
41 points found in the current study. Although in the present study an orthopedic surgeon
confirmed that there was no indication for an invasive treatment, this baseline characteristic
implies that the RealHealth programme treated patients with equivalent severity of disability.
At 2-year follow up a 13-point improvement in ODI score was found for the surgical group and
9 points for the rehabilitation group. Although we had only 1-year results, the current study
shows 12 points improvement in ODI, which compares favorably with both the rehabilitation
and surgical intervention groups of the UK MRC trial. Considering the generally accepted
MCID, a 10-point improvement is needed to show meaningful clinical relevance [17,20].
In short, the RealHealth programme seems to be superior to the surgical or rehabilitation
treatments: the effect size for quality of life related to physical functioning is extremely large
(d= 1.3) and considered large for disability (d= 0.8). The comparison for reduction of disability
is equivalent: 0.8 vs. 0.7 and 0.6, for surgical and rehabilitation treatment, respectively. This
conclusion is substantiated since 80% of the RealHealth participants reported a meaningful
improvement in quality of life after a year and 56% reported that they functioned better
than previously. Therefore, the RealHealth programme seems to be an important alternative
intervention when fusion surgery is considered. The improvement found with the RealHealth
programme in comparison to the intensive outpatient rehabilitation programme reported by
Fairbank et al. [5] may be explained by the fact that only 75h of outpatient rehabilitation had
been offered during a 3-week period. Once more the RealHealth programme’s 100h seems to
validate the guideline value of 100h exposure to cognitive behavioral techniques [8].
Limitations of the study
This study also has its limitations. According to the inclusion criteria used for the cognitive
behavioral RealHealth programme, patients are required to have no indication for surgical
treatment and had to be motivated to change their behavior with regard to their pain
complaints. This implies that a selection bias might have been introduced, especially since the
Sint Maartenskliniek is a specialized hospital to which patients are often referred for second
opinion or as a last resort. This limits the generalizability of the results. However, this type
of treatment will not be efficacious if patients are not motivated to change their behavior.
Therefore, it is possible that in general practice, the results could be less favorable since the
inclusion criteria would not be as narrowly defined.
In the study reported here, several precautions were taken to enhance internal validity and
minimize the potential influence of bias and confounding on the outcome factors, these
include multivariable adjustment, sensitivity analysis and standardization. Emphasis should
to be placed on the use of sensitivity analyses, which was motivated by the fact that there
were item-missing data on the outcome measurements. Although no systematic pattern was
discerned, these missing data need to be taken into consideration when the results of the
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study are estimated and interpreted. The analyses indicate the ranges within which the effects
may be expected and do not give an exact estimate of the magnitude of the effect. The use
of SMR provides information about the magnitude of effect compared to other studies and/
or populations. An SMR, a rate ratio, is thus an estimate of relative treatment improvement.
However, since an external reference has been used to calculate the SMRs, discrepancies
in the population characteristics are likely and it is not possible to judge whether sufficient
controls have been conducted to enhance the internal validity within the studies reported
in the literature. However, the SMRs can be accepted as a technique to enable a measure of
comparison.
In summary, the comparisons with other treatments seem to indicate that the intensity,
duration and frequency of a cognitive behavioral pain management programme may
be the most important key to success. The results of the short and intensive RealHealth
programme are promising, but further research is needed to determine which factors of
CLBP are influenced by this treatment programme, and to answer the frequently reported
question [2,9,12]: ‘Which type of patient benefits the most?’ It is interesting to note that even
participants with longstanding CLBP complaints (mean complaint duration in the RealHealth
programme was 12 years) seem to experience benefits from this short, intensive programme,
suggesting that CLBP duration is not an important factor for the management of CLBP. Factors
such as mood, fear of movement, catastrophizing, coping strategies, and self-management,
which will be analyzed in a following study, do seem to be important factors. Although the
comparison technique used in this study has some drawbacks, it is justified to conclude that
the RealHealth programme seems to be allow CLBP patients to achieve clinically relevant
improvement; the treatment effect seems to be comparable to spinal surgery and to achieve
better results than less intensive rehabilitation programmes.
Acknowledgement
The authors thank the multidisciplinary treatment team at Realhealth NL who were
responsible for the intake procedure and training the participants in pain management
programme. Particular thanks are for Cissy Matthijssen (RealHealth NL), Lauren White
(RealHealth UK) for their assistance in completing the database, and Patricia G. Anderson for
her editorial assistance.
Daily functioning after a pain management programme
41
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deconditioning and chronic low back pain: a hypothesis-oriented systematic review. Disabil.Rehabil.
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4. Picavet HS, Schouten JS. Musculoskeletal pain in the Netherlands: prevalences, consequences and risk
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5. Fairbank J, Frost H, Wilson-MacDonald J, Yu LM, Barker K, Collins R. Randomised controlled trial to compare
surgical stabilisation of the lumbar spine with an intensive rehabilitation programme for patients with
chronic low back pain: the MRC spine stabilisation trial. BMJ 2005;330:1233
6. Koes BW. Surgery versus intensive rehabilitation programmes for chronic low back pain. BMJ 2005;330:12201221
7. Mirza SK, Deyo RA. Systematic review of randomized trials comparing lumbar fusion surgery to nonoperative
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8. Guzman J, Esmail R, Karjalainen K, Malmivaara A, Irvin E, Bombardier C. Multidisciplinary bio-psycho-social
rehabilitation for chronic low back pain. Cochrane.Database.Syst.Rev. 2002:CD000963
9. Smeets RJ, Vlaeyen JW, Hidding A, Kester AD, van der Heijden GJ, Knottnerus JA. Chronic low back pain:
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results of a randomized controlled trial. Pain 2008;134:263-276
10. National Institute for Health and Clinical Excellence. Low Back Pain: Early management of persistent
non-specific low back pain [Report]. NICE Clinical Guideline 88. London, National Collaborating Centre for
Primary Care; 2009
11. Chou R, Loeser JD, Owens DK, Rosenquist RW, Atlas SJ, Baisden J et al. Interventional therapies, surgery, and
interdisciplinary rehabilitation for low back pain: an evidence-based clinical practice guideline from the
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12. McCracken LM, Turk DC. Behavioral and cognitive-behavioral treatment for chronic pain: outcome,
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13. Smeets RJ, Vlaeyen JW, Hidding A, Kester AD, van der Heijden GJ, van Geel AC et al. Active rehabilitation for
chronic low back pain: cognitive-behavioral, physical, or both? First direct post-treatment results from a
randomized controlled trial. BMC.Musculoskelet.Disord. 2006;7:5
14. Roland M, Morris R. A study of the natural history of back pain. Part I: development of a reliable and sensitive
measure of disability in low-back pain. Spine 1983;8:141-144
15. Roland M, Fairbank J. The Roland-Morris Disability Questionnaire and the Oswestry Disability Questionnaire.
Spine 2000;25:3115-3124
16. Ostelo RW, de Vet HC, Knol DL, van den Brandt PA. 24-item Roland-Morris Disability Questionnaire was
preferred out of six functional status questionnaires for post-lumbar disc surgery. J.Clin.Epidemiol.
2004;57:268-276
17. Ostelo RW, Deyo RA, Stratford P, Waddell G, Croft P, Von Korff M et al. Interpreting change scores for pain and
functional status in low back pain: towards international consensus regarding minimal important change.
Spine 2008;33:90-94
18. Fairbank JC, Couper J, Davies JB, O'Brien JP. The Oswestry low back pain disability questionnaire.
Physiotherapy. 1980;66:271-273
02
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Daily functioning after a pain management programme
19. Wilson-MacDonald J, Fairbank J, Frost H, Yu LM, Barker K, Collins R et al. The MRC spine stabilization trial:
surgical methods, outcomes, costs, and complications of surgical stabilization. Spine 2008;33:2334-2340
20. Ostelo RW, de Vet HC. Clinically important outcomes in low back pain. Best.Pract.Res.Clin.Rheumatol.
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2005;19:593-607
21. Tafazal SI, Sell PJ. Outcome scores in spinal surgery quantified: excellent, good, fair and poor in terms of
patient-completed tools. Eur.Spine J. 2006;15:1653-1660
22. Glassman SD, Gornet M.F., Branch C., Polly D.Jr., Peloza J.D., Schwender J.D. et al. MOS Short Form 36 and
Oswestry Disability Index outcomes in lumbar fusion: a multicenter experience. Spine J. 2006;6:21-26
23. Nicholas MK. The pain self-efficacy questionnaire: Taking pain into account. Eur.J.Pain 2007;11:153-163
24. Ware JE, Jr.Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and
item selection. Med.Care 1992;30:473-483
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comparison of two techniques. J.Clin.Epidemiol. 1996;49:1215-1219
26. Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale, NJ: Lawrence Earlbaum
Associates; 1988
27. Rothman KJ, Greenland S, Lash TL. Modern Epidemiology. 3rd ed. Philadelphia: Lippincott Williams and
Wilkins; 2008; 664-681
43
Chapter 03
A short, intensive cognitive
behavioral pain management
program reduces healthcare use in
patients with chronic low back pain
Two-year follow-up results
of a prospective cohort
van Hooff ML
ter Avest W
Horsting PP
O’Dowd J
de Kleuver M
van Lankveld W
van Limbeek J
Published in: Eur Spine J. 2012; 21(7):1257-64
44
Abstract
Purpose: Cognitive behavioral interventions are recommended as non-invasive treatment
options for patients with chronic low back pain (CLBP). However, most treatment effects are
small and short-lived. Although a 2-week intensive pain management program for patients
with CLBP seems to be effective, the long-term results are not known. The purpose of this
study is to evaluate the stability of the 2-year follow up results and whether this is reflected in
the use of healthcare services.
Methods: A prospective cohort study was performed. Pre-treatment characteristics of patients
and data of outcomes obtained at 1-year follow up were used. At 2-year follow up a structured
interview was conducted following the principles of a post-marketing survey. Outcomes
included daily functioning, quality of life, current intensity of pain, disturbance of pain during
daily activities, and indicators of the use of pain medication and healthcare services.
Results: Of the 90 eligible patients 85 (94%) participated in the post-marketing survey. The
1-year clinical relevant effects are maintained at 2-year follow up. Effect sizes for functioning
and quality of life were large. More than 65% reached preset minimal clinically important
differences. At pre-treatment all patients consulted their general practitioner (GP) and
medical specialist (MS). At 2-year follow up 73% reported having consulted neither a GP nor
an MS during the previous year. Most of the patients indicated not to use any pain medication
(57%) and the percentage patients using opioids has decreased (14%). Moreover, 81% reported
to be at work.
Conclusions: The gained results from selected and motivated patients with longstanding CLBP
at 1-year follow up are stable at 2-year follow up. Above all, most of the participants are at
work and the use of both pain medication and healthcare has decreased substantially.
Outcomes and healthcare use after a pain management programme
45
Introduction
Low back pain is one of the most common disabling conditions and causes high health
expenditure in developed countries [1-3]. This condition has a high prevalence: over 70% of the
adult population experience at least one episode of low back pain [1,4-6]. In the Netherlands
the annual prevalence in 2003 was approximately 44% [1]. A minority (20%) develop chronic
low back pain (CLBP), meaning that the complaints persist at least 3 months [2] and are
associated with persistent or recurrent disability. These complaints may result in the
individuals experiencing a lower health-related quality of life; they cause a quarter of all sick
leave in the employed population [1,3,4]. The Dutch National Institute for Public Health and the
Environment (RIVM) estimated CLBP-related costs to be 0.9% of total healthcare costs in the
Netherlands [5], resulting in its being the top three of highest healthcare costs [6]. Moreover,
14% of the adult population with a disability allowance in the Netherlands is diagnosed with
CLBP. Therefore, CLBP is not only a burden for the patient but the related healthcare costs are
also a problem for society.
A wide range of interventions to manage CLBP is used including pharmaceutical, surgical and
non-surgical interventions [3,7,8]. However, many commonly used interventions lack evidence
of clinically relevant long-term effects [4]. International guidelines [9-11], a Cochrane review
[12] as well as recently performed randomized controlled trials have demonstrated that a
cognitive behavioral approach most effectively reduces disability in CLBP patients [8,13-15].
Nevertheless, most effects achieved by these non-invasive treatments are small and shortlived [14,16-18]. A systematic review with 1964 randomly allocated patients concluded that
100h or more of intensive, multidisciplinary rehabilitation with a functional restoration
approach including cognitive behavioral interventions reduces pain and improves
functionality [19]. Furthermore, most reported treatment programs have a mean duration of
4 weeks [18,20] or more [8,13-15].
A recently published study by Van Hooff et al. [21] evaluated the 1-year results of a cohort
of patients who participated in 2-week program provided by RealHealth NL. The program
is based on cognitive behavioral principles and aims at improving daily functioning by
self-management of lower back pain complaints. Participants with longstanding CLBP
complaints (12 years on average) learned to manage CLBP, improved fast in daily functioning
and experienced a fast improvement in their quality of life. These results were meaningful
and clinically relevant to the participants and comparable to results after spinal surgery and
superior to results for rehabilitation programs of longer duration. However, the question
remains whether these positive short-term effects are sustained in the long run and whether
these benefits are reflected in the degree of healthcare use and the use of pain medication.
Therefore, in this study the main purpose is to evaluate the stability of the 2-year (longterm) follow-up results of a short, intensive cognitive behavioral pain-management
program provided by RealHealth NL. The emphasis is on evaluating daily functioning, the
use of healthcare services, and pain medication 2 years after the intervention. We hope
that improvements gained in the first year (short-term) will be maintained and the use of
healthcare services and pain medication will be reduced in the second year of follow up. 03
46
Outcomes and healthcare use after a pain management programme
Materials and Methods
03
Study design and Setting
This study is an extension of a prospective cohort study in which the effectiveness of a intensive
cognitive behavioral pain management program was evaluated after 1 year of follow up [21].
We used data obtained by questionnaire at pre-treatment, including patient characteristics,
outcome measures and indicators of healthcare and pain medication use. Outcome
assessments performed at 1 year after treatment yielded the primary outcome measure and
health-related quality of life (Short-Form 36). The outcomes were compared with outcome
assessments at 2-year follow up. To achieve a high response rate a structured interview
following the principles of a post-marketing survey was added to obtain data at 2-year follow
up. A short description of participants, treatment, and outcome measures follows.
Patients and Treatment
A detailed description of participants and treatment has been reported previously [21].
Patients entered the study consecutively. The main inclusion criteria for the intervention were
low back pain for at least 6 months, no indication for surgical or other invasive pain treatment
confirmed by spinal surgeons at the Sint Maartenskliniek, no intention of seeking medical
treatment in the year following the 2-week program, age between 20 and 65 years, motivation
to change behavior, willing to follow the program and to reside in a hotel for 2 weeks, able to
speak and read Dutch. The main exclusion criterion was psychiatric disorders.
The evidence-based, intensive cognitive behavioral pain management program was
developed by the RealHealth Institute in the United Kingdom and follows published
international guidelines [9-11]. In the Netherlands all sessions are delivered by the trainers of
the RealHealth multidisciplinary team. The team consists of a psychologist, a physiotherapist
and an occupational therapist. The full program comprises an assessment day for intake, the
10-day residential program with two follow-up days: 1-month and 1-year post-treatment. The
main aim of the program is to improve daily functioning. This is achieved by increasing the
capability of self-manage the CLBP complaints. The program consists of 100h of participant
contact time, approximately 50h of cognitive behavioral training, 35h of graded physical
activities, and 15h of education in which the cognitive behavioral principles are integrated.
The program is delivered in a 2-week, group-orientated residential setting.
Outcome assessment: Procedure
Participants who had completed the 1-year follow up were contacted. All recruited respondents
were telephoned by a secretary and were asked if they were willing to participate in a followup study, including a telephone survey at a later time. When the respondent consented, the
secretary made the appointment for a telephone call; the questionnaire booklet as well as
a background information sheet was sent. The participants completed the questionnaire
without assistance. The questionnaires are in the ‘Outcome Measures’ section, which included
daily functioning, health-related quality of life, different pain scales, and questions about
use of healthcare services, pain medication and return-to-work. An independent researcher
(WterA) conducted the 20-min standardized telephone interviews in the period March–June
2010. During the telephone interview, the answers were passed without any discussion. A
small gift voucher for flowers as a present for participation was sent after the interview was
completed.
Outcomes and healthcare use after a pain management programme
47
Outcome Measures
Primary outcome:
- Roland and Morris Disability Questionnaire (RMDQ)
The RMDQ [22] contains 24 questions and measures functional disability in patients with
low back pain [8,22]. The total score ranges between 0 (no disability) and 24 (maximal
disability).
Secondary Outcomes:
- Short-Form 36 Health Survey Questionnaire (SF36)
The SF36 [23] is a generic instrument to measure the health-related quality of life. The
validated Dutch language version has been used in a wide range of studies among patients
with chronic health conditions including CLBP [24]. The instrument contains 36 items in 8
subscales. The subscales results were combined into two summary scores: the SF36 Physical
Component Score (SF36 PCS) and the SF36 Mental health Component Score (SF36 MCS).
- Healthcare use
Indicators for healthcare use were consultation of a general practitioner (GP) or a medical
specialist (MS) and referral to a physical therapist (PT) or a psychologist (PS) during the
previous 12 months as well as current pain medication consumption (analgesics). Patients
were asked to provide information before the program and at 2-year follow up. Consultation
and referral questions were scored on a dichotomous scale (yes/no), which in addition to
information about the frequency of these visits yielded an impression of the program’s
impact on healthcare use. Pain medication was classified in accordance with the threestep World Health Organization (WHO) analgesic ladder. These steps are (1) non-opioid
analgesics with adjuvant therapy when needed, (2) an addition of a weak opioid, and (3)
a strong opioid addition to non-opioid and adjuvant therapy [25]. For this study the first
step was split into two categories: (1A) paracetamol also known as acetaminophen in the
USA, and (1B) non-steroidal anti-inflammatory drugs (NSAIDs). Pain medication was then
classified as: ‘none-light’ (none and WHO-step 1A) and ‘moderate-severe’ (WHO-steps
1B-3). The ‘none/light’ classification indicates analgesics, which have no or only few side
effects [3,16,26]. The analgesics in the ‘moderate-severe’ classification are known to have
adverse side effects, especially when used for a long period [3]. Furthermore, we classified
consumption of analgesics as being ‘structural’ (daily) and ‘incidental’ (only when needed or
less than once a week).
Tertiary outcome:
- Visual Analogue Scales for pain to measure current intensity and disturbance during daily
activities (VAS ‘current intensity’ and VAS ‘disturbance ADL’)
Participants were asked about the current intensity of their back pain for the day of the
questionnaire and about the disturbance of back pain during daily activities. Both severity
and disturbance were marked on a line of 100 mm, with 0 mm indicating ‘no pain’ and 100
mm ‘unbearable pain’ [27,28].
03
48
03
Outcomes and healthcare use after a pain management programme
Statistical Analysis
Frequencies of characteristics assessed at pre-treatment and healthcare use are described.
To compare the characteristics of non-responders, an independent Student’s t test was
performed for the pre-treatment characteristics and the outcome measures. Maintenance of
gained results at 2-year follow up for all outcomes, except for healthcare use, was calculated
with a paired samples Student’s t test.
To explore clinical relevance we calculated effect sizes (Cohens’ d) for primary and secondary
outcomes (RMDQ and SF36 PCS) to indicate the magnitude of treatment effect for the
RealHealth program. This measure is defined as the difference between the means of the pretreatment assessment and of the 2-year follow up divided by the pooled standard deviation.
An effect size (d) of 0.2 is considered to be small, 0.5 moderate, while 0.8 indicates a large effect
[29]. Moreover, an effect size (d) of 1 is equivalent to a change of 1 standard deviation in the
study sample.
All statistical analyses were conducted using SPSS, version 17.0 for Windows. We set the level
of significance at 0.05. Pie charts to present frequencies are created in STATA version 10.0.
Results
Response
In March 2010 we had complete data sets available for 90 participants (84%), who were
eligible to be contacted for the 2-year follow up. A total of five patients were seen as nonresponders, either because they could not be reached in time (three patients) or was in final
stage of illness and had other priorities (one patient) or wished not to co-operate (one patient).
These five non-responders were not significantly different to the included participants with
regard to pre-treatment characteristics and outcome measures: RMDQ, SF36 and both VAS
scales (‘current intensity’ and ‘disturbance ADL’). A total of 85 participants (94%) joined in the
post-marketing survey at 2-year follow up.
Patient characteristics
Table 3.1 shows the pre-treatment characteristics of the 85 participants. They reported
longstanding CLBP (11 years on average) and 29% had an earlier surgery for their back problem.
Outcomes and healthcare use after a pain management programme
49
Table 3.1 Pre-treatment characteristics and 2-year follow-up results of return-to-work as reported by
the participants (n= 85)
Pre-treatment characteristics
n= 85
Sociodemographic
Age, mean (SD, range min-max) in years
42.9 (± 8.4, 23-60)
Gender n (%), male : female
35 (41%) : 50 (59%)
Pre-treatment assessment
2-year follow up
57 (68%) : 28 (32%)
69 (81%) : 16 (19%)
At work – Full time
31 (37%)
32 (38%)
At work – Part time
26 (31%)
37 (44%)
Unemployed because of CLBP
13 (15%)
8 (9%)
4 (5%)
3 (4%)
11 (13%)
5 (6%)
Work status n (%)
Yes : no
Unemployed because of other causes
Disability pension
CLBP History
Duration of LBP, mean (range min-max) in years
11.3 (1-51)
Previous surgery n (%) yes : no
25 (29%) : 60 (71%)
Clinical outcome
In Table 3.2 outcome measures are presented except those for healthcare use. Between at 1and 2-year follow-up assessments the mean scores remained stable. Only pain ‘disturbance of
ADL’ significantly improved between 1- and 2-year follow up: df (1,84), t= 2.57, p= 0.01. In Figure
3.1 the trends, means with 95% confidence intervals for the primary outcome ‘functional
disability’ as measured with the RMDQ, are graphically presented.
Table 3.2 Mean (SD) for outcome measures at 1- and 2-year follow up with t-values for paired
comparisons and significance levels (n= 85)
1-year FU
2-year FU
t-value
p-value
7.5 (5.0)
7.2 (5.0)
0.75
0.45
SF36 PCS
64.6 (17.8)
65.9 (20.6)
-0.50
0.62
SF36 MCS
70.9 (15.2)
71.9 (17.1)
-0.52
0.60
VAS ‘current intensity’
35.9 (23.4)
35.0 (27.5)
0.96
0.34
VAS ‘disturbance in ADL’
35.3 (26.9)
27.1 (27.1)
2.57
0.01*
Primary outcome
RMDQ
Secondary outcomes
Tertiary outcomes
FU, Follow up; RMDQ, Roland and Morris Disability Questionnaire; SF36 PCS, Short Form 36 Physical Component Scale; SF36 MCS, Short Form
36 Mental Component Scale; VAS, Visual Analogue Scale, with ‘current intensity’ indicating pain severity and ‘disturbance in ADL’ indicating
disturbance of pain during daily activities
*p< 0.05
03
50
Outcomes and healthcare use after a pain management programme
Figure 3.1 Roland and Morris Disability Index (RMDQ); means and 95% confidence intervals. Trend of
maintenance of gained results between 1-year and 2-year follow up assessment
03
Healthcare use
At the pre-treatment assessment all participants reported to have consulted their general
practitioner (GP) for their back problem, at least once in the past year, and all of them were
referred to a medical specialist (MS; i.e. orthopaedic surgeon, neurologist, pain consultant,
rheumatologist, physiatrist or anaesthesiologist). Furthermore, at pre-treatment assessment
48% of the participants (n= 41) had consulted at least two different MS in the previous year. At
2-year follow up only a quarter of all participants, 27% (n= 23) reported having consulted their
GP in the last year and 14 of these 23 consulted an MS just once. The remaining 73% consulted
neither a GP nor an MS in that year.
At the pre-treatment assessment most of the participants (94%; n= 80) indicated to have had
physical therapy for their back problem in the previous year. In addition, 15% (n= 13) visited a
psychologist. At 2-year follow up the allied healthcare visits have considerably decreased, 29%
(n= 24) reported to have had physical therapy and only 1% (n= 1) consulted a psychologist for
their back pain-related problems in the last year.
Medication use decreased from 87% (n= 74) at baseline to 43% (n= 37) at 2-year follow up.
At pre-treatment assessment 68% of the participants (n= 58) used analgesics for their back
problem on a structural basis, while 13% (n= 11) did not use any pain medication. The pie charts
in Figure 3.2 show the frequencies of analgesic consumption as classified in WHO analgesic
ladder both at pre-treatment and at 2-year follow up. At 2-year follow up the ‘none-light’
consumption group has increased to almost three quarters of the participants (n= 60; 71%),
while the ‘moderate-severe’ group has decreased to 29% (n= 25).
Outcomes and healthcare use after a pain management programme
51
Figure 3.2 Pie charts illustrating percentages of participants (n= 85) who use pain medication, classified
in accordance with the steps in WHO analgesic ladder[25] and differentiated in consumption groups:
‘none-light’ (green) and ‘moderate-severe’ (red)
Consumption: Pain medication
Pre-treatment assessment
2-year follow-up
03
3%
10%
13%
11%
15%
22%
15%
57%
40%
None
WHO_1B: NSAID
14%
WHO_1A: Paracetamol
WHO_2: Weak Opioid
WHO_3: Strong Opioid
Clinical Relevance
The effect size (Cohens’ d) for functioning (RMDQ) is 1.6 and for functioning-related quality
of life (SF36 PCS) is 1.4. The effect sizes of both measures were larger than 1 and, therefore,
classified as ‘large’.
These results were further substantiated by data related to work status as presented in
Table 3.1. At 2-year follow up, 81% of all participants reported being at work. Eight of the 13
participants who had reported at pre-treatment assessment being unemployed because of
their back problem were working 2 years after the treatment. Moreover, 5 out of 11 participants
who received a disability allowance at baseline indicated having returned to work.
Discussion
The main purpose of this study was to evaluate the 2-year follow up results of the cognitive
behavioral pain management program offered by RealHealth NL in patients with CLBP. We
questioned whether improvements gained in the first year would be maintained and whether
this would be reflected in the use of pain medication and healthcare services. Patients in
our study population appeared to have a mean baseline level of functioning as measured
with RMDQ (13 ±4). This level is indicative for a moderate to severe level of disability, which
is comparable to patients being treated in other trials and daily practice in the Netherlands
52
03
Outcomes and healthcare use after a pain management programme
[8,21]. In this study we confirmed that the previously reported 1-year clinically relevant
effects on daily functioning and quality of life were maintained at the 2-year follow up.
Participants even reported experiencing less pain while performing activities; this decrease
was statistically significant. Moreover, healthcare use (i.e. GP, MS consultations and pain
medication use at 2-year follow up) decreased between baseline and 2-year follow-up
assessment. Positive outcomes of the intervention were further corroborated by work status
data. Most of the participants returned to work, with 81% actually at work at 2-year follow
up. These results suggest that patients who participated managed to incorporate the learned
self-management techniques in daily life and that they changed their occupational and social
behavior.
Many commonly used interventions lack evidence for the maintenance of clinically relevant
long-term effects [4]. This study shows large effect sizes (Cohens’ d= 1.4-1.6). Although we
had five non-responders in the current study they did not differ in patient characteristics
and outcomes at baseline to the included patients. Their dropout was not related to either
the treatment program or the study itself. Therefore, it is noteworthy that patients with
longstanding CLBP complaints, 11 years on average, benefit from this short and intensive pain
management program which is based on international guidelines [9-11]. Post hoc analyses
revealed that no significant correlations existed between duration of CLBP and change in the
outcome measures at 1-year follow up (RMDQ r= 0.05; SF36PCS r= 0.07; current pain r= 0.15;
pain disturbance ADL r= 0.09). The current study results suggest that the duration of CLBP is
not an important factor for the management of CLBP, whereas duration and intensiveness of
the program are important [7,12,21].
It is known that CLBP accounts for considerable healthcare and socioeconomic costs [5,6,14].
These healthcare costs are, among other things, related to sick leave and disability allowance,
referrals to general practitioners and medical specialists, use of allied health care and
pharmaceutical prescriptions for analgesics. Therefore, we evaluated healthcare use on all
of these dimensions of healthcare costs. The results of this study show that healthcare use
is decreased at long-term follow up. A marked reduction of analgesic use is seen and a shift
of most patients is shown from the ‘moderate-severe’ (WHO-steps 1B-3; 65%) to the ‘nonelight’ (none and WHO-step 1A; 71%) category of the WHO-analgesic ladder. Moreover, with
a reduction in analgesic use a decrease of pain intensity and pain experience during daily
activities (VAS scores) is shown, as well as maintenance of these results at 2-year follow up.
In patients with CLBP antidepressants are sometimes prescribed for pain reduction (selective
serotonin reuptake inhibitors [SSRI] and tricyclyc antidepressants [TCA]). We found at baseline
that only 11% used antidepressants (4% TCA and 7% SSRI) and at long-term follow up a
reduction in consumption is seen: only two respondents (2%) reported to use this medication
(2% TCA and none used SSRI). This implies that the program is successful not only on healthcare
use with a reduction in healthcare costs, but also on safety possibly resulting in less adverse
side effects. When the results are extrapolated to the Dutch adult population a quarter of the
patients with CLBP could benefit from this program and therefore an estimated half of the
healthcare costs could be saved.
Outcomes and healthcare use after a pain management programme
Limitations of the study
This study has some limitations. The external validity of the study might be limited, depending
to whom the results are generalized. Since we studied a prospective cohort with carefully
selected patients over a period of time, we have to restrict the generalization to patients with
similar characteristics. The patients included had no indication for a surgical intervention and
they had to confirm that they were motivated to change their behavior with regard to the
back pain complaints. Therefore, generalization to the general population is limited.
We evaluated healthcare use by means of self-reported questionnaires and, therefore, bias
could have been introduced. We took this aspect into account in the design of the study, a
structured post-marketing survey, and by asking the participants to request additional
information at general practitioner or pharmacy if necessary. A possible bias could have been
introduced due to the fact that patients had to recall what happened in the last year.
The intervention described in this study uses a wide range of techniques based on the principles
of CBT. As yet, it is unclear which techniques or parts of the intervention are responsible for the
observed effect. Therefore, we studied the program as an integral program. The main aim of
the study was to evaluate the stability of positive outcomes of a short, intensive intervention
and its impact on healthcare use. Therefore, we did not evaluate frequently reported cognitive
and emotional factors as fear of movement, catastrophizing, and anxiety [4,30-32]. These
cognitive and emotional factors contribute, among other factors, to a certain extent to the
main outcome functioning and quality of life. We showed a long-term significant improvement
on the mental component scale of the SF36, but a closer exploration of these cognitive
behavioral factors and their impact on functionality is needed. Moreover, patients attending
in this program have to be motivated to change behavior. Although a selection criterion for
treatment, we neither assessed this factor at baseline nor assessed it systematically over
time. Therefore, a clear description of ‘motivation to change behavior’ in the subgroup of CLBP
patients benefitting from this program cannot be given. ‘Readiness or motivation to change
pain-related behavior’ is a multidimensional construct recently described in the literature
[33,34]. As individuals may vary in their readiness to learn and adopt new coping skills or selfmanagement strategies it may be a key element in understanding how participants benefit or
fail to benefit from this program.
Conclusion
In a selected and motivated group of patients with longstanding CLBP the results of a
short, intensive cognitive behavioral pain management program gained in the first year are
maintained at 2-year follow up. Above all, at follow up most of the participants are at work,
they perform a gainful employment, and the results suggested that the use of both pain
medication and healthcare have decreased substantially.
Acknowledgement
The authors thank Mrs. P.G. Anderson for her editorial comments.
53
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54
Outcomes and healthcare use after a pain management programme
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Chapter 04
Predictive factors for successful
outcome one year after an intensive
combined physical and psychological
programme for chronic low back pain
Van Hooff ML
Spruit M
O’Dowd JK
van Lankveld W
Fairbank JC
van Limbeek J
Published in: Eur Spine J. 2014;23(1):102-12
58
Abstract
Purpose: The aim of this longitudinal study is to determine the factors, which predict a
successful 1-year outcome from an intensive combined physical and psychological (CPP)
programme in chronic low back pain (CLBP) patients.
Methods: A prospective cohort of 524 selected consecutive CLBP patients was followed.
Potential predictive factors included demographic characteristics, disability, pain and
cognitive behavioural factors as measured at pre-treatment assessment. The primary outcome
measure was the Oswestry Disability Index (ODI). A successful 1-year follow-up outcome was
defined as a functional status equivalent to ‘normal’ and healthy populations (ODI ≤22). The
2-week residential programme fulfills the recommendations in international guidelines. For
statistical analysis we divided the database into two equal samples. A random sample was
used to develop a prediction model with multivariate logistic regression. The remaining cases
were used to validate this model.
Results: The final predictive model suggested being ‘in employment’ pre-treatment (OR 3.61
[95%CI 1.80-7.26]) and an initial ‘disability score’ (OR 0.94 [95%CI 0.92-0.97]) as significant
predictive factors for a successful 1-year outcome (R2=22%; 67% correctly classified). There
was no predictive value from measures of psychological distress.
Conclusion: CLBP patients who are in work and mild to moderately disabled at the start of a
CPP programme are most likely to benefit from it and to have a successful treatment outcome.
In these patients the disability score falls to values seen in healthy populations. This small set
of factors is easily identified, allowing selection for programme entry and triage to alternative
treatment regimes.
Prediction of successful outcome after a pain management programme
59
Introduction
Chronic low back pain (CLBP) is a major cause of distress and disability and in the Netherlands
CLBP accounts for considerable healthcare and socioeconomic costs [1,2]. CLBP is defined as
back symptoms persisting for at least 3 months [3] and these symptoms are associated with
persistent or recurrent disability. Multiple studies have emphasized the psychosocial influence
on the development of chronicity and the persistence of pain complaints [4-6]. Increased
distress accompanies more severe pain, enhances pain-related disability and contributes to
the development of chronicity of LBP [7-9]. Some evidence suggests that fear of movement [8]
and catastrophizing [8,10,11] play a role when pain has become persistent.
In line with these findings, international guidelines [12-14] and a Cochrane review [15] have
recommended multidimensional interventions using a cognitive behavioural approach to
improve psychological and physical functioning. However, most of the interventions studied
show only small, short-lived effects [7,15-17]. One explanation for these small effects could
be the heterogeneity of the CLBP population studied. Although the aetiology of chronic
low back pain remains unknown, it has been suggested that several subgroups could be
identified amongst CLBP patients who are likely to benefit from specific recommended
interventions [14]. It is possible that the efficacy of the interventions employing physical and
cognitive behavioural approaches would be improved by matching interventions to patient
characteristics.
Multiple studies, including several systematic reviews, have studied patient characteristics
to identify potentially predictive factors for treatment outcome in CLBP [6,18,19]. In the most
recent review, Van der Hulst et al. [6] analyzed the prognostic value of numerous biomedical,
demographic and psychosocial factors in 17 internally valid studies (n=3,356) to determine
the multidisciplinary rehabilitation treatment outcome in patients with non-specific CLBP.
Due to methodological flaws in the included studies, they were not able to define a generic
set of predictive factors. These methodological problems include heterogeneity in the study
populations, the high number of prognostic factors, and the wide variety of treatment
and outcome measures. Against this background, more research related to the subject is
warranted.
A recent study reviewed the results of a short, intensive, 2-week residential combined physical
and psychological (CPP) programme for patients with longstanding CLBP who were not
eligible for spinal surgery. The main goal of that programme is to improve daily functioning.
On average, there was a large, clinically relevant improvement in terms of both disability
and quality of life. Both remained stable during the following 12 months [20]. Two years after
participation in that programme, not only did these post-treatment improvements remain
consistent, there was a substantial reduction in healthcare use and an increased return to
work [21]. Although large effect sizes for disability had been found, the study showed a wide
range in the improvements of disability among participants. Identifying the predictive factors
associated with improvement in disability would enable the selection of those CLBP patients
who are most likely to benefit from such a programme, and ultimately, to develop treatment
regimes for those who will not.
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Prediction of successful outcome after a pain management programme
The purpose of this longitudinal study is to determine those factors pre-treatment that
predict a successful CPP programme outcome. We defined successful outcome as a clinically
relevant and consistent improvement at 1-year follow up towards the values seen in healthy
populations. The data from524 consecutive CLBP patients were used to answer this. We
expected that the pre-treatment degree of experienced pain intensity, belief in the ability to
manage and to cope with CLBP complaints, the degree of disability, and employment status
were the most likely predictive factors for treatment outcome. We expected high psychological
distress to be an indicator of poor outcome [8,22,23].
04
Methods
Study design
The predictive value of patient characteristics, including disability, pain severity, cognitive and
behavioural factors were analysed prospectively. These analyses were related to the patient’s
disability 12 months following the 2-week residential CPP programme.
Patients
The study group consisted of patients with CLBP referred to a tertiary orthopaedic hospital,
specialized in spine care. Patients who had not improved following conservative treatment
delivered in primary care [21] and who were not eligible for spinal surgery or invasive pain
management were referred by the spine surgeons for the CPP programme. The main inclusion
criteria were (1) low back pain for at least 6 months, (2) age between 18 and 65 years, (3)
willingness to change behaviour, (4) willingness to follow the 2-week programme in a hotel
facility, and (5) able to speak and read Dutch. The main exclusion criteria were involvement
in litigation and/or compensation claims and psychiatric disorders as formally and primarily
diagnosed by psychiatrists, in accordance with the DSMIV classification. Final inclusion was
based on an extensive intake procedure and all patients were assessed by a multidisciplinary
team consisting of a psychologist, a physiotherapist, an occupational therapist, and a
movement teacher.
Intervention
The CPP programme is NICE guidelines compliant [14]; it is a CPP residential 2-week
programme including a cognitive behavioural approach. The programme runs in collaboration
with the spine surgeons. The group-orientated training sessions in the 2-week programme are
delivered by a multidisciplinary team, extensively trained in cognitive behavioural techniques
for chronic pain. The programme involves 100 h of patient contact time, delivered in a grouporientated residential setting, including 40 h of cognitive behavioral training, 30 h of physical
activities, and a 10 h of education. It includes a pre-treatment assessment day, the 10-day
residential programme, and 1 day follow-up assessments at 1 and 12 months post-treatment.
The main goal of the intervention is to improve daily function, and this is made clear to the
patient. This goal is achieved by increasing the participant’s ability to self-manage, addressing
the psychological impact of pain, and increasing physical condition; all are directed towards
decreasing disability and thus enhancing future return to work. A more detailed description of
the intervention is reported in a previously published article [20].
Prediction of successful outcome after a pain management programme
61
Outcome measures
We used a self-report questionnaire at pre-treatment, at the end of the 2-week residential
programme (post-treatment), and at 12-months follow up. These assessments are an integral
part of the programme. At pre-treatment assessment, participants provided information on
medical history, pain history, pain scores, consumption of pain medication, and employment
status.
In this study, age was categorized in tertiles (years; age ≤42, 43-50, >50). We dichotomized
values for the consumption of pain medication and employment status (‘employed’) into (1=
yes; 0= no). At each assessment participants completed questionnaires on functional status,
pain severity, psychological distress, self-efficacy, pain catastrophizing, and fear of movement.
All these self-report measures have previously been validated in CLBP samples.
Self-report measures
The primary outcome variable for this study is functional status as measured by the Oswestry
Disability Index (ODI, version 1.0 in Dutch) [24]. The ODI measures the impact of LBP on daily
functioning in ten domains of daily life. In ‘normal’ healthy populations the weighted mean
ODI score is 10 (SD range 2-12) and in chronic back pain 43.3 (SD range 10-21) [25].
We used several secondary outcome variables to quantify aspects of physical and psychosocial
functioning.
(1) Current pain severity was assessed with the Numeric Rating Scale (NRSseverity) [26], which is
used to measure the experienced intensity of pain. The ordinal scores range from 0 to 100,
with higher scores indicating higher levels of pain intensity.
(2) The Modified Zung Self-Rating Depression Scale (ZSDS) [27] is an indicator of psychological
distress and depression. Patients are asked to rate 23 items on a four-point ordinal scale.
Total scores range between 0 and 69, with higher scores indicating higher levels of
depressed mood. For patients with CLBP, the following classification has been given: <17
‘normal’, 17-33 ‘at risk’ and >33 ‘depressed mood’ [28].
(3) We used the Pain Self-Efficacy Questionnaire (PSEQ, Dutch translation) [29] to measure the
strength of the patient’s belief about the ability to accomplish a range of activities despite
the pain. The PSEQ is a ten-item inventory with responses rated on a seven-point ordinal
scale. The total score ranges from 0 to 60, with higher scores indicating higher perceived
self-efficacy beliefs.
(4) Dysfunctional cognitive behavioural factors (i.e. pain-related catastrophizing and fear of
movement) were assessed with the Pain Catastrophizing Scale (PCS) and the Tampa Scale
for Kinesiophobia (TSK). We used a Dutch translation of the PCS based on the original
version [30]. The items are scored on a five-point ordinal scale. The total score is between
0 and 52 points, with higher scores reflecting higher levels of pain catastrophizing. Fear
of movement/(re)injury in individuals with pain was measured by the TSK [27,31,32]. The
unweighted sum score ranges between 17 and 68 points, with higher scores indicating
higher levels of fear of movement.
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Prediction of successful outcome after a pain management programme
Data analysis
Descriptive analysis
Pre-treatment patient characteristics were descriptively summarized, with categorical
data in count and percentages and continuous variables as means and standard deviations
(SD). The percentage non-responders were calculated and the pre-treatment data of nonresponders and responders compared. To evaluate differences between both groups at pretreatment, we used Chi square tests for categorical variables and independent Student’s t
tests for continuous variables.
04
Definition of ‘ successful treatment outcome’
The ODI as the primary outcome measure was used to define successful treatment. ‘Normal’
healthy populations have an ODI mean score of 10 (SD 2-12) [25]. Therefore, being successful
was defined as having reached a maximum of 22 points on the ODI at the 1-year follow up,
including the maximum reported standard deviation of 12 points (mean plus 2 SD). The scores
of the patients were then dichotomized into ‘success’ (value= 1) and ‘failure’ (value= 0) for the
programme, and both groups were compared to pre-treatment characteristics.
Prediction analysis
We considered all pre-treatment variables as factors that could influence the outcome. These
influencing factors were identified by a prediction model. To develop the prediction model,
associated factors were first identified by using Pearson’s correlation coefficients. To predict
those factors with contribution to the probability of a successful outcome, a univariate logistic
regression analysis was performed. Subsequently, we randomly divided the complete dataset
into two equal samples. One sample was used to develop the final prediction model, and the
second was used to validate that model. The final prediction model with odds ratios (OR) and
95% confidence intervals (95%CI) for predictive factors, was based on a multivariate logistic
regression analysis. The dichotomized primary outcome variable disability (success/failure)
was used as the dependent variable in this model. In one block the identified and significant
pre-treatment patient characteristics and pre-treatment values on secondary outcomes were
entered into the model as independent variables. A forward, stepwise selection method was
used for analysis. The procedure starts with the independent variable that correlates most
strongly with the dependent variable. Subsequently, the next independent variable is selected
and added to the final model. The remaining cases were used to validate the final prediction
model that had been developed. For this procedure, the identified predictive factors from the
model developed were entered into the model as independent variables.
This final prediction model was then used to calculate a pre-treatment probability as to
whether an individual patient belongs to the group that will have a successful treatment
outcome. This is estimated with the formula: p (success/failure)= ef(x) / 1+ef(x). For this purpose,
all identified significant predictor variables were included in the logistic function: f(x) =
a+b1x1+b2x2 … bkxk. The calculated probabilities are between 0 and 1, and interpreted as
follows: <0.5 probability in favour of failure, >0.5 probability in favour of success, and 0.5 equal
likelihood for either outcome.
In the literature it has been hypothesized that patients with high psychological distress have
a poor outcome [22], and more specifically, that the level of depressed mood contributes to
pain-related disability [7,8]. Where in the above multivariate logistic regression analysis,
Prediction of successful outcome after a pain management programme
63
psychological distress appeared to be a predictive value for treatment outcome, additional
separate analyses are performed.
All data analyses were performed using SPSS version 18.0. An α of 0.05 was considered
statistically significant. A scatter plot to give an illustration of disability in the study sample
was created in STATA version 10.0.
Missing data
As self-report questionnaires were used as outcome measures, we expected missing data
during the follow-ups. To handle such missing data, the multiple imputation (MI) method
was used under the assumption that the data were ‘missing at random’ (MAR). This implies
that the missing data are related to other observed or documented patient data but not to
unobserved outcomes. The MI-technique replaces each missing value of the incomplete data
set with a set of plausible values (n= 10, current study), derived from the available data. These
values represent the uncertainty in the correct value to impute. To generate these values to
impute, the data augmentation Markov chain Monte Carlo replacement method was used.
In this study ten datasets were generated; each generated dataset was analysed according to
the previously mentioned statistical tests. Overall means, beta weights and standard errors
were calculated.
Results
Study population
The spine surgeons recruited 727 CLBP-patients for pre-treatment assessment. Between
October 2006 and January 2011, 524 patients (72.1%) were included and participated in the
programme. Of this sample (n=524), 67 patients (12.8%) had data missing from at least one
assessment after the pre-treatment assessment. The flow diagram (Figure4.1) shows the
available patient data at each stage of the study. At post-treatment assessment, data for 25
patients were missing. These included the first group of ten patients where this assessment
had not been conducted. In addition, 15 patients left during the 2-week residential
programme. The missing data of the remaining 42 patients were randomly divided between
the 1- and 12-month assessments. These 67 (25+42) patients with missing data are not
significantly different from the patients with complete data sets with regard to pre-treatment
characteristics and the pre-treatment scores on the various outcome measures: ODI, PCS, TSK,
NRSseverity, ZSDS, and PSEQ.
General pre-treatment characteristics for the complete study population (n=524) are given in
Table 4.1. The reported mean age was 45 (±9.6) years; a small majority was female (58%). The
mean LBP duration was 13 (±10.8) years, indicating that our study population had longstanding
CLBP. At pre-treatment assessment, two-thirds of the patients were at work (68%); one third
had undergone surgery for LBP. 04
64
Prediction of successful outcome after a pain management programme
Figure 4.1 Flow diagram of CLBP patients recruited by the spine surgeons at the outpatient orthopaedic
department for the CPP programme and handling of the data of these patients
Recruited (n= 727)
Attending intake procedure
(multidisciplinary team)
04
Included (n= 524)
Participating in CPP programme
Excluded after intake procedure (n= 727)
I. Failed to meet inclusion criteria
• Prefer biomedical treatment
(n= 36)
• Age
(n= 2)
• Language
(n= 3)
• Individual approach required
(n= 42)
• Mental / Physical ability
(n= 22)
II. Included, but decided not to join
III.Included, but wished to postpone their
participation until a later time
IV.Reason unknown
Prediction model:
Development
Random sample
(n= 262) Imputation
Prediction model:
Validation
Random sample
(n= 262) Imputation
(n= 47)
(n= 44)
(n= 7)
Patients with missing data (n= 67)
No data post-treatment (n= 25)
• No post-treatment assessment
(n= 10)
• Left during 2-week programme
(n= 15)
- Lack of motivation
(n= 8)
- Illness
(n= 4)
- Family circumstances
(n= 3)
No data at follow-up * (n= 42)
• 1-month follow-up assessment
(n= 20)
• 1-year follow-up assessment
(n= 22)
* Missing data random divided between 1 and 12 months follow-up
Handling of data: all cases (n= 524)
Study sample analysed with
Multiple Imputation techniques
(n= 105)
Prediction of successful outcome after a pain management programme
65
Table 4.1 Pre-treatment characteristics reported by patients with CLBP participating in the CPP
programme (n= 524)
Pre-treatment characteristics
Total (n=524)
Disability
categorical variables
n (%)
Successa (n=217)
n (%)
Failurea (n=307)
n (%)
Gender, female
303 (57.8)
118 (54.4)b
185 (60.3)b
Employment status, yes
356 (67.9)
194 (89.4)c
162 (52.8)c
Pain medication, yes
454 (86.6)
176 (81.1)d
278 (90.6)d
Previous surgery, yes
169 (32.3)
54 (24.9)e
115 (37.5)e
Sociodemographic
CLBP History
Pre-treatment characteristics
Total (n=524)
Disability
continuous variables
mean (SD)
Success (n=217)
mean (SD)f
Failurea (n=307)
mean (SD)f
45.4 (± 9.6)
43.7 (± 9.2)
46.6 (± 9.8)
12.5 (± 10.8)
11.7 (± 9.9)
13.0 (± 11.3)
41.4 (± 14.1)
33.7 (± 13.1)
46.8 (± 12.0)
ZSDS Zung Self-rated Depression Scale
26.2 (± 9.3)
24.4 (± 9.9)
27.5 (± 8.6)
NRS Numeric Rating Scale
60.7 (± 21.1)
56.4 (± 22.2)
63.7 (± 19.8)
PCS Pain Catastrophizing Scale
22.9 (± 8.9)
22.3 (± 8.7)
23.4 (± 8.9)
TSK Tampa Scale for Kinesiophobia
39.6 (± 6.4)
39.0 (± 6.5)
40.0 (± 6.4)
PSEQ Pain Self-Efficacy Questionnaire
32.4 (± 10.8)
36.3 (± 10.1)
29.6 (± 10.4)
a
Sociodemographic
Age, in years
CLBP History
Duration of LBP, in years
Primary outcome
ODI Oswestry Disability Index
Secondary outcomes
Success number of patients reaching at 1-year follow up a ‘normal’ value of ten points on ODI (SD 12); Failure number of patients reaching at
1-year follow up an ODI value of >22 points
b 2
χ = 1.80, p= 0.21; c χ2 = 78.32, p<0.001; d χ2 = 9.81, p<0.05; e χ2 = 9.20, p<0.05
f
All variables p<0.001
a
Table 4.2 Means and standard deviations (SD) for the primary outcome of disability as measured with
the Oswestry Disability Index (ODI) in this study and in reference populations
Mean
SD
Pre-treatment assessment
41.4
14.1
One-year follow-up assessment
27.6
16.4
‘Normal’ population [25] (n=461)
10.2
Range 2.2-12.0
Chronic back pain population [25] (n=1,530)
43.3
Range 10.0-21.0
RealHealthNL programme (n=524)
a
b
b
a
Current study; b Values based on different study populations
04
66
04
Prediction of successful outcome after a pain management programme
Disability in the study sample
As shown in Table 4.2, the mean pre-treatment disability (ODI) score for the study sample is
comparable with the reported weighted mean score in chronic back pain populations [25]
(41.4 [SD 14.1] and 43.3 [SD range 10.0-21.0], respectively). Figure 4.2 shows that most of the
patients are improved at one-year follow up (green values). Moreover, at one-year follow up
217 patients (41.4%) reached the value for disability as measured in ‘normal’ populations; the
green values below the black dashed horizontal line. Of these patients, 60 (27.7%) already
had an ODI pre-treatment value of 22 or less. At one-year follow up, the mean improvement
in disability was 31.0% in relation to the pre-treatment value (25th percentile 59.0%; 50th
percentile 32.3%; 75th percentile 8.5%).
