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Title
Preferences for cancer investigation: a vignette-based study of primary care attenders
Authors
Jonathan Banks, Sandra Hollinghurst, Lin Bigwood, Tim J Peters, Fiona M Walter, Willie
Hamilton
Corresponding author
Jonathan Banks PhD
School of Social & Community Medicine
University of Bristol,
Canynge Hall, 39 Whatley Road
Bristol BS8 2PS
Tel: 0117 92 87230
E Mail: [email protected]
Lin Bigwood MA & Sandra Hollinghurst PhD
School of Social & Community Medicine
University of Bristol,
Canynge Hall, 39 Whatley Road
Bristol BS8 2PS
Professor Tim J Peters PhD
School of Clinical Sciences
69 St Michael's Hill,
Bristol, BS2 8DZ
Fiona M Walter MD
The Primary Care Unit, Department of Public Health & Primary Care
University of Cambridge
Strangeways Research Laboratory, Wort's Causeway
Cambridge, CB1 8RN
Professor William Hamilton MD
University of Exeter
College House, St Luke’s Campus
Exeter, EX2 4TE
1
Abstract
Background
The UK lags behind many European and developed countries in terms of cancer survival.
Initiatives to address this disparity have focused on barriers to presentation, symptom
recognition and referral for specialist investigation. The threshold risk of cancer in primary care
warranting specialist investigation has come under particular scrutiny, though UK population
preferences for referral thresholds have not been studied. We investigated preferences for
diagnostic testing for colorectal, lung, and pancreatic cancer in a large sample of primary care
attenders.
Methods
Electronic survey of general practice attenders aged ≥40 using vignette-based questionnaires.
The vignettes outlined: the symptoms potentially representing lung, pancreatic, or colorectal
cancer; the risk posed by the symptoms (1, 2, 5 & 10%); and the testing process. The outcome
was whether or not respondents indicated that they would opt for cancer testing on each of a
maximum of three vignettes – one for each cancer with risk allocated randomly. The main
analysis used logistic regression.
Findings
3,469 participants completed 6,930 vignettes, with 3,052 (88%) opting for investigation. A
higher risk of cancer was weakly associated with increased opting for investigation: odds ratio
for a one percentage point increase in cancer risk 1·02 (95% confidence interval 0·99 to 1·06;
p=0·189), though in the case of colorectal cancer there was a strong association (OR 1·08; 95%
CI: 1·03 to 1·13; p=0·001). In multivariable analysis, age predicted opting for investigation, with
ages 60-69 higher, and age ≥70 lower, against reference ages of 40-59 (p=0·035 colorectal;
p<0·0001 pancreas and lung). Other variables associated with increased likelihood of opting for
investigation were: shorter travel times to testing centre (colorectal and lung), a family history
of cancer (colorectal and lung), and higher household income (colorectal and pancreas).
Interpretation
Participants in this sample expressed a clear preference for testing at all risk levels, including 1%.
This shows an appetite for testing at risk levels well below current UK guidelines and contributes
to the ongoing design of cancer pathways, particularly in primary care. The public engagement
with this study should encourage GPs to involve patients in decision making around risk, referral
and investigation.
This paper presents independent research funded by the National Institute for Health Research
(NIHR) Programme Grants for Applied Research programme, RP-PG-0608-10045.
2
Preferences for cancer investigation: a vignette-based study of primary
care attenders
Introduction
Over one in three people in the UK will develop cancer during their lifetime. Although cancer
mortality in the UK has improved recently, it still lags behind average European figures.1 A number of
initiatives have sought to address this, including the Cancer Reform Strategy and the establishment
of the National Awareness and Early Diagnosis Initiative (NAEDI).2 Earlier diagnosis is considered to
be one of the main ways to improve UK survival, particularly by refining selection of patients for
cancer investigation.3 Almost 90% of patients with cancer are diagnosed after experiencing
symptoms, and most of these patients present to primary care.4 Selection of patients for
investigation is not straightforward: over-investigation has clinical and financial costs, and underinvestigation risks delay in diagnosis, with clinical and medico-legal costs. This selection process is
undertaken by clinicians, who have largely determined provision of cancer diagnostic services.
However, other groups have a legitimate interest in this decision: providers of cancer diagnostic
services, government, the taxpayer, insurers, and, most importantly, patients.
Most common symptoms of cancer may also represent benign disease. In deciding whether to
investigate for possible cancer, General Practitioners (GPs) use their experience and national
guidelines, especially the highly influential National Institute for Health and Care Excellence (NICE)
guidance issued in 2005.5 This guidance also underpins the provision of two-week wait clinics, which
promise that patients are seen within that time. NICE guidance describes symptoms, or
combinations of symptoms and signs, deemed worthy of investigation. By implication, the likelihood
of the patient having cancer is high enough to justify investigation, though no explicit risk threshold
warranting investigation for cancer has been published in UK or any other national guidance.6 The
percentage of patients referred to two-week wait clinics who transpire to have cancer varies across
cancer sites, geographical areas, and GPs.7 However, only a quarter of cancers are diagnosed
through these clinics, with other patients presenting as emergencies or being referred to other
specialist services.8,
9
Recent research in primary care has estimated the risk of cancer for many
symptoms, with several symptoms recommended by NICE having a high likelihood of cancer: few of
the NICE recommendations equate to risks below 5%.10, 11
NICE referral guidance strongly recommends involving the patient in making the decision to be
tested,5 though there has been very little research on patient preferences in the diagnostic sphere.
Previous research has focussed on treatment or follow-up options,12 and patient preferences for
screening,13 predictive investigation,14 or sharing risk information.15 Patients certainly fear cancer –
ahead of knife crime, Alzheimer's disease, and job loss, for example. Nevertheless, it is unknown to
3
what extent patients would choose investigation for cancer when provided with the relevant
information about cancer risk, the details of investigation, and possible outcomes. We addressed
this issue in the study reported here.
Method
This was a vignette-based survey to determine the likelihood