Figure 4.2 Functional status as measured with the ODI (0-100) in the study sample (n= 524).
Prediction model for success at one-year follow up
Overall, small Pearson correlations were found between pre-treatment patient characteristics
and pre-treatment values for primary and secondary outcome measures as well as the
outcome of being successful on the ODI; Pearsons’ r ranging from <0.01 (pre-treatment
pain duration) to 0.62 (pre-treatment disability). This means that no strong co-linearity
exists between different variables and successful outcome. In Table 4.1 the pre-treatment
characteristics are described for the success and failure groups after the programme. As
shown in Table 4.1, all but one categorical variable (‘gender’; χ2= 1.80, p= 0.21) as well as all
the continuous variables were significantly associated with the outcome of 1-year successful
diminution of perceived disability. A univariate logistic regression model was built with all
these variables entered in one block. Pre-treatment age categories, previous surgery, being
employed as well as pre-treatment pain self-efficacy and pre-treatment disability appeared
to be potential predictor variables. With a forward selection method and in one block, these
variables were included in the model. The final prediction model revealed being employed (OR
3.61 [95%CI 1.80-7.26]) and pre-treatment disability (OR 0.94 [95%CI 0.92-0.97]) as significantly
contributing factors for clinically relevant improvement in disability, defined as having values
Prediction of successful outcome after a pain management programme
67
measured in ‘normal’ populations (Table 4.3). No interaction effects between different pretreatment characteristics were found. Moreover, the results obtained by the ten databases
that were generated from the MI-database produced the same result.
These results imply that a patient has a 1.3-fold risk of failure in the programme when not
employed at the pre-treatment assessment. Moreover, the predictive value of disability is
protective, meaning that for each point that the pre-treatment ODI-score is closer to the
normal value, the probability that that patient will meet the success criterion increases by
6.0%. Overall, using this final model, 66.8% of the participants had been correctly classified as
being successful.
The validity of the model was checked with the remaining cases (n= 262; Table 4.4). A
multivariate prediction model with the same variables as found in the prediction model that
had been developed was built. As shown in Table 4.4, the results are comparable to those found
using the other half of the dataset. However, most of the 95%CI limits around the calculated
OR’s (Exp [b]) are broader. This means that the model is less precise for the second half of the
dataset, even though both the explained variance and the percentage participants correctly
classified are higher than that found for the model developed with the first half of the dataset
(R2= 40.0% [Hosmer & Lemeshow]) and 75.0%, respectively).
To predict a patient’s probability of being successful after having participated in the
programme, the identified contributing factors were included in the logistic function. For
example, a patient who is employed at pre-treatment assessment, and who has a pretreatment ODI value of 35, is classified as probably being successful in the programme (p=
0.70). On the other hand, a patient who is not employed at pre-treatment assessment, and
who has a pre-treatment ODI value of 60, will probably be a failure in the programme (p= 0.13).
Contribution of psychological distress
As psychological distress appeared not to be a predictive factor for treatment outcome, a
separate analysis was not performed. Therefore, there is no evidence to support the hypothesis
that an association exists between ‘depressed mood’ and failure 1 year after the programme.
04
68
Prediction of successful outcome after a pain management programme
Table 4.3 Development of a multivariate logistic regression model for being successful at 1-year follow
up (n= 262; 50% random selection of cases).
Forward selection method
Β (SE)
Wald
p
(final model)
95% Confidence Interval for Exp (b)
Lower
Exp (b)
Upper
0.91
0.93
0.95
Included:
Step 1.
04
Functional status (ODI)
-0.07 (0.01)
37.35
0.00
Constant
2.39 (0.48)
24.97
0.00
Employed
1.28 (0.36)
12.97
0.00
1.80
3.61
7.26
Functional status (ODI)
-0.06 (0.01)
24.32
0.00
0.92
0.94
0.97
Constant
1.62 (0.52)
9.69
0.002
10.88
Step 2.
5.05
R2= 0.22 (Hosmer & Lemeshow), 0.17 (Cox & Snell), 0.23 (Nagelkerke)
Model χ2(2)= 62,136 p<0.001; 66.8% correct classification
ODI, Oswestry Disability Index
Table 4.4 Validation of developed multivariate logistic regression model for being successful at 1-year
follow up (n= 262; 50% remaining cases).
Forward selection method
Β (SE)
Wald
p
(final model)
95% Confidence Interval for Exp (b)
Lower
Exp (b)
Upper
0.88
0.91
0.93
Included:
Step 1.
Functional status (ODI)
-0.09 (0.01)
50.74
0.00
Constant
3.70 (0.56)
43.20
0.00
Employed
1.84 (0.40)
21.39
0.00
1.96
6.29
13.70
Functional status (ODI)
-0.09 (0.01)
36.47
0.00
0.89
0.92
0.94
Constant
2.80 (0.61)
21.23
0.00
40.35
Step 2.
R = 0.40 (Hosmer & Lemeshow), 0.25 (Cox & Snell), 0.34 (Nagelkerke)
2
Model χ2(2)= 101,651 p<0.001; 75.0% correct classification
ODI, Oswestry Disability Index
16.38
Prediction of successful outcome after a pain management programme
69
Discussion
The most important finding of this longitudinal study is that being employed, and the level of
disability before treatment are predictive factors for relevant improvement in CLBP patients’
functional status at 1-year follow up. In contrast to our expectation, the pre-treatment degree
of experienced pain intensity and belief in one’s ability to manage and to cope with chronic
low back pain (CLBP) complaints appeared not to be predictive of outcome. Moreover, the
results revealed that 1 year after the programme, highly distressed patients who were referred
to the programme, were not at risk of being a failure.
Previously, this combined physical and psychological (CPP) programme has been evaluated
for patients who met the inclusion criteria [20,21]. The present analysis was conducted to
determine whether it would be possible to enhance the efficacy of the programme by further
patient selection by identifying a subgroup of patients who could benefit of the programme.
As the main goal of the intervention is to improve disability, success at 1-year follow up was
defined as having reached 22 points or lower on the ODI. We reasoned that less change is not
clinically relevant.
A minimal clinical important difference (MCID) of ten points on the ODI has been recommended
as a measure for clinical relevancy in CLBP [33]. Although consensus has been reached for this
MCID value, the value is still arbitrary because some of the studies upon which the consensus
is based contain heterogeneous CLBP-population samples and were derived from primary care
[33]. It is difficult to measure what is clinically relevant to patients [34]. Patients who are highly
disabled at pre-treatment assessment and who did reach the MCID value after treatment
could be classified as improved success whilst in fact they are still disabled. Therefore, we
decided to use ODI values seen in ‘normal’ healthy populations as a measure of success. The
current study results show that at 1-year follow up 217 patients (41.4%) reached this ODI value.
With the exception of one study, which was performed in primary care [35] and included CLBP
patients who were who were still at work and who were less disabled (ODI 20 [range 2-52]),
we are not aware of any studies performed in secondary or tertiary care investigating factors
predicting a functional outcome related to ‘normal’ and healthy populations.
Prediction model: pre-treatment ‘employed’ and pre-treatment ‘disability’
Being employed appeared to be the most important predictive factor (OR 3.61 [95%CI 1.807.26]; dichotomized). To a lesser extent, the level of pre-treatment disability predicts the
outcome (OR 0.94 [95%CI 0.92-0.97]; decrease per point on ODI). These findings are consistent
with the results of the systematic review by Van der Hulst et al. [6]. We recommend screening
CLBP patients for these factors. It is known that CLBP patients who are significantly disabled
and who are absent from work pre-treatment have a poor outcome [36,37]. The ODI might have
screening potential as it has been shown to be of predictive value for chronicity [37]. Patients
who are moderately disabled and who are at least partially employed before treatment
could be given a higher priority for entry into a CPP programme. From an organisational and
economic perspective, patients who are at work and who are mildly disabled might benefit
from a shortened programme. To substantiate these ideas more research is needed.
04
70
04
Prediction of successful outcome after a pain management programme
In the current study the prediction model (Table 4.3) has wider confidence intervals for the
validation model (Table 4.4), and a lower explained variance (R2 22% versus 40% [Hosmer &
Lemeshow]), resulting in a greater number of cases correctly classified (67% versus 75%)
for the validation model. Because of these discrepancies and to estimate the stability of
the prediction model we performed a post-hoc multivariate logistic regression analysis on
the random sample (n=252) using a bootstrap procedure that is 500 repeated samples with
replacement. All potential prediction variables were then entered in one block. This result
is comparable to the final prediction model (Model χ2[5]= 68,157 p<0.001; R2 24% [Hosmer
& Lemeshow]; 23% [Cox & Snell]; 31% [Nagelkerke]; 70% correct classified). Based on these
results we conclude that the final prediction model, as initially developed, is robust. This model
explains 22% (Hosmer & Lemeshow) of the total variance. Moreover, 67% of the patients were
correctly classified. Although inconsistent evidence does exist for predictive factors that were
identified for outcome of interventions with a physical and cognitive behavioural approach,
a comparable and typical low amount of explained variance has been found [38-41]; as well
as the percentage correctly classified patients [42]. Because physical and psychosocial factors
only marginally contribute to treatment success, other non-specific or moderating factors
such as clear treatment rationale, a highly structured programme, providing a pressurecooker model programme, the dose of treatment, skilful staff, and the patient’s readiness
to change pain-related behaviour have been proposed as being predictive for a successful
outcome [11,43,44]. There are two increasingly suggested specific contributing factors to
functional treatment outcome in chronic musculoskeletal pain: expectancy of treatment
outcome [45] and central sensitisation [46-48]. Central sensitization includes features of
referred pain, hypersensitivity to peripheral stimuli and neuropathic pain, which are felt to
represent peripheral manifestations of augmented central pain sensations. However, further
research is required to determine which specific factors contribute to a successful outcome
for CLBP patients in a CPP programme.
Some inconsistent qualitative evidence has been reported which is related to other potential
and a priori predictive factors that might be expected for this study: experienced pain intensity
[6,49], gender [7,23], or self-efficacy [35,50,51]. However, no support for these predictive
factors could be found in the present study. It has also been suggested that improvement
of dysfunctional cognitive behavioural factors such as catastrophizing cognitions and fear
of movement behaviour might contribute to a successful outcome [11,52]. This suggestion is
endorsed by the fear avoidance model (FAM) which postulates a causal relationship between
pain catastrophizing, fear of movement, disability and experienced pain severity [4]. Some
studies have concluded that the impact of these dysfunctional cognitive behavioural factors
on outcome measures as pain as well as functional status are diminished [15,53] or are even
absent [6], which is consistent with the results of the present study.
Studies investigating the predictive value of psychological distress have only yielded
inconclusive and tentative evidence [6,15]. Self-rated depressive mood has been reported to
be of prognostic value [8,18,22,39,54]; furthermore, it has been suggested that patients with
reported symptoms would benefit less from a multidisciplinary programme compared to
patients with no or only mildly depressive symptoms [7,18,23]. In the current study, despite
a small association between the level of distress and being successful at 1-year follow up
(Pearson’s r –0.23, p<0.001), no predictive value of psychological distress could be found in the
final prediction model. This means that CLBP patients who are distressed at pre-treatment
assessment might benefit from a CPP programme.
Prediction of successful outcome after a pain management programme
Strengths and Limitations
The strengths of this study are the large sample size (n= 524) and the wide range of available
pre-treatment data. This means there was enough statistical power to study the contribution
of the different potential predictive factors towards successful treatment outcome over
time. Although data were missing on at least one assessment for 67 (13%) patients, no pretreatment differences between non-responders and responders were seen. Our main results
are based on the multiple imputation (MI) technique. MI is a technique that depends on
model-based imputation of multiple values for each missing observation instead of only
one estimate as in single imputation techniques. The major advantage of this method, over
single imputation techniques or ‘complete cases only’, is that it does not underestimate
variability. Single imputation methods could result in the estimated standard errors being too
small, whereas multiple imputation results in the correct magnitude for estimated standard
errors and confidence intervals [55,56], i.e. these imputed values reflect the uncertainty in
estimation caused by the missing values [56]. Thus, the information contained within the
missing data seems similar in nature to the information actually documented. This implies
that the conclusions based on the results obtained with MI are robust. Moreover, the large
study sample gave us the opportunity to develop a prediction model in a 50% random sample
of the original set and to validate and check this final model with the remaining data.
Limitations in this study include possible selection bias. Therefore, generalization to common
clinical practice is limited as our findings are theoretically relevant only to specialised back
care. There are no data for those patients not selected (28%), it is possible that other factors
could be predictive for a successful treatment outcome. It is possible that these patients were
not ready or motivated to change pain-related behaviour. Although a selection criterion for
treatment, we neither assessed this factor in a valid and reproducible way at pre-treatment
nor assessed it systematically over time. Further research is needed to assess this factor and to
evaluate its contribution to the outcome.
Conclusion
The study results imply that CLBP patients who are in work and mild to moderately disabled
at the start of a CPP programme benefit from it and have a successful treatment outcome. In
these patients the disability falls to values seen in healthy populations. Even psychologically
highly distressed patients may respond positively to this programme. The limited number of
predictive indicators is extremely useful. The small set of easily identified indicators might
speed up assigning priority for programme entry and triage to alternative treatment regimes.
Acknowledgement
The authors thank the multidisciplinary team at RealHealthNL who were responsible for the
assessments and treatment of the participants in the CPP programme. Particular thanks to
Patricia G. Anderson for her editorial assistance.
71
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72
Prediction of successful outcome after a pain management programme
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THEME B:
Outcomes assessment
76
77
Chapter 05
Evidence and practice
of spine registries
A systematic review and recommendations
for future design of registries
van Hooff ML
Jacobs WCH
Willems PC
Wouters WJM
de Kleuver M
Peul WC
Ostelo RWJG
Fritzell P
Published in: Acta Orthop. 2015;86(5):534-44
Appendix to Chapter 05 - editorial comment
(after Chapter 06 - page 130-133)
Guest editorial:
Spinal disorders, quality-based healthcare and spinal registers
Fairbank JCT
Published in: Acta Orthop. 2015; 86 (5): 521–522
78
Abstract
Purpose: We performed a systematic review and a survey in order to 1) evaluate the evidence
for the impact of spine registries on quality of spine care, and with that, on patient-related
outcomes, and 2) evaluate the methodology used to organize, analyze, and report the ‘quality
of spine care’ from spine registries.
Methods: To study the impact, the literature on all spinal disorders was searched. To study
methodology, the search was restricted to degenerative spinal disorders. The risk of bias in the
included studies was assessed with the Newcastle-Ottawa Scale. Additionally, a survey among
registry representatives was performed to acquire information about the methodology and
practice of existing registries.
Results: 4,273 unique references up to May 2014 were identified and 1,210 were eligible for
screening and assessment. No studies on Impact were identified, but 34 studies were identified
to study the methodology. Half of these studies (17 of the 34) were judged to have a high risk of
bias. The survey identified 25 spine registries, representing 14 countries. The organization of
these registries, methods, analytical approaches and dissemination of results are presented.
Interpretation: We found a lack of evidence that registries have had an impact on the quality of
spine care, regardless of whether the intervention was non-surgical and/or surgical. To improve
the quality of evidence published with registry data we present several recommendations.
Application of these recommendations could lead to registries showing trends, monitoring
the quality of spine care given, and ultimately improving the value of the care delivered to
patients with degenerative spinal disorders.
Evidence and practice in spine registries
79
Introduction
Lumbar spine disorders are a heterogeneous group of conditions with a lack of diagnostic
clarity. Thus, in both surgical and non-surgical spinal interventions there are large variations
in practice. The increasing frequency of spine-related interventions with increasing costs
has led to a shift towards the delivery of value-based spine care [1]. Here, value is expressed
as patient-centred outcomes (safety and effectiveness; quality) divided by the related costs
of care or per unit cost [2]. While Randomized Clinical Trials (RCTs) are considered the gold
standard for assessing the efficacy of interventions, the difficulties with RCTs, specifically
for assessing surgical procedures in spinal disorders, are acknowledged [3]. Some barriers
are surgeon preferences, patient selection, patients’ reluctance regarding randomization,
difficulties in blinding, high cost, the need for long-term follow up, the often high proportions
of loss to follow up, and the problem with crossover. Well-designed observational cohort
studies, reflecting daily clinical practice, have been reported to produce as trustworthy and
externally valid results as RCTs [4-6], [7-10].
An outcome registry is an organized system that uses observational study methods [11],
based on STROBE recommendations [12]. Registries could therefore, be used to describe care
patterns, including appropriateness of care and disparities in the delivery of care. Registry data
could also be used to understand variations in treatment and outcomes and to identify and
select subgroups in the heterogeneous chronic low back pain population, with a probability
of successful or poor outcome. The ultimate goal of health services registries is to increase
value of delivered care (i.e. outcome per unit cost) [13]. Moreover, it has been suggested that
measuring with continuous feedback (audit cycles) of outcomes captured in registries raises
the awareness and improves quality of care [14]). However, as yet, little is known about the
effect of registries on the quality of spine care and the methods for registering and feedback.
This study had 2 aims: 1) to evaluate the available evidence for the effect and possible impact
of introducing and using spine registries on quality of spine care after any intervention and
on patient-related outcomes; 2) to evaluate the methodology used to organize, analyze, and
report the ‘quality of spine care’ from spine registries.
Methods
We performed a systematic review according to the PRISMA statement for reporting in
systematic reviews and meta-analyses [15]. In addition, for the second aim (regarding
methodology) a survey among spine registry representatives was performed to acquire
information about the current status of existing spine registries. The complete protocol of
this study was presented at the preconference meeting of the International Society for the
Study of the Lumbar Spine 2014 (ISSLS) [16]. Selection of studies and appraisal of their quality
was performed independently by MH and WJ. Discrepancies were discussed during consensus
meetings, with mediation by a third author (PW) were disagreements persisted.
Search
A comprehensive search was conducted because terminology in the field of chronic low back
pain is not yet standardized, and because we aimed to include both randomized and non-
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Evidence and practice in spine registries
randomized studies. The search was performed by one of the authors (WJ) on May 12, 2014,
using the most common databases: CBRG trials register (up to search date), MEDLINE (from
1966 to search date), EMBASE (from 1980 to search date), and ISI Web of science (up to search
date). The search string for MEDLINE is given in Appendix 1 (See Supplementary data) and was
adapted for the additional databases. No language or date restrictions were made. References
and citation of selected articles were tracked and included in the search.
Impact of registries on quality of spine care
Articles were included if they met the following criteria:
05
Types of studies
Studies on spine registries based on results from prospectively acquired data were included.
To comply with the definition of patient or outcomes registry, we used the following
registry characteristics: inclusion principle, mergeable data, standardized dataset for all
consecutively included patients, rules for data collection (i.e. systematically and prospectively
collected, including pre-intervention data), knowledge about patient-related outcomes, and
observations collected over time (i.e. follow-up assessments) [17]. Studies were included if
published between 2000 and May 2014 and written in English.
Types of spine disorders
We included patients of all ages with spine disorders who underwent any elective or acute,
non-surgical or surgical spinal intervention. The following specific disorders were defined:
degenerative disc disease (DDD, ‘non-specific’ and/or chronic low back pain, segmental
pain), spinal stenosis, disc herniation, spondylolisthesis/-lysis (isthmic/degenerative), failed
back surgery syndrome, spinal deformities (degenerative deformity: de novo, osteoporotic,
idiopathic, neuromuscular, congenital), spinal oncology, spine trauma, and infections of the
spine.
Types of interventions
Interventions were included that provide a system to register quality of spine care, i.e.
outcomes, including a system for feedback: quality improvement strategies [18-20]. These
strategies include those targeted: health systems (e.g. team changes), healthcare professionals
(e.g. reminders), and patients (e.g. reminders). Specific improvement strategies included:
(clinical) audit and feedback, (electronic) patient registries, case management, clinician
education, (promotion of) self-management, patient reminder systems, and continuous
quality improvement.
Types of outcome measures
Quality of care is a multidimensional concept and is defined in many ways, e.g. ‘doing the right
thing, at the right time, in the right way, for the right person, and having the best possible
results’ [21]. Following this definition, the outcomes of spine interventions are a proxy for
quality of care. As measures for quality of spine care we included patient-related outcome
indicators: patient-reported outcome measures (PROMs) and clinical outcome measures.
PROMs [22] are functional status (e.g. Roland and Morris Disability Questionnaire [RMDQ],
Oswestry Disability Index [ODI], Scoliosis Research Society-22 [SRS22]), pain intensity back and
leg (e.g. Visual Analogue Scale [VAS], Numeric Pain Rating Scale [NPRS]), and health-related
quality of life (e.g. Short Form-36 [SF36], EuroQol 5 Dimensions [EQ5D]). Clinical outcomes
Evidence and practice in spine registries
81
were regarded as re-intervention (i.e. reoperation), complications, and failed back surgery
syndrome (FBSS).
The search did not reveal any studies related to the first aim of this study (impact) concerning
the effect and possible impact of introducing and using spine registries on the quality of spine
care and on patient-related outcomes (Figure 5.1).
Methodology used in existing spine registries
Selection criteria
The same criteria were used as for the first aim, but they were restricted to include studies
with patients with degenerative lumbar spine disorders: degenerative disc disease (DDD,
‘non-specific’ and/or chronic low back pain, segmental pain), spinal stenosis, disc herniation,
spondylolisthesis/-lysis (isthmic/degenerative), and spinal deformities (degenerative
deformity: de novo, osteoporotic).
Risk of bias assessment
The included studies were assessed for methodological quality, to get an impression of the
quality of published scientific studies based on registries. Quality was assessed with the
Newcastle-Ottawa Scale (NOS; Appendix 2, see Supplementary data) for cohort studies[23].
Studies were considered to be of high quality if the total score was 6 or more (75% of the
maximum score). The clinical relevance of study results was assessed with 3 questions: 1) ‘Are
the patients described in detail so that you can decide whether they are comparable to those
that you see in your practice?’; 2) ‘Are the interventions and treatment settings described well
enough so that you can provide the same for your patients?’; 3) ‘Were all clinically relevant
outcomes measured and reported?’.
Data extraction and management
Using forms already developed, the following data were extracted: authors (affiliation,
sponsoring), name and type of registry (i.e. based on exposure: health service, disease/
condition and medical devices [11]), setting (nationwide, multicentre), diagnosis, methods
(purpose, study design, outcomes, covariates, statistical analysis, patient numbers recruited
and included), follow-up response, non-responder analysis, conclusion. MH extracted the data
and WJ checked the data; inconsistencies were discussed and PW was consulted if necessary.
Survey
A web-based survey, built in the Harvard Business online Qualitrics Survey Software and
provided by International Consortium for Health Outcomes Measurement (ICHOM), was
performed among spine registry representatives. The survey consisted of 21 questions
regarding: 1) organizational structure and financing, 2) methodology used and outcome
assessment, 3) procedures concerning response rates and missing data, and 4) approaches for
analysis and reporting.
The sample included participants of the ICHOM Low Back Pain Working Group, representatives
of spine registries identified through spine registry websites, and corresponding authors of
publications on spine registries as identified in this systematic review. All recipients were
contacted by e-mail and asked to participate in an online survey. Subjects who did not respond
were sent a reminder after 2 weeks.
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Evidence and practice in spine registries
Analyses
Results from the included studies in the review were not pooled; instead, we compared and
reported on the methods used in these studies. The data from the survey are described and
support the results found in the review. The PROMs used were checked with the ICHOM-LBP
PROMs criteria [24]: 1) functional status (ODI [0-100] version 2.1a); 2) pain intensity (NPRS [010] back and leg; average pain during last 7 days); 3) health-related quality of life (EQ5D-3L and
EQ-VAS); 4) timeline assessments included were baseline, 3 and 6 months, and 1, 2, and 5 years
after the ‘index event’ (3 months and 5 years assessments were optional). The ‘index event’ was
defined as the reported first intervention episode.
05
Figure 5.1 Flowchart of studies through the different phases of the systematic review.
Literature search (n = 5,417):
- PubMed, 897
- Embase, 1,247
- Web of Science, 1,637
- Cochrane Central, 1,636
Duplicates
n = 1,144
Unique references
n = 4,273
Excluded (n = 3,063):
- no outcome, 2,429
- language, 129
- conference, 398
- before 2000, 107
Screened and assessed for
eligibility by 2 reviewers
n = 1,210
Excluded (n = 1,176):
- not relevant, 1,138
- indication, 17
- single center, 8
- other methods, 8
- duplicate, 4
- closed register, 1
- no description, 1
Included from survey
n=1
Included by both reviewers
n = 30
Included by both reviewers
n=3
Total included (n = 34)
Aim 1: n = 0
Aim 2: n = 34
Evidence and practice in spine registries
83
Results
Impact of registries on quality of spine care
Included studies
4,273 unique references were identified 1,210 of which were eligible for screening and
assessment (Figure 5.1). No studies on the effect of spine registries on quality of care were
identified.
Methodology used in existing spine registries
Included studies
34 studies were identified for study of the methodology used to organize, analyze, and report
the quality of spine care in degenerative lumbar spine disorders (Appendix 3, see Supplementary
data; Table S1). The 34 studies were based on 11 separate registries, representing 7 countries.
Indications included were disc herniation (3), spinal stenosis (9), chronic low back pain (5),
adult deformity (5), and spinal disorders (7). In 3 studies a mixture of indications (non-specific
subacute and chronic neck, back, and low back pain) was included, but these allowed to
extract data of methodology used for separate indications.
Risk of bias
Half of the studies were classified as having a high methodological quality (17 of 34; Table 5.1).
Although ‘selection of the non-exposed cohort’ (item 2) scored high quality (i.e. low risk of
bias), 21 studies were rated ‘n.a.’ as these studies did not include a control group. In 20 of the
34 studies, a low risk of bias in ‘comparability’ (item 5a) was seen, meaning studies controlled
for the most relevant case-mix variables (i.e. diagnosis and baseline outcome score). In all
studies the ‘assessment of outcome’ (item 6) was rated ‘self-report’ (c), and with that scoring
low quality. The follow up was long enough for outcomes to occur (item 7; 29 of 34). However,
low quality was seen in the adequacy of follow up of cohorts (item 8; 18 of 32). Although in
almost all studies the clinical relevant outcomes are measured and reported (31 of 32; ‘clinical
relevance’ [item 3]), in less than one-third of the studies (10 of 32) the description of patients
and intervention (‘clinical relevance’, items 1 and 2) was sufficiently detailed.
Survey
We identified 25 spine registries, representing 14 countries, within the ICHOM Low Back Pain
Working Group (ICHOM-LBP WG; 10) through the literature (10; 4 overlap with ICHOM-LBP
WG) and through internet searches (9). We were unable to make contact with representatives
of 7 of the multicentre registries; the remaining 18 were invited to participate in the survey. 16
of them responded, representing 12 countries and 2 including ‘diverse’ countries (Spine Tango
and European Spine Study Group database [ESSG]). The non-responders were representatives
of Russian and Indian registries.
An overview of existing spine registries is presented in Table 5.2: survey responders (16) and
searches though internet and literature (6). 3 multi-centre registries in the USA were found
through internet searches, but we were unable to obtain relevant information (NASS Spine
Registry, SMISS Prospective Data Registry, and Scolisoft Scoliosis Database [see references for
websites]); these registries were not included in Table 5.2.
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Organization and Methods used in spine registries
Organization (Table 5.2)
9 of 22 registries are organized on a nationwide basis. Most spine registries started within
the last decade. All registries are health services registries, except for Kaiser Permanente
which is a device or implant registry and SWISSspine, a device or implant registry with health
technology assessment purposes.
05
Methods (Table 5.2)
All registries incorporated the main patient-reported outcome domains. ODI, NPRS back and
leg, and EQ5D are mainly used as PROMs. In the majority of the registries clinical outcomes
(e.g. complications and reoperations) are also registered. All registries have baseline and
12- and 24-months follow-up assessments, except for NORspine and N²QOD (with only a
12-months follow up). Although 15 registries report on lumbar spine disorders, only 3 fulfil all
the ICHOM-LBP criteria for PROMs. The Adult Deformity Outcomes Database registry has the
longest follow up (25 years). To improve the response rate, all registries use postal, e-mail or
telephone reminders.
Analyses and reporting
In the 34 scientific publications, various analytic approaches were used (Appendix 3, see
Supplementary data, Table 5.4), varying from descriptive statistics, all studies, to multivariate
techniques as mixed linear modelling [25,26] and propensity modelling [27,28]. To evaluate
the study purpose all studies used 1 or more PROMs as an outcome measure. In 8 studies
secondary clinical outcomes were defined: complications [25,27,29], reoperation [30], BMI [31],
adverse events [32], and Bridwell classification for fusion rates [33]. In 5 studies, no adjustment
for covariates was performed to explain variation in outcomes [33-37]. In the remaining 29
studies patient characteristics were used as covariates, varying from 17 predefined covariates
[38] to adjustment for baseline PROMs only [39]. Adjustment for baseline PROMs was not
performed in 8 studies [27,30,32,40-44]. In 8 studies, a dropout analysis was performed to
compare baseline characteristics (missing data on assessments) with the remaining cases. To
handle missing data, multiple imputation techniques were applied in 2 studies [38,41]. In the
remaining studies complete case analysis was performed.
All 16 registries representatives reported in the survey, to describe the population and
outcomes using descriptive statistics and to provide feedback reports on a regular basis to
all participating institutions and spine societies. Benchmarking is performed against the
average value of participating institutions in 10 registries (Table 5.2). The 12-months followup responses on PROMs vary from 20% (British Spine Registry) to 88% (Neuroreflexotherapy
registry within Spanish National Health Service [NRT en el SNS]).
Evidence and practice in spine registries
85
Discussion
We found a lack of evidence to support or refute the effect that spine registries may have on
the quality of spine care and on patient-related outcomes. Nonetheless, the publications that
have resulted from the spine registries have yielded relevant evidence on interventions or
predictive factors for spinal disorders. We have therefore described the methodology used to
organize, analyze, and report the ‘quality of spine care’ from spine registries. To improve the
quality of results published with registry data and to study the effects of spine registries in
future; we have formulated and included several recommendations, which are summarized in
Table 5.3. First of all, the registries should be methodologically well constructed and we need to
learn from existing registries so that a more standardized approach to registering and analysis
are achieved to allow international collaboration, national and international benchmarking,
and to make sure that in future spine care is value-based (Table 5.3; recommendation [rec.] 1).
Quality improvement in spine care
Although we did not find any scientific evidence for an effect of introducing and using spine
registries on the quality of spine care, in 16 registries feedback reports are compiled and
disseminated on a regular basis to the participating institutions and the spine societies in
order to improve the quality of spine care delivered. In general, improvement strategies include
(clinical) audit and feedback, (electronic) patient registries, case management, clinician
education, (promotion of) self-management, patient reminder systems, and continuous
quality improvement [18-20] (Table 5.3; rec. 2).
That registries can have an important effect on quality of health care has, however, been
reported in other fields. For example, the Swedish Hip Register has shown that prospectively
and systematically collected data decreased revision rates, by describing trends in outcomes
adjusted for case-mix factors and early problems [58]. Antibiotic treatment for patients with
hard-to-heal ulcers was reduced from 71% before registration to 29% after registration and
feedback [59]. A collaborative cohort study of 5 ICUs in the USA showed that an evidence-based
intervention resulted in a large sustained reduction (up to 66%) in the rate of catheter-related
bloodstream infection, which was maintained throughout the 18-months study period [60].
A study of 13 patient registries in 5 countries demonstrated that these systems have great
potential to both improve health outcomes and lower health care costs[13].
Recently, reports from Sweden indicate that spine registries have a positive effect on
health care, i.e. on patient-related outcomes, by the SweSpine registry (complying with the
recommendations in Table 3). For example, the national mean length of stay (LoS) for surgery
in lumbar disc herniation today is 2 days, with a range of 0-4 days. After introduction of new
routines the LoS in 1 university hospital was reduced from 4 to 2.5 days, giving the same patientrelated outcomes at lower costs [61]. Another example is a change of surgical procedure in
elderly with lumbar spinal stenosis (LSS). 2-year registry data on 8,785 elderly patients showed
that surgery can be limited to an invasive procedure of decompression alone, in order to avoid
unnecessary complications associated with fusion procedures [62]. These registry findings
have recently been confirmed with a multicentre RCT among 229 elderly patients with 1- or
2-level LSS. After 2 years, no benefit from adding fusion to decompression surgery was found,
which means that in this population a less invasive procedure of decompression can reduce
the number of complications and costs for society [63].
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Evidence and practice in spine registries
Quality of studies based on registry data
In the present study, only half of the publications could be regarded as having a low risk of
bias, as assessed on the Newcastle-Ottawa Score (NOS). The main weaknesses of the included
studies were the inaccurate descriptions of the patients and interventions studied, and the
lack of long-term assessment of the outcome. We therefore recommend to use the STROBE
guidelines for reporting observational studies [12] (Table 5.3; rec. 3). Moreover, as it is known
that during the first year after spine surgery changes in patient-related outcomes are seen
[6,27,64,65], a minimum follow-up period of 1 year is recommended (Table 5.3; rec. 4). As
stability of patient-reported outcome measures (PROMs) results is seen between 2 and 4
years [6,27] longer follow-up periods are desirable. Another weakness causing high risk of bias
according to NOS is that the assessment of outcomes in all studies was performed by PROMs.
As PROMs are self-report measures, these measures are assessed as low quality by NOS
(Appendix 2, see Supplementary data). Although of lower quality methodologically, PROMs
are the recommended outcome measures in spine surgery [22], as there is no valid biomedical
measure currently available to evaluate recovery after a spinal intervention. Although they
are usually defined as clinical patient-related outcomes, reoperation and complications are in
fact process measures for a complicated course to an endpoint defined by PROMs.
Methodology of studies based on registries
Although all 34 studies met the 6 inclusion criteria for registry characteristics [17] (Table 5.3; rec.
5), we found various analytical approaches. Thus, we cannot give the best approach to use when
comparing institutions in the search to identify best practices. In measurement of patientbased outcomes, the PROMs used should ideally fulfill the criteria of good measurement
properties [66]. Recently, consensus was reached within the ICHOM collaboration on
which PROMs should be recommended for the evaluation of outcomes of interventions for
degenerative lumbar spinal disorders (Oswestry Disability Index [ODI], Numeric Pain Rating
Scale [NPRS] back and leg, and EuroQol 5 Dimensions [EQ5D]; [24]; Table 5.3; rec. 6). Although
as yet only 3 lumbar spine patient registries (SweSpine, Dutch Spine Surgery Registry and
Spine Tango) use the specific ICHOM PROMs, every other studied registry already evaluated
functional status, pain intensity, and quality of life with PROMs, but the assessment used
other tools.
To prevent selection bias [67] and to explain real differences in outcomes between institutions
multivariate approaches with adjustment for covariates (corrections for differences in
characteristics of patients treated in hospitals; ‘case-mix adjustments’) and correction for
chance variation (reliability adjustments) are needed [64,68-70] (Table 5.3; rec. 7). A shortcoming
of these techniques is that they only account for known covariates. In this systematic review
we found that a large variety and number of covariates are included in different registries. A
recently published study showed that a large number of patient characteristics (biomedical,
psychosocial and health-related indicators) could influence the outcome of interventions
of lumbar spinal disorders or maintain the complaints [71]. Within the ICHOM collaboration
consensus was reached to use a minimum set of factors: age, sex, education level, work
status, duration of sick leave, smoking status, comorbidities, BMI, duration of back/leg pain,
morbidity state, diagnosis and indication surgery, need for continuous analgesic use, prior
intervention, and baseline patient-reported disability, back and leg pain baseline, and healthrelated quality of life [24] (Table 5.3; rec. 7). Currently, none of the registries collect data of all of
these recommended factors. Within the countries influenced by the SweSpine registry format
Evidence and practice in spine registries
87
(Sweden, Norway, Denmark, and the Netherlands), consensus has been reached to implement
all these factors in the registry, to allow them to be used as covariates in future benchmark
analyses. When benchmarking across centers, it has been suggested that together with these
patient-related covariates, center-specific characteristics might also influence the outcome
of surgery in degenerative lumbar spine disorders [64].
In the registries, the 12-months follow up on PROMs varied from 20% (British Spine Registry) to
88% (NRT en el SNS). A suggested rule of thumb is that a loss to follow up larger than 20% would
probably lead to bias in results, whereas a rate of less than 5% would not [72,73]. A recently
performed study on Norwegian registry 2-year follow-up data on 633 patients showed that a
loss to follow up of 22% would not alter conclusions about the outcome of interventions [74].
Efforts should be made to increase 12- and 24-months follow-up responses to 60-80% (Table
5.3; rec. 8). Although patients are 3 times more likely to respond when invited for follow-up visits
[74], it is too demanding for all parties involved to arrange long-term follow-up visits in large
patient registries [75]. Solberg et al. [74] found that forgetfulness is the most important reason
for not responding, which could possibly be prevented by modern communication techniques
as text messages and email (Table 5.3; rec. 9). To handle missing data in most registries only
analyses are performed on complete cases. To understand potential sources of bias, a nonresponder analysis on baseline characteristics should be provided (Table 5.3; rec. 10). Statistical
sensitivity techniques are available to test whether there is bias present. When missing at
random, indicating that the missing data are related to other observed or documented patient
data but not to unobserved outcomes, we recommend multiple imputation techniques (Table
3; rec. 11). The major advantage of this method over single imputation techniques or ‘complete
cases only’ is that it does not underestimate variability [76,77].
Strengths and Limitations
To evaluate the risk of bias in the studies included, as a quality assessment, we defined a
cutoff value (total score ≥6 [75%]) for the Newcastle-Ottawa Scale (NOS) for cohort studies.
However, research is needed to identify whether this is the correct tool for assessing risk of
bias in patient registries. Another limitation is that selection bias might be present in the
spine registries identified. We identified 2 types of registries: national and institutional. The
national registries are in most cases part of an obligatory, government or insurer driven
need for quality control and/or audit. The multicentre institutional registries carry the risk of
selection bias (e.g. many institutional registries include premier spine institutes with selected
patients) and even more when they are sponsored by industry (ESSG, SWISSspine, Canadian
Spine Outcomes, and Research network; Indian Spine Registry) or by membership (SSE Spine
Tango, British Spine Registry, National Spine Network Spine Outcomes Registry). Although we
performed a profound search and gained an overview of 25 large registries for degenerative
spinal disorders we cannot rule out that more spine registries exist.
The main strength of this study was that we adopted a systematic approach, including a
systematic search and an appraisal of quality. In addition, we conducted a survey among
representatives of all the known registries to add information to that found in the literature.
To increase the response, we contacted (successfully) all the representatives of the spine
registries to complete our data.
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Evidence and practice in spine registries
Conclusions
Currently, despite there being some evidence in other fields of healthcare, there is a lack of
evidence to either support or refute the impact that spine registries may have on the quality
of spine care and, with that, on patient-related outcomes. To improve the quality of results
published from registry data, we have formulated several recommendations. With the first
indications of the effects of the SweSpine registry already known (e.g. improved outcomes
after feedback on length of stay and no patient-related benefit from adding fusion to
decompression surgery), we believe that application of these recommendations could lead
to spine registries demonstrating trends and outcomes, monitoring the quality of spine care
delivered, resolving controversies in the management of degenerative spinal disorders, and
ultimately improving the value of the care given to our patients.
Acknowledgements
The authors thank members of the ICHOM Low Back Pain Working Group and all participants
who completed the spine registry survey. Particular thanks are to Caleb Stowell (ICHOM) for
his support in building and managing the survey in the Harvard Business’ Qualitrics online
web-application and to Serge Stommels for his support in translating Russian texts in relation
to the Russian Spine Registry.
Supplementary data
Appendices 1-3 are available at Acta’s website (www.actaorthop.org), identification number
8170.
NOS Newcastle-Ottawa Scale; n.a. not applicable
* score NOS; a high quality; b n items, considering n.a.; c National Outcomes registry; d Community outcomes management study;
e
Adult Deformities Outcomes Database; f Multicenter registry for lumbar spine surgery; g Singapore General Hospital Spine Outcomes Registry
Explanation NOS, including description of items a-d and method of scoring, is given in Appendix 2:
Selection: 1 representativeness exposed cohort; 2 selection non-exposed cohort; 3 ascertainment exposure; 4 outcome not present at start study
Comparability: 5a and 5b Comparability cohorts on the basis of design/analysis
Outcome: 6 outcome assessment; 7 follow up long enough; 8 adequacy follow up
Explanation Clinical relevance (yes/no):
1 Are the patients described in detail so that you can decide whether they are comparable to those that you see in your practice?
2 Are the interventions and treatment settings described well enough so that you can provide the same for your patients?
3 Were all clinically relevant outcomes measured and reported?
NORspine
NORspine
NRT en el SNS
NRT en el SNS
NRT en el SNS
NRT en el SNS
SweSpine
SweSpine
SweSpine
SweSpine
SweSpine
SweSpine
SweSpine
SweSpine
SweSpine
SweSpine
SweSpine
SSE Spine Tango
SSE Spine Tango
SSE Spine Tango
SWISSspine
SWISSspine
SWISSspine
SWISSspine
N2QOD
Nat Outc Reg c
Com outc m study d
A D O Database e
A D O Database e
A D O Database e
A D O Database e
A D O Database e
Multicenter reg f
Singapore GH Reg g
Nerland et al. (2014) [25]
Solberg et al. (2013) [39]
Corcoll et al. (2006) [34]
Kovacs et al. (2012) [41]
Kovacs et al. (2007)
Royuela et al. (2014) [38]
Fritzell et al. 2014
Forsth et al. (2013) [49]
Jansson et al. (2005)
Jansson et al. (2009)
Knutsson et al. (2013) [31]
Robinson et al. (2013) [26]
Sanden et al. (2011)
Sigmundsson et al. (2012) [42]
Sigmundsson et al. (2013) [37]
Sigmundsson et al. (2014)
Stromqvist et al. (2012) [48]
Berg et al. (2010)
Grob and Mannion (2009) [35]
Porchet et al. (2009)
Aghayev et al. (2012)
Aghayev et al. (2010)
Schluessmann et al. (2009)
Zweig et al. (2011) [43]
McGirt et al. (2013) [40]
Deer et al. (2004) [32]
Taylor et al. (2000)
Bridwell et al. (2007) [30]
Glassman et al. (2009) [44]
Glassman et al. (2007)
Kasliwal et al. (2012) [28]
Schwab et al. (2008) [29]
Adogwa et al. (2014) [27]
Seng et al. (2013) [33]
Percentage with *, aor yes
Spine registry
Study
94
b*
a*
a*
b*
b*
b*
b*
b*
b*
a*
a*
a*
b*
a*
c
c
b*
a*
a*
a*
a*
a*
a*
a*
a*
a*
a*
a*
a*
b*
b*
a*
a*
a*
1
92
a*
a*
n.a.
a*
n.a.
n.a.
n.a.
n.a.
n.a.
a*
n.a.
n.a.
a*
b
a*
n.a.
a*
n.a.
a*
n.a.
n.a.
a*
a*
n.a.
n.a.
n.a.
a*
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
a*
17
c
d
d
d
d
d
d
d
c
d
d
d
d
d
d
d
a*
d
d
d
a*
d
d
d
d
d
a*
c
d
d
b*
b*
d
a*
3
Selection
2
86
a*
a*
b
a*
a*
a*
a*
b
a*
a*
a*
a*
a*
a*
a*
b
a*
a*
a*
a*
a*
a*
a*
a*
a*
a*
a*
a*
b
a*
a*
a*
b
a*
4
59
no
no
yes *
yes *
yes *
no
no
yes *
no
n.a.
yes *
yes *
yes *
yes *
no
no
no
no
yes *
no
yes *
yes *
yes *
yes *
yes *
yes *
yes *
no
yes *
yes *
yes *
no
no
yes *
5a
71
no
yes *
yes *
yes *
yes *
yes *
yes *
yes *
no
n.a.
yes *
yes *
yes *
yes *
no
no
no
no
yes *
no
yes *
yes *
yes *
yes *
yes *
yes *
yes *
yes *
yes *
yes *
yes *
no
no
yes *
5b
Comparability
0
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
6
85
a*
a*
a*
a*
a*
a*
a*
a*
a*
a*
a*
a*
a*
a*
a*
a*
a*
a*
a*
b
a*
a*
a*
a*
a*
a*
a*
a*
b
b
b
b
a*
a*
7
Outcome
7 (8) a
5 (7)
5 (7)
5 (7)
6 (8)
6 (8)
6 (7)
2 (7)
6 (8) a
3 (7)
6 (8) a
2 (7)
3 (8)
5 (8)
6 (8) a
5 (7) a
5 (7) a
4 (5) a
c
c
c
c
c
c
d
d
c
c
b*
b*
d
d
c
c
d
n.a.
4 (7)
5 (7) a
6 (8) a
4 (8)
5 (8)
5 (8)
50
d
d
c
d
a*
13
a
a
a
a
a
a
a
d
4 (7)
4 (7)
c
d
3 (7)
c
3 (7)
4 (7)
c
4 (7)
6 (7)
b*
c
3 (7)
c
c
2 (7)
c
a
7 (7)
n.a.
Total
*scoreb
8
no
31
no
no
yes
yes
yes
no
yes
no
no
n.a.
yes
no
no
no
no
no
yes
no
no
no
yes
no
no
no
no
no
no
no
yes
yes
no
yes
31
yes
no
no
no
no
no
no
no
yes
n.a.
yes
yes
no
no
no
no
yes
no
no
no
yes
no
no
no
no
no
no
no
yes
yes
yes
yes
no
n.a.
2
3
97
yes
yes
yes
yes
yes
yes
yes
no
yes
n.a.
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
n.a.
Clinical relevance
n.a.
1
Evidence and practice in spine registries
89
Table 5.1 Risk of bias assessment according to Newcastle-Ottawa scale (NOS)
05
Sweden
Norway
Denmark
The Netherlands
UK
Spain
Switzerland
Diverse
Canada
Singapore
Australia
USA
USA
USA
Germany
Diverse
SweSpine
NORspine
DaneSpine
Dutch Spine Surgery
Registry
British Spine Registry
NRT en el SNS
SWISSspine
SSE Spine Tango
Canadian a
Singapore b
Newro Foundation
Texas Back Institute
Kaiser c
N²QOD d
Schön-Clinics Spine Registry
European Spine Study Group
Survey respondents
Location
M
M/I
M
M
I
I
N/I
N/M
M
N
N
N
N
N
N
N
Setting 2
2010
2010
2012
2009
New
2010
2001
2012
2002
2005
2002
2012
2014
2009
2006
1998
Since
(year)
D
L; C; D; T; I; M
L; C; D
O,
instrumented
procedures
L; C; D; T; I; M
L; C
L; C; D; T; I; M
L; C; T
L; C; D; T; I; M
L; C; D; T; I; M
L; C
L; C; D; T; I; M
L & D (mainly);
C; T; I; M
L; C; D; T; I; M
L; D
L; C; D; T; I; M
Location
spine 3
ODI; SRS22r;
COMI
ODI
ODI
n.a.
ODI
ODI; RMDQ
ODI; NASS
ODI
ODI; COMI
NASS; COMI
RMDQ
ODI
ODI
ODI
ODI
ODI
Functional
status 4
NRS B&L
VAS B&L
NPRS B&L
n.a.
VAS B&L
NRS B&L
NPRS B&L
VAS B&L
COMI:
NPRS B&L
NPRS B&L
NPRS B&L
VAS B&L
NPRS B&L
VAS B&L
NPRS B&L
VAS B&L
Pain 5
SF36
EQ5D
EQ5D
n.a.
SF12, future
EQ5D
SF12, future
EQ5D
SF36
SF12; EQ5D
EQ5D
occasion.
EQ5D
not meas.
EQ5D
SF36; EQ5D
EQ5D; SF36
occasion.
EQ5D
SF36; EQ5D
Quality of
Life 6
Outcomes Lumbar spine
B; P; 6w; 6;
12; 24
B; P; 3; 12; 24
B; 3; 12
P
B; 3 %
B; 6w; 3; 6;
12; 24
B; 1; 3; 6; 24
B; P; 3; 12; 24
B; P; 6w; 3; 12;
24 $
B; P; 3; 6; 12; 24;
O, 5y;10y
B; P; 3; O, each
3mo #
B; 3; 12; 24; O, 5y
B; P; 2/6; 12; 24*
B; P; 3; 6; 12; 24;
O, 5y;10y
B; P; 3; 12
B; P; 12; 24;
O, 5y
PROMs assessments 7
n.a.
No
No
No
No
No
No
No
Yes
No
No
No
Yes
No
No
Yes
ICHOM
LBP
PROMS
criteria
Benchmark 6
n.a.
average &
individual
centers
average
only own data
only own data
only own data
only own data
average
average
average
only own data
average &
individual
centers
(planned)
average &
individual
centers
(planned)
average
average
average &
individual
centers
05
Registry
name 1
Yes
Yes
Yes; 1
Yes
No
No
Yes; 1
No
Yes; 3
Yes; 4
Yes; 4
No
No
No
Yes; 2
Yes; 12
Scientific
publication 8
4 10
5
3.3 (2-5)
5.3 (5-6) 10
4.0 (2-6)
4.5 (2-7)
5.3 (2-7) 10
NOS Risk of
Bias score 9
90
Evidence and practice in spine registries
Table 5.2 Registry characteristics
India
USA
USA & Canada
USA Spine Deformity
Study Group
USA International
Spine Study Group
Indian Spine (Surgery)
Registry 12
National Spine Network e; 12
Multicenter registry f; 13
ADO Database g;14
ATSD Database h;15
M
M
M
M
M; future
M
2010
2002
2003
1995
Plan.
2012
D
D
L
L; C
L
L
SRS-22; ODI
SRS-22; ODI
ODI
ODI
Not found
ODI
SRS-22
(pain)
SRS-22
(pain)
VAS B&L
Not found
Not found
VAS
SF36
SF12
Not found
SF36 or SF12
or SF8
Not found
SF36
B; 12; 24
B; 6; 12; 24;
5y; 10y; 15y;
20y; 25y
B; P; 12; 24
B; 12
optional: 3;
6; 24
Not found
B; P; not
reported
n.a.
n.a.
No
Not found
Not found
No
Yes
Not found
Yes; 1
Yes; 1
Yes; 5
Yes
Not found
Not found
Not found
Not found
Not found
Not found
4.6 (4-6)
5
3
n.a. not applicable
1
Registry names: a Canadian Spine Outcomes and Research Network; b Singapore General Hospital Spine Outcomes Registry; c Kaiser Permanente Spine Implant Registry; d National Neurosurgery Quality and Outcomes
Database (N²QOD); e National Spine Network Spine Outcomes Registry (SpineChart); f Multicenter registry for lumbar spine surgery; g Adult Deformity Outcomes Database; h Adult Thoracolumbar Spinal Deformity Database
2
Setting: N National, M Multicenter, I Institutional
3
Location: L Lumbar spine; C Cervical spine; D Spinal Deformity; T Spine Trauma; I Spinal Infections; M Spinal metastases; O Other, …
4
Functional status: ODI Oswestry Disability Index; RMDQ Roland and Morris Disability Questionnaire; NASS North American Spine Society lumbar spine outcome scale; COMI Core Outcome Measures Index; SRS22 Scoliosis
Research Society 22 questions
5
Pain: VAS Visual Analogue Scale; NPRS Numeric Pain Rating Scale;
6
Quality of Life: SF8, SF12, SF36 Short Form 8 or 12 or 36 questions; EQ5D EuroQol 5 Dimensions (including EuroQol VAS)
7
PROMs at: B Baseline; P Peri-operative; 6w 6 weeks; 1 1 month; 3 3 months; 6 6 months; 12 12 months; 24 24 months; O Other, …; * 2 months in hernia/stenosis; # until discharge; $ at least 1 follow up; % variabel: when patient
returns to clinic
8
n; according to Appendix 2; Table 1
9
NOS Risk of Bias score Newcastle-Ottawa scale – total score; median (range) according to Table 1
10
high quality
11
Shevelev et al. [79]; 12 See references for websites
13
Adogwa et al. [27]; 14 e.g. Kasliwal et al. [28] (see Table 1); 15 Scheer et al. [78]
Russia
Russian Spine Registry 11; 12
Other sources
Evidence and practice in spine registries
91
05
92
Evidence and practice in spine registries
Table 5.3 Recommendations to improve the quality of study results published from registry data
Organization and Method
05
1.
Use a standardized approach to registering in design, methodology, and analysis to allow
international collaboration, to achieve benchmark purposes, and to make sure that in future
spine care is value based.
2.
Study and incorporate strategies to improve quality of care, e.g. continuous feedback and audit
cycles of results collected in spine registries of delivered spine care.
3.
To increase the quality of registry studies the population needs to be well defined, in terms of
diagnosis and indication for surgery. Both in the developmental stage of a registry and when
reporting on registry data follow the STROBE guidelines.
4.
Include a minimum follow-up period of 1 year for surgically treated patients.
5.
To meet the definition of a patient registry all registry characteristics should be present ([17].
This means an inclusion principle, mergeable data, standardized dataset for all consecutively
included patients, rules for data collection [i.e. systematically and prospectively collected,
including pre-intervention data], knowledge about patient-related outcomes, and observations
collected over time [i.e. follow-up assessments])
Patient-related outcomes
6.
Patient-reported outcome measures for degenerative lumbar spine disorders are PROMs with
good measurement properties and as recommend by ICHOM. Although often defined as clinical
patient-related outcomes (i.e. re-operation, complications, and Failed Back Surgery Syndrome),
these indicators are in fact process measures for complicated course.
Analyses and Report
7.
To explain differences in outcomes with advanced multivariate analytical techniques, include a
reliability adjustment and an adjustment for covariates. For degenerative lumbar spine disorders
the recommended factors in ICHOM could be used as covariates.
8.
To reduce bias in results a 60-80% 12-months follow-up response is recommended.
9.
To increase PROMs response at follow up reminders by text messages or email could be sent.
10.
To understand potential sources of bias a non-responder analysis on baseline characteristics
should be provided, including a quantitative sensitivity analysis in order to evaluate to which
extent the results are affected by bias.
11.
Multiple imputation techniques are recommended for sensitivity analysis when missing data are
randomly divided.
Practical issues a
a
12.
Linkage between electronic medical records and registry data to avoid double data entry and to
enhance routine in daily practice.
13.
Participating departments should have direct access to their own data and should have real-time
comparisons with other departments and if available, with the national mean.
14.
After approval, analyzed results corrected for case mix should be presented for public on open
web pages in order to increase credibility and to make adequate and relevant comparisons.
not discussed in this study
Evidence and practice in spine registries
93
Appendix 1: Search strategies
MEDLINE - Pubmed
(“Lumbar vertebrae”[MH] OR
“Spine”[mesh] OR
“intervertebral disk”[mesh] OR
“intervertebral disc”[tiab] OR
spine[tiab] OR
spinal[tiab] OR
vertebra*[tiab] OR
disc[tiab] OR
discs[tiab] OR
disk[tiab] OR
disks[tiab])
AND
(“low back pain”[tiab] OR
“back pain”[mesh] OR
“back pain”[tiab] OR
“intermittent neurogenic claudication”[tiab]
OR
“intermittent claudication”[mesh] OR
“intermittent claudication”[tiab] OR
”neurogenic claudication”[tiab] OR
dorsalgia[tiab] OR
backache[tiab] OR
lumbago[tiab] OR
(lumbar[tiab] AND (“pain”[mesh] OR
“pain”[all fields])) OR
“sciatica”[mesh] OR
“sciatica”[all fields] OR
sciatica[tiab] OR
“Spondylolisthesis”[mesh] OR
“spondylolisthesis”[tiab] OR
“isthmic”[tiab] OR
“lytic”[tiab] OR
“low-grade”[tiab] OR
“lumbar stenosis”[ tiab] OR
“spinal stenosis”[mesh] OR
“spinal stenosis”[TIAB] OR
“stenosis” [TIAB] OR
“scoliosis”[TIAB] OR
“deformity”[ti] OR
"Scoliosis"[Mesh] OR
“degenerative disc disease”[tiab] OR
“spinal diseases”[mesh] OR
“intervertebral disk displacement”[mesh] OR
“intervertebral disk displacement”[ tiab] OR
“discitis”[mesh] OR
“discitis”[all fields] OR
“spondylosis”[tiab] OR
((disc[tiab] OR discs[tiab] OR disk[tiab] OR
disks[tiab]) AND degeneration[tiab]) OR
herniated[tiab] OR
hernia[tiab] OR
“Failed back surgery syndrome” [TIAB] OR
“FBSS” [TIAB] OR
“myelomeningocele”[TIAB] OR
“Ankylosing spondylitis” [TIAB] OR
“tumours” [TIAB] OR
“metastases” [TIAB] OR
“Trauma” [TIAB] OR
“Fracture” [TIAB])
AND
("Clinical Audit"[Mesh] OR
"audit"[TIAB] OR
"Quality Assurance, Health Care"[Mesh]
"Outcome and Process Assessment (Health
Care)"[Mesh]
"Quality Improvement"[Mesh]
"Benchmarking"[Mesh] OR
"Benchmarking"[TIAB] OR
"Register"[TIAB] OR
"Registry"[TIAB] OR
"Registries"[Mesh])
Within Reference manager on all fields
(indexed and non-indexed)
("Outcome and Process Assessment (Health
Care)"[Mesh] OR
"Quality of Life"[Mesh] OR
“Functional status”[TIAB] OR
“disability”[tiab] OR
“Patient reported outcome” [tiab] OR
"PROMS"[tiab])
05
94
Evidence and practice in spine registries
Appendix 2: NEWCASTLE - OTTAWA QUALITY ASSESSMENT SCALE for COHORT STUDIES
Note: A study can be awarded a maximum of one star (*) for each numbered item within the
Selection and Outcome categories. A maximum of two stars can be given for Comparability.
05
Selection
1) Representativeness of the exposed cohort (dependent on the diagnostic group)
a) truly representative of the average case in the community *
b) somewhat representative of the average case in the community *
c) selected group of users eg nurses, volunteers
d) no description of the derivation of the cohort
2) Selection of the non-exposed cohort
a) drawn from the same community as the exposed cohort *
b) drawn from a different source
c) no description of the derivation of the non-exposed cohort
3) Ascertainment of exposure
a) secure record (eg surgical records) *
b) structured interview *
c) written self-report
d) no description
4) Demonstration that outcome of interest was not present at start of study
a) yes *
b) no
Comparability
5) Comparability of cohorts on the basis of the design or analysis
a) study controls for the most relevant case mix variables (1. Diagnosis and 2. Baseline
outcome score) *
b) study controls for any additional factor *
Outcome
6) Assessment of outcome
a) independent blind assessment *
b) record linkage *
c) self-report
d) no description
7) Was follow-up long enough for outcomes to occur
a) yes (select an adequate follow up period for outcome of interest) *
b) no
8) Adequacy of follow up of cohorts
Evidence and practice in spine registries
95
a) complete follow up - all subjects accounted for *
b) subjects lost to follow up unlikely to introduce bias - small number lost → 20%; 80%
response *
c) follow up rate < 80% (select an adequate %) and no description of those lost
d) no statement
Total score (n stars)
05
Kovacs et al., 2012 [41]
Corcoll et al., 2006 [34]
Solberg et al., 2013 [39]
NORspine
Norwegian Registry for
Spine Surgery
Nerland et al., 2014 [25]
Spain
NRT en el SNS
Registry within Spanish
National Health
Service
Spain - Balearic Islands
NRT en el SNS
Registry within Spanish
National Health
Service
Norway
NORspine
Norwegian Registry for
Spine Surgery
Norway
Name Registry
To explore the feasibility of
implementing a registry in routine
practice.
To develop predictive models
to quantify the likelihood that
a given patient experiences a
clinical relevant improvement
To describe the implementation
of Neuroreflexotherapy and the
audit results
To estimate cut off values for
success
To study the equivalence of
changes in functional outcomes
Study purpose
Acute and chronic
Low Back Pain with
or without leg pain
Seeking care
Non-specific
subacute and
chronic neck, back,
and low back pain.
Lumbar disc
herniation
Lumbar spinal
stenosis
Indication
PROMs:
RMDQ
VAS (10cm) Back pain intensity
VAS (10cm) Leg pain intensity
Secondary PROMs:
VAS pain intensity of local and
referred pain
RMDQ
Rates of referral and appropriate
referral
Patient satisfaction
Physician satisfaction
Secondary PROM:
Global perceived effect (7-point
Likert scale)
PROMs:
ODI v.1
NPRS (0-10) Back pain intensity
NPRS (0-10) Leg pain intensity
EQ5D
Clinical:
perioperative complications
duration of surgical procedures
length of hospital stay
Secondary PROMs:
EQ5D
PROM:
ODI v.2.0
Outcomes 1
Independent variables in
model:
Gender
Age
Duration of current pain
episode (acute, subacute,
chronic)
Employment status
Education
Recruitment setting
Previous back surgery
Current episode because
of Failed Back Surgery
Syndrome
Diagnostic procedures/tests
current episode
Concomitant treatments
Not reported
Adjustment for baseline
scores:
ODI v.1
NPRS Back pain intensity
NPRS Leg pain intensity
EQ5D
Adjustment for:
Numbers of levels operated
(one or two)
Age
BMI
Baseline ODI value
Covariate adjustment
05
Author, year
Descriptive statistics
Improvement based on
Minimal Clinical Important
Change
Multivariate logistic
regression models using
backward strategy
Methods Missing data:
Multiple imputation
analysis (n= 5 imputed
datasets)
Descriptive statistics
Descriptive statistics
Treatment effect: Paired
Students t-tests
Subgroup comparison: oneway ANOVA
Relationship Global
Perceived change and
change scores: Spearman
rank correlation coefficient
Cut off values for success:
ROC analyses and AUC
Methods Missing data:
Complete cases analysis
Descriptive statistics
Mixed linear models
Statistics
96
Evidence and practice in spine registries
Appendix 3: Table S1. Study characteristics
Fritzell et al., 2014 [57]
Royuela et al., 2013 [38]
Kovacs et al., 2007 [48]
Sweden
SweSpine
Swedish National
Spine Register
Spain
NRT en el SNS
Registry within Spanish
National Health
Service
Spain - Balearic Islands
NRT en el SNS
Registry within Spanish
National Health
Service
To compare PROMs between
primary LDH and recurrent LDH.
To determine risk factors for worse
outcomes.
To assess the feasibility of using a
registry in routine practice.
To develop models predicting the
probability of improvement
To identify prognostic factors for
clinical outcome.
Lumbar disc
herniation
Non-specific
subacute and
chronic neck, back,
and low back pain.
Non-specific
subacute and
chronic neck, back,
and low back pain.
PROMs:
VAS (10cm) leg pain intensity
VAS (10cm) back pain intensity
ODI
EQ5D
Satisfaction and Global assessment
of change in leg pain
PROMs:
RMDQ for LBP / NDI for neck pain
VAS (10cm) local pain intensity
VAS (10cm) referred pain intensity
PROMs:
RMDQ
VAS (10cm) local pain intensity
VAS (10cm) referred pain intensity
Descriptive statistics
Improvement based on
Minimal Clinical Important
Change
Multivariate logistic
regression models
Nomograms to illustrate
results of models
Methods Missing data:
Multiple imputation
analysis (n= 10 imputed
datasets)
Descriptive statistics
Comparison baseline
characteristics between
groups: independent
Students’ t-test continuous
variables, Chi-square test
ordinal data.
In outcome calculation
ANCOVA was used.
Multivariate logistic
regression analysis
Independent vars in model:
Reason for referral (neck,
back LBP)
Gender
Age
Baseline PROMs
Number of days with
implanted surgical staples
Duration of current pain
episode (classified)
Duration since first
diagnosis (classified)
Employment status
Type of pain
Diagnosis of fybromyalgia
Other comorbidities
Involvement in employment
claims
Involvement in litigation
Diagnostic tests before
Neuroreflexotherapy (NRT)
Imaging findings
History of spine surgery
Treatments before NRT
Adjustments for:
Age
Gender
Smoking
Baseline value of analysed
PROM
Descriptive statistics
Multivariate logistic
regression models using
backward strategy
Independent variables in
model:
Reason for referral (neck,
back)
Gender
Age
Baseline PROMs
Number of days with
implanted surgical staples
Duration of current pain
episode (classified)
Duration since first
diagnosis (classified)
Failed previous surgery for
current episode
Evidence and practice in spine registries
97
05
Knutsson et al., 2013 [31]
Jansson et al., 2009 [50]
Jansson et al., 2005 [49]
Sweden
SweSpine
Swedish National
Spine Register
Sweden
SweSpine
Swedish National
Spine Register
Sweden
SweSpine
Swedish National
Spine Register
Sweden
SweSpine
Swedish National
Spine Register
To determine the association
between BMI and outcome of
lumbar spine surgery.
To report HRQoL outcome in an
Lumbar Spinal Stenosis cohort
To compare the findings with the
Swedish population.
To report the health-related
quality of life outcome in Lumbar
Disc herniation.
To compare the results with the
Swedish population.
To compare satisfaction after
decompression alone and
following decompression and
fusion.
Lumbar spinal
stenosis
Lumbar spinal
stenosis
Lumbar disc
herniation
Age: ≥ 50 years
Lumbar spinal
stenosis in one
or two levels,
with and without
pre-operative
spondylolisthesis
PROMs:
VAS (10cm) leg pain intensity
VAS (10cm) back pain intensity
ODI
EQ5D
Satisfaction 3-point Likert scale
Clinical outcome:
Height & weight (BMI)
PROM
EQ5D score and EQ-VAS
PROM:
EQ5D
PROMs:
VAS (10cm) leg pain intensity
VAS (10cm) back pain intensity
ODI
EQ5D
Satisfaction and Global assessment
of change in leg pain
Adjustment for:
Age
Gender
Smoking
Use of analgesics
Previous back surgery
Duration od symptoms
PROMs: Baseline values
Covariates:
Age
Gender
Smoking status
Type of surgery
Duration of back and leg
pain
Pre-operative walking
distance
PROM: baseline EQ5D
Covariates:
Age
Gender
Smoking status
Type of surgery
Duration of back and leg
pain
PROM: baseline VAS leg pain
Pre-operative walking
distance
PROM: baseline EQ5D
Baseline value of analysed
PROM
A frailty component was
included to handle withinhospitals dependencies
in patient selection and
surgical technique
Adjustments for:
Age (continuous)
Gender
Smoking
Duration of symptoms
Previous spinal surgery
Baseline analgesic use
05
Forsth et al., 2013 [62]
Descriptive statistics
General linear models
(GLM).
Restricted cubic-spline
logistic regression analysis
Descriptive statistics
MANOVA, adjusted for
covariates.
Descriptive statistics
MANOVA, adjusted for
covariates.
Descriptive statistics
Adjusted means were
estimated using Students’
t-tests.
Multivariate logistic
regression analyses
98
Evidence and practice in spine registries
Sigmundsson et al., 2013 [37]
Sigmundsson et al., 2012
[42]
Sanden et al., 2011 [55]
Robinson et al., 2013 [26]
Sweden
SweSpine
Swedish National
Spine Register
Sweden
SweSpine
Swedish National
Spine Register
Sweden
SweSpine
Swedish National
Spine Register
Sweden
SweSpine
Swedish National
Spine Register
To determine how different
constellations of back and leg pain
influence preoperative health
related quality of life.
To determine predictive factors of
surgical outcome.
To determine the relation
between smoking status and
disability after surgical treatment.
To compare the 2-year results of 3
methods of lumbar fusion (UIF, IPF,
and TLIF/PLIF).
Lumbar spinal
stenosis
Lumbar spinal
stenosis
Lumbar spinal
stenosis
Degenerative disc
disease
PROMs:
VAS (10cm) leg pain intensity
VAS (10cm) back pain intensity
ODI
Walking distance (categorized)
SF36
EQ5D
PROMs:
VAS (10cm) leg pain intensity
VAS (10cm) back pain intensity
ODI
Walking distance (categorized)
EQ5D
PROMs:
VAS (10cm) leg pain intensity
VAS (10cm) back pain intensity
ODI
Walking distance (categorized)
SF36
EQ5D
PROMs:
VAS (10cm) leg pain intensity
VAS (10cm) back pain intensity
ODI
EQ5D
Descriptive statistics
General Linear Models
(GLM), adjusted means
Multivariate logistic
regression
Descriptive statistics
Paired Students’ t-test;
Mann Whitney U, Kruskall
Wallis)
Multivariate regression
analysis
MANOVA for variation in
PROMs.
Descriptive statistics
Parametric tests:
Satterthwait t-test
Non-parametric tests:
Mann-Whitney test, test for
trend (Chi-square)
Controlled for:
Age
Duration of back and leg
pain
MRI: Multilevel stenosis and
spondylolisthesis
MRI: Central dural sac area ?
PROMs: baseline values
Walking distance, Back and
Leg pain
Not reported
Descriptive statistics
PROC MIXED and KenwardRoger method, adjusted
means
Modified Poisson regression
approach
Adjustment for:
Age
Gender
Smoking
Use of analgesics
PROMs: Baseline value
under study
Year of surgery: as 2 of the
methods were unevenly
distributed over study
period. In many hospitals
1 surgical method
predominated.
Adjustment for:
Age
Gender
Smoking
Use of analgesics
Previous back surgery
Duration od symptoms
PROMs: Baseline value
understudy
Evidence and practice in spine registries
99
05
Berg et al., 2010 [47]
Stromqvist et al., 2012 [61]
Sweden
SweSpine
Swedish National
Spine Register
Sweden
SweSpine
Swedish National
Spine Register
Sweden
SweSpine
Swedish National
Spine Register
To determine whether a registry
can provide the same information
as an RCT.
To elucidate the incidence of dural
lesions in decompressive surgery,
to identify risk factors and effect
on postoperative outcome.
To evaluate outcome of surgery
and to explore the role of spinal
fusion in predominant back pain
and predominant leg pain.
CLBP - Degenerative
disc disease
Lumbar spinal
stenosis
Lumbar spinal
stenosis
Complications
Reoperations
Work status
Medication
Satisfaction with operation
(categorized)
Secondary PROMs:
VAS (10cm) leg pain intensity
VAS (10cm) back pain intensity
ODI
Walking distance (categorized)
SF36
EQ5D
Global rating scale for improvement
of back and leg pain
PROMs:
VAS (10cm) leg pain intensity
VAS (10cm) back pain intensity
ODI
SF36
EQ5D
Satisfaction with operation
(categorized)
Not reported
Risk factors:
Age
Gender
Smoking
Work
Consumption of analgesics
Walking distance
Clinical risk factors:
Dural lesion
Number of levels
decompressed
Baseline PROM score
Satisfaction with operation
(categorized)
Clinical:
Dural lesion
Adjustments for:
Age
Gender
Duration of Leg and Back
Pain
Comorbidity
Smoking
PROMs:
VAS (10cm) leg pain intensity
VAS (10cm) back pain intensity
ODI
Walking distance (categorized)
SF36
EQ5D
05
Sigmundsson et al., 2014
[56]
Descriptive statistics
Two-tailed Mann-Whitney
U; Wilcoxon rank sum tests
Students’ t test; Spearman
r, Fisher exact; Chi-square
tests
Descriptive statistics
Logistic regression analysis
Descriptive statistics
Linear regression analysis.
Cox proportional hazard
model (Robust)
Outcomes compared with
unadjusted nonparametric
tests, test for trend (Chi
square), Mann Whitney
U test.
100
Evidence and practice in spine registries
Aghayev et al. 2010 [45]
Aghayev et al. 2012 [46]
Porchet et al. 2009 [51]
Grob and Mannion, 2009
[35]
Switzerland
SWISSspine
SWISSspine Registry
Switzerland
SSE
Spine Tango Surgery
Registry
SWISSspine
SWISSspine Registry
Switzerland
SSE Spine Tango
Surgery Registry
Switzerland
SSE Spine Tango
Surgery Registry
To evaluate the outcomes
of all single-level Dynardi
TDAs compared with all other
prostheses in the SWISSspine
data pool.
To compare back and leg pain
alleviation after total disc
arthroplasty and ALIF stratified
by implant and surgeon from the
SWISS-spine and Spine Tango
registries.
To compare outcome after lumbar
disc excision with and without the
use of the microscope.
To investigate the occurrence of
post-surgical complications form
the patient’s perspective.
CLBP - Degenerative
disc disease
CLBP - Degenerative
disc disease
Lumbar /
lumbosacral
degenerative
disorders
Spine surgery for
different pathologies
of the cervical and
lumbar spine
PROM:
NASS, used
- VAS (10 cm) Back pain intensity
- VAS (10 cm) Leg pain intensity
EQ5D
PROM:
NASS, used
- VAS (10 cm) Back pain intensity
- VAS (10 cm) Leg pain intensity
EQ5D
Secondary PROMs:
Satisfaction intervention (5-point
Likert scale)
Global perceived effect (5-point
Likert scale)
Patient-rated complications
(dichotomous)
PROM:
COMI, incl.
- NPRS (0-10) Back pain intensity
- NPRS (0-10) Leg pain intensity
Secondary PROMs:
Satisfaction intervention (5-point
Likert scale)
Global perceived effect (5-point
Likert scale)
Patient-rated complications
(dichotomous)
PROM:
COMI
Occurrence / nature of postop
complications
Covariates:
Device used
Gender
Age (categorized)
Surgical volume of center of
intervention
Pharmacologically treated
depression
Preoperative PROM
scores (pain and EQ5D;
categorized)
Baseline PROM score
Covariates:
Implant
Surgeon
Depression
Age
Gender
Follow-up interval
Length of stay (LoS)
Descriptive statistics
Wilcoxon rank-sum test
Chi-square tests
Multiple logistic regression
models; backward
elimination
Descriptive statistics
First step: univariate
logistic regression
Second step: generalized
linear model (GLM),
adjusted
Descriptive statistics
Unpaired Students t tests
Contingency analyses (Chisquare tests)
Gender
Age categories (<60; >60)
Health insurance (Private;
Basic obligatory)
Comorbidity (ASA score)
Baseline PROM score (COMI,
NPRS back and leg)
Descriptive statistics
To evaluate group
differences: Chi-square
tests for proportion
differences
Not reported
Evidence and practice in spine registries
101
05
Deer et al. 2004 [32]
McGirt et al. 2013 [40]
SWISSspine
SWISSspine Registry
Zweig et al. 2011 [43]
USA
National Outcomes
Registry for LBP
USA
N2QOD
National Neurosurgery
Quality and Outcomes
Database
Switzerland
SWISSspine
SWISSspine Registry
To obtain data on patient
demographics, clinical practices,
and long-term outcomes for
patients with CLBP treated
with implantable drug-delivery
systems.
To provide an overview of the
aims, registry design and methods
of the N2QOD pilot year lumbar
module.
To prove that preoperative
nucleus pulposis status
and presence or absence of
radiculopathy has an influence on
clinical outcomes in patients with
mono-segmental lumbar total
disc replacement.
To report the methodology
and implementation of the
SWISSspine registry and early
results of the cases with TDA.
CLBP - intrathecal
Drug Delivery (IDD)
Lumbar spinal
disorders:
- symptomatic
lumbar disc
herniation
- symptomatic
recurrent lumbar
disc herniation
- lumbar stenosis
- lumbar adjacent
segment disease
Not reported
mono-segmental
TDR surgery for
Degenerative disc
disease Hernia
nucleus pulposis no radiculopathy,
Stenosis, Hernia
nucleus pulposis radiculopathy
Not reported
Lumbar Total Disc
Arthroplasty (TDA)
PROMs:
NPRS (0-10) back and leg pain
ODI v1.0
Secondary
Return to work
Satisfaction (with IDD, recommend
IDD to others, and quality of life)
Adverse events
PROMs:
Patient satisfaction
NPRS (1-10) back and leg pain
ODI
EQ5D
Occupational outcome (return to
work, capacity)
Perioperative measures:
Blood loss
Length of Stay
Need for inpatient rehabilitation or
skilled nursing
90-day morbidity
readmission
reoperation
PROM:
NASS, used
- VAS (10 cm) Back pain intensity
- VAS (10 cm) Leg pain intensity
EQ5D
PROM:
NASS, used
- VAS (10 cm) Back pain intensity
- VAS (10 cm) Leg pain intensity
EQ5D
Patient characteristics:
age, gender, underlying
cause of pain, type of pain,
previous pain treatments,
use of systemic opioids,
work status, trialling site,
trial duration, type of
medical insurer, previous
psychological evaluations,
implant location, type of
system.
Patient characteristics and
demographic factors for
risk-adjustment
Adjustement for covariates:
Gender
Age
Preoperative pain
medication
Intervertebral level of
intervention
Pharmacologically treated
depression
Type of work
Working activity level
Covariates:
Prosthesis used
Gender
Age
Surgical volume of center of
intervention (categorized)
Pharmacologically treated
depression
Preoperative PROM scores
(pain and EQ5D)
05
Schluessmann et al. 2009
[54]
Descriptive statistics.
Chi-square tests and Paired
t-tests treatment effect.
Repeated measures ANOVA
outcomes over time .
Descriptive statistics
Risk-adjusted models
Complete cases analyses
Descriptive statistics
Univariate logistic
regression or ANOVA
General linear modelling
(GLM).
Bonferroni-Holm
adjustments for multiple
testing .
Descriptive statistics
Wilcoxon rank-sum test
Chi-square test
Multiple logistic regression
models, backward
elimination
102
Evidence and practice in spine registries
Kasliwal et al. 2012 [28]
Glassman et al. 2007 [52]
Glassman et al. 2009 [44]
Bridwell et al. 2007 [30]
Taylor et al. 2000 [53]
USA
Adult Deformity
Outcomes Database
USA
Adult Deformity
Outcomes Database
USA
Adult Deformity
Outcomes Database
USA
Adult Deformity
Outcomes Database
USA; community-based
Community outcomes
management study
To assess differences in surgical
parameters (e.g. Surgical time,
blood loss), complication
rates, and outcomes in adults
undergoing spinal deformity
correction who either did or did
not have a history of a shortsegment spinal procedure.
To determine whether
perioperative complications alter
clinical outcomes.
To examine outcomes after
adult deformity surgery. Do
1-year outcomes predict 2-year
outcomes?
To prospectively analyse the
responsiveness of the SRS-22 to
change 1 and 2-years following
primary surgery.
To examine factors associated
with favourable self-reported
outcomes 1 year after elective
surgery.
Adult deformity
Adult deformity
Adult deformity
Adult deformity
Lumbar spinal
disorders:
- degenerative
changes
- herniated disc
- instability (incl.
Spondylolisthesis)
- spinal stenosis
Clinical:
Complications
PROMs:
SRS-22
ODI v1
NPRS (0-10) for back and leg pain
SF12 (physical and mental
component scores)
PROMs:
SRS-22
ODI
NPRS (0-10) for back and leg pain
SF12 (physical and mental
component scores)
Clinical:
Complications
PROMs:
SRS-22
ODI
NPRS (0-10) for back and leg pain
SF12 (physical and mental
component scores)
PROMs:
SRS-22
ODI
SF12
Patient-reported questions:
- back surgery changed quality of life
- functioning better/worse than
before surgery
- rate of overall treatment of back
problem
- bothersomeness back pain
- bothersomeness leg pain
- interference of physical health in
activities
- most strenuous level of physical
activity
Descriptive statistics
Descriptive statistics
Matched-pairs sample
t-test statistics and posthoc ANOVA for treatment
effect and differences in
subgroups
Descriptive statistics
Propensity modelling.
Analysis: 1-way and
repeated measures ANOVA.
Descriptive statistics
Propensity modelling
Wilcoxon signed-rank or
Fisher exact tests used to
compare outcomes.
Subgroup analyses based
on:
Diagnosis
Curve type
Three defined complication
cohorts were matched:
Age (categorized)
Diagnosis
Baseline PROM SRS-22 total
score
Distal fusion level
Sagittal balance at 1-year
post-operation
Patients with/without prior
surgery were matched:
Age (categorized)
Baseline PROM ODI score
Cobb angle
Sagittal Vertical Axis (SVA)
Descriptive statistics
Chi-square test, Fisher
exact test differences
characteristics
Unconditional logistic
regression techniques used
Multivariate logistic
regression models
Age (categorized)
Curve type (major curve
location)
Baseline scores on patientreported questions
Age
Gender
Smoking habits
Duration of symptoms
Clinical signs
Diagnosis
Surgical procedure
Previous surgery
Work status
Workers’ compensation
Seeing attorney
Evidence and practice in spine registries
103
05
Singapore
Singapore General
Hospital Spine
Outcomes Registry
USA & Canada
Multicenter registry for
lumbar spine surgery
To compare midterm clinical and
radiological outcomes of minimal
invasive surgery (MIS) versus open
transforaminal lumbar interbody
fusion (TLIF).
To assess the effect of incidental
durotomies on the immediate
postoperative complications.
To investigate the patientreported outcomes at longer-term
follow up following lumbar fusion.
To determine if models for
predicting outcome and
complications can be constructed.
Lumbar spinal
disorders
Lumbar spinal
disorders:
- Degenerative disc
disease
- Grade
spondylolisthesis
with central of
foraminal stenosis
Adult deformity
Clinical:
Bridwell classification
PROMs:
ODI
Neurogenic Symptom Score (NSS)
SF36
VAS Back pain
VAS Leg pain
Clinical:
Postoperative complications
PROMs:
VAS Back pain
VAS Leg pain
ODI
Clinical:
Complications
PROMs:
SRS-22
ODI v1
NPRS (0-10) for back and leg pain
SF12 (physical and mental
component scores)
Not reported
Patients with durotomy
and controls were matched
using propensity modelling
(1:2) `based on:
Age
Gender
Comorbidities
Other relevant surgical
factors
Baseline PROM scores
Diagnosis
Classification type (type and
modifiers)
Surgical procedure
Age
Gender
BMI
Previous surgery (revision
state)
Pearson Chi-square,
Students’ t-test to
compare differences in
characteristics.
ANOVA to evaluate
differences in PROMs.
Independent Students’
t-test to compare
differences between
groups.
Descriptive statistics
Student t-test, MannWhitney U test and Chisquare tests.
Propensity modelling to
stratify risk.
Descriptive statistics
Two approaches were
used to determine factors
predicting successful
surgical outcome:
1. Binary logistic regression
models were built to
examine how factors
combine and interact.
2. Multiple linear regression
analyses using backward
and stepwise techniques
were used to eliminate
redundant predictive
factors.
Subsequently, binary
logistic regression
to predict a reported
complication.
1
PRO, M Patient-reported outcome measure; ODI, Oswestry Disability Index; RMDQ, Roland and Morris Disability Questionnaire; NPRS, Numeric Pain Rating Scale; VAS, Visual Analogue Scale; NASS, North American Spine Society
lumbar spine outcome scale; COMI, Core Outcome Measures Index; SF36, SF 12, Short Form 36 or 12 questions; EQ5D, EuroQol 5 Dimensions (including EQ VAS); SRS-22, Scoliosis Research Society 22 questions
Seng et al. 2013 [33]
Adogwa et al. 2013 [27]
USA
Adult Deformity
Outcomes Database
05
Schwab et al. 2008 [29]
104
Evidence and practice in spine registries
Evidence and practice in spine registries
105
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Guest editorial: Spinal disorders, quality-based healthcare and spinal registers
Acta Orthop. 2015; 86 (5): 521–522
See after Chapter 06 - page 130-133
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Chapter 06
A proposed set of metrics for
standardized outcome reporting
in the management of low back pain
Clement RC, Welander A, Stowell C, Cha TD, Chen JL, Davies M, Fairbank JC,
Foley KT, Gehrchen M, Hägg O, Jacobs WC, Kahler R, Khan SN, Lieberman IH,
Morisson B, Ohnmeiss D, Peul WC, Shonnard NH, van Hooff ML, Wassan AD,
Willems PC, Yeo W, Fritzell P
Published in: Acta Orthop. 2015;86(5)523-33
Appendix to Chapter 06 - editorial comment
(after Chapter 06 - page 130-133)
Guest editorial: Spinal disorders, quality-based healthcare and spinal registers
Fairbank JCT
Published in: Acta Orthop. 2015; 86 (5): 521–522
112
Abstract
Background & Purpose: Outcome measurement has been shown to improve performance in
several fields of healthcare. This understanding has driven a growing interest in value-based
healthcare, where value is defined as outcomes achieved per money spent. While low back
pain (LBP) constitutes an enormous burden of disease, no universal set of metrics has yet been
accepted to measure and compare outcomes. Here, we aim to define such a set.
Materials & Methods: An international group of 22 specialists in multiple disciplines of spine
care was assembled to review literature and select LBP outcome metrics through a 6-round
modified Delphi process. The scope of the outcome set was degenerative lumbar conditions.
Results: Patient-reported metrics include a numeric pain scales, lumbar-related function
using the Oswestry Disability Index, health-related quality of life using the EQ-5D-3L
questionnaire, and questions assessing work status and analgesic use. Specific common and
serious complications were included. Recommended follow-up intervals include 6, 12 and 24
months after initiating treatment, with optional follow-up at 3 months and 5 years. Metrics
for risk stratification were selected based on pre-existing tools.
Interpretation: The outcome measures recommended here are structured around specific
etiologies of LBP, span a patient’s entire cycle of care, and allow for risk adjustment. Thus, when
implemented, this set can be expected to facilitate meaningful comparisons and ultimately to
provide a continuous feedback loop, enabling ongoing improvements in quality of care. Much
work lies ahead in implementation, revision, and validation of this set, but it represents an
essential first step toward establishing a community of LBP providers focused on maximizing
the value of care we deliver.
Proposed set of metrics for LBP
113
Introduction
Measuring outcomes in healthcare has well documented benefits as well as challenges [1,2].
Simply asking providers to report their outcomes has been shown to improve performance
[3]. Additionally, understanding one’s results empowers a provider to continuously learn from
and refine the care he or she delivers [4]. On a broad scale, outcome reporting also facilitates
dissemination of best practices between physicians and makes it possible to compare the
quality delivered by different providers, allowing patients to make intelligent choices about
where to seek care [4]. This type of continuous improvement and informed decision making
could be an important driving force in improving healthcare delivery by refocusing the system
on value (defined as the outcomes of care divided by the cost). This concept of ‘value-based
healthcare’ has been gaining attention both throughout the medical field [1,5] and specifically
within the spine community [6,7]. With evolving reimbursement systems in many countries, it
is also conceivable that there will be growing interest in ‘value-based reimbursement’ in the
future, with payment levels adjusted based on outcomes. This type of scheme will only be fair
with a broadly-accepted and risk-adjusted set of outcome metrics.
Low back pain (LBP) is a growing problem in the population and constitutes a major
component of the global burden of disease [8]. Measuring outcomes in the field of low back
pain is challenging. Numerous disease states affect the low back, resulting in low back
pain, leg pain or both; to compare outcomes, patients must be accurately stratified by both
diagnosis and severity. Moreover, existing treatment algorithms are complex and often
controversial, including both operative and non-operative options and frequently requiring
multidisciplinary provider teams. Additionally, low back pain rarely causes death or other
objective end points, so outcomes are best measured by patient-reported metrics, which are
inherently subjective and require thorough psychometric testing.
A substantial amount of work has already been done in the field of low back pain and wellvalidated tools exist for measuring disease-specific outcomes [9]. Similarly, several large
registries are already in existence collecting outcomes, along with many other data points
[10-13]. Previous consensus-based efforts have been made to define sets of outcome measures
or domains for research purposes [14-16]. Still, the field of low back pain care has not yet
developed a universal international set of outcomes to be measured and compared as a part of
standard clinical practice. This type of outcome set requires availability and validity in many
languages, requires capacity for case-mix adjustment to ensure that comparisons are made
fairly, and should focus on the outcomes that matter most to patients. The purpose of this
study was to define such a set based on international and interdisciplinary expert and patient
opinion.
Methods
The set of outcomes we present, referred to as the standard set, was developed by consensus
among a 22-member ‘working group’ mostly comprised of surgical, rehabilitation and medical
experts in the field of low back pain, many of whom are active in spine registries (all members
are listed as authors). The group also included a former spine patient involved in patient
support groups (MD). The working group was convened and organized by the International
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Proposed set of metrics for LBP
Consortium for Health Outcomes Measurement (ICHOM), a non-profit organization focused
on the development of standard sets of outcomes and risk factors for multiple medical
conditions [17]. The working group’s efforts were coordinated by a core ‘project Team’
consisting of a working group lead (PF), a project leader (AW), a research fellow (RC), and the
ICHOM vice president of research and development (CS).
06
The project was structured as a modified Delphi process [18] involving 6 teleconferences
held between June and November of 2013. The goals of these calls were choosing inclusion
and exclusion criteria for the relevant patient population, selecting and defining outcome
metrics, and identifying initial disease conditions and risk factors that would allow patient
stratification and case-mix adjusted comparisons between providers. Teleconferences were
structured around proposals by the project team regarding how best to meet the goals of
the group. These proposals were based on review of academic literature, review of existing
practices among spine registries, and in some cases, direct input from working group members
and other experts in the field.
Decisions were made by surveys, which were designed based on the project team’s proposals
and the relevant discussion held during the teleconference. Surveys were circulated by email
following teleconferences to all working group members along with detailed minutes. In a
small number of cases, live votes were orchestrated during a call. For surveys and votes with
less than a two-thirds majority or with a particularly vigorous debate, the issue was revisited
by the project team and a new proposal was presented to the working group for consideration.
Several recurrent themes emerged throughout this process, and developed into guiding
principles for the group’s collaboration. First, we aimed to identify outcome metrics that are
most important to patients, which often resulted in favoring subjective information reported
by patients rather than objective clinical information traditionally followed by physicians.
Second, we sought genuine outcome metrics to gauge quality, not process metrics, which
are often used as inexact proxies for quality, as they are frequently easier to track. Third, a
consistent effort was made to simplify the set of outcomes and associated data, especially the
information requested from physicians in order to boost compliance. As such, we acknowledge
that the goal of the standard set should be to allow comparisons of clinical outcomes and,
while it will be sufficient to answer certain research questions, many academic pursuits will
require collection of additional data points. Fourth, when possible, existing tools with proven
validity and reliability such as the Oswestry Disability Index (ODI) and EQ-5D were selected
in their original format to preserve their proven psychometric properties. Finally, a conscious
effort was made to be continually aware of potential bias favoring surgical patients, given the
predominance of surgeons in the working group, which reflects the predominating focus on
surgical patients in the existing spine registries.
ICHOM had access to all data during the project, but neither ICHOM nor its funders had
editorial control over the final publication. The manuscript was drafted by the project team’s
research fellow (RC) and subsequently edited based on input of all the experts and co-authors.
Proposed set of metrics for LBP
115
Results
Response rates for the 5 working group surveys among the 22 working group members were
21, 20, 21, 20, and 21, respectively. Two original working group members participated in less
than half of teleconferences and surveys and are not included either in these response rates or
in the final list of members.
Scope: Degenerative lumbar conditions
The standard set targets degenerative lumbar conditions, which comprise the vast majority
of all of lumbar pathology [22]. Other areas of spine care involve different patient populations,
treatment approaches, and outcomes - and should be addressed in the future by analogous
condition-specific outcome sets. Formal inclusion criteria selected by the working group
consist of lumbar spinal stenosis, lumbar spondylolisthesis, degenerative disc disorders
including disc herniation, degenerative scoliosis, other degenerative lumbar disorders,
and acute and chronic lumbar back pain and back-related leg pain without a clear etiology
(often colloquially termed mechanical or non-specific pain). The relevant corresponding
exclusion criteria include spinal infection, tumor, fracture, traumatic dislocation, congenital
or idiopathic scoliosis, and age under 18 years.
Outcome domains (Table 6.1)
Traditionally, the 6 domains most commonly used to study outcomes among patients with
degenerative lumbar conditions have been function, pain, health-related quality of life
(HRQOL), work status, treatment complications and medication requirements [19]. This pattern
suggests that historically, spine providers have felt that these domains most accurately reflect
success rather than failure in this field. Furthermore, after careful consideration including
discussion with the group’s patient representative, the working group considered these are
the factors that matter most to patients. The group also agreed that the combination of these
factors provides adequate domain coverage for comprehensive assessment of treatment
outcomes in this population. Other metrics that have been used to study LBP care - including
psychosocial factors such as depression and ‘global effect’ [19] - were excluded from the set,
as historically they have been studied with inconsistent definitions [19] and they are probably
reflected in other domains such as HRQOL.
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Table 6.1 Patient-reported outcome measures
Outcome
Measurement
Tool
Definition/Wording
Answer options
Pain
Numeric pain
rating Scale
How would you rate
your average back pain
over the last week?
0 (no pain) - 10 (worst pain
imaginable)
How would you rate
your average leg pain
over the last week?
Disability
Oswestry disability
index
06
Quality of Life
EQ5D-3L
EQ-VAS
Work Status
Analgesic Use
Pain intensity
Personal Care (washing,
dressing, etc.)
Lifting
Walking
Sitting
Standing
Sleeping
Sex Life (if applicable)
Social life
Traveling
0 (no pain) - 10 (worst pain
imaginable), verbal or visual
(horizontal)
6 options for each domain
ranging from no problem
to severe impairment (see
appendix)
Mobility
Self-Care
Usual Activities
Pain/Discomfort
Anxiety/Depression
3 options for each domain
ranging from no problem
to severe impairment (see
appendix)
Indicate on this scale
how good or bad your
health is today
Vertical visual analog scale:
0 (Worst imaginable health
state) - 100 (Best imaginable
health state)
What is your current
work status?
Working full time, working
part time, Seeking
employment (I consider
myself able to work but
can't find a job), Not
working by choice (retired,
student, homemaker, etc.),
Unable to work due to
problem other than my back
and/or leg pain, Unable to
work due to back and/or
leg pain
Are you working
at a physically less
demanding job now
because of your back
and/or leg pain?
Yes, No, N/A
How long after you
received treatment
for low back pain did
you return to work? (if
applicable)
< 3 months, 3-6 months, 6-9
months, 9-12 months, 1-2
years, >2 years
Do you take nonnarcotic pain relieving
medication or tablets
for your back problems?
Yes regularly, Yes
sometimes, No
Do you take narcotic
pain relieving
medication or tablets
for your back problems?
Yes regularly, Yes
sometimes, No
Timeframe for
capturing
Baseline, index
event(s), 6 months, 1
year, 2years
Baseline, index
event(s), 6 months, 1
year, 2 years
Baseline, index
event(s), 6 months, 1
year, 2years
Baseline, index
event(s), 6 months, 1
year, 2years
6 months, 1 year,
2years
Baseline, index
event(s), 6 months,
1 year, 2 years
Proposed set of metrics for LBP
117
Patient-reported outcome measures (PROMs)
The core component of the standard set is a constellation of PROMs covering the 6 domains
listed above, collected at the time of enrollment for treatment and then at regular time
points. (As detailed below, some information on clinical complications also requires clinician
reporting.) PROM instruments were chosen by the working group on the basis of clinical
interpretability, feasibility of implementation, and psychometric properties (validity,
reliability, and responsiveness) [20].
Common and well validated methods for measuring pain include the numeric rating scale
(NRS) and the visual analog scale (VAS) [19,21], and the major existing spine registries are
divided between those options [10-12]. While there is no gold standard, a VAS allows patients
to provide a more specific response while a NRS is typically easier to use as it can be performed
verbally and does not require exact size calibration when reprinted or generated on a monitor.
The common 0-10 horizontal version asking for average pain over the last week has been
shown to be valid, reliable and to allow adequately specific responses among spine patients
[21-24]. This option was chosen by the working group (with 21 of 22 members in agreement) for
inclusion in the standard set, both for back and leg pain individually.
Numerous tools have been studied for measuring lumbar-related function in patients with
low back pathology [9,19]. The ODI is the most commonly used and cited tool for this purpose,
followed by the Roland Morris Disability Questionnaire (RMDQ) [19] and the Core Outcome
Measures Index (COMI) [25]. While all of these have been shown to be valid, reliable and
responsive in this population, the ODI is the most heavily studied, providing superior clinical
interpretability [19]. We also felt the ODI to be the most feasible to implement as it is validated
in 14 languages [as opposed to 9 for each of the RMDQ [19] and COMI [23]] and is relatively
short [10 items as opposed to 24 in the RMDQ [26] and 7 in the COMI [27]]. All are free with
online registration being required for use of the ODI [19]. For these reasons, the working group
unanimously chose the ODI 2.1a for inclusion in the standard set.
There are several tools for measurement of HRQOL in LBP patients exist [28-32], with the most
common and heavily studied being the SF-36 followed by the EQ-5D and accompanying EQVAS, Nottingham Health Profile (NHP) and SF-12 [19]. The SF-36 has been shown to be valid,
reliable and responsive in this population, while the NHP and SF-12 have been proven valid and
reliable [19]. To our knowledge, these have not been studied for responsiveness and none of the
psychometric properties of the EQ-5D have yet been examined among LBP patients. However,
the EQ-5D tool has an excellent track record among other demographics as well as the general
population [33,34], and has been shown to correlate well with the ODI in LBP patients [35].
Additionally, the volume of recent citations suggests a relatively rapid increase in the use and
dissemination of this tool, which is consistent with the anecdotal experience of working group
members. The EQ-5D and EQ-VAS also has the advantage of being relatively brief (6 items as
opposed to 36 in the SF-36, 38 in the NHP, and 12 in the SF-12) and has proven psychometric
properties in over 160 languages (in comparison to 155 for the SF-36, 2 for the NHP and 134 for
the SF-12) [19]. The EuroQol tool is also inexpensive [36] relative to the SF tools [37,38], while
use of the NHP is free. Lastly, the EQ-5D is superior for health economics evaluations as it is a
preference-based tool that allows utility calculations and cost effectiveness analysis [19]For
these reasons, the working group chose the EQ-5D for inclusion in the standard set, with 21 of
22 members in favor.
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Proposed set of metrics for LBP
Existing practices used by current registries for questioning patients about analgesic use
and working status were reviewed, and the approach used by the international Spine Tango
registry was felt to be the most concise and thorough [10]; the wording was modified slightly
by the working group.
06
Complications and adverse events
Adverse consequences of treatment, e.g. invasive procedures, comprise another category
of outcomes. While no objective criteria were used, the working group aimed to include
complications and adverse events that are relatively frequent, severe, avoidable and feasible
to capture. Careful attention was paid to the balance between gathering sufficient data to
allow comparisons between providers and keeping the collection process simple enough
to facilitate a high level of compliance. The decision was made to request that providers
report complications/adverse effects recognized at the time of an initial procedure or during
the associated hospitalization, which is considered the index period. Subsequently, when
completing PROMs questionnaires 6 months after an index period, patients should be asked
to report specified complications that occurred after this period. The interventions of interest
are surgeries and injection therapy, and for convenience, the same list of complications and
timeframe for collection should be used for both.
Early provider-reported complications selected for inclusion during the index period include
death, nerve injury, dural tear, vascular injury, deep infection and pulmonary embolus (PE)
(Table 6.2). In regions where reliable administrative death records are readily accessible, the
working group recommends the use of such administrative data to more accurately track outof-hospital mortality within the first 30 days. At the time of follow-up PROM questionnaires,
patients should be asked if they experienced a deep wound infection or PE as these can be
particularly detrimental complications but may only occur or be recognized after the index
period. As providers may not be made aware of unplanned re-hospitalizations within 30
days of the index period, which have become a popular healthcare quality metric, patients
should also be asked to report such events [39,40]. In countries and practices with reliable
administrative documentation of re-hospitalization, such as electronic medical records
or insurance databases, the working group recommends using this administrative data to
record such events. Reoperations after an index procedure, and the underlying cause, should
be reported by providers (Table 2).
Baseline characteristics and risk factors for case-mix adjustment
In order to statistically adjust analyses for fair and meaningful calculations, relevant data
on patients’ risk factors and initial conditions must be collected. The working group tried to
balance the time and financial cost of collecting data with the need for accurate comparisons,
while seeking internationally comparable data points. This information was addressed in 4
categories: demographics, baseline clinical status, baseline functional status and previous
treatments (Table 6.3). Common demographics currently in use in international registries
were reviewed and age, sex and socioeconomic status were chosen, with education level
being used as an internationally acceptable proxy for the latter. Specifically, the United
Nations Educational, Scientific and Cultural Organization (UNESCO) definitions of education
levels, which allow for international and cross-cultural comparisons, were selected for use
[41]. Race and ethnicity were discussed but they were ultimately felt to be of limited value as
risk adjusters.
Proposed set of metrics for LBP
To define a patient’s baseline clinical status, the lumbar pathology criteria defined and studied
by Glassman et al. [42] were selected, primarily for its applicability to both operative and
conservatively-treated patients (Table 6.3). To our knowledge, no single tool has been validated
to define the diagnoses of patients across the entire realm of degenerative lumbar pathology,
and the Glassman criteria is the only such tool that has been shown to be reliable between
providers. Additionally, our review suggests that providers will rapidly be able to learn and
use these criteria. In addition to these clinical data, indications for surgery should be recorded
to facilitate risk stratification. After review of the literature and current registries, the set
of operative indications used by the Swespine registry [12] was felt to be the most complete
yet concise example of such a list, and was chosen for inclusion in the standard set, to be
completed by providers at the time of surgery (Table 3). Additionally, the American Society of
Anesthesiologists (ASA) Physical Status Classification System has been shown to be prognostic
for many surgical procedures [43-45] and the working group felt it should be reported before
surgery.
In addition to data related directly to the lumbar spine and surgical risk, a patient’s baseline
clinical status also encompasses other comorbidities, which have historically been the basis
for risk adjustment in large patient populations. Patient-reported responses to the Charlson
comorbidity Index [46] have been proven predictive of both mortality and various PROMs
[47,48]. To our knowledge, no comorbidity list has been validated for risk adjustment in LBP
patients. For this purpose, we chose the collection of 13 conditions used by the UK National
Health Service for risk stratification in total hip replacement [49]. This set was augmented
with 2 conditions included in the Charlson index that the working group considered
particularly prescient in the LBP population: paraplegia/hemiplegia and HIV/AIDS (Table 6.3).
Smoking habits [50,51] and BMI [52-54] have been shown to provide prognostic value in lumbar
patients and were therefore also designated for collection at baseline. It should be noted that
depression - which is included among the patient-reported comorbidities described above
and which has been shown to be predictive of outcomes among spine patients [55-57] - was
discussed at length, and the working group concluded this information should be collected by
patient report rather than formal depression screening or physician report, both for the sake
of efficiency and because depression is likely reflected in other PROMs such as HRQOL. Lastly,
some PROMs collected at baseline provide relevant information about a patient’s baseline
clinical status and should be used for risk adjustment analyses - namely pain level, duration of
symptoms, and current analgesic use.
Similarly, a patient’s baseline functional status is delineated through initial PROMs collection,
i.e. by measuring disability, HRQOL, work status and (when applicable) duration of sick leave.
Finally, the working group felt strongly that information on previous treatments is essential for
accurate risk adjustment, and selected previous surgery and injection therapy for collection
at baseline (Table 6.3 and Figure6.1A), as history of each of these has been shown to be
prognostic for subsequent treatment outcomes [58-61]. Stratification of previous operations
as either discectomy, decompression, or fusion was deemed to be adequately simple for
data collection purposes while being sufficiently detailed for risk adjustment. Additionally,
while technically a process metric, the working group recommends providers record the
types and levels of surgeries and injections performed at the time of intervention to further
facilitate risk stratification (Figure 6.1B). Again, this level of detail is intended to be as brief as
possible in order to streamline data collection while simultaneously allowing meaningful risk
adjustment.
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120
Proposed set of metrics for LBP
Figure6.1A. A tool for recording the date and type of prior treatment
6.1B. A tool for recording interventions performed on an ongoing basis
Figure 1A. Prior surgical interventions
"Indicate those that apply by entering month/year of surgery in boxes below."
Procedure type
T12-L1
L1-L2
L2-L3
L3-L4
L4-L5
L5-S1
L3-L4
L4-L5
L5-S1
Discectomy
Decompression
(laminectomy)
Fusion
Figure 1B. Interventions
06
"Indicate type and level of current procedural intervention."
Procedure type
T12-L1
L1-L2
L2-L3
Discectomy
Decompression
(laminectomy)
Fusion
Other back surgery
Injection therapy
‘Index events’ and timeframe of follow-up
Regarding the timing of data collection, we elected to establish follow-up at 6 months, 1 year
and 2 years after initiating treatment (Table 6.1 and Figure 6.2). Additional follow-up points at
3 months and 5 years were recommended, though not mandatory, as the former is probably
meaningful in the management of non-operatively-treated patients but less so for surgical
patients; and for the latter, the contrary is usually true. To simplify data collection and improve
compliance, we decided to record complications only following index operations and not after
reoperations, which would complicate the follow-up process substantially.
Index events, a term adopted from the SweSpine Registry [12], are points in the course of care
that should trigger the follow up schedule to be reset. The initiation of treatment for any new
condition, whether managed surgically or not, clearly constitutes an index event. Reoperation
for management of a complication or failure to attain the therapeutic goals of an initial
surgery is not an index event. However, surgery for a new diagnosis or at a new vertebral level
is considered to be a new index event and should cause follow up, including all measurement
of PROMs, to be reset (Figure 6.3). At that point, the follow-up schedule started after the
initial index event is discontinued, as it is not practical to simultaneously conduct 2 follow up
schedules for a single patient.
Proposed set of metrics for LBP
121
Figure 6.2. The recommended timeline for collection of each outcome measure
Figure 2. Timeline of outcome measurements Data points Baseline Index period1 6 mts2 1 yr 2 yrs3 PROMs for pain, disability and Q.O.L. Work status Time to return to work Continuous oral analgesic use Mortality Need for reopera+on Captured when reoperation(s) occurs Cause of reopera+on Need for rehospitalisa+on Complica+ons: Nerve root injury, Vascular injury, Dural tear, Other complica+ons 06
Complica+ons: Deep wound infec+on, Pulmonary embolus Risk factors Descriptors of clinical condi+on Type and level of surgery and surgical indica+on Patient-­‐reported Physician-­‐reported Administratively-­‐reported (when available) 1. Risk factors and descriptors of clinical condition reported pre-­‐intervention, complications and mortality reported at discharge 2. Collection also recommended at 3 months, but only deemed mandatory as displayed 3. Collection also recommended at 5 years, but only deemed mandatory as displayed Figure 6.3. A classification scheme to define interventions as either index events or reoperations
Figure 3. Defini-on of index events and reopera-ons Initiation of non-­‐surgical treatment or 1st lumbar surgery (Always an index event) Data captured at this time: Risk factors, descriptors of clinical condition, and when applicable, surgical indication, in-­‐hospital complications, type and level of procedure (Follow up: 6 mos, 1 yr, and 2 yrs) 2nd and following lumbar surgeries An index event if 1. Operation is on a different level than index surgery, regardless of diagnosis 2. Operation is on the same level as prior surgery, but for a different diagnosis Follow up: 6 mos, 1 yr, and 2 yrs (Follow up for prior index is discontinued) Considered reoperation (not an index event) if 1. Operation is on the same level for the same diagnosis as index event 2. Operation is on the same level as index event due to a complication 3. Operation is on another level but due to complication from index surgery Data captured at time of reoperation: Risk factors, descriptors of clinical condition, cause of reoperation, in-­‐
hospital complications, type and level of procedure Follow up: Continues as planned from index surgery 122
Proposed set of metrics for LBP
Table 6.2 Adverse outcomes of treatment
06
Outcome
Definition/Wording a
Answer
Options
Mortality
Death in-hospital (all-cause mortality)
Yes/No
Nerve root injury (including
cauda equina syndrome)
Iatrogenic nerve root damage
Yes/No
Vascular injury
Clinically significant iatrogenic
damage to a vessel
Yes/No
Dural tear
Iatrogenic damage of the dura with
liqour emission
Yes/No
Other2
(e.g. hematoma, malpositioned
implant, DVT without PE, device
failure, persistent donor-site pain,
other)
Yes/No
Deep wound infection b
Post-intervention deep/subfascial
wound infection
Yes/No
Pulmonary embolus c
PE diagnosed by radiologic study after
the intervention
Yes/No
Rehospitalization
Were you admitted to an acute care
facility as an in-patient within 30 days
from the date of your intervention for
ANY reason (do not include admissions
to rehabilitation hospital or nursing
home)?
Yes/No,
date(s)
Time frame for
capture
Reported by
While in-house for
procedure
Provider
While in-house for
procedure and again on
next patient follow up
questionnaire
Provider reports
if occuring inhouse, otherwise
Patient reports at
next follow up
Next patient follow up
questionnaire
Patient
At time of reoperation
Provider
Need for reoperation
a
b
c
(if yes, specify cause)3
Second or multiple performed
interventions caused by complications
after index surgery, not planned in
advance
Hardware removal
Removal of implants: e.g. screws, rods
Yes/No
Symptomatic non-union
Pain related to failure of bony
consolidation of bridge/union at
minimum 12 months after surgery
Yes/No
Neuro-compression
Compression of neural structures with
or without neurological deficits
Yes/No
Postoperative infection
Superficial or deep (subfascial)
wound/tissue infection after surgery
Yes/No
Implant malposition
Incorrect position of the implant
Yes/No
Implant failure
Problem due to an implant e.g.,
loosening, breakage
Yes/No
Wrong site surgery
Unintentional intervention on the
wrong level/site, not on level of main
pathology
Yes/No
Sagittal imbalance
Sagittal malalignment of the spine
Yes/No
CSF leakage
Including CSF fistula,
pseudomeningocele, etc.
Yes/No
Epidural hematoma
Bleeding hematoma outside dural sac
but inside bony spinal canal (with or
without neuro-compression)
Yes/No
Other
State reason for reoperation
Complication definitions modified from Spine Tango registry
Definition provided is designed for providers, a modified definition will be included on patient questionnaires
Reoperation definition and definitions for causes of reoperation modified from Spine Tango registry
Proposed set of metrics for LBP
123
Table 6.3 Risk factors and Initial conditions
Categories and
metrics
Definition/wording
Answer options
Timeframe
for capture
Reported
by
Date of birth
dd/mm/yyyy
Baseline
Patient
Male/female
Baseline
Patient
Please indicate your
highest level of schooling
completed*
None, primary, secondary, tertiary
Baseline
Patient
Symptoms
Back pain dominant (acute), leg pain dominant
(acute) back pain = leg pain (acute), back pain
dominant (chronic), leg pain dominant (chronic)
back pain = leg pain (chronic), neurogenic
claudication, cauda equina syndrome
Baseline and
at time of any
intervention
Provider
Structural pathology
No study or interpretation available, age
appropriate, disc pathology with normal
height, disc space collapse, spondylolysis/
spondylolisthesis, scoliosis/kyphosis, facet
pathology, non-union
Compressive pathology
No study or interpretation available, no clinically
relevant compression, central compression,
lateral compression, combined central & lateral
compression, recurrent compression following
surgery at the same level
How would you rate your
average back pain over
the last week?
1-10, as per Table 1
How would you rate your
average leg pain over the
last week?
1-10, as per Table 1
How long have you had
your current back pain?
I don't have back pain, < 3 months, 3-12 months,
1-2 years, >2 years
How long have you had
pain radiating to your
leg(s)?
I don't have pain radiating to my legs,
< 3 months, 3-12 months, 1-2 years, >2 years
Smoking habits
Do you smoke?
BMI
Indicate the patient's
height
Indicate the patient's
mass
Measured in kg
Comorbidities
Indicate if you have been
diagnosed with each of
the following conditions
ASA score (surgical
patients only)
Physical Status
Classification System
Demographics
Age
Gender
Education level
Baseline clinical
status
Glassman criteria
Pain
Duration of
symptoms
Surgical indication
06
Baseline
Patient
Baseline
Patient
Yes/no
Baseline
Patient
Measured in cm
Baseline
Provider
Heart disease, hypertension, poor circulation,
lung disease, diabetes, kidney disease, liver
disease, nervous system disease, cancer,
depression, arthritis, peptic ulcer disease,
hemiplegia/paraplegia, AIDS
Baseline
Patient
1. healthy, 2. mild/moderate, 3. severe, 4. life
threatening, 5. moribund, unknown
At time of
operation
Provider
Paramedian disc herniation, central disc
herniation, central spinal stenosis with
degenerative listhesis, central spinal stenosis
without degenerative listhesis, lateral spinal
stenosis, isthmic spondylolysis/spondylolisthesis,
segmental pain (with or without degenerative
listhesis, degenerative scoliosis, other
At time of
operation
Provider
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Proposed set of metrics for LBP
Baseline
functional status
Disability
ODI
As per Table 1
Baseline
Patient
Quality of Life
EQ-5D-3L
As per Table 1
Baseline
Patient
Work status
What is your current work
status?
As per Table 1
Baseline
Patient
Are you working at a
physically less demanding
job now because of your
back and/or leg pain?
As per Table 1
Are you currently on sick
leave from work?
Yes, full time for my back problems, Yes parttime for my back problems, Yes due to another
disease, No
Baseline
Patient
If yes, for how long?
1 week or less, 1-4 weeks, 1-3 months, 3-6 months,
6-9 months, 9-12 months, 1-2 years, > 2 years
Surgery
Please specify any prior
procedure(s) and the
level(s) by ticking one or
several of the boxes below
See Figure 3
Baseline
Patient
Injection therapy
Have you previously
received spinal
injections for your
current symptoms? (e.g.
epidurals, specific nerve
root injections, facet
injections or discograms)
Yes/no
Baseline
Patient
Duration of sick
leave (if applicable)
06
Prior treatment
*Level of schooling using culture-specific definitions per ISCED (International Standard of Schooling Classification, UNESCO) [40]
Discussion
We present a standard set of clinical outcome metrics for the use in clinical practice for
assessing the management of degenerative low back conditions based on the existing
literature and on international expert opinion. The set includes patient-reported information
on physical function, HRQOL, pain and work status as well as complications of treatment and
baseline characteristics to facilitate risk adjustment.
Several registries of spine patients already exist, tracking tens of thousands of patients
in numerous countries [10-12]. While these undertakings have been beneficial in many
regards, including providing descriptive information about spine care at a population level
and answering research questions involving comparisons of various interventions, broader
international comparisons have been limited because each existing registry has developed
its own metrics for gauging outcomes and definitions for categorizing specific diseases and
associated risk factors. Furthermore, registries often do not capture the complete patient
population for various diseases because most, but not all [62], spine registries do not follow LBP
patients who are managed non-operatively. This limitation precludes complete comparisons
of all available treatment options. Moreover, existing registries often do not capture the entire
cycle of care but instead tend to focus on the course of surgical care.
Proposed set of metrics for LBP
The proposal we present aims to overcome these shortcomings by establishing a standard
terminology for measuring outcomes in LBP patients, largely based on well-validated tools
that are available in numerous languages. This specific outcome set is particularly well
suited to facilitating meaningful comparisons between providers, because it stratifies
patients by disease and includes the entire patient population associated with a given
diagnosis throughout the full course of their care. Several recommendations have previously
been published for standardized outcome measurement in low back pain research, but not
specifically for use in everyday clinical practice [14,15,63]. Most recently, a research task force
chartered by the National Institute of Health (NIH) Pain Consortium described an outcome
set for use in chronic LBP research centered on patient-reported outcomes and largely relying
on the Patient Reported Outcome Measurement Information System (PROMIS) instrument
[63]. While there is substantial overlap in the domains chosen by our working group and those
selected by the NIH task force, the work of the latter is not adequately comprehensive to launch
into clinical practice as it leaves several decisions to the discretion of future researchers, such
as the timeline of patient follow up, the specific adverse events to be recorded, and even
which PROMs tools should be used. Furthermore, while the PROMIS instrument offers great
potential efficiency through computer adaptive testing and may eventually become favorable
to the legacy measures recommended here, it is not yet broadly translated and validated
beyond English [64] and is therefore not ready for international use.
A similar effort is currently being conducted by the ‘International Steering Committee for
the Core Outcome Set for Low Back Pain’ [16]. Initial findings presented at the ‘Core Outcome
Measures in Effectiveness Trials’ (COMET) meeting in November 2014, prioritized 3 domains
identical to those chosen by our working group: physical function, pain intensity, and HRQOL,
with work ability ranked fourth. While useful for guiding researchers who are developing
LBP outcome measures, these recommendations are not detailed enough for use in clinical
practice. Another commendable effort was previously described as part of the Multinational
Musculoskeletal Inception Cohort Study Collaboration (MMICS), which again showed
substantial overlap with the domains and variables chosen by our working group [15]. While
reasonable for research efforts, the MMICS outcome set and especially the associated timeline
for collecting data would be overly burdensome for ongoing use in non-research settings.
With the working group’s goal fulfilled, including a complete set of outcomes and associated
data defined; the focus can be shifted to implementation. For providers, group practices, and
registries that ascribe to the benefits of outcome measurement, this set will be available
for voluntary adoption. Practices with existing data collection processes may be able to
incorporate the standard set into ongoing workflows in ways that will minimize additional
work after an initial learning curve. Other organizations may need to begin by establishing
an infrastructure for prospective data collection. ICHOM is committed to facilitating broad
adoption of this set and has made the full recommendations of this group freely available on
its website, along with a reference guide to assist with technical aspects of implementation
[65]. Looking forward, revisions to this outcome set will be needed. For example, computerized
adaptive testing may provide efficiency gains in PROM collection as software progresses [66].
ICHOM and representatives from the working group plan to actively monitor use of this set
through a steering committee comprised of representatives from several existing outcome
measurement efforts. Their work will involve communication with users, including collection
of direct feedback. The frustrations and innovations of providers employing this set will be
125
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126
Proposed set of metrics for LBP
crucial to its improvement, and structured revisions to the set will be reviewed on an annual
basis. The steering committee will also be available to communicate with relevant third
parties. For example, some instruments recommended in this outcome set, such as the EQ-5D,
are proprietary and continued inclusion in the set may be dependent on future negotiated
agreements.
06
Our work has a number of limitations that should be mentioned. Firstly, the proposed
outcome set remains untested, and while it is largely based on existing tools and familiar data
points, the specifics of survey circulation and the associated timeframes for data collection
and reporting will inevitably lead to bumps in the road. Secondly, despite our best efforts to
generate diverse international consensus, our outcome set surely is not equally applicable to
all cultures. Much work in linguistic and cross-cultural validation remains. Still, we feel that
our work represents a sufficient and important starting point. Thirdly, much work remains
to be done on the practical issues of compiling and analyzing data, ultimately building
robust risk-adjustment models with appropriate quality assurance to produce reports that
accurately reflect provider performance while simultaneously protecting patient privacy. This
will be particularly important if value-based reimbursement does indeed come to fruition.
For example, in Sweden there are ongoing efforts in conjunction with the Swespine Registry
to link reimbursement levels to postoperative patient-reported outcomes. ICHOM intends
to continue its facilitative role to guide development of such models and their inclusion in
quality reporting initiatives.
In summary, the members of the working group feel that the introduction of this set of
outcomes for the treatment of degenerative low back pathology is an essential step toward
an international spine community that routinely measures and reports its performance
in common and meaningful ways. We invite all providers caring for patients with low back
pain to join us in measuring this set; the full list of metrics, contact information, and other
resources to facilitate implementation are available on the ICHOM website [65].
Proposed set of metrics for LBP
127
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following epidural steroid injections. J.Bone Joint Surg.Am. 2013;95:961-964
62. Kessler JT, Melloh M, Zweig T, Aghayev E, Roder C. Development of a documentation instrument for the
conservative treatment of spinal disorders in the International Spine Registry, Spine Tango. Eur.Spine J.
2011;20:369-379
63. Deyo RA, Dworkin SF, Amtmann D, Andersson G, Borenstein D, Carragee E et al. Focus article: report of the NIH
Task Force on Research Standards for Chronic Low Back Pain. Eur.Spine J. 2014;23:2028-2045
64. NIH PROMIS Website. PROMIS: Translations [Internet]. 2014 [cited 2014 Dec 12]. Available from: http://www.
nihpromis.org/measures/translations
65. ICHOM Website. ICHOM - International Consortium for Health Outcomes Measurement - Low Back Pain
[Internet]. 2014 [cited 2014 Dec 21]. Available from: http://www.ichom.org/project/low-back-pain/
66. Fries JF, Bruce B, Cella D. The promise of PROMIS: using item response theory to improve assessment of
patient-reported outcomes. Clin.Exp.Rheumatol. 2005;23:S53-S57
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Guest editorial
Guest editorial:
Spinal disorders, quality-based healthcare and spinal registers
Acta Orthop. 2015; 86 (5): 521–522
Jeremy Fairbank
Professor of Spine Surgery, University of Oxford, UK
06
In this issue of Acta Orthopaedica 2 articles [1,2] represent waymarks on a road towards
a conception of universal value-based healthcare for spine. This goal is expected to be a
convergence of the interests of patients, payers, politicians and clinicians. The articles are
focused on the painful lumbar spine, which represent the top ranking chronic healthcare
complaint [3]. Clinicians’ interest in quality dates back to Florence Nightingale in the Crimea.
For patients it goes back to time immemorial. For economists it has become an issue in the
last 2 decades. All politicians should be interested in this topic, and this is kindled by public
dissatisfaction and the rising costs of healthcare.
ICHOM (International Consortium of Health Outcomes Measurement, www.ichom.org/) is an
organisation recently founded by the Institute for Strategy and Competitiveness at Harvard
Business School, the Boston Consulting Group, and the Karolinska Institute to enable the shift
towards value-based health care. The concept of value-based health care has been described
by Michael Porter, a co-founder of ICHOM, as the only strategy that will fix health care [4]. The
central point of his work is the need to look at outcomes and cost together in driving clinical
improvement and policy.
Health registers play a central role in the measurement of outcomes and thereby enable
the shift towards a value-based system: the Swedish Knee Arthroplasty Register (start 1975)
(www.knee.se) and the Swedish Hip Arthroplasty Register (start 1979) (www.shpr.se), being
the first and most notable in the musculoskeletal world. In 2012 ICHOM identified 4 areas of
healthcare to define international standard sets of outcome measures. One of these was low
back pain, and one output of this process is the paper by Clement et al. [1]. There have been
earlier attempts to identify optimum outcome measures for research [5,6], but this is the first
to search for an international consensus on quality measures for use in daily clinical practice.
ICHOM is in the process of extending this exercise, which involves a defined methodology,
to many other areas of healthcare: it has now completed 12 ‘standard sets’ (of outcome
measures), and plans to have 50 completed by 2017.
Since the establishment of the Swedish Spine Register (SweSpine, www.swespine.se) in 1992,
spine registers have sprung up in other countries. The systematic review by van Hooff et al.
[2] is a first attempt to see if these registers are influencing quality. Whilst the case remains
unproven, they are able to cite a number of examples where it would appear that a register
has altered behaviour and improved quality. I do not doubt that, as this movement evolves, so
we shall see better evidence of impact. This can only be good from the patient perspective, but
Registers do not yet to have the capacity to answer the universal question as to which doctor is
likely to deliver an individual the optimum health care. The register should be able to confirm
whether a given provider is an outlier nationally (and if ICHOM is successful) internationally.
The ambitions of ICHOM are much grander: it is their intention that health care systems should
reimburse providers on the basis of quality rather than quantity. This is beginning to happen
Guest editorial
131
in Sweden, but I believe it will be some time before such systems evolve in other healthcare
economies. There are early signs of this movement developing in my country.
There is devil in the detail. Table 5.3 in van Hooff et al. gives a detailed list of recommendations
for enhancing spine registers. Register models can only work with patient involvement and
particularly the completion of follow-up questionnaires has to be high. Van Hooff et al.
recommend 60 to 80% compliance. The reported completion rate from the National British
Spine Register is only 20%. Subtle ‘sticks and carrots’ need to be developed to encourage
patient completion. It means the forms have to be a short and clear. More qualitative
research is needed to explore these issues. Consideration may be needed to offering adequate
reimbursement for the time and trouble of completing outcome measures [7].
The outcome measures themselves require care and attention. Most have evolved since
the 1970s. Some like EQ-5D, are managed by committees. Others like ODI, are managed by
their original authors. Others, such as NRS pain, are essentially orphans since their original
description by Huskisson in the 1970’s [8-10]. ICHOM has a duty to ensure that the measures
they recommended are looked after and not subjected to alterations. It is vital that they are
translated accurately by a standard protocol. ODI, for example, recommended as part of
the ICHOM low back pain outcome set, is now licenced to the MAPI Trust in Lyon, which has
pioneered good practice in this regard (www.proqolid.org/instruments/oswestry _disability_
index_odi). ICHOM should consider sponsoring orphan instruments (perhaps at MAPI) such as
NRS to ensure that they are delivered in as consistent a way as possible.
It must be noted that there are problems with registers and the interpretation of their data.
Most are owned and managed by clinicians. So long as this model is transparent, it probably
keeps the data safer from meddling than it would be in the hands of governments, who
also serve as purchasers. Registers need funding, which also generates problems of long
term viability and conflicts of interest [2]. Properly defining criteria of success and failure is
an important challenge. The Swedish Knee and Hip Registers and its various international
descendants have used revision rates as an important criterion of failure. When this is
applied to the knee register, unicompartmental knee replacements are shown to have higher
revision rates than total knee replacement, arguably not because they actually fail more
frequently, but because surgeons are more ready and willing to revise a unicompartmental
knee replacement than a total knee replacement [11]. Unsurprisingly this view is disputed by
the directors of knee registers [12], but some complex issues of quality and cost are involved
here. I see a parallel situation in the use of interspinous spacers to treat spinal stenosis. 2 RCT’s
have shown similar outcomes between spacers and conventional decompressive surgery but
with higher revision rates in the spacer group [13,14]. Both these examples are significant
because the initial implant cost is high, but they do reflect the important point that defining
outcome metrics is potentially treacherous. This matters in many ways, but particularly when
reimbursement depends on it. Rigorous metrics defined based on established methodologies,
arguably such as those presented in the ICHOM standard set, should present an answer to this
challenge.
Those registers that use mortality as an outcome, such as cardiac surgery, may make cardiac
surgeons more risk averse so that they avoid high-risk patients [15,16]. Statistical variation
becomes a major problem when these results are distilled down to individual surgeon data.
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Guest editorial
This has provoked problems previously in the US and currently in the UK where SSMD (Surgeon
Specific Mortality Data) has recently become mandated. Discussion on this continues [15-19].
The quality movement in healthcare needs the strong support of everyone involved. We need
the education and involvement of our public and politicians to make this happen. As van Hooff
et al. spell out, registers are important, and need good methodology and design, with care
and attention to deliver quality data. How these data are interpreted and presented will need
continual scrutiny and innovation as their importance in the health economy increases.
Conflict of interest
Jeremy Fairbank is coauthor of the Clement et al. paper, and is a copyright holder of the
Oswestry Disability Index
06
Guest editorial
133
References
1. Clement RC, Welander A, Stowell C, Cha TD, Chen JL, Davies M et al. A proposed set of metrics for standardized
outcome reporting in the management of low back pain. Acta Orthop. 2015;86:523-533
2. van Hooff ML, Jacobs WC, Willems PC, Wouters MW, de Kleuver M, Peul WC et al. Evidence and practice in
spine registries. Acta Orthop. 2015;86:534-544
3. Vos T, Flaxman AD, Naghavi M, Lozano R, Michaud C, Ezzati M et al. Years lived with disability (YLDs) for
1160 sequelae of 289 diseases and injuries 1990-2010: a systematic analysis for the Global Burden of Disease
Study 2010. Lancet 2012;380:2163-2196
4. 5. Porter M, Lee T. The strategy that will fix health care. Harvard Business Review 2013;91:50-70
Deyo RA, Battie M, Beurskens AJ, Bombardier C, Croft P, Koes B et al. Outcome measures for low back pain
research. A proposal for standardized use. Spine (Phila Pa 1976.) 1998;23:2003-2013
6. Deyo RA, Dworkin SF, Amtmann D, Andersson G, Borenstein D, Carragee E et al. Report of the NIH task force
on research standards for chronic low back pain. Spine (Phila Pa 1976.) 2014;39:1128-1143
7. Williams CM, Maher CG, Hancock MJ, McAuley JH, Lin CW, Latimer J. Recruitment rate for a clinical trial
was associated with particular operational procedures and clinician characteristics. J Clin.Epidemiol.
2014;67:169-175
8. Huskisson EC. Measurement of pain. Lancet 1974;2:1127-1131
9. Scott J, Huskisson EC. Graphic representation of pain. Pain 1976;2:175-184
10. Scott JHuskisson EC. Vertical or horizontal visual analogue scales. Ann.Rheum.Dis. 1979;38:560
11. Goodfellow JW, O'Connor JJ, Murray DW. A critique of revision rate as an outcome measure: re-interpretation
of knee joint registry data. J.Bone Joint Surg.Br. 2010;92:1628-1631
12. Robertsson O, Graves S, Hooper G, Lidgren L, Rothwell A, de Steiger R. Letter: A critique on revision rate as
an outcome measure (A critique on revision rate as an outcome measure: Re-interpretation of knee joint
registry data. J.W. Goodfellow, J.J. O'Connor, and D.W. Murray. J Bone Joint Surg [Br] December 2010 92B:1628-1631). J Bone Joint Surg [Br] 2011;93-B
13. Moojen WA, Arts MP, Jacobs WC, van Zwet EW, van den Akker-van Marle ME, Koes BW et al. Interspinous
process device versus standard conventional surgical decompression for lumbar spinal stenosis:
randomized controlled trial. BMJ 2013;347:f6415
14. Stromqvist BH, Berg S, Gerdhem P, Johnsson R, Moller A, Sahlstrand T et al. X-stop versus decompressive
surgery for lumbar neurogenic intermittent claudication: randomized controlled trial with 2-year followup. Spine (Phila Pa 1976.) 2013;38:1436-1442
15. Westaby S, Baig K, Pepper J. Publishing SSMD: the risks outweigh the benefits. Bulletin of the Royal College
of Surgeons of England 2015;97:155-9
16. Westaby S, Baig K, Pepper J. Publishing SSMD: and another thing. Bulletin of the Royal College of Surgeons of
England 2015;97:212-3
17. Bridgewater B. Patient-facing data is essential in the digital era. Bulletin of the Royal College of Surgeons of
England 2015;97:160-3
18. Gottlieb G. Outcomes data: the road to expansion and enhancement. Bulletin of the Royal College of
Surgeons of England 2015;97:214-5
19. MacFie J. FSSA statement on individual surgeons' outcomes data. Bulletin of the Royal College of Surgeons
of England 2015;97:214-5
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Chapter 07
The Oswestry Disability Index
(Version 2.1a)
Validation of a Dutch language version
van Hooff ML
Spruit M
Fairbank JCT
van Limbeek J
Jacobs WCH
Published in: Spine 2015;40(2):E83-90
136
Abstract
Study design: A cross-sectional study on baseline data.
Objective: To translate the ODI version 2.1a into the Dutch language and to validate its use in a
cohort of chronic low back pain patients in secondary spine care.
Summary of Background data: Patient-reported outcome measures (PROMs) are commonly
accepted to evaluate the outcome of spine interventions. Functional status is an important
outcome in spine research. The ODI is a recommended condition-specific PROM used to
evaluate functional status in patients with back pain. As yet, no formal translated Dutch
version exists.
Methods: The ODI was translated according to established guidelines. The final version was
built into the electronic web-based system in addition with the Roland & Morris Disability
Questionnaire (RMDQ), the NRS for pain severity, SF36 for quality of life, and the Hospital
Anxiety and Depression Scale (HADS). Baseline data were used of 244 patients with chronic
low back pain who participated in a combined physical and psychological program. Floor and
ceiling effects, internal consistency, and the construct validity were evaluated using quality
criteria.
Results: The mean ODI (standard deviation [SD]) was 39.6 (12.3); minimum 6, maximum 70. Most
of the participants (88%) were moderately to severely disabled. Factor analysis determined
a one-factor structure (36% explained variance) and the homogeneity of ODI items is shown
(Cronbach’s α= 0.79). The construct validity is supported as all (6:6) the a priori hypotheses
were confirmed. Moreover, the ODI and RMDQ, showed a strong significant correlation (r=
0.68, p< 0.001) and an overlap: mean difference of -18 (95% limits of agreement: -44 to 8).
Conclusions: The Dutch ODI version 2.1a is a valid and valuable tool for the measurement of
functional status and disability among Dutch patients with CLBP. This translated conditionspecific PROM-version is recommended for use in future back pain research and to evaluate
outcome of back care in the Netherlands.
Validation of Dutch ODI v2.1a
137
Introduction
Low Back Pain (LBP) has the largest global burden of disease[1] and is associated with a
substantial amount of morbidity. Functional status is an important outcome in research
evaluating surgical and non-surgical interventions for LBP[2,3] and to assess patients’ progress
in routine clinical practice. Limitations in functional status (disability) as assessed by patientreported outcome measures (PROMs) is widely accepted[4] and the Oswestry Disability Index
(ODI version 2.1a)[5,6] is commonly used as a PROM. The ODI has been translated into various
languages[7-22]. Recently, based on international consensus, the ODI is included as a PROM in
the International Consortium for Health Outcomes Measurement (ICHOM) standard set for
LBP[3,23].
Prior to its use, the questionnaire should be translated to the native language of users and
should have undergone a cross-cultural adaptation and validation process. A multistep
approach is recommended in order to reach equivalence between the original and the target
language[24,25].
A systematic search of literature and a discussion with the initial developer of the ODI
revealed that, as yet no formal Dutch version 2.1a exists. The objectives of this study were: (1)
to translate and adapt the ODI version 2.1a into the Dutch language and (2) to investigate the
validity and internal consistency of the translation in a cohort of chronic low back pain (CLBP).
Materials and Methods
Patients
Orthopaedic spine surgeons of a specialized hospital for spine care recruited patients with
CLBP. The patients were referred to and participated in a short, intensive two-week Combined
Physical and Psychological (CPP) program, as provided by RealHealthNL Sint Maartenskliniek
Nijmegen (Zevenheuvelenweg, Berg en Dal, The Netherlands)[26].
Translation and cross-cultural adaptation procedure
We used a multistep approach [24,25] using published guidelines [24,27] recommended by
the American Academy of Orthopedic Surgeons Outcomes Committee. The first step was a
forward translation performed by two native Dutch speakers (T-1, T-2) with a background in
health sciences, and familiar with the concepts being examined. A third native Dutch speaker
(T-3) without a medical education assisted in the translation with an appreciation of the level
of understanding of the typical patient that would ultimately be completing the questionnaire
(naïve translator). The second step was a comparison of the translation with the original and
consensus was reached in case any discrepancies existed. The versions were synthesised to
one common Dutch version; T-123. The third step was a back translation of T-123 by two native
English speakers (one American and one British), both bilingual with Dutch as their second
language. One was familiar with the concepts of disability and the other was a professional
translator in the medical field. Both carried out their back translation independently (BT-1,
BT-2). The fourth step was to develop a pre-final Dutch version by an expert committee with
access to all translations. The expert committee consisted of all translators, an orthopaedic
spine surgeon, and an independent methodologist. The committee examined the translations
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Validation of Dutch ODI v2.1a
and discussed all parts of the questionnaire (instructions, items, and response options). The
fifth step was to test the pre-final version in a group of 10 patients with CLBP. They were
asked to complete this version and to give their comments. All findings of this phase of the
adaptation process (face validity) were evaluated by the expert committee before the final
Dutch version (ODI version 2.1a) was compiled and further tested for validity.
Evaluation of the psychometric properties of the Dutch ODI version 2.1a
Procedure and Data collection
The Dutch ODI version 2.1a was built into the electronic web-based system of the CPP program,
together with all other questionnaires. Outcome assessment is a routine part of the program
and patients are systematically followed over time[28]. Therefore, we were able to extract all
relevant pretreatment data from the database. All measures, except the ODI, have previously
been validated in CLBP samples.
07
Self-report measures
Oswestry Disability Index (ODI, version 2.1a)
The ODI was originally developed in 1980 (version 1)[5] and slightly modified in 1989 [29] to
the version 2.1, which is regularly used today[30]. A single word change in the introductory
statement has led to the 2.1a version [31]. This ODI version measures the impact of LBP on
the patients’ functional ability in 10 domains of activities in daily life (‘personal care’, ‘lifting’,
‘walking’, ‘sitting’, ‘standing’, ‘sleeping’, ‘sex life’, ‘social life’, and ‘travelling’). Each domain or
item consists of 6 statements (scores 0-5) and is scored by the patient in reference to his/her
current functional status. The total score is a sum of all completed items and expressed as a
percentage of the maximum score[6]. To avoid confusion with percentages as mathematical
expressions the percentage is referred to as a total score, ranging from 0 to 100, with higher
scores indicating higher disability [11].
To validate the Dutch ODI we used several measures: (1) Roland & Morris Disability
Questionnaire (RMDQ; score 0-24)[32], with higher scores indicating higher disability; (2)
Numeric Rating Scale (NRSpain; score 0-100)[33] with higher scores indicating higher levels of
pain severity; (3) Health-related quality of life as measured with the Short-Form 36 Health
Survey Questionnaire (SF-36)[34], consisting of 2 summary scores of eight subscales: Physical
and Mental Component Score (both scores 0-100; and (4) Hospital Anxiety and Depression
Scale (HADS) containing 2 subscales to screen for disturbance of symptoms of anxiety and
depression (HADS-A and HADS-D; both scores 0-21)[35].
Procedure and criteria
‘Floor and ceiling effects’ [36] were determined by calculating the number of individuals
obtaining the lowest (0-10) or the highest (90-100) ODI-scores. We included range of 10
points referring to the minimal clinical important difference (MCID)[37], which is widely used
to report a clinical relevant difference between assessments. Floor and ceiling effects are
considered to be present if more than 15% of the patients achieved the extreme ends [36].
To examine ‘internal consistency’ an exploratory factor analysis (EFA) with a varimax rotation
was conducted to determine whether the items form 1 predefined factor covering the overall
scale [36]. A factor analysis with a principal component technique was chosen as the aim
was to explore an underlying construct rather than to reduce the number of items[38]. To
Validation of Dutch ODI v2.1a
139
test the factorability, inter-item correlations of the 10 items of the ODI were inspected and
the significance level of the Bartlett test of sphericity and the Kaiser-Meyer-Olkin measure
of sampling adequacy were calculated. A significant Kaiser-Meyer-Olkin measure of
sampling adequacy value of >0.6 was considered acceptable [38,39]. The number of factors
was determined by visual inspection of the scree plot, the percentage of unique variance
(>5%), Eigenvalues more than 1, and factor interpretability. Only items with factor loadings
more than 0.40 (20% explained variance) were retained and items with cross-loadings on
more than 1 factor within 0.20 of the primary loading were dropped because of inadequate
discrimination. Moreover, Cronbach α was calculated. A Cronbach’s α between 0.70 and 0.95
indicates good internal consistency [36].
‘Construct validity’ is supported when at least 75% (≥5) of the predefined hypotheses are
confirmed (Table 1)[36]. The strength of the correlations is interpreted as ‘weak’ (r=0.10-0.30),
‘moderate’ (r= 0.31-0.50), or ‘strong’ (r= 0.51-1.00)[40,41]. We found no studies in which the ODI
was validated to the HADS-A and HADS-D (Table 7.1). Therefore, a priori hypothesises related
to a weak correlation with HADS-A and HADS-D were based on the assumption that the ODI
deliberately focussed on physical activities and not the psychological consequences of CLBP[6].
We expected a moderate association for the SF-36 Mental Component Scale as previous
studies revealed that although the mental health subscale showed a weak correlation the
remaining subscales showed a moderate relationship [8,12,14,18].
Statistical analyses
The distributions of the ODI items, ODI total score, and all study variables were examined
with the Kolmogorov-Smirnov test. Descriptive statistics are provided; mean and standard
deviation (SD) for continuous variables and counts and percentages for categorical variables.
The means (SDs), inter-item and item-total correlations were calculated for each item
as well as for the total score. To assess internal consistency explanatory factor analysis
(EFA) was conducted to explore the factor structure of the questionnaire as, as yet no clear
hypothesis about the factor structure exists. Moreover, Cronbach α was calculated. Pearson’s
r correlations were calculated in order to determine whether our a priori hypotheses were
confirmed (Table 7.1). As the RMDQ measures the same construct, we assessed the mean
difference and the 95% limits of agreement to explain the difference between the two scales,
which is illustrated in the Bland-Altman plot [42,43]. To perform the analysis, the scaling of the
RMDQ score was adjusted to the ODI scale (0-100). Furthermore, we compared to the results
of the original developer [6].
A p< 0.05 was considered statistical significant. All statistical analyses were performed using
STATA version 10.0 (StataCorp, College Station, TX). 07
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Validation of Dutch ODI v2.1a
Table 7.1 A priori hypotheses for evaluating the measurement properties of the Dutch ODI version 2.1a
Hypothesis
General aspects
1. The total score is normally distributed
2. The percentage of missing data per item and the total score is < 5%
3. Floor and ceiling effects in the total scores are less than ≤ 15% [37]
Internal consistency
4. The Cronbach’s α is 0.70 ≤ α ≤ 0.95 [37]
5. The item-total correlation is strong (r 0.51-0.82) [11,20,21]
Construct validity
A. Strong positive correlation:
6. Disability (RMDQ; r 0.61-0.84) [6,7,9,11-15,17,20-22]
B. Strong negative correlation:
07
7. Quality of Life – Physical component (SF36-PCS; r -0.75) [8,12]
C. Moderate to strong positive correlation:
8. Pain severity (NRSpain; VAS r 0.33-0.87) [7-9,11-16,19-22]
D. Moderate positive correlation:
9. Depression (HADS-D)
E. Moderate negative correlation:
10. Quality of Life- Mental component (SF36-MCS) [8,12]
F. Weak positive correlation:
11. Anxiety (HADS-A)
ODI indicates Oswestry Disability Index; r Pearson correlation coefficient
RMDQ Roland and Morris Disability Questionnaire; SF-36 36-item Short Form Health Survey Questionnaire; NRS Numeric Rating Scale; HADS-D
Hospital Anxiety and Depression Scale for Depression; HADS-A Hospital Anxiety and Depression Scale for Anxiety; VAS Visual Analogue Scale; MCS
Mental Component Score; PCS Physical Component Score.
Validation of Dutch ODI v2.1a
141
Results
A total of 244 patients (140 females [57.4%]), with mean age 45.6 (SD, 10.8 yr) years, and
with longstanding CLBP (mean, 12.7 yr [SD, 10.4 yr]), participated in the CPP program (May
2012-March 2013). In total, 41.0% (n= 100) reported previous back surgery (Table 7.2). Based
on the ODI, the majority of the participating patients (88.2%) were moderately to severely
disabled (Table 7.3).
General aspects and Floor and Ceiling effects
Data on all variables were normally distributed between found minimum and maximum
ranges of each self-report measure used (Table 7.2). Table 7.4 shows the means (SD) and the
floor and ceiling values for the different ODI items in this patient sample. The floor value was
reached more often in ‘personal care’ (41.8%), ‘walking’ (27.0%), and ‘sex life’ (16.0%). None
of the patients left an item unanswered. One patient (0.4%) achieved a total score in the
range 0-10 (ODI= 6) and the highest total score was 70 (1 patient [0.4%]). None of the patients
reached highest total scores of 90-100. For the total score, no floor and ceiling effects seem to
be present. Table 7.2 Pre-treatment patient characteristics
Pre-treatment characteristics
(n= 244)
Sociodemographic
Age; mean (SD, range min-max) in years
45.6 (± 10.8, 19-69)
Gender; n (%), male : female
104 (42.6%) : 140 (57.4%)
Work status; n (%) yes : no
192 (78.7%) : 52 (21.3%)
CLBP History
Duration of LBP; mean (SD, range min-max) in years
12.7 (± 10.4, 1-55)
Previous surgery; n (%) yes : no
100 (41.0%) : 144 (59.0%)
Pain medication; n (%) yes : no
214 (87.7%) : 30 (12.3%)
Self-report measures
mean (SD, range min-max)
Functioning
Disability in functional status (ODI)
39.6 (± 12.3, 6-70)
Disability in functional status (RMDQ)
13.7 (± 4.1, 2-21)
Quality of Life
Physical component (SF36-PCS)
42.9 (± 15.7, 10-84)
Mental component (SF36-MCS)
58.5 (± 21.5, 6-96)
Pain
Severity (NRSpain)
57.9 (± 23.5, 0-100)
Cognition & Behaviour
Catastrophizing cognitions (PCS)
21.2 (± 10.4, 0-51)
Fear of movement behavior (TSK)
31.5 (± 5.0, 19-42)
Self-efficacy (PSEQ)
11.8 (± 3.2, 2-21)
Anxiety (HADS-A)
6.7 (± 3.3, 0-18)
Depression (HADS-D)
6.3 (± 3.8, 0-18)
SD indicates standard deviation; RMDQ Roland and Morris Disability Questionnaire; SF-36, 36-item Short Form Health Survey Questionnaire;
SF-36-MCS Mental Component Score; SF-36-PCS Physical Component Score; NRS Numeric Rating Scale; HADS-D Hospital Anxiety and
Depression Scale for Depression; HADS-A Hospital Anxiety and Depression Scale for Anxiety; PCS Pain Catastrophizing Scale; TSK Tampa Scale for
Kinesiophobia; PSEQ Pain Self-Efficacy Questionnaire.
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Validation of Dutch ODI v2.1a
Table 7.3 Pre-treatment clinical characteristics; severity of disability of patients with CLBP* participating
in a CPP program in secondary care.
Category
Description
n (%)
0 - 20
Minimal disability
16 (6.6)
21 - 40
Moderate disability
117 (48.0)
41 - 60
Severe disability
98 (40.2)
61 - 80
Crippled
13 (5.3)
81 - 100
Bed bound
0
* Classification according to Fairbank et al.[5]
ODI indicates Oswestry Disability Index; CPP Combined Physical and Psychological
07
Internal consistency
The initial analysis of the 10 items of the ODI showed that the Bartlett test of sphericity
was significant (χ2= 508.11, df= 45, p< 0.001) with a Kaiser-Maier-Olkin measure of sampling
adequacy value of 0.85, indicating the appropriateness of conducting a factor analysis. The
inter-item Pearson r correlations ranged from 0.10 (item 6 and item 7) to 0.44 (item 9 and item
10), indicating no multicollinearity. Table 4 shows that all items are similarly associated with
the total score. The scree plot of Eigenvalues, the percentage of variance, and the number
of Eigenvalues more than 1 indicated a 1-factor solution. Because of a 1-factor solution, no
rotation could be performed. This factor with an Eigenvalue of 2.8 explains 35.6% of the total
variance (Table 7.4). The Cronbach α was 0.79 and the item-total correlations ranged from
0.48 (for item 7; ‘sleeping’) to 0.68 (for items 9 and 10; ‘social life’ and ‘travelling’) (Table 7.4),
confirming the internal consistency of the ODI in our patient sample.
Table 7.4 Characteristics of the Dutch ODI version 2.1a
Item
Mean (SD)
Floor,
n (%)
Ceiling,
n (%)
Missing,
n (%)
Item-Total
correlation
Factor
Loading
1. Pain intensity
2.58 (0.82)
1 (0.4)
1 (0.4)
0
0.54
0.55
2. Personal care
0.86 (0.87)
102 (41.8)
1 (0.4)
0
0.56
0.57
3. Lifting
2.67 (1.18)
7 (2.9)
7 (2.9)
0
0.55
0.53
4. Walking
1.04 (0.87)
66 (27.0)
0
0
0.63
0.65
5. Sitting
2.38 (0.96)
4 (1.6)
3 (1.2)
0
0.58
0.58
6. Standing
2.87 (1.15)
2 (0.8)
7 (2.9)
0
0.59
0.57
7. Sleeping
1.45 (0.87)
16 (6.6)
3 (1.2)
0
0.48
0.47
8. Sex life (if appl.)
1.82 (1.40)
39 (16.0)
12 (4.9)
0
0.64
0.62
9. Social life
2.16 (1.01)
21 (8.6)
1 (0.4)
0
0.68
0.69
10. Travelling
1.95 (1.07)
5 (2.0)
4 (1.6)
0
0.68
0.69
Eigenvalue
2.8
% of variance
35.6%
Cronbach α
0.79
ODI indicates Oswestry Disability Index; SD indicates standard deviation
Validation of Dutch ODI v2.1a
143
Construct validity
The data of the 2 disability scores, ODI and RMDQ, showed a strong significant correlation with
one another (r= 0.68, p< 0.001) (Figure 7.1; Table 7.5). Using the regression equation of ODI on
RMDQ (Figure 7.1; Y= 11.542 + 2.030 * X), extrapolation to the minimum RMDQ score (= 0) and the
maximum RMDQ score (= 24), yielded ODI scores of 12 and 60. The Bland-Altman plot (Figure
7.2) shows a mean difference of -18 with wide 95% limits of agreement (95% LoA) (-44 to 8). A
trend tends to be seen that the higher the mean values the more negative the differences are.
The correlations of the ODI total score with measures of pain, quality of life, and psychological
symptoms are displayed in Table 7.5. These relationships varied from r= 0.22 (p<0.001,’weak’;
HADS-A) to r= -0.57 (P<0.001, ‘strong’; SF-36 Physical Component Score). As all (100%; 6:6) of
the a priori hypotheses were confirmed, construct validity is supported (Table 7.5). Figure 7.1 Relationship between the total scores at pre-treatment assessment of ODI and RMDQ (n= 244)
07
Relationship between the total scores at pre-treatment assessment of ODI and RMDQ (n= 244). Regression formula: Y= 11.542 + 2.030 x X; R2= 0.45;
Pearson r= 0.68 (p<0.001). ODI indicates Oswestry Disability Index; RMDQ Roland and Morris Disability Questionnaire
144
Validation of Dutch ODI v2.1a
Figure 7.2 Bland-Altman plot of differences between ODI and RMDQ for patients with CLBP.
07
Bland-Altman plot of differences between ODI and RMDQ for patients with CLBP. Middle horizontal line indicates the mean difference (value =
-18). Upper en lower horizontal lines indicate the upper and lower limits of agreement (2SD on either side of mean difference [value = 8 and -44
respectively]). SD indicates standard deviation; ODI Oswestry Disability Index; RMDQ Roland and Morris Disability Questionnaire; CLBP chronic
low back pain.
Table 7.5 Predefined hypotheses and correlations of variables with the ODI dimension
Predefined hypothesis
Correlation
Pearson’s r*
Confirmed (Yes/No)
0.68
Yes
-0.57
Yes
0.40
Yes; moderate
0.40
Yes
-0.43
Yes
0.22
Yes
Strong positive correlation:
Disability (RMDQ)
Strong negative correlation:
Quality of Life – Physical component (SF36-PCS)
Moderate to strong positive correlation:
Pain severity (NRSpain)
Moderate positive correlation
Depression (HADS-D)
Moderate negative correlation:
Quality of Life - Mental component (SF36-MCS)
Weak positive correlation:
Anxiety (HADS-A)
* All correlations p<0.001
ODI indicates Oswestry Disability Index; RMDQ Roland and Morris Disability Questionnaire; SF-36, 36-item Short Form Health Survey
Questionnaire; NRS Numeric Rating Scale; HADS-D Hospital Anxiety and Depression Scale for Depression; HADS-A Hospital Anxiety and
Depression Scale for Anxiety; MCS Mental Component Score; PCS Physical Component Score.
Validation of Dutch ODI v2.1a
145
Discussion
In this study we translated and adapted the Oswestry Disability Index (ODI) version 2.1a as
a condition-specific PROM, for Dutch-speaking patients. We examined and confirmed the
validity and the internal consistency of the Dutch ODI in a cohort of patients with chronic low
back pain (CLBP) in secondary care to have a formal ODI and to avoid future inappropriate use
[31].
Translation and trans-cultural adaptation
In line with the German translation [11], the Dutch and English languages are also closely
related and the translation is carried out with almost literal equivalence for many of the
terms used. We used the international SI unit of length as the metric equivalent for walking
distances (i.e. 1km; 500m; 100m, recommended by the original author). The ‘walking’ itemtotal correlation was however comparable with other items (Table 7.4; r= 0.63) and 174 of the
244 patients (71%) selected 1 of the 3 distances. No changes were needed after testing the prefinal version. The final version is available from PROQOLID website [44].
General aspects & Floor and Ceiling effects
Because of web-based assessments with compulsory items we had no missing values, even
the item about sex life, which was a non-compulsory item. This is in contrast to previously
reported missing values, ranging from 15% to 23% [11,15,16,21]. Although for the total score no
floor and ceiling effects are shown, for the individual items ‘sex life’, ‘walking’ and ‘personal
care’ we found floor effects with percentages exceeding the recommended 15%, which is
comparable with a previous validation study [16].
Internal consistency
As yet, no clear hypothesis of the factor structure of the ODI exists. We found that the items
of the ODI loaded on 1 factor, explaining 36% of the variance, suggesting that other nonmeasured factors or domains are involved in the concept of functional status. This 1-factor
structure was previously determined, though with a higher proportion of explained variance:
45%-55%[14,19,21]. Other studies found a 2-factor structure [15,16,45,46] and a difference
between static physical activities and dynamic physical activities [45] or between painrelated activities and pain-related participation was suggested as a possible explanation
[15,46]. Furthermore, homogeneity of the Dutch ODI-items is confirmed by Cronbach α (α=
0.79; 0.70 < α < 0.95) and although the α is lower it is similar to those previously reported (0.83
≤ α ≤ 0.94)[7-22].
Construct validity
We formulated several specific a priori hypotheses to confirm the construct validity of the
Dutch ODI to avoid a possible risk of bias in explanations for the associations found[36]: all
(100%) the hypothesized associations were confirmed. A strong relationship between the
RMDQ and the ODI was shown (r= 0.68, p< 0.001), similar as previously reported (r= 0.61-0.84)
[7,9-15,17,18,20-22], and suggesting interchangeability of the two measures. Because the use
of correlation coefficients might be misleading[42], we calculated 95% limits of agreement
(95% LoA). We found similar mean differences and wide but smaller 95% LoA than reported
by Fairbank and Pynsent[6] (mean [95% LoA]: -18 [-44 to 8] and 17 [-50 to 15], respectively). The
difference in precision of estimated LoA might be explained by a difference in patient samples
07
146
Validation of Dutch ODI v2.1a
used[42]. Moreover, our results substantiate the trend that the greater the mean values the
more negative the differences are. It was noticed that extrapolation of the regression equation
for the relationship between ODI and RMDQ to a maximum score RMDQ score (24 points),
yielded an ODI score of just 60. In our study a small proportion of patients were ‘crippled’ (5.3%;
n= 13; Table 3). If these patients were to deteriorate after an intervention, the RMDQ might
not be responsive enough to detect the change. Moreover, improvements on the RMDQ could
only be detected in patients for whom the corresponding ODI-score is less than 60. Our finding
tends to confirm previous suggestions that the ODI may be more appropriate than the RMDQ
in use in patients with a higher degree of disability: at high levels of disability the ODI still
detects change when the RMDQ points are at a maximum [11,30]. Frost et al. [47] concluded
that the ODI is more responsive at the lower extreme end than the RMDQ and suggested to use
the ODI in minimally disabled patients. Although an interesting recommendation, we cannot
draw any firm conclusions regarding the lower end of the ODI since we only had 1 patient who
scored less than 12.
07
To formulate an a priori hypothesis for association with pain severity we only found studies
that included a VAS as measure. As visual analogue scale (VAS) and NRS are closely related
[48], the VAS results can be interpreted as NRS results. We found a comparable moderate
relationship between ODI and NRS as previously reported, suggesting that the constructs
of disability and pain intensity only partially overlap. This is explained by the construction
of the ODI; only 1 of the items is related to pain. The assumption is supported that the ODI
assesses the physical component of health-related quality of life (SF-36 Physical Component
Scale)[6,8,12,15]. The hypotheses for the psychological aspects (HADS ‘anxiety’ and HADS
‘depression’) are confirmed. This is consistent with the evidence found in a recently published
study in which an overview is given of all factors influencing treatment outcome in CLBP (i.e
disability, pain, and quality of life) [49].
Limitations
A potential limitation of this study was that the sample consisted largely of patients with
moderate to severe CLBP-related disability (n= 225, 88%; mean [SD], 40 [12]) and selected
for a CPP program, meaning that the sample is not representative for the whole Dutch CLBP
population. The Dutch ODI should also be formally tested in primary care settings, although
other translations have shown to be valid in these settings [6,9,10,15-17,22]. We do realise
that the test-retest reliability was not established. The Dutch language is closely related to
the English and German languages and we expect no differences as these versions showed
very strong agreement between measurements on 2 occasions (Pearson r= 0.89 [6] and ICC
[intraclass correlation]= 0.96 [11], respectively). The test-retest reliability is commonly studied
in other languages as well; the ICC’s varied between 0.88 and 0.99 [9-12,15-22]. Finally, other
measurement properties as responsiveness and possible cut-off scores for successfulness of a
spinal intervention still need to be determined in future longitudinal studies.
Validation of Dutch ODI v2.1a
147
Conclusion
We produced a valid Dutch version of the Oswestry Disability Index for the measurement of
functional status and disability among Dutch patients with CLBP. The translated questionnaire
is a valuable tool and the authors recommend this translated 2.1a version as a conditionspecific PROM for use in future back pain research purposes and to evaluate outcome of back
care. The official version is implemented and used in the Dutch Spine Surgery Registry in the
Netherlands.
Key points
• The Dutch version of ODI 2.1a is a valid and valuable tool to measure functional outcome in
spine care.
• Factor analysis suggested a 1-factor structure.
• The Dutch ODI showed a strong correlation with the NRS pain severity as well as the Dutch
RMDQ and the physical component of SF-36.
• The Dutch ODI is recommended as a condition-specific PROM for use in future Dutch back
pain research and to evaluate outcome of back care.
• The Dutch ODI is implemented in the Dutch Spine Surgery Registry for the spine society in
the Netherlands.
Acknowledgements
The authors thank the multidisciplinary team at RealHealth NL, who were responsible for the
assessments of the participants in the CPP program. They also thank Frank Laumen (EasyFile)
for his support in building and managing the electronic web- based system, including the
database.
07
148
Validation of Dutch ODI v2.1a
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151
Chapter 08
Determination of the
Oswestry Disability Index score
equivalent to a
“satisfactory symptom state”
in patients undergoing surgery
for degenerative disorders of the
lumbar spine
A Spine Tango registry-based study
van Hooff ML
Mannion AF
Staub LP
Ostelo RWJG
Fairbank JCT
Published in: Spine J. 2016 Oct;16(10):1221-1230. Epub 2016 Jun 22
152
Abstract
Background Context: The achievement of a given change score on a valid outcome instrument
is commonly used to indicate whether a clinically relevant change has occurred after spine
surgery. However, the achievement of such a change score can be dependent on baseline
values and does not necessarily indicate whether the patient is satisfied with the current
state. The achievement of an absolute score equivalent to a patient acceptable symptom state
(PASS) may be a more stringent measure to indicate treatment success.
Purpose: This study aimed to estimate the score on the Oswestry Disability Index (ODI, version
2.1a; 0-100) corresponding to a PASS in patients who had undergone surgery for degenerative
disorders of the lumbar spine.
Study Design / Setting: This is a cross-sectional study of diagnostic accuracy using follow-up
data from an international spine surgery registry.
Patient Sample: The sample includes 1,288 patients with degenerative lumbar spine disorders
who had undergone elective spine surgery, registered in the EUROSPINE Spine Tango Spine
Surgery Registry.
Outcome Measures: The main outcome measure was the ODI (version 2.1a).
Methods: Surgical data and data from the ODI and Core Outcome Measures Index (COMI)
were included to determine the ODI threshold equivalent to PASS at 1 year (±1.5 months; n=
780) and 2 years (± 2 months; n= 508) postoperatively. The symptom-specific well-being item
of the COMI was used as the external criterion in the receiver operating characteristic (ROC)
analysis to determine the ODI threshold equivalent to PASS. Separate sensitivity analyses
were performed based on the different definitions of an ‘acceptable state’ and for subgroups
of patients. JF is a copyright holder of the ODI.
Results: The ODI threshold for PASS was 22, irrespective of the time of follow up (area under
the curve [AUC]: 0.89 [sensitivity (Se): 78.3%, specificity (Sp): 82.1%] and AUC: 0.91 [Se: 80.7%,
Sp: 85.6], for the 1- and 2-year follow-ups, respectively). Sensitivity analyses showed that the
absolute ODI-22 threshold for the two follow-up time-points were robust. A stricter definition
of PASS resulted in lower ODI thresholds, varying from 16 (AUC=0.89; Se: 80.2%, Sp: 82.0%) to
18 (AUC=0.90; Se: 82.4%, Sp: 80.4%) depending on the time of follow up.
Conclusions: An ODI score ≤22 indicates the achievement of an acceptable symptom state and
can hence be used as a criterion of treatment success alongside the commonly used changescore measures. At the individual level the threshold could be used to indicate whether or not
a patient with a lumbar spine disorder is a ‘responder’ after elective surgery.
PASS for ODI
153
Introduction
In Western societies, low back pain (LBP) has the largest disease burden [1]. It is associated
with a substantial amount of morbidity, and complaints are multidimensional. Functional
status is an important patient-related outcome when evaluating surgical and non-surgical
interventions for LBP. One important feature of outcome instruments measuring functional
status is their ability to detect meaningful change from the patient’s perspective. In the
absence of appropriate objective clinical outcome measures, the use of patient-reported
outcome measures (PROM) to assess treatment outcome is commonly accepted [2]. The
Oswestry Disability Index (ODI) [3], and the ODI version 2.1a [4,5] in particular, is widely
accepted and recommended as a condition-specific PROM in interventional studies [6]. As
such, medical decision-making increasingly relies on this measure. Although most clinicians
and researchers agree that the success of any intervention should be judged from the patient’s
perspective, to date no consensus exists for criteria indicating ‘success’.
In health services research it is important to define clear criteria for treatment ‘success’.
Success can be conceptualized in two ways: (1) relevant change or improvement, and (2)
achievement of an acceptable state. With the first concept, the emphasis is on whether or not
an individual has improved after an intervention [7], whereas with the second the emphasis is
on whether or not the achieved outcome is acceptable from the patient’s perspective [7]. The
concept of change (minimum clinically important difference or change) is frequently used in
spine research to assess treatment success. In relation to this it is important to specify whether
the observed change in an individual’s scores is merely the result of measurement error or
whether it constitutes a real change, and whether that change is also clinically relevant to
the patient [8]. However, it is difficult to measure what is clinically relevant to patients [9],
and methodological issues such as population-dependency and baseline dependency [10] are
encountered. Moreover, assessment of change does not indicate whether a ‘normal’ or ‘healthy’
symptom state is reached. For these reasons, we have previously used a more stringent
definition of success based on achievement of values seen in ‘normal’, healthy populations
[11]. The threshold used was the achievement of an ODI-value, derived from ‘normal’ subjects
with little or no back pain, of ≤22 [4,11]. The use of ‘normal, healthy population’ values as the
reference might however be criticized, as the ODI is a condition-specific instrument.
An alternative approach to measuring success is to identify the value beyond which patients
consider themselves well or consider their health state to be acceptable, i.e. the concept of
the patient acceptable symptom state (PASS) [12,13]. Determination of the absolute cutoff value (threshold) at follow up, equivalent to achievement of a PASS, would assist in
interpreting scores at the individual level and would allow determination of the proportion
of patients within a group who achieve this level, when evaluating the effectiveness or
success of interventions. Achievement of this threshold might be more important than the
achievement of a given change value and it probably reflects the ultimate goal of treatment
from the patient’s perspective [12,14]. The concepts of ‘feeling better’ and ‘feeling good’ are
complementary but distinctly different; a patient’s condition can be markedly improved by
the intervention but can still be suboptimal [7,12,13].
The purpose of the present study was to estimate the score on the ODI (version 2.1a)
corresponding to a ‘patient acceptable symptom state’ in patients undergoing surgery for
08
154
PASS for ODI
degenerative disorders of the lumbar spine. To assess the robustness of the findings, we
performed sensitivity analyses with different definitions for ‘acceptable state’ and in various
subgroups of patients.
Materials and Methods
08
Study population
This cross-sectional study was performed using postoperative data from the Spine Tango
Spine Surgery Registry of EUROSPINE, the Spine Society of Europe (SSE) [15,16], and according
to the STARD statement for reporting studies of diagnostic accuracy [17]. The study dataset
was prepared in August 2014 by linking the surgical data, recorded on the SSE Spine Tango
Surgery 2006 form (ST-2006-form), with the last available follow-up ODI and Core Outcome
Measures Index (COMI) [18,19], which had to have been completed on the same day (Figure
8.1). The surgical inclusion criteria were based on the data documented using the registry’s ST2006-form: lumbar, lumbo-sacral, sacral, or coccyx as the level of procedure, and degenerative
disease (black disc or disc degeneration, spondylosis, spondylarthrosis, adjacent segment
degeneration, spinal stenosis, disc herniation) or spondylolisthesis (degenerative) as main
pathology. The data from 2,530 patients satisfied these inclusion criteria.
The registry’s ST-2006-form was also used to derive descriptive information on the patient
samples to perform sensitivity analyses. Data for the following variables were extracted: date
of birth (age), gender, (number of) previous spine surgeries, morbidity state (American Society
of Anesthesiologists physical status score [ASA score]), surgical measures (type of surgery), and
surgical complications. Patient-reported complications recorded on the Spine Tango patient
follow-up questionnaire were also used.
Outcome measure
The Oswestry Disability Index (ODI, version 2.1a) [5] was the main outcome measure. The ODI
(10 items) measures the impact of LBP on patients’ functional ability in 10 aspects of daily life.
The total ODI score is a sum score and ranges from 0 to 100; higher scores indicate greater
disability.
External criterion (anchor)
The anchor used to assess the success of surgery, i.e. achievement of an acceptable symptom
state at follow up, was the response on the symptom-specific well-being (SSWB) item of the
COMI [19,20]: “If you had to spend the rest of your life with the symptoms you have now, how
would you feel about it?” The responses are given on a 5-point Likert scale: ‘very satisfied’,
‘somewhat satisfied ‘, ‘neither satisfied nor dissatisfied’, ‘somewhat dissatisfied’, and ‘very
dissatisfied’.
PASS for ODI
155
Figure 8.1 Data flow.
ST-2006-form completed
n = 30,878
Follow-up ODI
n = 27,203
Follow-up COMI
n = 38,906
Included:
ODI and COMI completed on the same day
Follow-up ODI and COMI pair
n = 15,358
Follow-up ODI and COMI pair,
linked with ST-2006-form
n = 2,787
Primary diagnosis:
Degenerative lumbar spine
disorder
n = 2,530
Included:
Last available follow-up ODI and COMI pair
correctly linked with ST-2006-form
Included:
ST-2006-form ‘main pathology’:
degenerative disease and degenerative
spondylolisthesis
Included:
1-year follow-up data (± 1,5 months)
2-year follow-up data (± 2months)
1 or 2-year follow-up data
available
n = 1,288
1 - year follow-up data
available for analysis
n = 780
2-year follow-up data
available for analysis
n = 508
ST-2006-form, SSE Spine Tango 2006 surgery form; COMI, Core Outcome Measures Index; ODI, Oswestry Disability Index.
Values for success (PASS)
For the analyses the 5-point Likert scale of the COMI SSWB item was collapsed to a dichotomous
outcome variable (1=acceptable; 0=unacceptable). We performed two separate analyses.
The main analysis considered patients who reported feeling ‘very satisfied’ and ‘somewhat
satisfied’ as an acceptable symptom state (PASS 1), whereas the sensitivity analysis included
only those who reported feeling ‘very satisfied’ (PASS 2). All other categories were considered
to represent ‘unacceptable’. To determine PASS we defined two study samples: those with a
1-year follow up (±1.5 months) and those with a 2-year follow-up assessment (±2 months).
08
156
PASS for ODI
Statistical analyses
Baseline demographic and perioperative data of patients in both study samples were
described as means and standard deviations (SD) for continuous variables and as counts (and
percentages) for categorical variables. Differences between samples were examined with
independent Student t-tests for continuous variables and with Pearson chi-square tests for
categorical variables. Proportions (%) are presented for both the distribution of responses on
the SSWB item and the % categorized as ‘acceptable’ and ‘unacceptable’.
08
The ODI threshold for the patient acceptable symptom state (PASS 1) was determined using
receiver operating characteristics (ROC) analyses. The corresponding ROC curve is a plot
for each cut-off value that represents the relation between the proportion of patients who
were correctly classified in the ‘acceptable’ group, based on the COMI SSWB score (sensitivity
[true-positive]; Y-axis) and the proportion of patients who were incorrectly classified in the
‘acceptable’ group (1-specificity [false-positive]; X-axis). The corresponding ROC tables show
for each ODI cut-off value the relation between sensitivity, specificity, and the percentage
correctly classified. The ODI ‘acceptable’ threshold is the value that provides the best balance
between sensitivity and specificity, as it represents the lowest overall misclassification
(i.e. minimum of false-positives and false-negatives, or the maximum sum of specificity
and sensitivity [21]). The area under the curve (AUC) indicates the probability of correctly
differentiating between an ‘acceptable’ and an ‘unacceptable’ state, and an AUC value of >0.7
is considered satisfactory [22]. For each PASS the AUCs at both follow-up assessments were
compared for the discriminative ability of the ODI. When satisfactory, the ROC analyses were
subsequently used to determine the ODI cut-off values.
Separate sensitivity analyses were performed based on the second definition of ‘acceptable’
(PASS 2) and for subgroups of patients based on factors possibly influencing the surgical
outcome. These factors were: gender (male; female), age group (<65 years; ≥65 years), previous
surgery (yes; no), surgical procedure (decompression; fusion [i.e. fusion alone, decompression
and fusion with or without stabilization]), surgical complications (yes; no; [wrong level, nerve
root damage, cauda equina damage, spinal cord damage, bleeding in spinal canal, bleeding
outside spinal canal, malposition of implant, dural lesion, wound infection, implant failure,
other]), and patient-reported complications (yes; no).
The statistical analyses were conducted using STATA version 12 for Windows (StataCorp,
College Station, Texas, USA). Statistical significance was accepted at p<0.05.
Results
To determine the ODI threshold corresponding to PASS at the different predefined follow-ups,
the data of 1,288 patients with degenerative lumbar spine disorders undergoing elective spine
surgery were included, with 1-year (±1.5 months; n= 780) or 2-year (± 2 months; n= 508) follow
up. The characteristics of the two study samples (mean age: 58.3 [standard deviation: 14.9]
years) did not differ (Table 8.1).
PASS for ODI
157
Table 8.1 Characteristics of the two study samples.
Characteristics
Total patient sample 1-year
follow up (n= 780)
Total patient sample 2-year
follow up (n= 508)
p value
Gender, n (%), male : female
373 (47.8) : 407 (52.2)
243 (47.8) : 265 (52.2)
0.996a
Age, mean ±SD, (range, min-max) (y)
58.1 ±15.1; (19-87)
59.1 ±15.2; (19-87)
0.481b
0.588a
Age group
< 65 n (%)
475 (60.9)
317 (62.4)
≥ 65 n (%)
305 (39.1)
191 (37.6)
180 (23.1) : 600 (76.9)
122 (24.0) : 386 (76.0)
Previous surgery
0.698a
n (%), yes : no
0.732a
Number of previous surgeries, n (%)
1
137 (76.1)
96 (78.7)
2
29 (16.2)
18 (14.8)
3
8 (4.4)
4 (3.3)
4
4 (2.2)
2 (1.6)
5
2 (1.1)
2 (1.6)
107 (59.4) : 42 (23.3) : 31 (17.3)
60 (49.2) : 40 (32.8) : 22 (18.0)
Previous surgery same level
n (%), yes : no : partially
Morbidity ASA classification, n (%)
0.233a
0.452a
ASA 1
193 (24.7)
108 (21.3)
ASA 2
308 (39.5)
205 (40.4)
ASA 3
108 (13.9)
72 (14.2)
ASA 4
1 (0.1)
3 (0.5)
ASA 5
-
-
Unknown
170 (21.8)
120 (23.6)
Decompression
487 (62.4)
335 (65.9)
Fusion
293 (37.6)
173 (34.1)
36 (4.6) : 736 (94.4) : 8 (1.0)
31 (6.1) : 472 (92.9) : 5 (1.0)
0.241a
192 (24.6) : 588 (75.4)
133 (26.2) : 375 (73.8)
0.527a
Surgical procedure, n (%)
0.201a
Complications
Surgical
n (%), yes : no : missing
Patient-reported n (%), yes : no
ASA, American Society for Anaesthesiologists; SD, standard deviation
Notes: Decompression included both anterior and posterior decompression. Fusion included fusion alone, decompression and fusion with or
without stabilisation (anterior and/or posterior). Surgical complications included wrong level, nerve root damage, cauda equina damage, spinal
cord damage, bleeding in spinal canal, bleeding outside spinal canal, malposition of implant, dura lesion, wound infection, implant failure, other.
Patient-reported complications: Did any complication arise as a consequence of your operation in our hospital (e.g. problems with wound healing,
paralysis, sensory disturbances)? Response categories: ‘yes’, ‘no’
a
Chi-square test was used.
b
Student’s t test for independent samples was used.
c
p <0.05 for differences between the study samples.
08
158
PASS for ODI
Distribution of ‘treatment success’ ratings
Table 8.2 shows the distribution of responses for the COMI SSWB item. At the 1-year and 2-year
follow-ups, a comparable proportion of patients reported an acceptable symptom state (PASS
1): 43.3% and 43.9%, respectively. For the PASS 2, the proportions were 24.0% and 24.6%,
respectively.
Table 8.2 Distribution of responses in relation to the COMI single item used to define the acceptability of
the symptom state.
Total patient sample 1-year
follow up (n= 780)
n (%)
Total patient sample 2-year
follow up (n= 508)
n (%)
Very satisfied (1)
187 (23.9)
125 (24.6)
Somewhat satisfied (2)
151 (19.4)
98 (19.3)
Neither satisfied nor dissatisfied (3)
113 (14.5)
61 (12.0)
Somewhat dissatisfied (4)
152 (19.5)
78 (15.4)
Very dissatisfied (5)
Acceptability of current state
SSWB
08
177 (22.7)
146 (28.7)
Acceptable (1-2) : Unacceptable state (3-5) yes : no
338 (43.3) : 442 (56.7)
223 (43.9) : 285 (56.1)
Acceptable (1) : Unacceptable state (2-5) yes : no
187 (23.9) : 593 (76.1)
125 (24.6) : 383 (75.4)
COMI, Core Outcome Measures Index; SSWB symptom-specific well-being.
Area under the curve (AUC) and threshold for PASS
The ROC analyses revealed that the AUCs for each definition of PASS, for each subgroup, and
for each follow-up assessment were >0.7 (0.83≤AUC≤0.96; Tables 8.3 and 8.4). The absolute ODI
threshold for each definition of PASS was 22, irrespective of the time of follow up (sensitivity
[Se]: 78.3%, specificity [Sp]: 82.1% and Se: 80.7%, Sp: 85.6%, with 79.6% and 83.5% correctly
classified for the 1- and 2-year follow-ups respectively; Table 8.3 and Figure 8.2).
Table 8.3 Results of ROC analyses
AUC
95% CI
Absolute ODI
threshold
Se
%
Sp
%
% Correctly
classified
PASS 1
0.89
0.86-0.91
22
78.3
82.1
79.6
PASS 2
0.89
0.86-0.91
16
80.2
82.0
81.5
PASS 1
0.91
0.89-0.93
22
80.7
85.6
83.5
PASS 2
0.90
0.87-0.92
18
82.4
80.7
81.1
1-year follow up (n=780)
2-year follow up (n=508)
PASS 1, patient acceptable symptom state with COMI SSWB answers ‘very satisfied’ and ‘somewhat satisfied’;
PASS 2, patient acceptable symptom state with COMI SSWB answer ‘very satisfied’; Se, sensitivity; Sp, specificity; ROC, receiver operating
characteristic; AUC, area under the curve; 95% CI, 95% confidence interval; ODI, Oswestry Disability Index; COMI, Core Outcome Measures Index;
SSWB symptom-specific well-being.
PASS for ODI
159
Threshold for PASS
Table 8.3 shows the absolute ODI threshold values for each definition of PASS and for each
follow-up assessment. The ODI threshold for PASS was 22, irrespective of the time of follow
up (AUC= 0.89 [Se: 78.3%, Sp: 82.1%] and AUC= 0.91 [Se: 80.7%, Sp: 85.6], with 84.0% and 84.2%
correctly classified for the 1- and 2-year follow-ups, respectively; Figure 8.2).
Figure 8.2 ROC for patient acceptable symptom states (PASS 1) using one and two-year follow-up
ODI-values.
08
AUC, area under the curve; 95% CI, 95% confidence interval; PASS ,1 patient acceptable symptom state with ‘very satisfied’ and ‘somewhat
satisfied’; ODI, Oswestry Disability Index; ROC, receiver operating characteristic.
Sensitivity analyses
Definition of success
For PASS 2, the ODI threshold was either 16 (1-year follow up) or 18 (2-year follow up)
(respectively, AUC= 0.91 [Se: 80.2%, Sp: 82.0%] and AUC= 0.90 [Se: 82.4%, Sp: 80.4%], with
81.5% and 81.1% correctly classified; Table 3).
Subgroups
The absolute ODI-22 threshold (PASS 1) for the two follow-up assessments was robust (Table
8.4a). Table 8.4a shows that the ODI threshold was slightly higher in patients with previous
surgery (ODI=23) than in those with no previous surgery (ODI=22). Similarly, the ODI for
decompression patients was slightly higher (ODI=23) than for fusion patients (ODI=22).At
2-year follow up the ODI threshold was 22 for all subgroups, except for those with perioperative
surgical complications as documented by the surgeon (ODI=20) and those who self-reported
no complications (ODI=24; Table 8.4a). For PASS 2 the ODI threshold values varied (14-18)
depending on the subgroup under investigation and the follow up used (Table 8.4b).
407
female
305
≥ 65
600
No
293
Fusion
736
No
192
588
- Yes
- No
Complications – patient
36
Yes
Complications – surgical
487
Decompression
Surgical procedure
180
Yes
Previous surgery
475
< 65
Age group
373
male
Gender
0.88
0.91
0.88
0.89
0.83
0.91
0.88
0.88
0.88
0.89
0.87
0.91
0.85-0.90
0.86-0.95
0.86-0.91
0.78-0.99
0.78-0.88
0.89-0.94
0.85-0.91
0.84-0.93
0.84-0.92
0.86-0.92
0.83-0.91
0.88-0.94
22
22
22
22
22
23
22
23
22
22
22
22
76.5
75.9
76.2
72.7
72.3
82.2
77.8
71.2
80.6
78.4
76.0
81.6
Se
%
9.02
0.01
0.07
2.97
Chi2
value
80.4
87.6
82.0
1.27
80.0 0.02
77.9
84.6
82.6
81.0
77.3
85.3
82.3
81.9
Sp
%
0.259
0.887
0.003*
0.917
0.795
0.085
p value
243
375
133
472
31
173
335
386
122
191
317
265
0.91
0.90
0.91
0.96
0.88
0.92
0.91
0.90
0.92
0.90
0.88
0.91
AUC
0.88-0.94
0.86-0.95
0.88-0.93
0.89-1.00
0.84-0.93
0.89-0.95
0.88-0.94
0.83-0.96
0.88-0.96
0.86-0.93
0.84-0.92
0.87-0.94
95% CI
n
Absolute ODI
threshold
2-year follow up (n= 508)
95% CI
24
22
22
20
22
22
22
22
22
22
22
22
Absolute ODI
threshold
81.2
84.5
79.9
90.7
80.7
83.6
80.6
81.3
82.7
79.4
80.0
81.3
Se
%
82.9
84.0
85.9
79.0
82.2
87.2
84.9
87.5
81.8
81.7
85.7
85.5
Sp
%
0.01
2.18
1.31
0.12
0.91
0.01
Chi2
value
0.934
0.872
0.252
0.726
0.340
0.996
p value
AUC
n
08
1-year follow up (n= 780)
160
PASS for ODI
Table 8.4a. Sensitivity analyses for PASS 1 for subgroups of patients.
435
female
305
≥ 65
600
No
293
Fusion
736
No
192
588
Yes
No
Complications – patient
36
Yes
Complications – surgical
487
Decompression
Surgical procedure
180
Yes
Previous surgery
475
< 65
Age group
355
male
Gender
n
0.91
0.91
0.89
0.88
0.87
0.92
0.87
0.95
0.89
0.89
0.91
0.91
AUC
0.88-0.94
0.85-0.97
0.86-0.92
0.73-1.00
0.82-0.92
0.87-0.93
0.84-0.90
0.91-0.98
0.85-0.93
0.86-0.92
0.87-0.94
0.87-0.94
95% CI
1-year follow up (n= 780)
18
18
16
18
18
16
16
16
16
18
18
15
Absolute ODI
threshold
84.6
91.4
80.8
71.4
80.6
81.7
79.3
85.7
82.1
82.4
80.2
81.4
Se
%
84.9
80.4
81.6
72.4
79.2
80.7
81.0
84.7
79.0
80.9
80.1
84.3
Sp
%
0.04
0.00
0.95
8.20
0.01
0.97
Chi
value
2
0.851
0.968
0.230
0.004*
0.908
0.325
p value
375
133
472
31
173
335
386
122
191
317
265
243
n
95% CI
0.85-0.94
0.86-0.94
0.86-0.94
0.84-0.94
0.77-0.95
0.87-0.94
0.86-0.94
0.83-0.93
0.89-1.00
0.88-0.93
0.88-0.94
0.86-0.95
AUC
0.89
0.90
0.90
0.90
0.86
0.91
0.90
0.88
0.96
0.91
0.90
0.91
2-year follow up (n= 508)
18
14
18
12
16
16
16
16
18
16
18
16
Absolute ODI
threshold
78.5
84.4
81.2
71.4
78.1
82.9
82.5
75.0
80.0
82.3
82.3
82.5
Se
%
80.5
88.1
80.9
87.5
83.9
85.0
83.0
89.0
81.5
85.2
82.3
83.3
Sp
%
0.02
0.17
0.44
0.80
0.01
0.05
Chi2
value
0.893
0.676
0.507
0.374
0.984
0.825
p value
PASS for ODI
161
Table 8.4b. Sensitivity analyses for PASS 2 for subgroups of patients.
08
162
PASS for ODI
Discussion
In the present study we identified the Oswestry Disability Index (ODI; version 2.1a) score
corresponding to a ‘patient acceptable symptom state’ (PASS). The absolute cut-off ODI value
(threshold) was generally estimated to be ≤22 and seemed to be robust for different subgroups
of patients, and at different follow-up assessments. This threshold is similar to the ‘normal’
value as recently defined by van Hooff et al. [11].
Our finding of the ODI threshold of ≤22 is in line with other studies. Tonosu et al. calculated the
cut-off values for the presence or absence of low back pain (LBP) in a random sample of people
working at a Japanese Internet research company (n=1,200). The authors found a similar
threshold of ODI≥22 in those who had LBP and disability [23]. In a large heterogeneous sample
(n=774) of inpatients with spinal disorders (e.g. acute and chronic LBP, herniation, stenosis,
scoliosis) a discharge threshold of ODI≤30 was found [24]. To our knowledge, the present study
is the first to report ODI threshold values based on PASS in patients with degenerative lumbar
spine disorders who have undergone lumbar spine surgery.
08
To quantify the PASS for the ODI, we used different external criteria as the anchor for a
successful outcome. When performing the sensitivity analyses with PASS 2 (‘very satisfied’),
we found lower ODI thresholds (ODI≤16-19), but with similar satisfactory areas under the
curve (AUC>0.7; Table 3). Overall, the results of the sensitivity analysis turned out to be robust;
a more stringent definition of success yielded lower ODI threshold values, meaning that the
anchor to perform the present study was well chosen.
As the use of absolute thresholds might be population-dependent, we performed different
sensitivity analyses for subgroups of patients. In the main analyses for PASS (‘very satisfied’
and ‘somewhat satisfied’), the AUCs were satisfactory (AUC>0.7; [22]). This means that for all
subgroups of patients studied, the ODI discriminates between acceptable and unacceptable
symptom states compared with the anchor used. The overall ODI threshold for each subgroup
was ≤22. Only for ‘previous surgery (yes)’ and ‘surgical procedure (decompression; commonly
performed for lumbar disc herniation and lumbar spinal stenosis)’ a slightly different ODI
threshold was found (each ODI≤23; Table 8.4a). However, these differences in ODI thresholds
were too small to be clinically meaningful. To establish whether the ODI score for the PASS was
time independent we provided estimations for the ODI thresholds for two different commonly
used times of follow up. We found no meaningful differences between the 1-year and 2-year
follow-up thresholds: the absolute values were similar and the 95% confidence intervals of
the AUCs showed overlap (Table 8.3). This means that the ODI-22 threshold associated with a
satisfied symptom state remains consistent.
Limitations
Some limitations of the present study should be mentioned. First, the EUROSPINE Spine Tango
Registry contains data from surgically treated patients in different centers and in various
countries [16]. Participation in the registry is voluntary and the ODI is not a compulsory
outcome measure for the majority of the centers, which instead use the COMI as standard.
Therefore, selection bias might be introduced. The completion of the PROMs is dependent
on patients’ willingness to cooperate. In a previous registry study on Spine Tango data it was
suggested that the proportion of dural lesions in spinal stenosis was a good indicator of the
PASS for ODI
completeness and the ‘honesty’ of the data submitted [25]. The authors found comparable
proportions to those seen in the Swedish SweSpine registry, which suggested credible or at
least similarly honest reporting. Second, we performed several sensitivity analyses to test the
robustness of the ODI-22 threshold. A previous study has shown that a higher preoperative
pain level is associated with a higher acceptable pain level postoperatively [26]; as such, a
sensitivity analysis including pre-defined subgroups with differing pre-operative disability
would have been interesting. However, the ODI is not a compulsory outcome measure
in the registry and insufficient baseline data were available for such an analysis. Further
research is needed to explore the influence of baseline ODI scores on the acceptable ODI
score postoperatively. Moreover, we did not perform a specific subgroup analysis based on
underlying pathologies of degenerative disorders of the lumbar spine. Although based on
the results of a recently published study [26] a slightly lower threshold might be expected for
lumbar disc herniation, the clinical relevance of such a difference is uncertain and might be
arbitrary as this value could be regarded as a value seen in ‘normal’ and healthy populations
(i.e. ODI≤22) [11]. Third, one of the participating centers used a version of the COMI that had not
been formally translated and validated. However, we do not think this would have introduced
any major bias, as we used only the single ‘symptom-specific well-being’ item of the COMI, and
the original item [19,20] is simply and clearly stated and not likely to be subject to different
interpretations. Fourth, to create the dataset for the current study, we started with 30,878
surgically treated patients. Because of the strict inclusion criteria, such as an ODI and COMI
completed on the same day, a large amount of data were excluded, leaving us with 780 and
508 patients at the 1-year and 2-year follow-ups, respectively. Moreover, in the present study
we used the data of the last available follow up on both ODI and COMI. By using this criterion
we might have lost the data of patients who completed the questionnaires at both timepoints, as only the last assessment was included. However, both samples were large enough
for analyses and had similar baseline characteristics, with the exception of the proportion that
had previous surgery. Fifth, the COMI SSWB item was used as an external anchor to assess the
achievement of an acceptable symptom state at follow up. Although the COMI has been shown
to be valid for patients with degenerative disorders of the lumbar spine undergoing surgery
[19], the single SSWB item was not specifically tested for its unique psychometric properties.
To evaluate the validity of the SSWB item as an anchor we carried out a post-hoc analysis of
the strength of the correlations between the postoperative ODI scores and the responses on
the SSWB (Pearson r) for the 1- and 2–year follow-up assessments: the coefficients were r=0.73
and r=0.77, respectively. These correlations are interpreted as ‘strong’ (0.51≤r≤1.00) [27,28]. In
evaluating the validity of transition ratings, a strong correlation (r≥0.50) with change scores in
a relevant health-related quality of life questionnaire suggests that the transition rating may
be used as an anchor[29]. By analogy, we believe that, with correlation coefficients ≥0.50, the
use of the COMI SSWB item as a reference standard (anchor) to define the ODI threshold for
an acceptable symptom state is justified. Finally, for the main analysis we used the responses
‘very satisfied’ and ‘somewhat satisfied’ on the COMI SSWB item to define an acceptable
symptom state. This was supported by the findings of a previous study in which ROC analysis
using the original dichotomized PASS (acceptance of the ‘current state’ [yes or no]) as the
external criterion revealed that ‘very satisfied, ‘somewhat satisfied’ and ‘neither satisfied /
nor dissatisfied’ were considered as ‘acceptable’ [30], together with our considerations as to
what should be considered minimally acceptable as a response for a ‘state for the rest of one’s
life’. We performed a sensitivity analysis with an even more stringent definition, which, as
expected, resulted in lower ODI cut-off values. However, the decision as to which definition of
‘acceptable state’ should be used remains somewhat arbitrary.
163
08
164
PASS for ODI
Conclusions
In the present study, we determined that an absolute ODI value of ≤22 best indicated a
satisfactory symptom state in a large sample of patients from the Spine Tango Registry who
had undergone surgery for degenerative disorders of the lumbar spine. As this threshold
appeared to be fairly consistent across sub-populations, we suggest that the same common
threshold could be used for all degenerative lumbar spine disorders when defining whether
a patient has reached an acceptable state after spine interventions (i.e. is a ‘responder’).
As the concepts of PASS and change are complementary, in line with another group [31,32],
we recommend using this threshold alongside the commonly used ‘change score’ measure
in reporting success. We suggest to report both measures and that the results should be
expressed as the proportions of patients achieving both measures at follow-up assessment.
08
Acknowledgement
The authors would like to thank Johanna E. Vriezekolk for her critical and independent review
of the analyses performed and the final version of the manuscript. The participants of the
Eurospine Spine Tango Register are acknowledged for their continuous contribution that
makes these studies possible reflecting the daily practice of spine surgeons. The data of the
following centres were used (in alphabetic order of country, city, hospital and department):
Dept. of Spinal Surgery in Royal Adelaide Hospital (Australia); Dept. of Orthopedic Surgery
and Traumatology in University Hospital of Cologne (Germany); Dept. of Special Spine Surgery
in Leopoldina Hospital of Schweinfurt (Germany); Dept. of Orthopaedic surgery in Tan Tock
Seng Hospital Singapore (Singapore); Dept. of Orthopedic Surgery in University Hospital of
Ljubljana (Slovenia); Dept. of Neurosurgery in Bethesda Hospital of Basel (Switzerland); Dept.
of Orthopedic Surgery in Salem Hospital of Bern (Switzerland); Dept. of Spine Surgery in The
Spine Center Thun (Switzerland); MEMdoc Hospital of Thun-Simmental AG (Switzerland);
Spine Unit of Nuffield Oxford Centre (UK); Division of Spine Surgery in NYU Hospital for Joint
Diseases of New York (USA).
PASS for ODI
165
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08
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30. Impellizzeri FM, Mannion AF, Naal FD, Hersche O, Leunig M. The early outcome of surgical treatment
for femoroacetabular impingement: success depends on how you measure it. Osteoarthritis.Cartilage.
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31. Escobar A, Gonzalez M, Quintana JM, Vrotsou K, Bilbao A, Herrera-Espineira C et al. Patient acceptable
symptom state and OMERACT-OARSI set of responder criteria in joint replacement. Identification of cut-off
values. Osteoarthritis.Cartilage. 2012;20:87-92
32. Escobar A, Riddle DL. Concordance between important change and acceptable symptom state following
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167
THEME C:
Prediction of outcomes
168
169
Chapter 09
The Nijmegen Decision Tool
for Chronic Low Back Pain
Development of a clinical decision tool
for secondary or tertiary spine care specialists
van Hooff ML
van Loon J
van Limbeek J
de Kleuver M
Published in: PLoS One. 2014;9(8):e104226
170
Abstract
Background: In Western Europe low back pain has the greatest burden of all diseases. When
back pain persists different medical specialists are involved and a lack of consensus exists
among these specialists for medical decision-making in Chronic Low Back Pain (CLBP).
Objective: To develop a decision tool for secondary or tertiary spine care specialists to decide
which patients with CLBP should be seen by a spine surgeon or by other non-surgical medical
specialists.
Methods: A Delphi study was performed to identify indicators predicting the outcome of
interventions. In the preparatory stage evidence from international guidelines and literature
were summarized. Eligible studies were reviews and longitudinal studies. Inclusion criteria:
surgical or non-surgical interventions and persistence of complaints, CLBP-patients aged
18-65 years, reported baseline measures of predictive indicators, and one or more reported
outcomes had to assess functional status, quality of life, pain intensity, employment status
or a composite score. Subsequently, a three-round Delphi procedure, to reach consensus
on candidate indicators, was performed among a multidisciplinary panel of 29 CLBPprofessionals (>five years CLBP-experience). The pre-set threshold for general agreement was
≥70%. The final indicator set was used to develop a clinical decision tool.
Results: A draft list with 53 candidate indicators (38 with conclusive evidence and 15 with
inconclusive evidence) was included for the Delphi study. Consensus was reached to include
47 indicators. A first version of the decision tool was developed, consisting of a web-based
screening questionnaire and a provisional decision algorithm.
Conclusions: This is the first clinical decision tool, based on current scientific evidence and
formal multidisciplinary consensus, that helps referring the patient for consultation to a spine
surgeon or a non-surgical spine care specialist. We expect that this tool considerably helps in
clinical decision-making spine care, thereby improving efficient use of scarce sources and the
outcomes of spinal interventions.
Development of NDT-CLBP
171
Introduction
In Western Europe Low back pain (LBP) is considered to have the greatest burden of disease
for society [1]. In this global burden of disease study LBP is ranked higher than for example
cancer, heart disease, cerebrovascular disease, chronic obstructive pulmonary disease and
asthma, osteoarthritis or diabetes. In the Netherlands, approximately 44% of the population
experiences at least once an episode of LBP, with one in five reporting persistent back pain
resulting in chronic low back pain (CLBP; LBP lasting for more than three months [2,3]) with
substantial limitations in functional activities after one year [4,5]. As the prevalence of CLBP
appears to be increasing [6], CLBP is not only a burden for the patient but the related healthcare
costs and productivity due to absence of work have a high health and socioeconomic impact
on western societies [7-9]. Not surprisingly, CLBP is among the most common complaints
of patients visiting a medical specialist in secondary care, i.e. spine surgeons, physiatrists,
rheumatologists, pain consultants. The high number of CLBP patients overwhelms these
healthcare providers and a significant number of second opinions and re-interventions are
evident. With the limited health care budgets and given the high prevalence of CLBP and its
substantial socioeconomically impact, it is essential to use resources of healthcare providers
efficiently and to triage CLBP patients adequately in order to make sure that these patients
see the right care giver timely. However, as yet such a valid classification system or decision
tool is lacking and secondary care medical specialists are failing to reliably identify which
patients will benefit from which surgical or non-surgical intervention.
One challenge in the development of a decision tool is that the CLBP population is
heterogeneous. Therefore, it is unlikely that one intervention benefits all [10]. A longstanding
duration of complaints is the only one common defining feature. It makes CLBP a complex
problem and in fact it is a symptom referring to the location of the problem rather than a
specific diagnosis [11]. The term itself is non-diagnostic for an underlying pathology and lacks
specificity. Many authors have emphasized the biospychosocial influences on the development
CLBP and persistence of symptoms [12,13] and a broad multidimensional approach is widely
recognised. However, the failure to differentiate between underlying causes is one of the
reasons that various surgical and non-surgical interventions exist for the same problem [14].
Moreover, studies evaluating these interventions for CLBP have led to inconsistent results
[3,15-19] and rarely show more than a small to moderate overall benefit [3,20,21].
It is suggested that several different CLBP patient profiles might be identified which are
likely to benefit from different recommended interventions [1,18,19,22-25]. These profiles are
based on indicators modifying the effects of interventions [26] and with that related to the
outcomes [24]. The ultimate outcomes of spinal interventions are patients’ improved quality
of life, restored functional status and relieved pain [27]. However, due to methodological
heterogeneity, the current evidence is inconclusive regarding predictive indicators for a
successful treatment outcome. Even though it is recognized that CLBP ‘without biological
causes’ has to be distinguished from other spinal disorders that respond reliably to surgery
[25,28], a recently performed nationwide survey among Dutch spine surgeons showed that
even in the group ‘with presumed biological causes’ a lack of consensus exists in surgical
decision making [29]. To distinguish patient profiles several treatment outcome-based
classifications for decision making exist. However, they are all developed and studied as
a guide for non-surgical interventions applied in primary care [24]. As a challenge with
09
172
Development of NDT-CLBP
probably the greatest potential for improving outcomes and efficiently guiding patients to
the right secondary health care professional (e.g. spine surgeon, pain consultant, physiatrist,
rheumatologist), it is recommended to develop a classification system to direct CLBP patients,
presented in secondary or tertiary back care, to both surgical and non-surgical interventions,
based on biomedical and psychosocial indicators [11,22-25,30,31].
Therefore, the purpose of this study is to develop a clinical decision tool for CLBP, based
on evidence in international guidelines and literature, and expert panel consensus using
indicators predicting a successful treatment outcome. The decision tool supports secondary
or tertiary back care specialists to decide which patients should be considered for a surgical
intervention and which patients for a non-surgical intervention and therefore, it aims to
triage patients to the appropriate health care professional. The ultimate goal is to improve
treatment outcomes and to reduce related costs for society.
Methods
09
This study aimed to identify indicators predicting the outcome of interventions and the
persistence of CLBP complaints by two stages: a preparatory stage followed by a threeround Delphi study. The preparatory stage consisted of a literature review. As we expected
inconclusive evidence in the literature, a formal consensus (Delphi) procedure among a
heterogeneous panel of experts in the CLBP field was planned and performed. We used a
Modified Delphi Technique in order to realise an optimal integration of research-based
knowledge and the clinical experience of experts [32] on this topic. Having identified the
predictive indicators, a clinical decision tool, including a screening questionnaire and a
provisional decision algorithm, was compiled. In the flow diagram of Figure 9.1 the overall
process of the development of the Nijmegen decision tool for CLBP is presented.
Figure 9.1 Flow diagram of the development of the Nijmegen Decision Tool for CLBP
Purpose as outlined by project team:
Development of a clinical decision tool for the
triage of CLBP patients
Preparatory stage:
Evidence from literature
Modified Delphi
(3 rounds)
The Nijmegen Decision Tool
for CLBP
Screening Questionnaire
Implementation web-based in
SweSpine Register
All new patients prospectively
registered
(start population cohort study)
Provisional decision algorithm
Development of NDT-CLBP
173
Preparatory stage: Evidence from literature
The indicator set from which a clinical decision tool can be constructed is based on evidence
found in international guidelines and in the literature, as these guidelines are normative for
evidence based daily practice. As a starting point, the clinical flag approach [33] for clinical
decision-making in CLBP and the indicators as recommended in the guidelines [22,23,34], are
used. We performed a literature review searching for indicators predicting outcome of invasive
or non-invasive interventions and persistence of CLBP. Appropriate studies were traced using
MedLine, EMBASE and the Cochrane Library. The most relevant used search terms were: ‘back
pain’ [MesH], ‘chronic’, ‘predict’, ‘prognosis’ [MesH], ‘persistent’, ‘treatment outcome’ [MesH],
‘rehabilitation’ [MesH], ‘surgery’ [MesH]. The search was restricted to include systematic and
narrative reviews, randomized controlled trials (RCT) and prospective cohort studies. Studies
were included when 1) CLBP was the primary complaint; 2) published in the period 2000-2010;
3) involved either surgical interventions for CLBP or non-surgical interventions or persistence
of CLBP complaints; 4) age between 18-65 years; 5) baseline measures of predictive indicators
are reported, as the time of assessment may influence the prognostic value of treatment
outcome [35,36]; 6) at least one of the reported outcome measures had to assess functional
status, quality of life, pain intensity, employment status or a composite score. CLBP was
defined as more than three months continual or recurrent episodes of LBP [2,3].
There were no language restrictions. Moreover, reference lists of included articles were
scrutinized to identify articles not captured in the database search. When a systematic review
was included, the original longitudinal studies (RCT or observational) of that systematic
review were excluded from the current sample to avoid duplication or double use of the same
data.
We used four international guidelines [22,23,31] and one national guideline [34]. The literature
search revealed 33 relevant papers: eight systematic reviews [36-43], four narrative reviews
[44-47], three randomized studies [48-50], and eighteen observational studies [51-68]. All
potential predictive indicators were classified into five main domains: sociodemographic;
pain; somatic; psychological; and functioning & quality of life. Of each paper, data of available
evidence was extracted regarding the predictive values of measured baseline determinants
(indicators). The evidence is weighed according to the Levels of Evidence as defined by the
Oxford Centre for Evidence-Based Medicine [69]. Per indicator the evidence is categorized
into four categories: 1) indicator with proven predictive value (PV; evidence found that the
concerning indicator has predictive value), 2) indicator with proven no predictive value (NP;
evidence found that the concerning indicator has no predictive value), 3) indicator with
inconclusive evidence (I; conflicting evidence found), and 4) indicator with no evidence found
in literature (N). Subsequently, all indicators (PV, NP, and I) were selected and used for Phase
2 of this study (the Delphi Study). Indicators with non-predictive value and categorized NP
were excluded from the sample as the evidence showed no predictive value for treatment
outcome or for persistence of CLBP complaints. The included indicators are summarized in an
evidence table, according to the design used in the related studies (data available in Table S1).
Per indicator the evidence was summarized: the evidence is conclusive and of predictive value
(C: PV) or the evidence is conclusive and of no predictive value (C: NP) or inconclusive evidence
(I). These results are used in the Delphi study (Delphi-1 & 2).
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Development of NDT-CLBP
Delphi Study
The Delphi technique is a commonly used method to develop clinical guidelines [70] and also
used in healthcare indicator research [71]. The technique was originally developed in the 1950s
by Dalkey and Helmer at the RAND Corporation as a method of eliciting and refining group
judgements [72]. Delphi may be characterized as a systematic method for structuring a group
communication process so that the process is effective in allowing a group of experts or ‘expert
panel’, as a whole, to deal with a complex problem [73]. The method relies on three key features:
1) anonymous response to guarantee equality in experts opinions, 2) iteration and controlled
feedback, and 3) statistical analysis of group responses [72]. The Delphi technique, as recently
described [32,71], is a structured process that uses a recommended series of two or three
rounds to gather expert opinions. When reaching consensus is difficult or consensus is unclear
a physical panel meeting at the end is recommended, under the condition that the meeting
should be well structured and should take place in favourable conditions (surrounding and
environment) with a moderator (process leader), who is not one of the panellists, to contain
the influence of dominant personalities (Modified Delphi Technique).
09
Project team
A project team was formed to conduct the process and the research and comprised a
methodologist who is also a physician and who has a background in statistics (JvL), an
orthopaedic spine surgeon (MdK) and a health scientist (MvH). The responsibilities of this
project team were performing a review of clinical predictive indicators, weighing the evidence
for each indicator, selecting a panel of experts, developing the questionnaires, organisation
and conduct of email rounds and consensus meeting, analysing the responses, and compiling
a draft version of the clinical decision tool.
Panellists
In the area of CLBP treatment different medical specialists are involved and knowledge
gaps exist between different medical specialties [24]. Therefore, a heterogeneous group of
experts was selected for the expert panel. Moreover, it is known that when exploring areas of
uncertainty, a heterogeneous group is appropriate [70] and it is expected that heterogeneity
in a decision-making group may lead to better performance [71]. Panellists were asked
based on their willingness to participate, their intention to commit to the process, and their
recognised knowledge of the topic. They were recruited in one hospital and were included in
the panel when they met the following criteria: (1) professional background as a orthopaedic
spine surgeon, anaesthesiologist & pain consultant, physiatrist, rheumatologist, psychologist,
physical therapist, occupational therapist, psychomotor therapist, nurse practitioner; (2) CLBP
care and cure is the main area of professional attention; (3) more than five years of clinical
experience in the field; and (4) ability and willingness to respond to each email Delphi round
within one week and to join the final Delphi consensus meeting.
Delphi procedure
The panellists were emailed explaining the purpose and the content of the study. To increase
participation the panellists were asked to reply if they were willing to join and whether they
intended to commit to the procedure. The whole procedure was performed in two months,
April-May 2011. Two email Delphi rounds were planned to reach consensus. Consensus
was defined as a ’general agreement of a substantial majority’. The threshold for general
agreement was set at ≥70%. If an indicator reached a second time disagreement, the indicator
Development of NDT-CLBP
175
is rejected. For the two email rounds participants were asked to respond and reply within one
week. A third round, the final consensus meeting was performed to reach consensus about
the included items and to construct a first draft clinical decision tool. During this meeting
participants were allowed to discuss issues and exchange views supported by evidence, with
the aim to resolve issues for indicators that had not passed the threshold for consensus. In
each round the purpose and procedure of the current Delphi round and following Delphi
rounds were explained.
Delphi-1
The initial draft list of indicators extracted from the literature review and arranged in a
conceptual framework of domains was provided to the expert panel. They were asked to
respond to three main sets of questions (Q). The Q1 set was based on international and national
guidelines, which recommend an assessment of a minimal set of consistent prognostic
indicators influencing the treatment outcome [22,23,31,34]. Compiled by the project team and
supported by the literature review, this minimal set consisted of 32 indicators (‘red’ and ‘yellow’
flags, expectation of recovery, socio-economic status, sick leave, pain severity, prior episodes
of LBP), for which agreement (YES or NO) was asked. The Q2 set was based on the results of the
literature review and included 26 indicators with weighted evidence for which agreement for
inclusion (YES or NO) was asked. Moreover, in Q3 the panellists were given the opportunity
to suggest additional indicators for inclusion, based on scientific evidence and provided to
the project team, and to write general comments. The items for which ≥70% agreement was
reached were selected and included in the draft list for the final Consensus meeting (Delphi-3).
The indicators for which consensus was not reached, were included in round 2 (Delphi-2).
Delphi-2
In the second round an anonymous feedback report with a summary of results of Delphi-1
was provided. In this summary an overview of results for each question and each indicator
was given in count and percentages of agreement. Moreover, all suggested and newly
formulated indicators, including the arguments and comments were presented. The Delphi-2
questionnaire contained both those indicators that did not reach the pre-set agreement level
of ≥70% (Q1 and Q2; Delphi-1) and those that were newly formulated by the panellists (Q3;
Delphi-1). In this round the panellists were requested to indicate with YES or NO which of the
indicators of Q1 and Q2 absolutely needed to be included in the list? In Q3 a possibility was
given to mention new indicators. The level of agreement was set at ≥70% among the panellists,
i.e. these indicators were selected and included in the draft list for the following Consensus
meeting (Delphi-3). A second time lack of consensus led to rejection of the concerning indicator.
Delphi-3 Consensus meeting
Before the meeting all panellists received a covering summary of results on both Delphi rounds
which was similarly described and drafted as for the results of the first round. Moreover, a
draft list was provided with indicators for which consensus (≥70%), no consensus (<70%) was
reached, and the rejected indicators. During the meeting all indicators for which previously no
consensus had been reached were reconsidered. Only if new arguments based on scientific or
clinical evidence were provided, an attempt to reach a new consensus on that item was made.
Moreover, the panellists were encouraged to consider alternative views when consensus
could not be achieved [70]. The meeting had a formal character to ensure that all panellists
had a chance to express their views, all indicators were considered, no discussion was allowed
09
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Development of NDT-CLBP
and only arguments could be provided, and the panellists made judgements individually.
Consensus was reached by voting; raising hands. Only those indicators with ≥70% agreement
were included in the final screening questionnaire, all others were rejected. A dedicated and
independent process leader is a key element for a successful consensus meeting; this person
facilitates the exchange of relevant information [70]. One of the project team members
(JvL) is an experienced Delphi round facilitator, who was not one of the panellists, but who
ensured that the process ran smoothly and that good-quality un-biased decisions were made.
The project leader (MvH), not a member of the expert panel, assisted the process leader in
process monitoring, ensured that all procedures ran according to the rules, counted the votes,
compiled the minutes during the meeting and provided a full report after the meeting. The
report included the followed procedures, the results of the voting rounds, the course of the
discussions, the decisions made, and the final list of ‘consensus indicators’. All panellists who
joined the consensus meeting received a copy.
09
Development of the ‘Nijmegen decision tool for CLBP’
The final list of ‘consensus indicators’ was used to compile a first version of the clinical decision
tool. For the screening questionnaire existing international patient reported outcome
measures (PROMs) were screened to identify whether the indicators are covered by these
PROMs. The indicators were compared to existing questions used in the Swedish Spine Register
(Swespine [www.4S.nu]). These questions were translated and screened for unambiguity and
whether they measured the construct as intended by the indicator. The remaining indicators
were converted to new questions. The screening questionnaire was built in the Dutch patient
interface of Swespine. Based on the list of consensus indicators, international guidelines, and
current practice a provisional decision algorithm was constructed.
Results
Preparatory stage: Evidence from literature
An initial draft list with 58 candidate indicators, categorized in five domains, and including the
evidence was compiled. Table 9.1 shows the evidence summarized for all candidate indicators
(the evidence and references per indicator are available in Table S1). For 38 (66%) candidate
indicators conclusive evidence was found indicating a predictive value for treatment outcome
or persistence of complaints (C: PV), 15 had inconclusive evidence for predicting outcome or
persistence of pain complaints (I), and for five indicators conclusive evidence was found that
the concerning indicator is of no predictive value (C: NP). These five indicators were removed
from the initial draft list, leaving 53 candidate indicators and they were included in the Delphi
study.
Development of NDT-CLBP
177
Table 9.1 Results Preparatory stage: Evidence from literature
Domain
Sociodemographic
Category 1
Study design 2
Evidence 3
SR
n
RCT
n
PC
n
NR
n
Personal
Age
Gender
Ethnicity
Body weight
Marital status 4
4
4
1
3
3
-
8
9
1
-
4
3
2
I
I
C: PV
I
C: NP
Health
Smoking
Previous back surgery
Use of analgesics
5
1
1
-
4
2
1
1
1
I
C:PV
I
Social
Education
Social status
Functioning – leisure
Social support
1
1
1
-
-
3
1
-
3
1
2
I
I
I
C: PV
Work
Socio-economic status *
Work satisfaction
Functioning – work
Sick leave *
Compensation
Litigation
Work ability
Work adjustment
Physical strenuousness
2
5
3
3
3
1
1
1
-
2
2
3
-
2
4
2
1
-
C: PV
I
I
C: PV
I
C: PV
C: PV
C: PV
I
Pain
Duration
Intensity *
Intensity – back
Intensity – leg
Interference daily activities
Frequency / preceding (prior)
episodes *
4
5
2
2
1
1
-
3
11
3
2
1
1
3
1
2
I
C: PV
C: PV
C: PV
C: PV
I
Somatic
Physical & Biological
Diagnosis; co morbidities
Bulging or protruded disc *
Loss of neurological function *
Red flags (n=10) * #
Strength; endurance; mobility 4
Central sensitisation 4
Postural control; psychomotor speed 4
1
2
1
-
2
2
1
1
1
4
1
1
-
2
-
-
C: PV
C: PV
C: PV
C: PV
C: NP
C: NP
C: NP
Psychic affect
Distress *
Anxiety *
6
3
2
2
3
2
4
4
C: PV
C: PV
Cognition
Catastrophizing *
Somatization *
Coping *
Intelligence 4
5
4
5
1
3
-
7
1
2
-
3
1
4
-
C: PV
C: PV
C: PV
C: PV
C: NP
Psychologic
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Development of NDT-CLBP
Behaviour
Fear of movement / (re)injury *
Expectations – work return *
Expectations – outcome / recovery *
Self-efficacy (incl. Readiness–to–
change)
Pain avoidance & pain persistence
Functioning &
Quality of Life
Functioning in daily activities &
walking
Health-related physical functioning
Health-related mental functioning
General perceived health
3
1
2
-
-
12
3
1
1
4
2
2
-
C: PV
C: PV
C: PV
C: PV
-
1
-
-
C: PV
6
1
9
3
C: PV
3
6
1
-
5
1
2
1
1
1
C: PV
I
C: PV
Initial draft list with indicators (n=58) indicating a predictive value for treatment outcome or persistence of back pain, categorized in domains,
including the number of studies found per study design and the resulting evidential value.
* Recommended in (inter-/) national guidelines; # Pain started age <20 or >50 years, recent trauma, constant progressive pain, history of
malignancies, prolonged use of corticosteroid use, HIV, recent unexplained weight loss, structural deformity, infectious disease (CBO 2010)
2
SR Systematic Review; R Randomized Clinical Trial; PC Prospective Cohort study; NR Narrative Review; n number of studies
3
I Inconclusive evidence; C Conclusive evidence; PV Predictive Value; NP No Predictive value
4
Not included for phase 2 Delphi Study
1
09
Delphi Study
Participants
A panel of 29 experts met the inclusion criteria and agreed to participate (orthopaedic spine
surgeon [n=7], anaesthesiologist & pain consultant [n=3], physiatrist [n=3], rheumatologist
[n=1], psychologist [n=4], physical therapist [n=7], occupational therapist [n=1], psychomotor
therapist [n=1], nurse practitioner [n=2]).
The response rate for the first Delphi round (Delphi-1) was 76% (n=22) and for Delphi-2 69%
(n=20). The main reason for not responding in the first two rounds was due to absence from
work and none of the approached panellists did not respond on both email rounds. All 29
panellists (100%) attended the final consensus meeting (Delphi-3).
Delphi-1
As shown in Figure 9.2, 48 indicators were selected in the first round based on consensus (≥70%
agreement level). For five indicators consensus was not reached. Moreover, 26 indicators were
newly formulated by the panel in the open end question (sociodemographic n=9; pain n=4;
somatic n=7; psychologic n=3; functioning and quality of life n=3) and these indicators were
added to the Delphi-2 questionnaire. These 26 indicators consisted of:
1. six indicators mentioned in the Dutch guidelines for general practitioners: self-management
of complaints, previous interventions, daily course of pain complaints, influence of rest,
mobility and posture, previous episodes, and comorbidities (range and severity) [74]. The
last two show overlap with previously identified indicators.
2. one indicator for inflammatory LBP (Calin criteria [75]).
3. ten newly formulated indicators with overlap with indicators of the initial draft list.
4. nine indicators with no predictive evidence and were rejected from the sample.
No further comments were made.
Development of NDT-CLBP
179
Delphi-2
As shown in Figure 9.2, 22 indicators were presented, including the 17 newly formulated and
the five indicators for which no consensus was reached in Delphi-1. Of these, 14 reached the
pre-set ≥70% agreement level for consensus. Five indicators were rejected as for the second
time no consensus was reached. No new indicators were suggested and no further comments
were made.
Delphi-3 Consensus meeting
All indicators on which consensus were reached in either Delphi-1 or 2 (62 indicators; 48+14)
and those indicators no consensus was reached in Delphi-2 (3 indicators) were briefly discussed
(Figure 9.2). After each indicator the panellists voted whether they still agreed or not. As shown
in Table 2, at the meeting consensus was reached for 47 indicators (pre-set ≥70% agreement
level), whereas eight indicators reached no consensus. These indicators were rejected, as well
as ten indicators showing an overlap with the initial indicators.
Consensus was reached to re-formulate one indicator ‘Body weight’ into ‘Body weight & BMI’
and another indicator ‘Pain-interference daily activities’ switched domains from ‘Pain’ to the
domain ‘Functioning & Quality of Life’.
The remaining 47 indicators formed the backbone of the screenings questionnaire (36 with
conclusive evidence for predictive value [77%] and 11 with inconclusive evidence; Table 9.2).
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Figure 9.2 Results of the Delphi Study. At each stage of the Delphi study the expert panel consensus for
presented indicators is shown. To reach consensus the level of agreement was set at ≥70%. Indicators
reaching full consensus were included in the Nijmegen Decision Tool.
Preparatory stage
Evidence from literature
Initial draft list
58 candidate indicators
Predictive value
Rejected: n = 5
NO
YES
Final list for Delphi
53 indicators (n = 53)
Delphi-1
Email round
Newly suggested
n = 26
Consensus (≥ 70%)
n = 48
YES
Delphi-1
Consensus?
n=53
Predictive value
Rejected: n = 9
YES
NO
No consensus (< 70%)
n=5
09
NO
n = 17
(Overlap * n=10)
Delphi-3
Consensus meeting
Delphi-2
Email round
YES
Consensus (≥ 70%)
n = 14
YES
Delphi-2
Consensus?
n=22
NO
Rejected: n = 5
NO
No consensus (< 70%)
n=3
Delphi-3
Consensus meeting
n=65
≥ 70% n=62 (Delphi-1&2)
≥ 70% n=3 (Delphi-2)
YES
Inclusion in Nijmegen Decision Tool
Consensus (≥ 70%): 47 indicators
n=36 conclusive evidence for
predictive value
n=11 inconclusive evidence
* overlap doublure in the definition of indicators
NO
Rejected: n = 18
Overlap * n=10
No consensus < 70% n=8
Development of NDT-CLBP
181
Table 9.2 Results of the Delphi Study
Domain
Category
Evidence
Sociodemographic
Personal
Age
Gender
Body weight & BMI
I
I
I
Health
Smoking
Previous back surgery
Use of analgesics
Self-management of complaints
Interventions in the past
I
C
I
C
C
Social
Social status
Functioning – leisure
Social support
I
I
C
Work
Socio-economic status *
Work satisfaction
Functioning – work
Sick leave *
Litigation
C
I
I
C
C
Duration
Intensity *
Intensity – back
Intensity – leg
Frequency / preceding (prior) episodes *
Daily course of pain complaints
Influence of rest, mobility, and posture
I
C
C
C
I
C
C
Diagnosis; co morbidities (Red Flag)
Bulging or protruded disc * (Red Flag)
Loss of neurological function * (Red Flag)
Red flags (n=11) *
Pain started age < 20 or > 50 years
Significant trauma
Pain is constant and non-mechanical
Pain in thoracic spine
Deformities (i.e. scoliosis, lumbar kyphosis)
Previous history of malignities/cancer
History of intravenous drug use
AIDS / HIV
Currently steroid use
Recent unexplained weight loss
Calin criteria for axial spondylarthritis
C
C
C
C
Pain
Somatic
Physical & Biological
Psychologic
C
Psychic affect
Distress *
Anxiety *
C
C
Cognition
Catastrophizing *
Somatization *
Coping *
C
C
C
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Development of NDT-CLBP
Behaviour
Fear of movement / (re)injury *
Expectations – work return *
Expectations – outcome / recovery *
Functioning &
Quality of Life
Functioning in daily activities & walking
Pain-interference daily activities
Health-related physical functioning
C
C
C
C
C
* Recommended in international guidelines
Newly formulated indicators are printed in italics
I Inconclusive evidence; C Conclusive evidence
Final list with ‘full consensus’ indicators categorized in domains, including the resulting evidential value.
The ‘Nijmegen decision tool for CLBP’
A first version of a clinical decision tool consisting of two parts was drafted by the project
team: (1) A screening questionnaire, including all 47 indicators, and (2) a provisional decision
algorithm.
09
1. The screening questionnaire
For the backbone of the screening questionnaire existing international patient reported
outcome measures (PROMs) with well-established psychometric properties were screened to
identify whether the 47 identified indicators were covered by these existing questionnaires
(Table 9.3). Four of the 47 indicators are outcome indicators and adequately measured by the
Oswestry Disability Index (ODI, version 2.1a) for functional status, the Short-Form 36 Health
Survey Questionnaire (SF36) and the EuroQol (EQ-5D) for quality of life, and the Numeric Rating
Scale (NRS) for back and leg pain. The STarT back is used as a screening tool for identifying
the amount of risk for three psychological indicators (distress, catastrophizing, and fear
of movement / (re)injury; i.e. ‘yellow flags’). The remaining 40 indicators were compared to
existing questions in the Swespine register. Analogous questions were translated and the
remaining indicators were added as dichotomous or multiple choice questions in the final
questionnaire. The complete screening questionnaire is available from the authors.
2. The provisional decision algorithm
The provisional decision algorithm is based on the flag approach and based on current
practice. The red flag signs are thought to be associated with underlying pathology. Therefore,
in the algorithm the presence of ≥ 1 red flag (e.g. previous history of malignancies, trauma)
is indicative for a consultation by a spinal surgeon, whereas a high risk on yellow flags (i.e.
distress, catastrophizing cognitions) is second most decisive as a high risk on yellow flags
might be predictive for treatment failure
Development of NDT-CLBP
183
Table 9.3 Backbone screening questionnaire
Domains
Flag approach
[33]
Results Phase 2
(current study)
Indicators (n=47)
Questions
Sociodemographic
Blue & Black
13
Multiple choice
3
Dichotomous
5
Multiple choice
2
NRS (0-10) *
Pain
n.a.
Somatic
Red
14
Dichotomous
Psychosocial
Yellow
3
STarT back screening tool [88]
4
Multiple choice
1
Dichotomous
2
ODI (v2.1a); SF36; EQ-5D *
Functioning &
Quality of Life
n.a.
* standard & agreed to implement in Swespine register www.4s.nu
Discussion
The purpose of this study was to develop a clinical decision tool for secondary or tertiary
care specialists to decide which patients with chronic low back pain (CLBP) should be seen
by a spine surgeon for consideration of a beneficial surgical intervention (including invasive
pain management), and which patients in the future should best be seen by other medical
specialists, e.g. physiatrists, rheumatologists or pain consultants. A study, consisting of a
preparatory stage in which evidence from literature was summarized followed by a threeround Delphi study, contributed to the developed Nijmegen clinical decision tool for CLBP,
which includes 1) a patient-based and web-based screening questionnaire and 2) a provisional
decision algorithm.
In the preparatory stage of this study, we included in the literature review the evidence found
in international guidelines [22,23,31] and the evidence from one national guideline [34], as
these guidelines are normative for evidence based daily practice. However, studies included in
these guidelines have led to inconsistent results and rarely show more than small to moderate
overall benefit for different types of interventions, which makes it difficult to interpret which
patient benefits from which intervention. Therefore, we performed a literature search covering
the whole spectrum of CLBP ignoring specific medical specialties (explicit knowledge). This is
supplemented by professional state-of-the-art knowledge derived from experiences in daily
practice and collegial meetings and conferences, in a formal consensus (Delphi) study (implicit
knowledge).
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Development of NDT-CLBP
The screening questionnaire
The literature search revealed a large number of published studies (n=33) related to the
identification of predictive indicators for a successful treatment outcome or the prediction
of persistence of CLBP complaints. As expected the result of this study is a long list of
predictive indicators (n=47), with most of them (77%) having scientific evidence for predictive
value. To list and classify the indicators in Table 9.2 and 9.3 we used the conceptual model of
patient outcomes [76] and identified five main domains: Sociodemographic, Pain, Somatic,
Psychologic, and Functioning and Quality of Life. Overall, we found strong predictive evidence
for successful outcome of spinal surgery for: previous back surgery and biological indicators
(i.e. diagnosis; co-morbidities as diabetes, bulging or protruded disc, loss of neurological
function, and ‘red flags’). In this study consensus was reached to add BMI and smoking as
indicators in the screening questionnaire and to evaluate their contribution to outcome of
surgical interventions over time. Although the evidence is growing that high BMI [77] and
smoking [63,64,78-80] are predictive for a poor outcome after surgery, the current scientific
evidence is still inconclusive. Along with the predictive value of psychological indicators
(yellow flags) [38,39,48] and expectations for treatment outcome [37,43,78] and work return
[37,43,56], predictive indicators as high disability [36,38,39,48,80], being unemployed [37,43,64],
and being involved in litigation and/or compensation claims [36,39,41,51,63,66,78] seem to lead
to unfavourable outcome for all CLBP interventions.
09
The provisional decision algorithm
For this study we used the recommended clinical flag approach [33] for clinical decisionmaking in CLBP as a starting point [22,23,34]. A diagnostic triage based on ‘red flag’ signs is
recommended [22,34,81] as red flag signs are features thought to be associated with a high
risk of serious underlying disorders, such as infection, inflammatory disease, cancer or
fracture [33,82] or nerve root disease [46]. The presence of a red flag alerts clinicians to the
need for further examination and specific management [82-84]. In this study consensus was
reached that the presence of one or more red flag signs is indicative for a consultation by a
spinal surgeon, which was incorporated as a first step in the provisional decision algorithm.
However, the guideline recommendations on diagnostic triage based on red flags are still not
very strong [81]. Most of the patients with back pain show at least one positive red flag and
do not have a serious underlying condition. Taking the guideline recommendations literally
could cause harm. These harms include unnecessary diagnostics, unnecessary exposure to
radiation, as well as unnecessary treatments, including surgery [85]. Moreover, a summary
[86] of two recently published Cochrane reviews aiming to detect the diagnostic accuracy
of red flags to screen for vertebral fracture [84] and malignancy [83] concluded that a lack of
evidence exists that one red flag used in isolation can be used to aid a clinician’s judgement.
We expect that combinations of red flags and clinical features might appear more informative
to assist clinical decision-making [83,84,86]. Even though it is recommended to assess the socalled yellow flags [22,23] as well, it remains unclear what these indicators contribute to actual
clinical decision-making. Large prospective studies are needed to evaluate the contribution of
these indicators to successful treatment outcome. In this study consensus was reached that a
high risk on yellow flags is the second most decisive for surgical or non-surgical interventions.
We currently perform further studies to examine multifactorial diagnostic models and with
that, the scientific value of combinations of flags and indicators, collected by means of the
screening questionnaire, in clinical decision-making for further diagnostics and/or treatment.
Development of NDT-CLBP
185
CLBP is a multifactorial health condition and therefore, it has been widely recommended
to develop a classification system or a decision tool to direct CLBP patients to interventions
based on biomedical and psychosocial indicators [11,22-25,30,31]. To date we are not aware of
any study covering the whole spectrum and to our knowledge the Nijmegen decision tool for
CLBP is the first published patient screening questionnaire and provisional decision algorithm.
The backbone of the screening questionnaire consists of Dutch versions of international
validated PROMs. To be able to make our future study results comparable and to be able to
perform benchmark studies in the future, we selected commonly used PROMs covering those
indicators that are treatment outcome-related (functioning in daily activities with ODI, quality
of life with SF36 and EQ5D, and pain intensity with NRS) [87]. These PROMs are also used in
the Swedish Spine Register (Swespine [www.4S.nu]). To screen yellow flags and determine the
risk of psychological influence on treatment outcome we implemented the Dutch version of
the STarT back screening tool [88-90]. Although validated and useful in primary care [88,91-93]
further research is needed to evaluate the validity and feasibility of prognostic screening with
this tool in secondary or tertiary back care. To our knowledge, for the remaining indicators
of the screening questionnaire no validated and reliable questionnaires exist. Large and
methodological sound studies are needed for the feasibility and validity of these questions
and whether (a combination of) these indicators contribute to successful treatment outcome.
In March 2012 the screening questionnaire was implemented in the Dutch patient interface of
the Swespine. Swespine was chosen as it is one of the largest, oldest and most studied national
registries, which covers both PROMs and clinical results [94], which allows benchmarking
data in future. After pilot testing and some minor adjustments (e.g. grammatical and spelling
mistakes, wording of questions, and technical issues related to the system), the web-based
register started in May 2012. The registry is an ideal instrument to obtain meaningful data
prospectively, to define normative values, to identify patient profiles, to confirm differences in
treatment outcomes for subpopulations [25,95]. The results can be used for quality assurance,
quality improvement and for research purposes [94]. To study the provisional clinical decision
algorithm, since May 2012 all LBP patients referred to our clinic complete the screening
questionnaire web-based and treated patients are systematically followed over time for two
years by completing the same PROMs at predefined follow-up moments. With that, in future it
should be possible to identify patient profiles (phenotypes} predicting a beneficial treatment
outcome for each type of surgical or non-surgical intervention, for all the referred, treated and
untreated patients. At the same time data of the individual patients are presented in PDFformat in the electronic medical record (EMR) of the patient and contributes to individual
decision-making in the clinic.
Strengths and Weaknesses
Although for 36 of the 47 indicators conclusive evidence is available in the literature that
they have predictive value for treatment outcome in patients with CLBP, for 11 indicators the
evidence was inconclusive. These indicators were included in the Delphi study, based on the
expert opinion of a panel of LBP clinicians. However, the formal, structured, and systematic
character of the Modified Delphi Technique is of great value in indicator research when
scientific evidence for indicators is inconclusive or lacking [71]. Moreover, to overcome the
knowledge gaps existing between different medical specialties in the CLBP field [24], we
used this technique in a multidisciplinary panel of specialists as it is argued to successfully
bring together and to synthesize the knowledge of the whole expert group [71]. All health
09
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Development of NDT-CLBP
professionals came from one hospital specialised in spine care and the generalisation to other
secondary or tertiary spine practices in other countries and healthcare environments might
be limited. Strength of this study is that the panel included diverse professionals covering
the secondary surgical and non-surgical CLBP care. Moreover, the decision tool is based on
international accepted guidelines and evidence published in literature, covering the whole
spectrum of CLBP. We weighed the evidence in literature according to the Levels of Evidence
[69]. By combining this explicit knowledge with the implicit knowledge of the expert panel in
the three-round Delphi study, after refinement of the decision algorithm, and after validation
of the tool in other settings, we expect that the Nijmegen Decision Tool for CLBP could be used
in general secondary and tertiary spine care.
Conclusion
This study has provided the first clinical decision tool for CLBP patients, based on current
scientific evidence and formal consensus, covering the whole spectrum of CLBP. We expect
that this relatively simple tool will considerably help a daily spine practice in clinical decisionmaking 1) to select the right CLBP patients for the right interventions, thereby improving the
outcomes of spinal interventions, and 2) lead to a reduction in healthcare costs by reducing
the number of inappropriate referrals to spine care professionals.
09
Functioning
& Quality of Life
Psychologic
Somatic
Physical & Biological
Pain
N
PV
Previous back surgery
Use of analgesics
PV
PV
PV
Social status
Functioning - leisure
Social support
PV
N
I
PV
PV
N
Diagnosis; comorbidities *
Bulging or protruded disc *
Loss of neurological function *
Red Flags (n= 10) *
PV
PV
Anxiety *
PV
N
PV
Somatization *
Intelligence
Coping *
N
General perceived health
IN
OUT
* International Guidelines [22,23,31]
I
Health (related mental QoL)
PV
Expectations - outcome / recovery *
I
PV
Expectations - work return *
Health (related physical QoL)
PV
Avoidance & persistence
PV
PV
Fear of Movement / (re)injury *
Functioning in daily activities & walking
PV
Self-efficacy (including Readiness to Change)
Behaviour
PV
Catastrophizing *
Cognition
Distress *
Psychic affect
PV
N
PV = Predictive value
NP = No predictive value
I = Inconclusive evidence
N = No evidence available
PV
PV
PV
PV
PV
I
PV
PV
N
PV
N
PV
PV
PV
PV
PV
PV
N
N
I
Postural control, psychomotor speed
I
N
Centralization phenomenon
I
Frequency / preceding (prior) episodes *
PV
PV
PV
PV
PV
N
I
PV
NP
N
PV
I
N
PV
PV
N
PV
I
N
PV
I
Strength, endurance, mobility
PV
Interference daily activities
PV
Litigation
I
PV
Compensation
N
PV
Sick leave *
Intensity - leg
N
Physical strenuousness
Intensity - back
N
Work adjustment
PV
PV
Functioning - work
Intensity *
I
Work satisfaction
PV
N
Work abiltity
Duration
PV
Socio-economic status *
Work
PV
Education
Social
I
Smoking
N
NP
NP
I
N
N
PV
PV
N
N
N
PV
N
PV
I
N
PV
PV
PV
PV
PV
N
NP
NP
NP
NP
N
PV
PV
PV
PV
NP
N
I
I
N
PV
PV
PV
PV
N
N
PV
NP
N
I
N
NP
N
NP
N
NP
PV (W)
I (S)
PV (S)
PV (S)
PV (S)
PV (S)
PV (W)
PV (W)
PV (W)
PV (S)
I (S)
PV (S)
PV (S)
PV (S)
PV (S)
PV (S)
PV (S)
PV (S)
PV (S)
NP (S)
NP (S)
NP (S)
I (S)
PV (S)
PV (S)
PV (W)
PV (S)
I (S)
PV (W)
I (S)
PV (S)
NP (S)
PV (S)
I (S)
I (S)
PV (S)
PV (S)
PV (W)
I (S)
I (S)
I (S)
I (S)
PV (S)
I (S)
PV (W)
I (S)
NP (S)
I (S)
PV [38]; I [39]
PV [38]
NP [41,45,47]; PV [37,44,46]
PV [41]
NP [43]; PV [38,45]
PV [51, 63]; I [39}
PV [41]
PV [66]
PV [38]
PV [38]
PV [38-39,43,65]
PV [38-39]
PV [39,56]
PV [38-39]
PV [38-39,55]
PV [41,52]
PV [46]
NP [67]; PV [42,44-47,49-50,53]
NP [47]; PV [42,44-46; 49-50,53,66]
PV [41-42,44-45,47,49-50,54,58,60-62,66]
NP [66]; PV [41-42,45]
NP [47]; PV [41-42,44-46]
PV [38-39,51,55-56,63](functioning),[43,65]
(walking)
PV [43,56,63-64]
PV [43,51,56,63-64]
PV [56]
NP [67]; PV [41,44,46-47,52-53]
NP [53,67]; PV [41,45]
NP [53]; PV [41,45]
NP [41]; PV [53]
PV [36]
PV [36,40,48], [66](walking]
PV [40,66]
PV [36,40]
I [36]
PV [40,48]
PV [66]
PV [40]; I [36]
PV [66]
NP [66]
NP [36]
NP [36]
NP [36,40]
PV [36]
Refences used:
Systematic reviews [36-43]
Narrative reviews [44-47]
Randomised studies [48-50]
Observational studies [51-68]
PV [43,55]
PV [37,53]
(W) weak = studies or narrative reviews
(S) strong = studies & reviews
or systematic reviews
NP [55]; PV [56]
PV [37,44-45]
PV [50]
PV [41-42,44-47(pain),49,52,54,57-62,66]
PV [55-56]
PV [43](comorbidity),[65](comorbidity)
NP [66]; PV [44]
PV [59](self-efficacy)
NP [55]; I [39]
NP [41]; PV [53]
NP [41,52]; PV [44,46]
PV [47](bothersomeness)
PV [36,66]
PV [36,40,48]
PV [51,56]
PV [56]
PV [38-39,51,55,65]
PV [41,44,46-47,52-53,57-62,66]
NP [47]; PV [41]
PV [38-39,43]
NP [36]
PV [66]; I [36]
I [36}
PV [36]
PV [36]
PV [36]
NP [61,66]; PV [44,52]
PV [46]
PV [44,47,53]
NP [43]
PV [43,64]
NP [53,67]; PV [37,46-47]
PV [36]
PV [36]
PV [44-45]
NP [36]
I [36]
NP [36}
PV [52]
NP [64]; PV [38]
PV [51,64]; I [39]
NP [38,43]; PV [51,63-64]; I [39]
NP [36]
NP [36]
NP [36]; PV [66]
Non-surgical
PV [47]
NP [46]; PV [45,47,52,53]; I [66]
PV [53]
NP [41,53]; PV [46]
PV [67]
NP [43](weight),[63](weight)
PV
NP [41](weight); I [46](weight)
I
Ethnicity
Health
Body weight
NP [38,43,65]
NP [52,67]
NP
Marital status
NP [55,65]; PV [39,43,51,56]
NP [41,44,47,52,58,60-61,67]; PV [45,66]
I
Gender
NP [38,63]; PV [39,43,55,65]
I (S)
Surgical
NP
NP [41,44,47,60-61,67]; PV [45-46,52,66]
I
Persistence LBP
I
Personal
Sociodemographic
Overall (weighted)
REFERENCES
Non-surgical
Persistence LBP
Surgical
EVIDENCE
Age
INDICATORS
DOMAIN
Development of NDT-CLBP
187
Supporting Information
Table S1. Preparatory stage – Summarized evidence and references per indicator
09
188
Development of NDT-CLBP
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193
Chapter 10
Patient-reported factors
partly predicted referral
to spinal surgery in
a consecutive cohort of 4,987
chronic low back pain patients
van Dongen JM
van Hooff ML
Spruit M
de Kleuver M
Ostelo RWJG
Under review
194
Abstract
Purpose: To determine which patient-reported factors are predictive of spinal surgery referral
among chronic low back pain (CLBP) patients.
Methods: 4,987 CLBP patients were included. Possible predictive factors were explored using a
screening questionnaire. Referral data were derived from hospital records. A prediction model
was obtained by backwards selection. The model’s performance and validation were assessed.
Results: Female gender, previous back surgery, high intensity leg pain, somatization, and
positive treatment expectations increased the odds of being referred to spinal surgery, while
being obese, having comorbidities, pain in the thoracic spine, reduced walking distance, and
consultation location decreased the odds. The model’s fit was good, its discriminative ability
was poor, and its explained variance was low. A post-hoc analysis indicated that consultation
location was significantly associated with spinal surgery referral, even after correcting for
case-mix variables.
Conclusion: Some patient-reported factors could be identified that are predictive of spinal
surgery referral. Although the identified factors are known as common predictive factors of
surgery outcome, they could only partly predict spinal surgery referral.
215
Chapter 11
Prognostic patient-reported
profiles for referral to secondary
or tertiary spine specialists
The Nijmegen Decision Tool
for Chronic Low Back Pain
van Hooff ML
van Dongen JM
Coupé VMH
Spruit M
Ostelo RWJG
de Kleuver M
Submitted for publication
216
Abstract
Objective: To develop and internally validate pre-treatment prognostic models for patient
triage to the right secondary care specialist, by identifying patient-reported profiles for
chronic low back pain (CLBP) that either predict ‘response’ or ‘non-response’ to elective lumbar
spine surgery, or to a multidisciplinary bio-psychosocial pain management programme.
Design: Observational study, using baseline and one-year follow-up data from a large
institutional spine outcome registry. Data on forty-seven evidence-based potential indicators
acquired before consultation, predicting ‘response’ or ‘non-response’ to treatment, were used.
Setting: Secondary referral spine centre.
Participants: Two treatment cohorts were selected from a source population of 3,410 referred
CLBP-patients: a spine surgery cohort (n=217 [6.4%]) and a pain management programme
cohort (n=171 [5.0%]). Main inclusion criteria were: age ≥18, CLBP (≥6 months), not responding
to primary care treatment.
Main outcome measures: The primary outcomes were ‘response’ and ‘non-response’ to
treatment in terms of functional ability. ‘Response’ (i.e. successful treatment outcome) was
defined as Oswestry Disability Index (ODI)≤22. ‘Non-response’ (i.e. failure after treatment) was
defined as ODI≥41.
Results: The different models’ explained variances (R2) were low for the pain management
models (23%-26%) and were modest for the surgical models (R2 30-39%). Although all the
models’ overall performances were acceptable (c-index 0.72-0.83), the surgical non-response
model performed best (R2 39%; c-index 0.83).
Conclusions: This study was the first to identify different patient profiles based on pretreatment patient-reported characteristics that predict response to treatment for CLBP.
In general the performances of all models were acceptable, but the ‘non-response’ model
to elective lumbar spine surgery performed remarkably well, suggesting that this profile
might contribute to avoiding unnecessary future surgeries. After including more patients
and after external validation in other secondary spine practices, these patient profiles could
potentially enhance timely patient triage to the right secondary care specialist, and ultimately
contributing to improved outcomes and a more efficient use of healthcare resources.
Trial registration: The Dutch Trial Register (NTR5946)
247
Chapter 12
Summary & General discussion
248
Summary and General discussion
249
The ultimate aim of the research presented in this thesis is to contribute to the body of
knowledge on outcomes of interventions for chronic low back pain (CLBP) and to identify
outcome-based subgroups of patients having different profiles. Based on work included
in this thesis, an article was published in a provincial newspaper in 2014 highlighting the
development of a tool to triage the right patient to the right medical specialist, based on
subgroups with different patient profiles, i.e. the Nijmegen Decision Tool for CLBP. The
headline stated ‘A questionnaire helps in low back pain’ [1]. Whilst we think we have taken
an important step forward in terms of the knowledge gained and identifying pre-treatment
profiles related to outcomes of interventions, a questionnaire as such is only a small piece of
the puzzle towards solving the tremendous worldwide burden of low back pain.
Despite decades of research, honed expertise, and improved quality of clinical trials, the
evidence regarding the effectiveness of the treatments offered to patients with CLBP is still
inconsistent [2-8], rarely shows more than a small to moderate overall benefit [2,7,9-12], and
demonstrates a lack of long-term efficacy in changing the prognostic paths [10]. Most patients
recover, but in around 20% the complaints persist for more than three months, resulting in
disabling CLBP. These patients bear the greatest proportion of the disease burden. One reason
for the overall disappointing outcomes is that the CLBP population is heterogeneous because
the condition lacks diagnostic clarity; as a consequence, there exists a plethora of invasive
and non-invasive interventions in secondary or tertiary healthcare for the same symptom.
To reduce the global societal burden of CLBP it is crucial to improve treatment outcomes and
to reduce the related costs, to improve the value of delivered healthcare. To achieve this it is
essential to know which outcomes are relevant to both patients and medical specialists and to
know which patients will benefit from spine surgery or from non-surgical treatments.
In the General introduction of this thesis the aims are described using three separate, though
related themes. In the first theme a non-surgical combined physical and psychological (CPP)
programme was evaluated and insight is given as to who could benefit from this programme.
In the second theme the focus is on the methodology used for outcomes assessment in the
evaluation of clinical practice and research of degenerative lumbar spine disorders. In the
third theme the development of a clinical decision tool for patient triage to a surgical or a
non-surgical medical specialist is described. In this Summary & General discussion the overall
research questions are answered by summarising and discussing the main findings per
theme. Considerations are described that warrant further exploration in relationship to the
methodology used, and some implications and recommendations for clinical practice and for
future research are presented. The discussion ends with concluding remarks.
12
250
Summary and General discussion
Theme A:
Introduction of a combined physical and psychological programme
Research questions
1. Does the novel CPP programme for CLBP improve patient outcomes and reduce healthcare
consumption?
2.Is it possible to identify a subgroup of patients that benefits most from the novel CPP
programme so that selection criteria can be optimised?
Summary of main findings
In the one- and two-year follow-up cohort studies presented in Chapter 2 and 3, selected and
motivated patients with longstanding CLBP participated in an intensive multidisciplinary
CPP programme. Participating patients were moderately to severely disabled, which is
comparable to patients being treated in secondary spine care. They learned to manage their
CLBP, and their daily functioning and quality of life improved meaningfully. The magnitude of
the improvement is comparable to that achieved with spinal surgery (Standardised Morbidity
Ratio [SMR] 98%) and better than that achieved with less intensive rehabilitation programmes
(SMR 136%) (Chapter 2). At the two-year follow-up of this cohort, the significant and clinically
relevant improvements in functional ability, pain and health-related quality of life achieved
at the one-year follow-up assessment were maintained. Above all, most of the participants
were employed and the results indicate that the use of both pain medication and healthcare
decreased substantially (Chapter 3). In Chapter 4, pre-treatment indicators of a successful
treatment outcome were identified. Successful treatment outcome was defined as a one-year
follow-up functional disability (disability) score falling to values seen in healthy populations
(Oswestry Disability Index, ODI ≤22). Patients who are employed at pre-treatment [OR 3.61 (95
% CI 1.80–7.26) and who are mild to moderately disabled at the start of a CPP programme [OR
0.94 (95% CI 0.92–0.97)] are most likely to benefit from this programme (R2=22%; 67% correctly
classified). No interaction effects between pre-treatment characteristics were found and, to
our surprise, no predictive value was found for psychological distress.
12
As continuous outcomes monitoring is part of the CPP programme, this gave us the
opportunity to further substantiate the ‘pilot’ results presented in Chapter 2 with one-year
follow-up results of a large cohort (n=848). The results of this recent study showed that these
patients had similarly good results: patients improved during the programme, showed further
improvement at the one-year follow-up, and half of the patients (51%, n=433) improved such
that their functional status was comparable to that of the healthy population [13].
Discussion
In a recent systematic review, moderate-quality evidence for moderate effects of
multidisciplinary bio-psychosocial treatments was found compared to usual care [12]. These
treatments are recommended for CLBP patients [14-16], but not often implemented.
In this thesis the clinical relevance of the CPP programme has been demonstrated: patients
improved meaningfully, healthcare consumption was reduced, and a relevant treatment effect
was found. We found large effect sizes for functional ability at the one-year follow-up (Chapter
2) and the two-year follow-up (Chapter 3), meaning that the programme shows relevant
effects. The two-year follow-up findings presented in Chapter 3 were further substantiated
Summary and General discussion
251
by the results of a recently performed long-term follow-up post-marketing surveillance study
involving 277 ex-participants (mean follow-up of 6.5 years [range: 5.5–7.5]; response 85%; no
baseline differences between responders and non-responders to the survey); positive results
were maintained after 6.5 years on average, and 80% of the participants were satisfied with
the treatment results [17].
We studied the intervention as an integral programme. The programme uses a wide range
of techniques based on cognitive behavioural principles. As yet, the working mechanisms
are unknown, so it is unclear which techniques or parts of the intervention are the effective
elements. In Chapter 4 we speculate that several aspects contribute to the success of this
programme, such as the programme’s structure (a. the intensity or dose of the programme),
the programme entrance criteria (b. motivation to change behaviour), and the content of the
programme (c. improvement of dysfunctional cognitive behavioural factors).
a)Intensity of the programme. Although conflicting evidence exists concerning stability over
time [18,19], it is assumed that dysfunctional behavioural cognitions in patients with
persistent pain of long duration are resistant to change [20]. In a systematic review, Guzman
et al. recommend 100 hours or more of intensive multidisciplinary rehabilitation including
cognitive behavioural interventions to improve functionality [21]. The CPP programme
studied in this thesis follows this recommendation in a ‘pressure-cooker’ structure. This
‘pressure-cooker’ structure might moderate the dysfunctional behavioural cognitions.
Patients with longstanding CLBP (mean 12 years, SD 11) benefit from this programme
(Chapter 2-3), but the influence of duration and intensity of the programme as moderating
factors remains elusive and needs to be further explored.
b) Motivation of participants to change behaviour. Although motivation is a selection criterion
for the programme, we neither assessed this factor in a clearly valid and reproducible
way at pre-treatment nor assessed it systematically over time. As ‘motivation’ is viewed
as a state that is amenable to change rather than a trait that is constant [22], it is possible
that those patients who were unsuccessful after having followed this programme were
actually not ready or motivated to change their pain-related behaviour. Motivation or
readiness to change pain-related behaviour is important for treatment compliance; it
plays an important role in accomplishing and achieving treatment goals and it positively
influences quality of life and may predict healthcare costs [23,24], completion of a treatment
programme [25], and treatment outcome [23,26,27]. The pain Readiness to Change (RtC)
model is used for conceptualising the process of adopting a self-management approach to
chronic pain [22]. According to the RtC model, individuals vary in their degree of readiness
to adopt a self-management approach. In Chapter 2 it is shown that behavioural change
is possible and that participants adopt self-management strategies to cope with back
pain complaints. The Multidimensional Pain Readiness to Change Questionnaire (MPRCQ)
[28,29] is designed to measure RtC related to specific components of self-management
targeted in multidisciplinary treatment programmes [30], completion of treatment, and
to predict treatment outcomes [29]. However, a recent study shows that, in patients with
CLBP at pre-treatment, coping behaviours instead of readiness to engage those behaviours
are associated with pain-related functioning [31]. Further research is needed to assess this
indicator in a clearly valid and reproducible way and to evaluate its contribution to the
outcome over time.
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c)Improvement of dysfunctional cognitive behavioural factors. It has been suggested that
improvement of such factors as catastrophising cognitions (i.e. exaggeration of the
threat value of pain sensations) and fear of movement behaviour might contribute to the
development of CLBP [32], to persistence of CLBP [33,34], and jeopardize successful treatment
outcomes [12,35-38]. This phenomenon is described in the fear avoidance model (FAM) [32].
The model postulates a causal relationship between pain catastrophising (a sign of serious
injury or pathology [39]), fear of movement, disability, and experienced pain severity [32,39].
Some studies have concluded that the impact of these dysfunctional cognitive behavioural
factors on outcome is diminished [40,41] or is even absent [42], which is consistent with
the results presented in Chapter 4. These findings corroborate the suggestion that the
sequence and relationships between pain catastrophising, fear of movement, and disability
postulated in the FAM maybe different for the development of CLBP than for the recovery of
disability as a result of an intervention [43]. The CPP programme has a beneficial impact on
cognitive behavioural variables [44], but a closer exploration of these cognitive behavioural
factors and their impact on functional ability is needed.
12
Methodological considerations
The studies presented in Chapter 2 and 3 followed an observational study design. To enhance
the internal validity of the studies, several precautions in the study methodology were taken
to minimise the potential influence of confounding on the outcomes. In evidence-based
medicine the randomised controlled trial (RCT) is regarded as the gold standard to secure
the internal validity of the study, because only the RCT is thought to resemble a true, pure
experiment from which causal inference can be concluded. However, in the last decade the
value of the RCT has been questioned for decisions about the use of interventions due to
drawbacks of the design and available evidence from RCTs [45]. In certain situations, as in an
RCT, ‘experimentation’ may be unnecessary, inappropriate, impossible, or inadequate [46].
Some of these are relevant in both surgical and conservative treatments. For example, an RCT
may be inappropriate because of the random allocation and blinding procedures used. When
the clinician and patient agreed upon the treatment, the clinician or patient (or both) have
their preferences. This arises when the effectiveness of the intervention depends on patients’
active participation in conservative programmes, which, in turn, depends on patients’ beliefs
and preferences. In (spine) surgery the results and effects also depend on surgical skills as well
as surgeons’ beliefs and preferences. As a consequence, the lack of any subsequent difference
in outcome between comparison groups may underestimate the benefits of the intervention.
To overcome these problems, alternatives have been suggested for which the key is to use all
available study designs, depending on the research question, and to perform every study with
scientific rigour [47]. One of the alternatives to the RCT is routine outcome monitoring with an
outcome registry, set up with an observational study design (Chapter 5). Recent spine-related
studies comparing RCTs with observational study designs show comparable results [48-52],
which suggests that observational study designs are complementary to RCTs.
The external validity of the study results presented in the Chapters 2-4 might be limited
because we studied the prospective cohort with carefully selected patients in a secondary
care setting. The conclusions of the studies performed in Chapter 2 to 4 are based on data
gathered through routine outcome monitoring rather than an RCT. The outcome monitoring
is performed through the web-based outcome registry of the CPP programme. The outcomes
registry follows the guidelines of observational studies [53] and the recommendations listed in
Summary and General discussion
253
Chapter 5. To further substantiate the effects found in Chapter 2, an historical controlled trial
was performed to compare the magnitude of treatment effects to those of other published
studies for similar populations. For this comparison an SMR was used, which is a rate ratio
to compare estimates of relative treatment improvement. We were limited to the external
references used to calculate these SMRs, but we found comparable effects on functional
outcome between the CPP programme and surgical interventions, and beneficial effects of
the CPP programme compared to less intensive treatment programmes (Chapter 2). The main
characteristics of the study populations were comparable, but unmeasured discrepancies are
still likely.
Implications for clinical practice and future research
Because of the issues discussed above regarding generalisability, implementation of
this CPP programme throughout the Netherlands could be challenging and the results
of implementation will need to be confirmed. Therefore, with implementation in other
healthcare settings, on-site continuous outcome monitoring is needed to demonstrate
continuous quality of care and to benchmark results. Cost-effectiveness studies are needed
to examine the impact and the value (i.e. outcomes relative to the costs [54]) of the delivered
care.
For a subgroup of participants in the CPP programme, i.e. those with previous lumbar spine
surgery, the efficacy and impact of this programme compared to spine surgery is not yet
clear. In the studies presented in Chapter 2-4, almost a third of the participants had previous
back surgery (i.e. failed back surgery syndrome [FBSS]). To study the cost-effectiveness in this
selected subgroup, a pragmatic RCT design is proposed with outcome monitoring over time.
Before random assignment, two recommendations are offered: a waitlist condition to wash
out previous treatment effects, and standardised management of expectations, because
expectation of the outcome is predictive of a successful surgical outcome (Chapter 10).
In Chapter 4, other moderating process factors were suggested which potentially predict
a successful outcome, such as a clear treatment rationale, a highly structured programme,
providing a pressure-cooker model programme, the intensity or dose of treatment, and a
skilful staff (e.g. the impact of the spine surgeon in the educational part of the programme).
These aspects should be further explored as potential working mechanisms of the programme.
Regarding the inclusion criteria, motivation or readiness to change behaviour and outcome
expectations might be relevant characteristics that need to be further studied.
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Summary and General discussion
Theme B: Outcomes assessment
Research questions
1. What is the current value and methodology of spine outcome registries in clinical practice?
2.Which patient-related outcome measures should be used for outcomes assessment for
degenerative lumbar spine disorders?
3. Which criterion can be used to define a successful outcome of interventions for patients
with degenerative lumbar spine disorders?
12
Summary of main findings
In Chapter 5 a systematic review is presented, in which 25 spine registries from around the world
were identified. No conclusions can be drawn on the value or the impact of these registries
on the quality of spine care, regardless of whether the intervention was non-surgical and/or
surgical. The 25 registries were heterogeneous. To improve the quality of evidence published
with registry data, we presented 14 recommendations. Two recognised shortcomings are
that different outcome measures are used and different core or standard outcome sets for
CLBP exist. However, going forward, consensus is needed in order to standardise outcomes
to be able to compare and benchmark outcomes for degenerative lumbar spine disorders. In
Chapter 6 a standard set of outcomes and influencing (risk) factors for use in clinical practice
and research is described. The set was compiled through a literature review and a worldwide
formal (modified Delphi) consensus procedure. One of the standard outcome instruments
agreed upon to assess functional ability is the Oswestry Disability Index version 2.1a (ODI) as
a patient-reported outcome measure (PROM). Because in the Netherlands several informal
translations exist, we translated this version of the ODI into the Dutch language according
to established guidelines and then evaluated the main methodological quality properties. In
Chapter 7 we describe this process and report that the Dutch version of the ODI proved to be
a valid and useful tool, with good measurement properties for the assessment of functional
ability amongst patients with CLBP. To indicate treatment success after spine surgery, a Patient
Acceptable Symptom State (PASS), equivalent to an absolute score on the ODI version 2.1a, was
estimated in Chapter 8. Using follow-up data from patients with degenerative lumbar spine
registered in the Eurospine Spine Tango Spine Surgery Registry, we estimated the PASS to be
22, irrespective of the time of follow-up. We recommend using this PASS as a threshold (ODI
≤22) to define treatment success alongside the commonly used change-score values.
Discussion
In order to improve consistency between registries, several recommendations were made
(Chapter 5). First, outcome registries should be methodologically well constructed, which
requires the use of observational study methods and the identification of best practices in
existing registries so that a standardised approach to registering and analysis can be achieved.
This effort will depend on international collaboration and benchmarking, and will contribute
to future value-based spine care.
Second, to improve the quality of spine care (i.e. outcomes of interventions; see General
Introduction, 3. Outcomes of interventions for CLBP), consistent improvement strategies
are needed (Chapter 5). For example, providing frequent continuous feedback (audit cycles)
of outcomes captured in registries raises awareness and is recommended to enhance
improvement of quality of care [55-59]. However, only two registry representatives reported
Summary and General discussion
255
doing monthly (or more frequent) audits (i.e. Texas Back Institute and the Dutch Spine Surgery
Registry; Chapter 5). However, these registries are new and started only recently, so no results
are currently available and therefore no firm conclusions can be drawn. In the past, data to
compare the performance of different healthcare providers were scarce. With Sweden as a
pioneer and the United States following with the National Surgical Quality Improvement
Program (NSQIP) [60], which was set up to continuously monitor and enhance the quality
of surgical care, clinical registries (audits) have been initiated at both regional and national
levels. This has led to a demonstrable improvement in clinical outcomes and smaller variation
between providers [9,58,61]. However, so far, we could not show this impact in spine care
(Chapter 5). The fact that registries can have an important effect on outcomes of interventions
(i.e. quality of healthcare) was reported in a study of 13 outcome registries in five countries in
other medical fields (e.g. hip arthroplasty, acute myocardial infarction and cataract surgery).
That study demonstrated that registries have great potential to improve health outcomes
and lower healthcare costs [58]. Studies describing the relationship between improvement
of outcomes and reduction of hospital costs by quality improvement programmes are
scarce [62], but a recent Dutch nationwide study presented evidence for simultaneous
quality improvement and cost reduction in colorectal surgery. The authors concluded
that participation in a nationwide quality improvement initiative with continuous quality
measurement and benchmarked feedback reveals opportunities for targeted improvements
[63].
A third recommendation presented in Chapter 5 is to use a standard set of patient-related
outcome measures with good measurement properties applied in a systematic approach,
such as presented in Chapter 6, to make future comparisons and benchmarking possible.
Currently, broad international comparisons are limited because there exists large variation
in the definitions of specific diseases, in included patient-related outcomes (PROMs and
clinical outcomes), and in associated influencing (risk) factors. In the literature, several
recommendations have previously been published for standardised outcome measurement in
low back pain research [64-67], but not specifically for use in the full cycle of care in everyday
clinical practice. An outcome set for use in everyday clinical practice and for continuous
improvement of the quality of spine care requires availability and validity in many languages,
capacity for case-mix adjustment to ensure that comparisons are made fairly, and should
focus on the outcomes that matter most to patients (Chapter 6). The proposed outcome set
in Chapter 6, which was achieved with formal international consensus, seems to fulfil these
requirements. Further research is needed to validate this set, including linguistic and crosscultural translation and adaptation. In order to improve outcomes of treatment and with
it the quality of spine care, research should focus on alignment of existing standard or core
outcome sets with the standard set presented in Chapter 6, which is also relevant for patients
and patient evaluation, and with the International Classification of Functioning, Disability,
and Health (ICF) [68].
Methodological considerations
When using outcome measures, clear criteria are required for the definition of treatment
success. This is a methodological challenge, as the interpretation of pre- and post-treatment
scores of PROMs has been a topic of research for more than two decades [69-71] and a
methodological concern remains on how best to estimate and interpret outcomes and
effects of interventions. Two different concepts to define treatment success are currently
commonly used and methodologically discussed: a) relative change values (i.e. relevant
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Summary and General discussion
change; improvement or deterioration) and b) achievement of an acceptable symptom state
by reaching absolute values.
a)Change measures are widely recommended and commonly used in spine research. These
relative measures are often referred to as a percentage baseline difference or a minimal
important change (MIC) value (i.e. minimal clinical important difference [MCID] or change
[MCIC]). A MIC value depicts a change, which is considered to be minimally important by
patients, clinicians, or relevant others [72]. Several drawbacks concerning the use of change
measures are acknowledged. For example, it is difficult to measure what is a clinically relevant
change to patients [73] because the definition of what is clinically important or relevant
or meaningful to patients is subjective. So far, there is no agreement on what constitutes
operational definitions of ‘important’ and ‘meaningful’ as applied to clinical changes [74].
Another drawback is that the achievement of change scores is highly dependent on baseline
values [75-77]. Furthermore, to determine the MIC value, global perceived effect (GPE) or
recovery (GPR) scales are used as the anchor (i.e. external reference). The GPE scale asks
the patient to rate, on a numerical Likert scale, how much their condition has improved or
deteriorated since some predefined time point. Some validity concerns are acknowledged
and it might be unsuitable for use as an external reference because patients can have
difficulty recalling their previous status, and their estimates of transition are biased by their
current health status [78]. Finally, a change value does not indicate whether the patient is
satisfied with the current state. Therefore, research into the concept of reaching absolute
values is needed. An example of such an absolute measure is the achievement of an absolute
score equivalent to a PASS.
12
b)The PASS as an absolute value or threshold might be a more stringent and adequate
measure to indicate treatment success. A PASS might be more important to patients than
change values, as it probably reflects the ultimate goal of a treatment from the patient’s
perspective: ‘It’s good to feel better but it’s better to feel good.’ [79,80]. It is a measure
related to the current state of the patient and it overcomes the baseline dependency as
encountered for change measures. The rationale for us to use a strict absolute threshold was
that patients with CLBP presenting in secondary or tertiary spine care are severely disabled.
When patients with such a high ODI-value at pre-treatment assessment improve and
reach a recommended change value of 10 points [81] or 30% change [81,82], they could be
classified as ‘successful’ whilst in fact they are still (severely) disabled. In treatments where
recovery from disability is a goal, a more stringent and absolute cut-off value, comparable
to ODI values seen in ‘normal’ healthy populations, should be a measure of treatment
success. The score associated with achieving PASS could be considered as a cut-off point for
determining whether patients are ‘responders’ after spine surgery and this threshold could
also be considered as a clinical treatment target. In this respect, treatment success would
be defined as the value beyond which patients can consider themselves well [83,84] or good
[80], an approach that is frequently used in the field of rheumatology [85]. In Chapter 8, we
determined the PASS for the ODI to be 22 (out of 100) and used an anchor-based approach.
As the external reference (anchor) the symptom-specific well-being (SSWB) Likert scale of
the Core Outcome Measures Index (COMI) was used: ‘If you had to spend the rest of your life
with the symptoms you have now, how would you feel about it?’ [86,87] (i.e. current status,
instead of asking patients). With this approach, potential recall bias is avoided as patients
are asked about their current status instead of how much their condition has changed since
some predefined time point.
Summary and General discussion
257
Implications for clinical practice and further research
Spine outcome registries can be used for continuous outcome monitoring. These registries
might be useful in post-marketing surveillance for both innovative surgical and non-surgical
treatments, after clinical introduction to the market, for monitoring the quality of care
delivered to improve treatment outcomes, for benchmarking, and for research purposes (e.g.
comparative effectiveness research). Moreover, comparing results of a strict multi-centre RCT
with ‘real-life’ outcome data from routine practice can be possible if the RCT is performed
within the framework of the registry, using the same questionnaires. This approach could
contribute to a better understanding of the effect, both efficacy and effectiveness, of (new)
interventions, and the external validity of the RCT can then be assessed.
A further recommendation proposed in Chapter 5, to improve the methodology of outcome
registries, is based on the finding that various analytical approaches have been used to explain
any possible differences in outcomes between spine practices. To prevent selection bias [88]
and to explain real differences in outcomes between institutions, multivariate approaches
with adjustment for covariates (i.e. corrections for differences in characteristics of patients
treated in hospitals; ‘case-mix adjustments’) and correction for chance variation (reliability
adjustments) are needed [89-92]. Owing to the fact that neither the aetiology (and thus the
underlying mechanisms) nor the set of case-mix indicators of CLBP is known, any comparison
of outcomes between institutions is a challenge. Advanced statistical techniques such as
multilevel random-effects regression models are recommended, as these models apportion
some of the variation between hospitals as being due to just chance [93,94], and need to be
further explored for future use in multicentre studies comparing treatment outcomes in CLBP
patients.
In the treatment of CLBP, an important outcome domain is functional ability. In the absence
of objective measures and, more importantly, to incorporate patient experience, PROMs are
used. To improve objectivity, measures of body function, such as mobility and muscle strength,
have been used, although the correlation between these measures and the level of activity in
daily life is very weak [95,96]. Promising preliminary results were obtained in studies involving
continuous measurement of patients wearing activity sensors whilst performing activities of
daily living [97-99]. Future research could quantify daily functioning by continuous activity
monitoring and explore its use in evaluating treatments for CLBP as a complement to the
commonly used PROMs.
To be able to define a successful outcome of an intervention from the patient’s perspective,
further research is warranted to determine which method is beneficial. Using PASS to define
treatment success, as equivalent to a ‘normal’ healthy symptom state seems promising for
evaluating spine surgery for lumbar spine disorders. We think the ‘ODI ≤22’ threshold might
be valuable for use in conservative treatments as well, but this needs to be further explored.
The concept of PASS gets closest to the patient’s perspective, approaching ‘It’s good to feel
better but it’s better to feel good.’ [79,80]. The PASS threshold is still a determination made by
the clinician or researcher rather than what the patient considers to be satisfactory, whereas
in evaluating treatment outcomes it is important to recognise the patient’s view as well.
Anchor-based methods do not account for the risks and costs of treatment, and rarely define
effects of intervention in terms of the difference in outcome with and without intervention.
The Smallest Worthwhile Effect (SWE) is a concept that uses a benefit−harm trade-off
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Summary and General discussion
method to determine the smallest effect that justifies the costs, risks and inconveniences
of an intervention [100-102]. The SWE is defined as an important change whilst considering
the burden of the intervention and focusses on whether it is worthwhile for the patient [100].
This novel method seems promising and needs to be further explored as it allows patients to
weigh the benefits of treatment against the risks, costs, and inconveniences of treatment; and
potentially provides estimates that are based on an intervention versus control comparison.
Another research area is the evolution of outcomes assessment with PROMs. A myriad of PROMs
exist that measure functional ability in patients with CLBP [103]. Even when the standard or
core outcome sets are aligned, multiple valid PROMs covering the different outcome domains
are still needed for evaluating spine treatments. It is essential to explore whether it is valuable
to combine PROMs into one outcome measure. A promising new approach in this area is the
Patient Reported Outcomes Measurement Information System (PROMIS NIH). PROMIS is a
system of reliable and precise measures of patient-reported health status for physical, mental
and social well-being [104]. PROMIS scales, once validated for a specific patient group, may
be calibrated and built into computer adaptive tests (CATs). A CAT integrates the advantage
of measurement theory and the power of computer technology to administer a PROM that
selects questions on the basis of a patient's response to previously administered questions
or other prior information [104]. Highly informative questions are selected and scores are
estimated that represent a person’s level in a domain (e.g. physical functioning, quality of life,
and pain) with the minimal number of questions without a loss in measurement precision
[104,105]. It will be interesting to explore whether these tailored and individualised CATs are
feasible and valid for use in future studies evaluating treatment outcomes of CLBP.
12
Summary and General discussion
259
Theme C: Prediction of outcomes
Research question
1. Is it possible to develop a triage tool for CLBP, which enables valid and reliable
identification of patient profiles that supports triage of the patients to a spine surgeon or
to non-surgical specialists?
Summary of main findings
Chapter 9 describes the development of a decision tool for secondary or tertiary spine
care specialists to decide which patients with CLBP should be seen by a spine surgeon or
by non-surgical medical specialists. Based on a literature review, consensus was reached
to include 47 indicators. A first version of the decision tool was developed, consisting of a
web-based screening questionnaire, systematic outcomes assessment, and a provisional
decision algorithm. In Chapter 10, ten patient-reported factors were found to be predictive
of referral to spinal surgery amongst CLBP patients (i.e. female gender, previous back surgery,
high leg pain intensity, somatisation, positive treatment expectations, being obese, having
comorbidities, pain in the thoracic spine, reduced walking distance, and consultation
location). The explained variance of the model was low (6%), which means that the model
could only partly predict spinal surgery referral amongst CLBP patients. A longitudinal study
is presented in Chapter 11, in which different patient profiles are identified for patient triage,
based on pre-treatment patient-reported characteristics and one-year follow-up outcomes.
Different pre-consultation profiles were determined that could predict ‘response’ and ‘nonresponse’ to spine surgery and to a CPP programme at follow-up. In general, the performances
of all models were acceptable; in particular, the ‘non-response’ model to elective lumbar spine
surgery performed remarkably well (R2 39%; c-index 0.83).
Discussion
Currently, a valid pre-treatment classification is lacking that accurately predicts a consistent
beneficial outcome after lumbar spine surgery and non-surgical treatments [106,107]. To our
knowledge, we present the first internally valid classification: a ‘proof-of-principle’ version of
the Nijmegen Decision Tool for Chronic Low Back Pain (NDT-CLBP), developed for secondary
care (Chapter 9-11). The current proof-of-principle tool consists of a comprehensive screening
questionnaire, systematic outcome monitoring (Chapter 9), and prognostic patient-reported
profiles related to treatment outcome (Chapter 11). The ultimate purpose of our research
programme is to reliably identify, in two phases, patients who would most likely benefit from
certain interventions. The first phase is aimed at identifying prognostic patient-reported
profiles to enhance timely patient triage to a spine surgeon or a non-surgical specialist for
consultation, as studied in Chapter 11. In the second phase, based on further diagnostics
(e.g. imaging), the profiles will be refined to include both the indicators from the first phase
and those from the diagnostic phase, to reliably refer the patient to the most appropriate
treatment. This second phase is planned and part of future research, but is beyond the scope
of this thesis.
International guidelines [14,15] recommend using the clinical flag approach [108] for clinical
decision-making in CLBP. A diagnostic triage based on ‘red flag’ signs is recommended
[14,15,109] as they are thought to be associated with a high risk of serious underlying disorders,
such as infection, inflammatory disease, cancer or fracture [108,110] or nerve root disease [111].
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Summary and General discussion
The presence of a red flag alerts clinicians to the need for further examination and specific
management [110,112,113]. Thus, we chose the red flag approach as a starting point for the
preliminary version of the decision algorithm, based on multidisciplinary consensus (Chapter
9). In Chapter 11 we report that most of the patients with CLBP (92%) show at least one positive
red flag but do not have a serious underlying condition. Taking the guideline recommendations
literally could cause harm (e.g. unnecessary diagnostics, unnecessary exposure to radiation,
unnecessary treatments, including surgery [114]), and these recommendations should
be reconsidered. To evaluate indicators predicting treatment outcome, in Chapter 11 we
determined different pre-treatment patient-reported profiles. The combination of indicators
determined in a profile is used to predict the individual probability of treatment outcome.
Owing to the high number of potential predictive indicators and the limited number of events
(events per variable [EPV]), we were not able to include interaction terms (e.g. combination of
red flags with yellow flags [e.g. somatisation or distress]). More detailed analyses including
these interaction terms are planned when more new patients are enrolled. Moreover, we
expect that combinations of red flags and clinical features, determined in the diagnostic
phase, might be more informative to assist in clinical decision-making [112,113,115]. This needs
to be further explored in the second phase of the NDT-CLBP when patient profiles for decision
to treatment, rather than triage alone, are to be analysed and built.
12
Methodological considerations
The patient-reported profiles determined in Chapter 10 and 11 were studied and reported in
line with the recommendations of the ‘prognosis research strategy’ (PROGRESS) [116] and the
‘transparent of a multivariable prediction model for individual prognosis or diagnosis’ (TRIPOD)
[117]. The patient-reported profiles are based on prognostic models. The establishment of
such profiles in clinical practice requires three distinct phases [118]: 1) Development (i.e.
identification of important predictive indicators from an observational study); 2) Validation
(i.e. testing of the profile’s predictive performance in new patients to determine whether
it remains reliable and stable); and 3) Impact analysis on daily practice (i.e. assessment of
the usefulness of the profile in the clinical setting to identify whether the validated profile
is likely to have meaningful, beneficial consequences). Such benefits may include more
accurate clinical decision-making in terms of selection and prioritisation of patients requiring
intervention, improved patient outcomes, and reduced costs of care [107,119-121]. Adams et al.
added an important fourth phase: Implementation (i.e. widespread acceptance and adoption
of the profile in clinical practice) [120].
In the studies of Chapter 10 and 11, the models were developed and internally validated to
correct for over-fit and optimism of performance measures [119,121-123]. In Chapter 10 we
identified ten prognostic patient-reported indicators for referral to lumbar spine surgery.
These indicators are not externally validated yet, but they are known as common predictive
indicators for surgical outcome, as previous studies have identified them, too (e.g. [124-126]).
This (preliminary) result gave us the confidence and arguments to further explore and examine
the patient-reported profiles longitudinally, based on treatment outcomes (Chapter 11). Due
to the observational study design used in Chapter 11, confounding by indication might be
present. Confounding by indication is where allocation to treatment is subject to a black box
of an unrecognised or unmeasured process associated with those who are treated, which is
guided by the experience and preferences of clinicians who use their expert judgment to decide
whether to treat a patient [127]. Concealed randomisation has been suggested to interfere in
Summary and General discussion
261
the relationship of prognosis and prescription [128]. Due to patient and clinician preferences,
and as lumbar spine surgery and CPP programmes are regarded as mutually exclusive,
randomisation is not feasible. We therefore described the source population and both the
cohorts and performed subgroup analyses to discover patterns and the patient profiles. As
mentioned above, owing to the relatively high amount of potential predictive variables and
relatively few events, expressed in EPV, we were not able to introduce interaction terms. As
such, we cannot rule out that patients might actually fit into both profiles, e.g. patients who
responded well to spine surgery might have responded well in the CPP programme as well.
However, one should bear in mind that the patient profiles are used for decision-making in
patient triage to a surgical or non-surgical specialist instead of the actual treatment. Future
studies are needed to validate the prognostic profiles using interaction terms for type of
treatment, and to further substantiate the decision process.
Implications for clinical practice and further research
Before widespread implementation and use of the patient profiles for triage to a surgical
or non-surgical specialist, as determined in Chapter 11, the underlying prognostic models
need to be further validated in new patients and in other, similar secondary spine practices,
and impact studies exploring the cost-effectiveness and the clinical usefulness are needed.
Including more patients with follow-up outcomes would allow studying interaction effects
between combinations of potential prognostic indicators and interaction effects between
types of treatment, which could be used to further refine the prognostic profiles. In the study
of Chapter 11, we analysed and described patient-reported profiles for elective lumbar spine
surgery and multidisciplinary bio-psychosocial treatment (i.e. CPP programme). Further
research is planned to explore patient profiles for other treatments, e.g. invasive pain
management or ‘no treatment’ (i.e. counselling and physical therapy in primary care), to
explore whether patients with features of axial spondylarthropathy could be determined by
their profile for early referral to rheumatologists for further diagnostics and treatment, and to
conduct a pilot study to determine whether the triage tool is feasible for use in primary care.
To develop the patient profiles (Chapter 11), we examined associations between potential
prognostic indicators and one outcome domain: functional ability. Strict evidence-based
absolute thresholds were used to define the outcome. As yet, no consensus exists on how
to define the outcome and which measure, relative or absolute change, to use to define
success or failure. To be able to define ‘response’ and ‘non-response’ after treatment for
CLBP, clear evidence-based and expert consensus-based criteria, including the measures
that operationalise these definitions, are needed for ‘responder analysis’ to make future
comparisons in both research and clinical practice possible. To define these criteria a research
approach comparable with the Osteoarthritis Research Society International (OARSI) set of
responder criteria for osteoarthritis [129] could be used.
The triage profiles of the NDT-CLBP belong to the first phase of the decision-making process
for a certain treatment. The next, second, diagnostic phase contributes to the final decision
between clinician and patient as to which treatment is most appropriate. Future research
should examine whether (combinations of) biomedical and psychosocial indicators that were
not included in Chapter 11 should be incorporated into the models, to extend and further
refine the different patient profiles. For this, relevant data of the diagnostic phase (e.g. specific
diagnosis [e.g. spondylolisthesis spinal stenosis], physical characteristics) should be added to
12
262
Summary and General discussion
the currently developed (patient-reported) triage tool. Growing interest exists to determine
clinical phenotypes. Phenotypes refer to observable traits of an individual organism [130],
consisting of biomedical and psychosocial factors. Based on novel techniques, preliminary
evidence suggests that radiographic characteristics (Modic changes), biomarkers, and genetic
profiles, might possibly explain CLBP bio-medically [131]. In line with the recommendation of
Samartzis et al. [131], a global consortium (i.e. AO Personalized Spine Care consortium) has been
set up, consisting of a multidisciplinary group of spine and pain specialists and researchers,
to further refine the understanding of CLBP and to further study both the decision tool for
patient triage and for treatment to enhance stratified and personalised spine care.
Towards a paradigm shift in CLBP, away from stepped care in secondary spine care?
Studying different prognostic patient profiles based on the NDT-CLBP might contribute to
further refine and support future treatment decisions in CLBP. CLBP is multifactorial in nature
and the underlying mechanisms remain largely unknown. As yet aetiological studies have
contributed little to diagnostics in CLBP and corresponding treatments that are ultimately
expected to lead to successful treatment outcomes. Although future studies may reveal
some aetiological factors, we speculate that a shift from classic causal reasoning towards
reasoning in prognostic patient profiles may form an alternative paradigm. Patient profiles
may contribute meaningfully to the optimisation of decision-making in the treatment of
CLBP, even without full knowledge of the aetiology of CLBP.
12
If the developed patient profiles are externally validated, the impact is shown and if they
are proven to be of value in decision making (i.e. they can predict which patient will benefit
from which treatment, even without a well-defined cause), then the recommendations in the
(inter-) national guidelines will need to be reconsidered. In the National Institute for Health
and Care Excellence (NICE) guideline [15] as well as in a recently released draft version of the
Dutch national guideline for instrumented lumbar spine surgery [132], a stepped care approach
is suggested: before lumbar spine surgery is considered, a CPP programme is indicated
(consensus; low quality evidence). Although further research is needed to substantiate and
validate the patient profiles developed in Chapter 11, the different profiles suggest that
different subgroups of patients could be identified in the heterogeneous CLBP population that
would benefit from treatments. This would mean — instead of the recommendation made in
the guidelines for a serial (stepped care) approach, yielding spine surgery as an ‘end-of-line’
treatment — that a more parallel approach might be feasible. For example, some patients
may be identified who will benefit from surgery, without having undergone a full nonoperative cycle of care, and some patients should never undergo surgery, despite failing all
non-operative treatments. Then, a remarkable paradigm shift in clinical reasoning of medical
specialists in spine care would be required.
Summary and General discussion
263
Concluding remarks
The CLBP population is heterogeneous and the condition lacks diagnostic clarity. The failure
to differentiate between underlying causes is one of the reasons why a plethora of invasive
and non-invasive interventions exist for the same symptom. Despite decades of research and
improved quality of clinical trials, the reality is that the treatments offered to patients have
led to inconsistent results. Based on the research in this thesis, it seems that:
1 The introduced CPP programme is effective for a selected subgroup of patients with CLBP.
2Using strict selection criteria for patient entrance to interventions, clear outcome
definitions and continuous outcome monitoring of treatments using an outcome registry
can contribute to improving the quality of delivered spine care.
3For the definition of treatment success in secondary spine care, the absolute ODI-22
threshold is recommended for use alongside the commonly used change measures.
4Different subgroups within the heterogeneous CLBP population are evident, based
on different prognostic patient-reported profiles and response or non-response after
treatments in secondary care. To our knowledge the developed prognostic patient-reported
profiles of the NDT-CLBP are the first that seem to recognise these more homogeneous
subgroups.
5 The non-response prognostic patient-reported profile for elective lumbar spine surgery
performed remarkably well. This suggests that patients with a high probability for
persisting severe disability after surgical intervention could be identified even before actual
consultation, so that unnecessary and unhelpful surgery could be avoided.
6 In the future, when these patient profiles have been shown to remain stable after validation
in new patients and in other secondary spine practices, they may be used to enhance timely
patient triage to the right surgical or non-surgical specialist and contribute to the decisionmaking between clinician and patient.
Subgrouping CLBP based on treatment outcomes still needs to be a research priority, and
further high-quality research is needed in the screening and diagnostics of CLBP. Exploring the
validity and the impact of the patient profiles presented in this thesis is required before firm
conclusions can be drawn regarding the NDT-CLBP. Including the diagnostics of the second
phase of the NDT-CLBP in the profiles of the decision tool might contribute to improvement
of treatment outcomes. These profiles could lead to a paradigm shift in clinical reasoning and
decision-making and ultimately to a more efficient use of healthcare resources and reduction
of the tremendous worldwide burden of low back pain.
12
264
Summary and General discussion
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Summary and General discussion
Key points thesis
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Key points thesis
What is already known on this topic
Theme A. Introduction of a combined physical and psychological (CPP) programme
- Worldwide, chronic low back pain (CLBP) is responsible for the greatest disease burden for
society in terms of years lived in disability.
- CLBP is not a diagnosis, but a symptom referring to the location of the problem and the
duration of the complaints.
- Although the exact aetiology is unknown it is recommended to identify subgroups
benefitting different interventions, as it is unlikely that one treatment benefits all.
- Multidisciplinary conservative treatment programmes provide moderate, short-lived
effects.
Theme B. Outcomes assessment
- A patient outcome registry is an organized system that uses observational study methods.
- A patient outcome registry can be used to describe care patterns, including
appropriateness of care and disparities in the delivery of care.
- Worldwide several spine outcome registries have been initiated on a regional or national
level, tracking tens of thousands of patients.
- It is suggested that outcome registries leads to demonstrable improvement in clinical
outcomes and smaller variation between providers
- Participation in nationwide quality improvement initiatives including continuous quality
monitoring and benchmarked feedback reveals opportunities for targeted improvements.
- Different core outcome sets for CLBP exist to standardize outcomes in research.
- An outcome set for use in every day clinical practice and to use for continuous
improvement of the quality of spine care is still lacking.
- Functional ability is one of the recognised outcome domains of treatments for
degenerative lumbar spine disorders.
- The Oswestry Disability Index (ODI) is a widely used patient-reported outcome measure
(PROM) and internationally recommended to evaluate functional ability in these patients.
- The interpretation of pre- and post-treatment scores of PROMs has been a topic of
research for more than two decades and is still subject to discussion.
- To evaluate the course and effect of interventions in patients with degenerative lumbar
spine disorders different measures of improvement in functional ability are used.
Key points thesis
What this thesis adds
Theme A. Introduction of a combined physical and psychological (CPP) programme
- The intensive multidisciplinary CPP programme is beneficial in improving and maintaining
patient relevant outcomes and reducing healthcare consumption for a carefully selected
group of patients with CLBP (Chapter 2-3).
- The study results are comparable with previously published results of spinal surgery
and seem to be even better than results from less intensive rehabilitation programmes
(Chapter 2).
- Patients who are employed and who are mild to moderately disabled at the start of a CPP
programme are most likely to benefit from this programme (Chapter 4).
Theme B. Outcomes assessment
- The current impact and value of spine registries on quality of care is not yet established,
regardless as to whether the intervention was non-surgical or surgical (Chapter 5).
- Methodological recommendations are presented to make future evaluations and
comparisons possible (Chapter 5). The recommendations comprise the organisation of
outcome registries, the methods and patient-related outcomes and influencing (risk)
factors used, and the analysis and reporting of results.
- Application of these recommendations could lead to registries showing trends in
effectiveness of interventions, monitoring the quality of spine care given, and ultimately
improving the value of the care given to patients with degenerative spinal disorders
(Chapter 5).
- An international multidisciplinary consensus-based standard set of well-validated
outcomes for CLBP was defined and is recommended for use in both clinical practice and
research (Chapter 6).
- These outcome measures are structured around the span of a patient’s entire cycle of care,
and allow for risk adjustment (Chapter 6).
- When implemented, this set facilitates meaningful comparisons of interventions and
between providers, ultimately providing a continuous feedback loop, enabling on-going
improvements in quality of care (Chapter 6).
- The Dutch ODI version 2.1a is a valid, reliable and useful tool with for the assessment of
functional ability and disability among Dutch patients with CLBP (Chapter 7).
- The use of the Dutch ODI is recommended for future research in patients with
degenerative lumbar spine disorders and for evaluating outcomes of secondary and
tertiary spine interventions in the Netherlands (Chapter 7).
- Absolute measures as a criterion of treatment success is recommended, because it is
independent of the pre-treatment value and it represents the patients’ perspective: ‘It’s
good to feel better but it’s better to feel good.’ (Chapter 8).
- An ODI score ≤22 indicates the achievement of a patient acceptable symptom state (PASS),
which also reflects a ‘normal’ healthy condition (Chapter 4 and 8).
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Key points thesis
What is already known on this topic
Continued from page 272
- To define treatment success two concepts are current: (1) relative change values and (2) the
achievement of an acceptable symptom state by reaching an absolute value.
- International consensus exists to use a relative change in ODI score to indicate relevant
improvement in functional ability in CLBP: (1) 30% reduction from baseline ODI score, or (2)
a 10 or 15 points reduction from baseline ODI score.
- Several drawbacks of change measures are acknowledged. For instance, the definition of
clinical/relevant importance or meaningful change is still arbitrary and change scores are
baseline dependent.
Theme C. Prediction of outcomes
- CLBP is a heterogeneous condition with a lack of diagnostic clarity and is one of the most
common complaints for which patients seek consultation in primary care
- It is estimated that 60-80% of the patients experience persistence of CLBP complaints
after a year and most of them consult secondary care spine specialists for their problems.
- In secondary care a large practice variation exists, as currently many of these healthcare
providers cannot reliably identify which CLBP patients will benefit most from a (non-)
surgical intervention.
- Lumbar spine surgeries represent a sizeable proportion of the total cost of back pain, but
spine surgery rates vary extensively across, and even within, countries.
- A lack of professional consensus among Dutch spine surgeons exists in decision-making
for spinal fusion and it is indicated that patient-related factors were not consistently
incorporated in the surgeons’ treatment strategy.
- To improve treatment outcomes in degenerative lumbar spine disorders it is recommended
to develop a classification system to direct both surgical and non-surgical interventions,
based on biomedical and psychosocial indicators and on treatment outcomes.
- Different non-surgical decision tools exist; none of them are aimed for patient triage.
Key points thesis
What this thesis adds
Continued from page 273
- The ODI-PASS is recommended for use alongside the commonly used change-score
measures in patients with degenerative lumbar spine disorders to evaluate the recovery
and the course of interventions, irrespective of the invasiveness (Chapter 8).
- On an individual level the threshold could be used to indicate whether or not a patient
with a degenerative lumbar spine disorder is a ‘responder’ after elective surgery (Chapter 8).
C. Prediction of outcomes
- The Nijmegen Decision Tool for Chronic Low Back Pain (NDT-CLBP) was developed using
scientific evidence and formal multidisciplinary consensus (Chapter 9) and is internally
validated to support patient triage to surgical and non-surgical spine specialists (Chapter 11).
- The online NDT-CLBP consists of: (1) a pre-treatment patient-based screening
questionnaire, based on biomedical and psychosocial patient-reported indicators; (2)
systematic outcome monitoring; (3) prognostic patient-reported profiles predicting
treatment outcomes of spine surgery and a multidisciplinary treatment programme
(Chapter 9 and 11).
- By means of pre-treatment patient-reported screening data derived from screening
questionnaire of the NDT-CLBP, several patient-reported indicators were identified that
are partly predictive of spinal surgery referral (e.g. previous surgery, leg pain intensity,
positive treatment expectations, comorbidities, reduced walking distance) (Chapter 10).
- Location of consultation was significantly associated with spinal surgery referral, even
after correcting for case-mix indicators, which suggests a practice variation and a lack of
consensus among spine surgeons (Chapter 10).
- The NDT-CLBP is a tool for (shared) decision-making and includes two phases: (1)
prognostic patient profiles, based on patient-reported characteristics predicting either
‘response’ or ‘non-response’ to treatment, to enhance timely patient triage to a spine
surgeon or a non-surgical specialist for consultation, and (2) based on further diagnostics
(e.g. imaging) and future research the profiles will be refined by including both the
indicators from the first phase as well as from the diagnostic phase, to reliably refer the
right patient to the right treatment (Chapter 11). A ‘proof-of-principle’ tool for phase 1 is
developed; phase 2 is planned, but is beyond the scope of this thesis.
- Although factors derived from the diagnostic phase (e.g. imaging) were not included,
treatment outcome was predicted to an acceptable and satisfactory degree, especially for
non-response to spinal surgery (Chapter 11).
- To our knowledge we are the first to identify prognostic patient profiles predicting whether
CLBP patients are a ‘responder’ or ‘non-responder’ to elective lumbar spine surgery or
multidisciplinary pain management programme that can be used for triaging CLBP
patients to the right secondary care specialist (Chapter 11).
- The next step is planned and consists of external validation of the prognostic patientreported profiles with new patients and using patient samples of other secondary spine
practices. This will be followed by an impact analysis of these patient profiles on decisionmaking, treatment outcomes, and costs.
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Key points thesis
Key points thesis
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Nederlandse samenvatting
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Nederlandse samenvatting
Achtergrond
Wereldwijd vormt lage rugpijn het grootste sociaal maatschappelijke gezondheidsprobleem
en wordt uitgedrukt in aantal jaren geleefd met functionele beperkingen. Dit gaat
gepaard met hoge kosten voor de maatschappij, onder meer als gevolg van werkverzuim,
arbeidsongeschiktheid en de hoge mate van zorggebruik. Chronische lage rugpijn (CLRP), lage
rugpijn die drie maanden of langer bestaat, is eigenlijk geen diagnose maar een symptoom
verwijzend naar de lokalisatie van het probleem en de duur van de klachten. Het blijkt één
van de meest voorkomende problemen te zijn waarvoor patiënten naar de huisarts of
fysiotherapeut gaan. De schatting is dat bij 60-80% van deze patiënten de klachten na een jaar
nog bestaan en de meesten consulteren dan medisch specialisten in de tweede lijn. De exacte
etiologie van CLRP is voor de grootste groep patiënten onbekend en daardoor is de diagnose
vaak ‘degeneratieve lage rug aandoening’ of ‘aspecifiek’. Doordat de etiologie onbekend is,
bestaat er een heel scala aan invasieve (bijvoorbeeld chirurgie, injecties) en conservatieve
behandelvormen (bijvoorbeeld fysiotherapie, rugschool, mono- of multidisciplinaire cognitieve
gedragstherapie, multidisciplinaire bio-psychosociaal pijnmanagement programma’s).
Ondanks decennia van wetenschappelijk onderzoek zijn de resultaten nog altijd inconsistent
en controversieel en laten chirurgische behandelopties en multidisciplinaire pijnmanagement
programma’s maar matige uitkomsten zien. Mede hierdoor bestaat grote praktijkvariatie
tussen zorgaanbieders en bestaat er onduidelijkheid over welke behandelingen voor wie
(kosten-)effectief zijn. Bovendien blijkt dat onder de Nederlandse wervelkolomchirurgen
geen consensus bestaat ten aanzien van de besluitvorming voor welke patiënten met CLRP
chirurgie geschikt is en worden patiënt-gerelateerde uitkomsten niet consistent betrokken in
de zorgevaluatie en de behandelstrategie van de chirurg.
De opbouw van het proefschrift
In hoofdstuk 1 is de huidige stand van zaken van de wetenschap beschreven met betrekking
tot het onderwerp CLRP in relatie tot dit proefschrift. Dit proefschrift kent drie aparte maar
onderling gerelateerde thema’s. De studies (hoofdstuk 2-11) binnen deze thema’s volgen min
of meer chronologisch het onderzoeksprogramma.
In het eerste thema (Thema A) wordt een conservatief multidisciplinair en intensief fysiek
en psychologisch pijn management programma (Combined Physical and Psychological
programme; CPP programma) geëvalueerd en wordt duidelijk wie baat zou kunnen hebben
bij dit behandelprogramma. Dit twee weken durend intensieve programma is eind 2006
geïntroduceerd binnen de Sint Maartenskliniek en wordt exclusief aangeboden aan
patiënten met langdurig bestaande CLRP, waarbij eerdere conservatieve behandelingen
hebben gefaald en voor wie wervelkolomchirurgie geen optie is. Het programma wordt
onder de verantwoordelijkheid van de wervelkolomchirurgen aangeboden in een hotelsetting buiten de kliniek en bestaat uit: fysieke training, cognitief-gedragsmatige training
met ‘graded activity’ en ‘graded exposure’ (het stapsgewijs opvoeren van respectievelijk
activiteiten en blootstelling aan activiteiten die beperkt zijn) en educatie. Om het individueel
beloop te monitoren en om het programma op groepsniveau te kunnen evalueren, worden
alle deelnemers gestandaardiseerd en systematisch tot een jaar na het programma gevolgd
op relevante uitkomstindicatoren (routine uitkomsten monitoring). Dit wordt online in een
zogenaamde patiënten uitkomstenregister bijgehouden.
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Het tweede thema (Thema B) is gericht op de impact van wervelkolom-gerelateerde
uitkomstenregisters (zoals beschreven in thema A) op de kwaliteit van de geleverde zorg.
Daarnaast is de methodologie van uitkomstenmeting, die wordt gehanteerd bij de evaluatie
van de klinische praktijk en in het wetenschappelijk onderzoek bij patiënten met CLRP, nader
bestudeerd. Om de zorg te kunnen evalueren en zorgaanbieders onderling te vergelijken
dienen dezelfde uitkomstdomeinen middels dezelfde uitkomstmaten, die relevant zijn voor
de patiënt, te worden gemeten. Echter, zo’n standaard set ontbreekt. Een alom (h)erkend
uitkomsten domein is de mate van functioneren. Dit domein wordt vaak geoperationaliseerd
middels de Oswestry Disability Index (ODI [0-100]; 0= geen beperking in functioneren, 100=
bedlegerig), een conditie-specifiek patiënt-gerapporteerde uitkomstmaat (patient-reported
outcome measure, PROM), zo ook in dit proefschrift.
De eerste twee thema’s zijn een opmaat voor het derde thema (Thema C) dat gaat over
de ontwikkeling en onderbouwing van een klinische beslistool voor CLRP op basis van de
verzamelde gegevens in een uitkomstenregister. Het doel van deze tool is het verrichten van
een poliklinische triage van patiënten naar een tweede of derdelijns wervelkolomchirurg
óf een niet-chirurgisch medisch specialist. Het vormt een eerste aanzet om te voldoen aan
een lang bestaande internationale aanbeveling om een classificatiesysteem te ontwikkelen
dat beslissingsondersteunend is voor verwijzing naar chirurgische en niet-chirurgische
behandelvormen, dat is gebaseerd op biomedische en psychosociale indicatoren en op de
uitkomsten van de behandeling. Er bestaan wel verschillende beslissingsondersteunende
tools in de klinische praktijk, de meeste zijn echter bedoeld voor gebruik in de eerste lijn
gezondheidszorg en geen van deze tools is geschikt voor triage van patiënten naar de tweede
lijn.
Tot slot worden in hoofdstuk 12 de bevindingen bediscussieerd en is de betekenis ervan voor de
klinische praktijk en toekomstig research uiteengezet. Per thema hebben we overkoepelende
onderzoeksvraagstellingen geformuleerd die middels de resultaten van de verschillende
studies zijn beantwoord.
De bevindingen per thema
Thema A: Introductie van een gecombineerd fysiek en psychologisch behandelprogramma
voor CLRP
Onderzoeksvraagstellingen:
1.Kunnen bij patiënten met CLRP die het geïntroduceerde CPP behandelprogramma hebben
gevolgd, de behandeluitkomsten verbeteren en het zorggebruik verminderen?
2.Is het mogelijk om bij patiënten met CLRP een subgroep te identificeren die het meest baat
hebben van dit nieuw geïntroduceerde CPP behandelprogramma (prognose van succes),
zodat de toelatingscriteria geoptimaliseerd kunnen worden?
In de één en twee-jaar follow-up cohort studies, gepresenteerd in de hoofdstukken 2 en 3,
namen geselecteerde en gemotiveerde patiënten met lang bestaande CLRP deel aan het CPP
programma. Patiënten waren matig tot ernstig beperkt in functioneren en vergelijkbaar met
andere patiënten met lage rugpijn die behandeld worden in de tweede lijn. Eén jaar na het
volgen van het programma konden de patiënten beter omgaan met hun rugklachten, hun
dagelijks functioneren en kwaliteit van leven was relevant verbeterd en de meesten waren
weer aan het werk (hoofdstuk 2). Dezelfde groep patiënten werd twee jaar na deelname
nogmaals bevraagd. Het bleek dat de significante en relevante verbeteringen waren
Dutch summary | Nederlandse samenvatting
behouden, de meeste patiënten waren weer aan het werk en het bleek dat men substantieel
minder zorg en minder (zware) pijnmedicatie gebruikte (hoofdstuk 3). In hoofdstuk 4 zijn
indicatoren geïdentificeerd die een succesvolle behandeluitkomst kunnen voorspellen
(prognose voor succesvolle behandeling). Succesvolle behandeluitkomst was gedefinieerd
als een functionele score vergelijkbaar met scores gezien in de ‘normale’, gezonde populatie
(ODI ≤22). Patiënten die voor het programma aan het werk waren en die relatief weinig of
matig beperkt in functioneren zijn bij aanvang hebben het meeste baat bij het programma.
Er zijn hierbij geen interactie effecten gevonden tussen patiëntkarakteristieken en ondanks
bevindingen in de literatuur bleek tot onze verrassing dat psychische ‘distress’, de beleving
van negatieve emoties als somberheid en gespannenheid, niet voorspellend was voor een
succesvolle behandeluitkomst. Ook patiënten met een hoge mate van ervaren ‘distress’
bij aanvang van het programma, hebben baat bij dit programma. Het beperkte aantal
geïdentificeerde indicatoren is bruikbaar voor de klinische praktijk, omdat ze makkelijk te
herkennen zijn en ze kunnen eenvoudig bijdragen aan een snelle triage en toewijzing van
patiënten aan dit programma.
Omdat continue uitkomstenmeting een vast onderdeel in het CPP programma is, waren we
in de gelegenheid om de één jaar ‘pilot’ resultaten, gepresenteerd in hoofdstuk 2, verder te
onderbouwen met die van een groot cohort (848 patiënten). Deze recente studie liet zien
dat de patiënten vergelijkbaar goede resultaten behaalden als de initiële pilotgroep. De helft
verbeterde dusdanig dat hun functionele status vergelijkbaar was met die van de ‘normale’
gezonde populatie. Het korte, intensieve pijn management programma kan dus het leven
aanzienlijk veranderen van een selecte groep patiënten met lang bestaande CLRP (gemiddeld
12 jaar).
Thema B: Uitkomstenmeting
Onderzoeksvraagstellingen:
1.Wat is de huidige waarde van wervelkolom-gerelateerde uitkomstenregisters voor de
dagelijkse klinische praktijk en welke methodologie is gebruikt in deze registers?
2.Welke patiënt-gerelateerde uitkomstmaten dienen te worden gebruikt voor evaluatie van
de behandeling van patiënten met degeneratieve lage rug aandoeningen?
3.Welk criterium kan worden gebruikt om een succesvolle behandeluitkomst bij patiënten
met degeneratieve lage rug aandoeningen te definiëren?
We hebben een systematische literatuurstudie uitgevoerd naar wervelkolom-gerelateerde
uitkomstenregisters en een vragenlijst onder vertegenwoordigers van deze registers uitgezet.
Wereldwijd hebben we 25 wervelkolomregisters geïdentificeerd. Er konden geen conclusies
worden getrokken over de waarde dan wel de impact van deze registers op de kwaliteit
van geleverde zorg, ongeacht of de zorg chirurgisch of non-chirurgisch van aard was. De 25
registers waren zeer divers en heterogeen van aard in bijvoorbeeld de opzet, de geïncludeerde
doelgroepen en behandelvormen, de methodologie en analysetechnieken en de rapportage.
Om in de toekomst de kwaliteit van het wetenschappelijk bewijs gepubliceerd met
registerdata te verbeteren hebben we 14 aanbevelingen geformuleerd. Deze aanbevelingen
kunnen leiden tot wervelkolom-gerelateerde uitkomstenregisters waarmee met de data
trends, patronen, uitkomsten en daarmee de kwaliteit van de geleverde zorg kunnen worden
bestudeerd. In de toekomst kunnen deze uitkomstenregisters tevens een bijdrage leveren in
het oplossen van controverses die bestaan ten aanzien van de behandeling van degeneratieve
wervelkolomaandoeningen.
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De beperkingen in de registers die we hebben bestudeerd waren onder andere gerelateerd aan
het feit dat verschillende uitkomstmaten zijn gebruikt, maar ook dat verschillende standaard
uitkomstensets blijken te bestaan voor de evaluatie van behandeling van CLRP. Om in de
toekomst behandeluitkomsten onderling te kunnen vergelijken tussen artsen, instellingen of
zelfs tussen landen, is het noodzakelijk (inter-)nationaal eenduidige definities te hanteren en
dient consensus te bestaan ten aanzien van een gestandaardiseerde, systematische werkwijze.
In hoofdstuk 6 is een studie beschreven waarbij, in een werkgroep van professionals en
patiënten, wereldwijd formele consensus is verkregen over een standaard uitkomstenset die is
gebaseerd op uitkomstdomeinen die relevant zijn voor de patiënt, inclusief de beïnvloedende
(risico)factoren, de meetinstrumenten en de meetmomenten. Deze set is relatief eenvoudig
te implementeren in de klinische praktijk om de geleverde zorg te evalueren en is geschikt
voor gebruik in wetenschappelijk onderzoek. Het advies is deze set op te nemen in landelijke
uitkomstenregisters.
Eén van de standaard uitkomstdomeinen waarover consensus is bereikt is de ‘mate van
functioneren’. De ODI versie 2.1a is wereldwijd een veel gebruikte PROM om functioneren te
objectiveren. Omdat in Nederland verschillende vertaalde versies in omloop waren hebben
we deze versie conform internationale richtlijnen vertaald en hebben we de methodologische
kwaliteit ervan bestudeerd. In hoofdstuk 7 staat het vertaalproces beschreven en is de
conclusie dat deze Nederlandse versie van de ODI een valide en bruikbare maat is met goede
meeteigenschappen. Geadviseerd wordt deze versie van de conditie-specifieke PROM te
gebruiken in toekomstig wetenschappelijk onderzoek en in de evaluatie van zorg bij patiënten
met lage rugpijn. Deze officiële versie is tevens opgenomen en geïmplementeerd in de
onlangs gestarte nationale wervelkolomregister voor registratie van chirurgisch behandelde
patiënten (Dutch Spine Surgery Registry).
Internationaal bestaat consensus om een verandering in ODI-score te gebruiken om klinisch
relevante verbetering te meten. Opties hiervoor zijn: (1) 30% vermindering van de baseline
ODI-score, of (2) 10 of 15 punten vermindering ten opzichte van de baseline ODI-score. Echter,
er zijn verschillende beperkingen in het gebruik van veranderingsscores bekend, bijvoorbeeld
de definitie van wat een klinische relevante of betekenisvolle verandering is en het feit
dat veranderingsscores afhankelijk zijn van de baseline score. Een ander concept om een
succesvolle behandeling weer te geven is het behalen van een absolute drempelwaarde.
In een studie beschreven in hoofdstuk 8, hebben we de ODI-score bepaald, waarbij patiënten
aangaven dat ze tevreden zijn met de rug zoals die op dat moment is (zogenaamde ‘patient
acceptable symptom state’; PASS), als maat voor succes na chirurgie bij degeneratieve lage
rug aandoeningen. Voor deze studie hebben we baseline en follow-up data (één en twee jaar
na de operatie) gebruikt van chirurgisch behandelde patiënten die zijn geregistreerd in Spine
Tango, de Eurospine spine surgery registry. De drempelwaarde voor de PASS werd geschat op
ODI-score van 22, onafhankelijk van het follow-up meetmoment. Deze waarde blijkt overeen
te komen met de waarde gezien in de ‘normale’ gezonde populatie. Omdat de concepten van
PASS en veranderingsscores complementair aan elkaar zijn, is de aanbeveling deze PASS als
absolute drempelwaarde (ODI ≤22) te gebruiken naast de veel gebruikte veranderingsscores.
Beide maten dienen bij follow-up metingen gerapporteerd te worden en uitgedrukt in
proporties van patiënten die de waarde hebben behaald.
Dutch summary | Nederlandse samenvatting
Thema C: Voorspellen van uitkomsten
Onderzoeksvraagstellingen:
1.Is het mogelijk een triage (beslissingsondersteunende) tool te ontwikkelen, gebaseerd op
valide en betrouwbare patiënten profielen, dat de triage van patiënten met chronische
lage rugklachten naar een wervelkolomchirurg of een niet-chirurgisch medisch specialist
ondersteunt?
Om de behandeluitkomsten en daarmee de kwaliteit van geleverde zorg te verbeteren hebben
we een triage ondersteunende tool ontwikkeld; de Nijmegen Decision Tool for Chronic Low
Back Pain (NDT-CLBP). Het doel is dat middels deze tool patiënten op basis van hun profiel
vroegtijdig naar de juiste zorgprofessional (chirurg of niet-chirurgisch medisch specialist)
kunnen worden verwezen. De ontwikkeling hiervan staat in hoofdstuk 9 beschreven. Op
basis van een literatuuronderzoek is een formele Delphi consensus procedure uitgevoerd.
Uiteindelijk zijn 47 indicatoren geselecteerd die mogelijk de behandeluitkomst en/of
het persisteren van lage rugpijn voorspellen. Een eerste ‘proof-of-concept’ versie van de
NDT-CLBP is opgezet, bestaand uit een web-based screeningvragenlijst en systematische
uitkomstenmeting (PROMs en klinische uitkomsten) die zijn ingebouwd in een online
uitkomstenregister en een eerste beslissingsalgoritme is opgesteld. Om te verifiëren of we
met dit systeem op de goede weg zaten, hebben we eerste analyses uitgevoerd met data van
de screeningvragenlijst dat is ingevuld door 4,987 patiënten met CLRP die naar de chirurg
zijn verwezen en vervolgens al dan niet een wervelkolomoperatie hebben ondergaan. Die
studie staat beschreven in hoofdstuk 10. Het bleek dat tien patiënt-gerapporteerde factoren
voorspellend waren voor indicatie operatie, namelijk vrouwelijk geslacht, eerdere rugoperatie
gehad, pijn in de boven-rug, verminderde loopafstand, positieve verwachtingen ten aanzien
van de behandeluitkomst, obesitas, comorbiditeiten, en de locatie van het consult. Echter, de
mate dat het model de uitkomst, verwijzing naar operatie, voorspelde was relatief laag en
daarmee lijken andere niet gemeten factoren meer bepalend. Ondanks deze matige prestatie
lijkt het mogelijk met patiënt-gerapporteerde pre-consult gegevens het behandelbeloop te
voorspellen.
In een vervolgstudie, gepresenteerd in hoofdstuk 11, hebben we bestudeerd of
behandeluitkomsten, ‘respons’ (succes) en ‘non-respons’ (falen) een jaar na chirurgie en CPP
programma, kunnen worden voorspeld. Hierbij is gekeken welke (combinatie van) patiëntgerapporteerde indicatoren, bepaald in hoofdstuk 9 en uitgevraagd middels de web-based
screeningvragenlijst van de NDT-CLBP, voorspellend zijn. Vier verschillende prognostische
patiënt-gerapporteerde profielen zijn geïdentificeerd, twee voor elke behandeling. Belangrijke
indicatoren die de behandeluitkomst bepalen zijn de mate van functioneren (ODI-score)
voor aanvang van de behandeling, eerdere lage rugoperaties hebben gehad, psychosociaal
disfunctioneren, verwachtingen ten aanzien van behandeluitkomst en een zogenaamde
rode vlag voor leeftijd (klachten gestart <20 of >50 jaar). De vier modellen zijn stabiel voor de
CLRP-populatie in Sint Maartenskliniek. De mate waarin de modellen de uitkomst voorspellen
is matig en zullen diagnostische indicatoren, bijvoorbeeld röntgenfoto’s en via lichamelijk
onderzoek, mogelijk mede bepalend zijn. Het non-respons model voor chirurgie presteerde
opmerkelijk goed.
Tot slot zijn in hoofdstuk 12 de belangrijkste bevindingen van dit proefschrift samengevat
en bediscussieerd. Methodologische overwegingen zijn per thema besproken evenals de
mogelijke betekenis van de bevindingen voor de klinische praktijk en zijn suggesties gedaan
voor verder onderzoek.
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Concluderend
Gebaseerd op de studies gepresenteerd in dit proefschrift blijkt dat het geïntroduceerde
CPP pijnmanagement programma werkzaam en succesvol is voor een zorgvuldig
geselecteerde subgroep van patiënten met CLRP. Continue uitkomstenmonitoring middels
een uitkomstenregister, een heldere definitie van behandeluitkomst en het hanteren van
strikte selectiecriteria voor behandeling zijn elementen die bijdragen aan het verbeteren
van de kwaliteit van geleverde zorg aan patiënten met CLRP. Voor de definitie van succes
als behandeluitkomst is onze aanbeveling om de absolute ODI drempelwaarde van 22 (uit
100) te gebruiken naast de alom bekende veranderingsmaten. Uit dit proefschrift blijkt dat
verschillende subgroepen van patiënten met CLRP te onderscheiden te zijn met verschillende
prognostische profielen die gebaseerd zijn patiënt-gerapporteerde vragenlijsten. Deze
profielen kunnen behulpzaam zijn bij de besluitvorming tussen de patiënt en de clinicus ten
aanzien van het vervolgtraject (verdere diagnostiek en eventuele behandeling). Het blijkt dat
voor de populatie CLRP patiënten in de Sint Maartenskliniek het relatief goed is te voorspellen
welke patiënten zullen falen na een operatie. Potentieel kunnen dan in de toekomst onnodige
verwijzingen en rugoperaties worden voorkomen en kunnen deze patiënten vroegtijdig
worden verwezen naar een niet-chirurgisch medisch specialist. Het onderzoeken van de
externe validiteit (generaliseerbaarheid) en de maatschappelijke impact van de ontwikkelde
patiëntprofielen is een vereiste voordat harde conclusies kunnen worden getrokken ten
aanzien van de NDT-CLBP.
Wanneer daadwerkelijk middels patiëntprofielen verschillende subgroepen zijn te
onderscheiden, zonder dat de etiologie volledig bekend is, dan leidt dit in de toekomst
mogelijk tot een meer parallelle benadering in besluitvorming voor behandeling. Echter, dit
staat haaks op de in (inter-)nationale richtlijnen aanbevolen seriële ‘stepped care’ benadering.
Hierbij wordt wervelkolomchirurgie als een ‘last resort’ beschouwd en wordt dus pas
geadviseerd als niets anders werkt. Wanneer de patiëntprofielen robuust blijken te zijn dan
zouden de aanbevelingen hieromtrent in internationale en in de recent verschenen nationale
conceptrichtlijn voor geïnstrumenteerde spinaalchirurgie bij degeneratieve aandoeningen
van de thoracolumbale wervelkolom, in heroverweging genomen moeten worden. Dit zou een
belangrijke paradigma verschuiving in het klinische redeneren en in de besluitvorming voor
medische specialisten betekenen.
Het prognostisch classificeren van patiënten met CLRP op basis van behandeluitkomsten
verdient de hoogste prioriteit op de research agenda en studies van hoge methodologische
kwaliteit zijn noodzakelijk voor juiste screening en diagnostiek bij deze doelgroep. Dit draagt
substantieel bij aan toekomstige verbetering van behandeluitkomsten bij deze patiënten
en kan het leiden tot een meer efficiënte gezondheidszorg, waarbij de enorme sociaal
maatschappelijke last beduidend is verminderd.
Dutch summary / Nederlandse samenvatting
Acknowledgements |
Dankwoord
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Acknowledgements | Dankwoord
Dankwoord
Yes, het eindstation is in zicht . Alhoewel, in zekere zin is mijn promotie slechts een halteonderweg, omdat de projecten, die de basis vormen voor dit proefschrift, ook gewoon mijn
werk is. In ieder geval, tot dusver betekent de reis die tot dit proefschrift leidde, zoveel meer
voor mij dan de afzonderlijke artikelen die het bevat. In letterlijke zin betekent het treinreizen,
vooral naar Nijmegen en later ook onder andere naar Amsterdam en figuurlijk geeft het mijn
ontwikkeling aan in een tweede carrière; die van de research en de klinische epidemiologie.
Met de verdediging van dit proefschrift rond ik een absoluut enerverende en inspirerende
tocht af, waarbij het laatste jaar vooral in het teken stond van het afronden van ‘het boekje’. Het
is nu echt ‘AF’, de spreekwoordelijke habijt kan definitief aan de kapstok of liever gezegd naar
zolder. Eindelijk kan ik iedereen bedanken die daar direct of indirect aan heeft bijgedragen,
want zoiets doe je niet alleen. Dus: ‘Iedereen bedankt’ . Tsja, dit is wat summier, een aantal
personen wil ik toch in het bijzonder danken en even in het zonnetje zetten.
Allereerst prof. dr. de Kleuver, beste Marinus, vanaf het begin ben je als inhoudelijk
eindverantwoordelijke betrokken bij de verschillende studies en de ideeën die we hadden
rondom triage. Je stap naar VUmc – Orthopedie betekende dat de deuren naar de academische
wereld wagenwijd open konden en vooral dat je promotor kon zijn. Wat een eer dat ik je eerste
promovenda ben. En ja, ik ben trots op mijn boekje maar nog meer op onze samenwerking en
wat we, samen met de spine unit, bereiken! Je visie, snelle in-/overzicht, deskundigheid, passie
voor de orthopedie/wervelkolomchirurgie en de wetenschap, werken bijzonder inspirerend.
Een betere supervisor die altijd bereikbaar is voor feedback, ‘waar ook ter wereld’ en tacticus
die denkt in mogelijkheden kan ik me niet voorstellen. Mede dankzij jouw gedrevenheid en
het in mij gestelde vertrouwen is het proefschrift afgerond. Je enthousiasme, betrokkenheid
en steun is van onschatbare waarde. Heel veel dank daarvoor. Met je aanstelling als
afdelingshoofd orthopedie in Radboudumc bestaat nu de mogelijkheid om de samenwerking
in orthopedie, klinische epidemiologie en outcome research een verdere boost te geven.
Prof. dr. Ostelo, beste Raymond, wat bijzonder dat je als oud-studiegenootje van KBW in
Maastricht nu mijn tweede promotor bent. In een later stadium ben je ‘ingevlogen’. Sinds de
komst van Marinus de Kleuver in VUmc ben je volop betrokken bij de verder ontwikkeling en
wetenschappelijke onderbouwing van de Nijmegen Decision Tool for Chronic Low Back Pain
(NDT-CLBP). Tijdens overleggen vullen jullie elkaar heel goed aan en je scherpe en kritische
methodologische blik en grenzeloze optimisme komen daarbij goed van pas. Daarbij hebben
we constructieve discussies, waar ik altijd vol nieuwe energie en inspiratie vandaan kom. Door
ook Hanneke van Dongen als post-doc HTA aan te stellen op het NDT-CLBP project hebben we
een top(kern)team en kan het niet anders dan dat de NDT-CLBP in welke vorm dan ook gaat
slagen. Veel dank daarvoor. Beste Hanneke, fijn dat we soms even de tijd nemen om heerlijk
te sparren.
Dr. Spruit (co-promotor), beste Maarten, initieel was je betrokken als inhoudsdeskundige en coauteur en later ook als co-promotor. Dat is niet voor niets: je scherpe analytische vermogen is
onevenaarbaar. In combinatie met Marinus de Kleuver en Raymond Ostelo prijs ik me gelukkig
met zo’n team, hoewel ik jullie nog niet één keer projectmatig samen aan tafel heb gehad .
Je rake opmerkingen en je scherpe kritische blik hebben me vaak verder geholpen en het heeft
dit proefschrift zeker naar een hoger plan getild.
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Een speciaal woord van dank is gericht aan dr. van Limbeek. Beste Jacques, als directeur van
het toenmalige Research Development & Education heb je me indertijd aangenomen als
kwaliteitsadviseur revalidatie. Als visionair en strateeg heb je me geïnspireerd en een snelle
scherpe denker zoals jij zijn er weinig. Evaluatie van behandelprogramma’s was onderdeel van
mijn werk en je hebt me de ruimte en mogelijkheden gegeven me als klinisch epidemioloog
te ontwikkelen en te profileren. Tot op de dag van vandaag ben ik daar erg blij om. Je deur
stond letterlijk altijd open voor methodologische en statistische vragen, waarop altijd een
individueel inspirerend college volgde. Daarbij heb je me ook het Miettiniaans denken
bijgebracht – dank daarvoor! Ik ben blij dat we samen nog een gastcollege van Ollie Miettinen
hebben kunnen bijwonen. Bovendien zal ik dankzij jou ook nimmer John Snow vergeten
(één van de grondleggers van de epidemiologie). Dank voor dit alles, ik zie uit naar je vragen
aangaande predictiemodellen tijdens de verdediging en ik hoop je van constructief repliek te
kunnen dienen.
Leden van de manuscriptcommissie, prof. dr. (Barend) van Royen (voorzitter beoordelingscommissie en afdelingshoofd VUmc orthopedie), prof. dr. (Maurits) van Tulder, prof. dr. (Ronald)
Bartels, prof. dr. (Jo) Nijs en dr. (Jaqcues) van Limbeek, dank voor de tijd en energie die jullie
hebben gestoken in het lezen en beoordelen van mijn proefschrift. Ik ben benieuwd naar
jullie vragen tijdens mijn verdediging. Beste Barend, ik voel me altijd erg welkom op jullie
afdeling en wat fijn dat ik altijd bij jullie terecht kon en van jullie diensten gebruik kon maken.
Dank voor je betrokkenheid. En Tsjitske Haanstra, beste Tjitske, wat een fijne samenwerking
hebben we en we vullen elkaar mooi aan. Ook al vertrek je naar de Brandwondenstichting, de
methodologie is wat ons verbindt en samen kunnen we de patiënt-gerelateerde uitkomsten
hoogtij laten vieren.
Veel dank gaat uit naar mijn beide paranimfen: Joke Vriezekolk en Nelleke Sicco Smit.
Joke, collega-vriendin ‘van-de-reuma’: je grenzeloze enthousiasme en betrokkenheid
inspireert mij. Je bent geweldig, je hebt het zelfs gered om bij één van mijn artikelen je
eerste ‘acknowledgement’ te behalen! Wat fijn dat je aan mijn zijde wil staan tijdens mijn
verdediging. Het geeft me nu al rust dat ik de lastige vragen kan doorspelen Nelleke, lieve
zorgzame vriendin ‘van-vele-jaren-terug’ en van het wildwater-kanoën. Nadat ik je geholpen
had je scriptie voor je echo-opleiding af te ronden, zou jij in ruil mijn ‘tasje vasthouden’ tijdens
mijn promotie. Weliswaar is het mijn boekje en excuses dat het wat zwaar is geworden. Het
is heerlijk om even op verhaal te komen bij je op de finca of om heerlijk samen een eind te
wandelen. Ik verheug me op je gezelschap voor, tijdens en uiteraard na de verdediging.
Natuurlijk dank ik ook al die patiënten die geparticipeerd hebben in de verschillende studies
en nog participeren in het onderzoek. Ook de Nederlandse Vereniging voor Rugpatiënten ‘De
Wervelkolom’ voor hun adviserende rol in het NDT-CLBP project.
Een deel van het onderzoek is uitgevoerd in samenwerking met de collega’s van RealHealthNL.
Veel dank voor jullie gedrevenheid, inzet en betrokkenheid. John O’Dowd, dear John, many
thanks for your trust in me, our collaboration and your introduction to prof. (Jeremy) Fairbank,
to further substantiate the findings of our RealHealthNL studies. Dear Jeremy, thanks for your
excellent and inspiring clinical and scientific insights, critical review, and collaboration. I am
looking forward to future projects.
Acknowledgements | Dankwoord
De stafleden orthopedie van Sint Maartenskliniek en in het bijzonder de leden van de spine
unit wil ik graag danken voor de interesse en de waardering voor het onderwerp van ‘outcome
assessment & decision-making’. Het vertrouwen dat jullie hebben en de betrokkenheid en
enthousiasme die jullie allen tonen is enorm. Het is fijn af en toe aan te mogen sluiten bij het
spine overleg en super-inspirerend om te horen hoe de (individuele) uitkomsten en de NDTCLBP nu al een bijdrage leveren in jullie drukke dagelijkse praktijk.
Lieve collega’s en oud-collega’s van OrthoResearch heel veel dank voor jullie vriendschap, steun
en begrip tijdens m’n promotietraject en vooral tijdens de welbekende ‘laatste loodjes’. De ‘rest’
van de afdeling Research, dank voor jullie gezelligheid, interesse, collegialiteit en natuurlijk
niet vergeten de cake-van-de-week. Dank ook aan de leden van de werkgroep MaartensFacts.
De overeenkomst tussen ‘lage rugpijn’ en ‘oude kaaskroketten’ is onmiskenbaar! Bart Nienhuis,
dank voor je interesse in mijn onderzoek, eerst als manager naast Jacques van Limbeek en
later als kamergenoot. Je kritische ‘down-to-earth’ houding ten aanzien van onderzoek met
vragenlijsten houd me scherp. Het doet me deugd dat je toch ook inziet dat het ergens toe kan
leiden. Het is fijn af en toe te filosoferen over de wetenschap en ‘het leven’ tijdens overheerlijke
bak eigenhandig gezette koffie .
Er is gelukkig meer dan alleen werk: beste familie en vrienden, ik heb jullie gemist. Eindelijk
heb ik meer tijd voor jullie en voor de geneugten van het leven. Daarbij hoort ook de muziek,
mijn cello voelde zich al bijna in de steek gelaten en ik ben blij dat er alweer mooie concerten
in het verschiet liggen.
Enkele persoonlijke woorden wil ik graag richten tot die mensen die me heel erg dierbaar
zijn. Helaas zijn Emile en Marjolein, pa en ma, niet bij de promotie, mijn trouwe fans van het
eerste uur. Zij hebben de basis gelegd voor wie ik nu ben en van jongs af aan heb ik van hen
alle gelegenheid gekregen om me verder ontwikkelen. Dankzij hen heb ik geleerd dat als
je gemotiveerd en gedisciplineerd bent, met hard werken van alles mogelijk is. Pa had de
verdediging graag mee willen maken, helaas laat zijn gezondheid vandaag de dag dit niet
meer toe en hopen we op een later en rustiger moment het feestje opnieuw over te doen bij
hem thuis. Eens te meer ben ik gelukkig dat ook Hans en Riet er zijn en zoveel interesse tonen.
Lieve Astrid, lief zussie en uiteraard ook Gerard, wat ben ik zielsgelukkig met jullie. Man̆ana is
toch nog gekomen. Volgende zomer samen genieten bij Man̆ana Man̆ana?
“Quand on travaille pour plaire aux autres
on ne peut pas réussir, mais les choses qu’on
a faites pour se contenter soi-même on
toujours une chance d’intéresser quelqu’un.”
(Marcel Proust, 1871-1922)
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Curriculum Vitae
292
Curriculum Vitae
Curriculum Vitae
Miranda van Hooff was born on May 27,
1969 in Diepenveen, The Netherlands.
After graduating secondary school
(HAVO, Alexander Hegius SG, Deventer)
in 1987 she studied physiotherapy at the
Saxion University of Applied Sciences in
Deventer (then IJselland). She followed
her last internship in a rehabilitation
centre for spinal cord injury in Grenoble
(France) where her interest in spinerelated disorders was stimulated. After
receiving her bachelors’ degree in 1991
she followed a master programme
health sciences for physiotherapists with
a specialisation in clinical epidemiology at the Maastricht University. After graduation in 1994
she worked from 1994 to 2006 as a physiotherapist specialised in neurological rehabilitation
and as a health care advisor at the rehabilitation center Klimmendaal (then Kastanjehof) in
Apeldoorn. Next to her work as a rehabilitation physiotherapist, in 2004 she worked as a parttime junior epidemiology advisor for health outcome indicators at the Knowledge Institute for
Medical Specialists (then CBO) in Utrecht.
Appreciating the importance of continuous health outcomes assessment and evaluation of
clinical performance by healthcare providers themselves, Miranda realized that working as a
health scientist, would indirectly affect more patients than she could ever treat as a therapist
herself. She decided to leave direct patient care behind. In 2006, she started working as a
senior quality advisor at the department of Rehabilitation in the Sint Maartenskliniek. In this
position she was responsible for the implementation and evaluation of treatment programmes
and the implementation of an organisation wide quality system. Since 2010, Miranda is a
full-time researcher to support research performed at the orthopaedic department of the
Sint Maartenkliniek. She is involved in several spine, hip arthroplasty, and prosthetic joint
infections related clinical (outcomes) studies and systematic reviews. In 2012, she started the
development of the international acclaimed Nijmegen Decision Tool for Chronic Low Back Pain
(NDT-CLBP) that culminated in this thesis. Late 2012 this thesis was conceptualised. In that
same year she was registered as an epidemiologist A. Next to her work at Sint Maartenskliniek,
from 2013 to April 2016 she worked as a part-time clinical epidemiologist at the Dutch Institute
for Clinical Auditing (DICA) to set up and implement for example the Dutch Spine Surgery
Registry (DSSR) for the Dutch Spine Society. She is still involved as a member of the scientific
committee of the DSSR and works in close collaboration with the Scandinavian spine registries
(SweSpine, NorSpine, DaneSpine).
Currently, she is working as a researcher & clinical epidemiologist at the Sint Maartenskliniek
and is engaged in several orthopaedic and especially in spine-related (outcomes) research
projects. She works in close collaboration with VU university medical centre, VU University
EMGO in Amsterdam, and the Radboud university medical centre in Nijmegen.
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Publications
296
Publications
List of publications
This thesis
Hooff ML, van Dongen JM, Coupé VMH, Spruit M, , Ostelo RWJG, De Kleuver M Prognostic
patient-reported profiles for referral to secondary or tertiary spine specialists – The Nijmegen
Decision Tool for Chronic Low Back Pain. [Submitted]
Van Dongen JM, Van Hooff ML, Spruit M, De Kleuver M, Ostelo RWJG Patient-reported factors
partly predicted referral to spinal surgery in a consecutive cohort of 4,987 chronic low back
pain patients. [Under review]
Van Hooff ML, Mannion AF, Staub LP, Ostelo RWJG, Fairbank JCT (2016) Determination of
the Oswestry Disability Index score equivalent to a ‘satisfactory symptom state’ in patients
undergoing surgery for degenerative disorders of the lumbar spine – A Spine Tango registrybased study. Spine J. Oct;16(10):1221-1230. doi: 10.1016/j.spinee.2016.06.010. Epub 2016 Jun 22.
Van Hooff ML, Jacobs WC, Willems PC, Wouters MW, De Kleuver M, Peul WC, Ostelo RW, Fritzell P
(2015) Evidence and practice in spine registries. A systematic review, and recommendations for
future design of registries. Acta Orthop Oct;86(5):534-44. doi: 10.3109/17453674.2015.1043174.
Clement RC, Welander A, Stowell C, Cha TD, Chen JL, Davies M, Fairbank JC, Foley KT,
Gehrchen M, Hagg O, Jacobs WC, Kahler R, Khan SN, Lieberman IH, Morisson B, Ohnmeiss
DD, Peul WC, Shonnard NH, Smuck MW, Solberg TK, Stromqvist BH, Van Hooff ML, Wasan
AD, Willems PC, Yeo W, Fritzell P (2015) A proposed set of metrics for standardized outcome
reporting in the management of low back pain. Acta Orthop. Oct;86(5):523-33. doi:
10.3109/17453674.2015.1036696.
Van Hooff ML, Spruit M, Fairbank JCT, Van Limbeek J, Jacobs WCH (2015) The Oswestry
Disability Index (version 2.1a): Validation of a Dutch language version. Spine (Phila Pa 1976) Jan
15;40(2):E83-90. doi: 10.1097/BRS.0000000000000683.
Van Hooff ML, Van Loon J, Van Limbeek J, De Kleuver M (2014) The Nijmegen Decision Tool for
Chronic Low Back Pain. Development of a clinical decision tool for secondary or tertiary spine
care specialists. PLoS One. Aug 18;9(8):e104226. doi: 10.1371/journal.pone.0104226. eCollection
2014.
Van Hooff ML, Spruit M, O’Dowd JK, Van Lankveld W, Fairbank JC, Van Limbeek J (2014)
Predictive factors for successful clinical outcome 1 year after an intensive combined physical
abd psychological programme for chronic low back pain. Eur Spine J 23(1):102-12.
Van Hooff ML, Ter Avest W, Horsting PP, O’Dowd J, De Kleuver M, Van Lankveld W, Van Limbeek
J (2012) A short, intensive cognitive behavioral program for pain management reduces
healtcare-use in patients with Chronic Low Back Pain. Two-year follow up results of a
prospective cohort. Eur Spine J 21(7):1257-64.
297
298
Publications
Van Hooff ML, Van der Merwe JD, O’Dowd J, Pavlov PW, Spruit M, De Kleuver M, Van Limbeek
J (2010) Daily functioning and self-management in patients with chronic low back pain after
anintensive cognitive behavioral programme for pain management. Eur Spine J 19(9):1517-26.
Other publications peer-reviewed journals
Van Diek FM, Albers CGM, Van Hooff ML, Meis JF, Goosen JHM [Accepted for publication] The use
of implant sonication when screening for infection in revision surgery. Acta Orthop.
Bier JD, Ostelo RWJG, Van Hooff ML, Wildervanck N, Koes BW, Verhagen AP [Accepted for
publication] Validity and reproducibility of the translated STarT Back Tool in low back pain
patients in Dutch primary care. Physical Therapy.
Baauw M, Van Hooff ML, Spruit M (2016) Current construct options for revision of large
acetabular defects. A systematic review. JBJS Reviews Nov;4 (11): e2. http://dx.doi.org/10.2106/
JBJS.RVW.15.00119.
Faraj SSA, Holewijn RM, Van Hooff ML, De Kleuver M, Pellisé F, Haanstra TM (2016) De novo
degenerative lumbar scoliosis: a systematic review of prognostic factors for curve progression.
Eur Spine J (2016) 25: 2347.
Jacobs AM, Van Hooff ML, Meis JF, Vos F, Goosen JH (2016) Treatment of prosthetic joint
infections due to Propioni bacterium. Acta Orthop Feb;87(1):60-6.
Baauw M, Van Hellemondt GG, Van Hooff ML, Spruit M (2015) The accuracy of positioning of
a custom-made implant within a large acetabular defect at revision arthroplasty of the hip.
Bone Joint J. Jun;97-B(6):780-5. doi: 10.1302/0301-620X.97B6.35129.
Altmann VC, Hart AL, Vanlandewijck YC, Van Limbeek J, Van Hooff ML (2015).The impact of trunk
impairment on performance of wheelchair activities with a focus on wheelchair court sports:
a systematic review. Sports Med Open. 2015;1(1):6. Epub May 7.
Hofstede SN, Nouta KA, Jacobs W, Van Hooff ML, Wymenga AB, Pijls BG, Nelissen RG, Marangvan de Mheen PJ (2015) Mobile bearing vs fixed bearing prostheses for posterior cruciate
retaining total knee arthroplasty for postoperative functional status in patients with
osteoarthritis and rheumatoid arthritis. Cochrane Database Syst Rev Feb 4;2:CD003130. doi:
10.1002/14651858.CD003130.pub3.
Althuizen MNR, Van Hooff ML, Van den Berg-van Erp SHM, Van Limbeek J, Nijhof MW (2012)
Early failures in large head metal-on-metal total hip arthroplasty. Hip Int 22(6):641-7
Conference proceedings thesis-related – oral presentations
Van Hooff ML, Van Dongen JM, Spruit M, Coupé V, Ostelo RWJG, De Kleuver M. Prediction of
treatment outcomes for patients with Chronic Low Back Pain: the development of a clinical
decision guideline for spine surgeons. XIV International Back & Neck Pain Forum Buxton (31
May – 3 June 2016)
Publications
Van Hooff ML, Van Dongen JM, Spruit M, Ostelo RWJG, De Kleuver M. Prediction of treatment
outcomes for patients with Chronic Low Back Pain: the development of a clinical decision
guideline for spine surgeons. Global Spine Congress Dubai (13-16 April 2016)
Van Hooff ML, O'Dowd JK, Van Loon J, Spruit M. Long-term follow-up results of a Combined
Physical and Psychological program for patients with Chronic Low Back Pain. Global Spine
Congress Dubai (13-16 April 2016)
Van Hooff ML, O’Dowd JK, Van Loon J, Spruit M. Long-term follow up of a combined Physical
and psychological programme for patients with longstanding chronic low back pain. SPBR
Bournemouth (5-6 November 2015)
Van Hooff ML (Invited speaker, in Dutch) RealHealthNL een innovatief programma: Uitkomsten
en voor wie geschikt? NOV Veldhoven (15-16 Oktober 2015)
Van Hooff ML, Jacobs WCH, Stoefs J, Fritzell P. During Pre-conference Focus group meeting:
Global collaboration on spine registries. ISSLS Seoul (2 June 2014)
Van Hooff ML, Spruit M, Mannion AF, Fairbank JCT. What is the level of disability on the
Oswestry Disability Index that most spine surgery patients are satisfied with? NOV Rotterdam
(6-7 February 2014)
Van Hooff ML, O’Dowd J, De Kleuver M, Fairbank J, Van Limbeek J. Clinical outcomes of a
combined physical and psychological program in a large cohort of longstanding chronic low
back pain. SPBR London (14-15 November 2013)
Van Hooff ML, O’Dowd J, Spruit M, Fairbank J, Van Limbeek J. Factors predicting clinical
outcome one year after an intensive pain management programme for chronic low back pain.
ISSLS Scottsdale (13-17 May 2013)
Van Hooff ML, O’Dowd J, Spruit M, Fairbank J, De Kleuver M, Van Limbeek J. Factors predicting
clinical outcome one year after an intensive pain management programme for chronic low
back pain. Nominated best paper award. Global Spine Congress Hong Kong (4-6 April 2013)
Van Hooff ML, De Kleuver M, Van Loon J, Van Limbeek J. Subgrouping patients with Chronic
Low Back Pain: Development of a clinical decision guideline for spine surgeons. Global Spine
Congress Hong Kong (April 4-6, 2013)
Van Hooff ML, O’Dowd J, Spruit M, Van Limbeek J. Factors predicting clinical outcome one year
after an intensive pain management programme for chronic low back pain. SBPR Isle of Man
(8-9 November, 2012)
Van Hooff ML, De Kleuver M, Van Lankveld W, Van Limbeek J. Subgrouping patients with chronic
low back pain. SpineWeeek ISSLS Amsterdam (28 May – 1 June 2012)
299
300
Publications
Van Hooff ML, Horsting P, O’Dowd J, De Kleuver M, Van Lankveld W, Van Limbeek J. Considerable
long term reduction in pain and healthcare use in patients with chronic low back pain after
a short intensive pain management program. SpineWeek ISSLS Amsterdam (28 May – 1 June
2012)
Van Hooff ML, Van der Merwe JD, O’Dowd J, Pavlov PW, Spruit M, De Kleuver M, Van Limbeek
J. Daily functioning and self-management in patients with chronic low back pain after an
intensive cognitive behavioral pain management program: 1 year follow up results. WEON
‘Research with Impact’ Nijmegen (10-11 June 2010)
Van Hooff ML, Van der Merwe JD, O’Dowd J, Pavlov PW, Spruit M, De Kleuver M, Van Limbeek J.
Results of a short intensive cognitive behavioral pain management program for patients with
chronic low back pain: a cohort study. SBPR Chepstow (November 5-6 2009)
Van Hooff ML, De Kleuver M, Van der Merwe JD, O’Dowd J, Pavlov PW, Spruit M, Van Limbeek J.
Results of a short intensive cognitive behavioral pain management program for patients with
chronic low back pain: a cohort study. EuroSpine Warsaw (21-24 November 2009)
Van Hooff ML, Van der Merwe JD, O’Dowd J, Pavlov PW, Spruit M, De Kleuver M, Van Limbeek
J. Resultaten van een kort, intensief cognitief gedragsmatig programma voor patiënten met
chronische lage rugklachten: een prospectieve cohort studie. Bijeenkomst Zorgverzekeraars.
Sint Maartenskliniek Nijmegen (4 September 2009)
Van Hooff ML, Van der Merwe JD, O’Dowd J, Pavlov PW, Spruit M, De Kleuver M, Van Limbeek J.
Results of a short intensive cognitive behavioral pain management program for patients with
chronic low back pain: a cohort study. Global Spine Congress San Fransisco (23-26 June 2009)
Van Hooff ML, Horsting P, De Kleuver M (in Dutch). Goed resultaat van een cognitief
gedragsmatig programma voor patiënten met chronische lage rugklachten: een prospectieve
cohort studie. NOV Spring meeting Utrecht (15 May 2009)
Conference proceedings thesis-related – poster presentations
Van Hooff ML, Van Dongen JM, Groot D, Spruit M, Coupé VMH, Ostelo RWJG, De Kleuver M.
Prediction of treatment outcomes for patients with chronic low back pain: The development
of a clinical decision guideline for spine surgeons. SpineWeek ISSLS Singapore (16-20 May
2016)
Van Hooff ML, Van Loon J, De Kleuver M. Feasibility of the Nijmegen Decision Tool to support
spine surgeons in the triage of Chronic Low Back Pain patients. ISSLS Seoul (3-7 June 2014)
Van Hooff ML, O’Dowd J, De Kleuver M, Fairbank J, Van Limbeek J. Clinical outcomes of a
combined physical and psychological program in a large cohort of longstanding chronic low
back pain. EuroSpine e-poster Liverpool (2-4 Oktober 2013)
Van Hooff ML, De Kleuver M, Van Loon J, Van Limbeek J. Development of a clinical decision tool
to support spine surgeons in the triage of chronic low back pain patients. EuroSpine e-poster
Liverpool (2-4 Oktober 2013)
Publications
Van Hooff ML, Horsting P, O’Dowd J, De Kleuver M, Van Lankveld W, Van Limbeek J. Positive
Long-term results of a short, intensive pain management program for functioning, quality of
life and healthcare use in patients with chronic low back pain. EFIC Hamburg (21-24 September
2011)
Van Hooff ML, Van Lankveld W, O’Dowd J, De Kleuver M, Van Limbeek J. Patients with
longstanding back pain improve on cognitive behavioral variables after a short, intensive pain
management program. EFIC Hamburg (21-24 September 2011)
Media thesis-related
Van Hooff ML, De Frêtes A, De Kleuver M (in Dutch). Nijmegen Decision Tool voor patiënten met
chronische lage rugklachten. Nederlands Tijdschrift voor Revalidatiegeneeskunde (NTR 2015).
De Kleuver M, Den Broeder A, Swierstra B, Van Hooff ML (in Dutch). Maartenskliniek draait
warm met uitkomstmaten. Medisch Contact (16 March 2015).
Van Hooff ML, De Kleuver M (spine unit SMK; in Dutch). Vragenlijst helpt bij lage rugpijn. De
Gelderlander (24 September 2014).
Van Hooff ML namens De Kleuver M, Ostelo RWJG, Voogt L. The Nijmegen Decision Tool for
Chronic Low Back Pain. Nominated for Porter Prize Value Based Healthcare Europe (January
2014).
Working group Low Back Pain of International Consortium for Health Outcomes Measurment
(ICHOM). Low Back Pain Data collection User Manual and Flyer Standard Set LBP (November
2013). Available from: http://www.ichom.org/project/low-back-pain/
Van Hooff ML namens RealHealthNL, Spine unit Sint Maartenskliniek (in Dutch). RealHealth:
Gezondheidswinst inzichtelijk. Bewezen effectief. Nominated for Achmea Quality Award 2013
(12 September 2013).
Middelhuis T, Van Hooff M, Spruit M. RealHealth & Sint Maartenskliniek (in Dutch). Beter
functioneren met chronisch lage rugpijn. Wervelwind (July 2013); p 11-3.
Van Hooff ML, O’Dowd J, Spruit M, Fairbank J, Van Limbeek J. Identified indicators that
predict clinical outcomes after intensive pain management program (Based on abstract
ISSLS Scottsdale (13-17 May 2013). Published online by HealthDay in Japanese as Educational
Material June 2013. Available from: http://www.ds-pharma.co.jp/
Trainers RealHealthNL, Van Hooff ML, Spruit M (in Dutch) en onder redactie van Kolkman M.
Pijn hebben mag. Reportage: Leren leven met chronische klachten. Psychologie Magazine
(May 2013); p 90-3.
Apeldoorn A, Van Hooff M, Ostelo R (in Dutch). De STarT Back Screening Tool. Screeningsinstrument lage rugklachten. FysioPraxis (April 2013); p 32-3.
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Publications
Van Hooff ML, De Kleuver M, O’Dowd J, Van Limbeek J. Considerable long-term reduction of
pain and healthcare use in Chronic Low back Pain patients after a short pain management
program. Clinical evidence for the RealHealthNL program. Spinal News International; Issue
24 (Juli 2012); p14.
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Theses Sint Maartenskliniek
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Theses Sint Maartenskliniek
Theses Sint Maartenskliniek
De Rooij, D. (1988). Clinical and serological studies in the connective tissue diseases.
University of Nijmegen, Nijmegen, The Netherlands.
Geurts, A. (1992). Central adaptation of postural organization to peripheral sensorimotor
impairments. University of Nijmegen, Nijmegen, The Netherlands.
Van Lankveld, W. (1993). Coping with chronic stressors of rheumatoid arthritis. University of
Nijmegen, Nijmegen, The Netherlands.
Tromp, E. (1995). Neglect in action: a neuropsychological exploration of some behavioural
aspects of neglect. University of Nijmegen, Nijmegen, The Netherlands.
Van Balen, H. (1997). A disability-oriented approach to long-term sequelae following traumatic
brain injury. Neuropsychological assessment for post-acute rehabilitation. University of
Nijmegen, Nijmegen, The Netherlands.
De Kleuver, M. (1998). Triple osteotomy of the pelvis.An anatomical, biomechanical and clinical
study. University of Nijmegen, Nijmegen, The Netherlands.
Hochstenbach, J. (1999). The cognitive, emotional, and behavioural consequenses of stroke.
University of Nijmegen, The Netherlands.
Donker, S. (2002). Flexibility of human walking: a study on interlimb coordination.
Groningen University, Groningen, The Netherlands.
Hendricks, H. (2003). Motor evoked potentials in predicting motor and functional outcome after
stroke. University of Nijmegen, Nijmegen, The Netherlands.
Hosman, A. J. F. (2003). Idiopathic thoracic spinal deformities and compensatory mechanisms.
University of Nijmegen, Nijmegen, The Netherlands.
Jongerius, P. (2004). Botulinum toxin type-A to treat drooling. A study in children with cerebral
palsy. Radboud University, Nijmegen, The Netherlands.
Van de Crommert, H. (2004). Sensory control of gait and its relation to locomotion after a spinal
cord injury. Radboud University, Nijmegen, The Netherlands.
Van der Linde, H. (2004). Prosthetic prescription in lower limb amputation. Development of a
clinical guideline in the Netherlands. Groningen University, Groningen, The Netherlands.
De Haart, M. (2005). Recovery of standing balance in patients with a supratentorial stroke.
Radboud University, Nijmegen, The Netherlands.
Den Otter, R. (2005). The control of gait after stroke: an electromyographic approach to
functional recovery. Groningen University, Groningen, The Netherlands.
305
306
Theses Sint Maartenskliniek
Weerdesteyn, V. (2005). From the mechanisms of obstacle avoidance towards the prevention of
falls. Radboud University, Nijmegen, The Netherlands.
Baken, B. (2007). Reflexion on reflexes. Modulation during gait. Radboud University, Nijmegen,
The Netherlands.
Gaasbeek, R. (2007). High tibial osteotomy. Treatment of varus osteoarthritis of the knee.
Radboud University, Nijmegen, The Netherlands.
Koëter, S. (2007). Patellar instability. Diagnosis and treatment. Radboud University, Nijmegen,
The Netherlands.
Langeloo, D. (2007). Monitoring the spinal cord during corrective spinal surgery: a clinical study
of TES-MEP. Radboud University, Nijmegen, The Netherlands.
Ruiter, M. (2008). Speaking in ellipses. The effect of a compensatory style of speech on functional
communication in chronic agrammatism. Radboud University, Nijmegen, The Netherlands.
Van den Bemt, B. (2009). Optimizing pharmacotherapy in patients with rheumatoid arthritis:
an individualized approach. Radboud University, Nijmegen, The Netherlands.
Van Nes, I. (2009). Balance recovery after supratentorial stroke. Influence of hemineglect and
the effects of somatosensory stimulation. Radboud University, Nijmegen, The Netherlands.
Aarts, P. (2010). Modified constraint-induced movement therapy for children with unilateral
spastic cerebral palsy: the Pirate group intervention. Radboud University, Nijmegen,
The Netherlands.
Groen, B. (2010). Martial arts techniques to reduce fall severity. Radboud University, Nijmegen,
The Netherlands.
Van Koulil, S. (2010). Tailored cognitive behavioral therapy in fibromyalgia. Radboud University,
Nijmegen, The Netherlands.
Boelen, D. (2011). Order out of chaos? Assessment and treatment of executive disorders in braininjured patients. Radboud University, Nijmegen, The Netherlands.
Heesterbeek, P. (2011). Mind the gaps! Clinical and technical aspects of PCL-retaining total knee
replacement with the balanced gap technique. Radboud University, Nijmegen,
The Netherlands.
Hegeman, J. (2011). Fall risk and medication. New methods for the assessment of risk factors in
commonly used medicines. Radboud University, Nijmegen, The Netherlands.
Smulders, E. (2011). Falls in rheumatic diseases. Risk factors and preventive strategies in
osteoporosis and rheumatoid arthritis. Radboud University, Nijmegen, The Netherlands.
Theses Sint Maartenskliniek
Snijders, G. (2011). Improving conservative treatment of knee and hip osteoarthritis.
Radboud University, Nijmegen, The Netherlands.
Vriezekolk, J. (2011). Targeting distress in rheumatic diseases. Utrecht University, Utrecht,
The Netherlands.
Willems, P. (2011). Decision making in surgical treatment of chronic low back pain.
The performance of prognostic tests to select patients for lumbar spinal fusion. Maastricht
University, Maastricht, The Netherlands.
Beijer, L. (2012). E-learning based speech therapy (EST). Exploring the potentials of E-health for
dysarthric speakers. Radboud University, Nijmegen, The Netherlands.
Hoogeboom, T. (2012). Tailoring conservative care in osteoarthritis. Maastricht University,
Maastricht, The Netherlands.
Brinkman, M. (2013). Fixation stability and new surgical concepts of osteotomies around the
knee. Utrecht University, Utrecht, The Netherlands.
Kwakkenbos, L. (2013). Psychological well-being in systemic sclerosis: Moving forward in
assessment and treatment. Radboud University, Nijmegen, The Netherlands.
Severens, M. (2013). Towards clinical BCI applications: assistive technology and gait
rehabilitation. Radboud University, Nijmegen, The Netherlands.
Stukstette, M. (2013). Understanding and treating hand osteoarthritis: a challenge.
Utrecht University, Utrecht, The Netherlands.
Van der Maas, A. (2013). Dose reduction of TNF blockers in Rheumatoid Arthritis: clinical and
pharmacological aspects. Radboud University, Nijmegen, The Netherlands.
Zedlitz, A. (2013). Brittle brain power. Post-stroke fatigue, explorations into assessment and
treatment. Radboud University, Nijmegen, The Netherlands.
Koenraadt, K. (2014). Shedding light on cortical control of movement. Radboud University,
Nijmegen, The Netherlands.
Smink, A. (2014). Beating Osteoarthritis. Implementation of a stepped care strategy to manage
hip or knee osteoarthritis in clinical practice. VU University Amsterdam, Amsterdam,
The Netherlands.
Stolwijk, N. (2014). Feet 4 feet. Plantar pressure and kinematics of the healthy and painful foot.
Radboud University, Nijmegen, The Netherlands.
Van Kessel, M. (2014). Nothing left? How to keep on the right track. Spatial and non-spatial
attention processes in neglect after stroke. Radboud University, Nijmegen, The Netherlands.
307
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Theses Sint Maartenskliniek
Altmann, V. (2015). Impact of trunk impairment on activity limitation with a focus on
wheelchair rugby. Leuven University, Leuven, Belgium.
Bevers, K. (2015). Pathophysiologic and prognostic value of ultrasonography in knee
osteoartrhitis. Utrecht University, Utrecht, The Netherlands.
Cuperus, N. (2015). Strategies to improve non-pharmacological care in generalized
osteoarthritis. Radboud University, Nijmegen, The Netherlands.
Kilkens, A. (2015). De ontwikkeling en evaluatie van het Communicatie Assessment & Interventie
Systeem (CAIS) voor het aanleren van (proto-)imperatief gedrag aan kinderen met complexe
ontwikkelingsproblemen. Radboud University, Nijmegen, The Netherlands.
Penning, L. (2015). The effectiveness of injections in cuffdisorders and improvement of
diagnostics. Maastricht University, Maastricht, The Netherlands.
Stegeman, M. (2015). Fusion of the tarsal joints: outcome, diagnostics and management of
patient expectations. Utrecht University, Utrecht, The Netherlands.
Van Herwaarden, N. (2015). Individualised biological treatment in rheumatoid arthritis.
Utrecht University, Utrecht, The Netherlands.
Wiegant, K. (2015). Uitstel kunstknie door kniedistractie. Utrecht University, Utrecht,
The Netherlands.
Willems, L. (2015). Non-pharmacological care for patients with systemic sclerosis.
Radboud University, Nijmegen, The Netherlands.
Witteveen, A. (2015). The conservative treatment of ankle osteoarthritis. University of
Amsterdam, Amsterdam, The Netherlands.
Zwikker, H. (2015). All about beliefs. Exploring and intervening on beliefs about medication to
improve adherence in patients with rheumatoid arthritis. Radboud University, Nijmegen,
The Netherlands.
Luites, J. (2016). Innovations in femoral tunnel positioning for anatomical ACL reconstruction.
Radboud University, Nijmegen, The Netherlands.
Pakvis, D. (2016). Survival, primary stability and bone remodeling assessment of cementless
sockets. An appraisal of Wolff’s law in the acetabulum. Radboud University, Nijmegen,
The Netherlands.
Lesuis, N. (2016). Quality of care in rheumatology. Translating evidence into practice. Radboud
University, Nijmegen, The Netherlands.
Schoenmakers, K. (2016). Prolongation of regional anesthesia. Determinants of peripheral nerve
block duration. Radboud University, Nijmegen, The Netherlands.
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Stellingen
1. Het triëren en juist toewijzen van chronische lage rugpijn patiënten voor de juiste behandeling
leidt tot betere uitkomsten. (dit proefschrift)
2. De drempelwaarde voor een succesvolle behandeluitkomst voor chronische lage rugpijn komt
overeen met de mate van functioneren van een gezonde populatie. (dit proefschrift)
3. De Nijmegen Decision Tool for Chronic Low Back Pain is volledig gebaseerd op het biopsychosociaal model, een unicum binnen de orthopedie alwaar het biomedisch model
dominant is. (dit proefschrift)
4. Een uitkomstenregister, opgezet conform observationele onderzoeksmethoden, is de basis voor
evaluatie van zorg, het vergelijken van interventies en value-based health care. (dit proefschrift)
5. Het concept van op behandeluitkomsten gebaseerde prognostische patiënt profielen bij
chronische lage rugpijn, leidt tot een paradigmaverschuiving in de moderne geneeskunde.
(dit proefschrift)
6. De onderzoeksvraag en daarmee het onderwerp van studie, is belangrijker dan de
onderzoeksmethode zelf. (opinie, gebaseerd op werk van Olli S. Miettinen, 1936- )
7. Afhankelijk van de vraagstelling heeft observationeel onderzoek een duidelijke meerwaarde
boven experimenteel onderzoek. (opinie)
8. Om interventies voor een specifieke doelgroep met elkaar te kunnen vergelijken zijn eenduidige
en alom geaccepteerde definities van ‘succes’ en ‘falen’ onontbeerlijk. (opinie)
9. Absolute maten voor behandelsucces zijn te prefereren boven relatieve maten, aangezien:
‘It’s good to feel better but it’s better to feel good. (Dougados, J.Rheumatol. 2005)’. (opinie)
10. A-specifieke lage rugpijn bestaat niet. (opinie)
11. It’s more important to know what sort of a person has a disease than to know what sort of a
disease a person has (Hippocrates, 460-377 BC).
12. The difficulty lies not so much in developing new ideas as in escaping from the old ones
(John Maynard Keynes,1883-1946).
13. De maatschappelijke impact van research heeft meer impact dan de hoogte van de impact factor.
(eigen ervaring)
14. Music is part of being human (Oliver Sacks, 1933-2015).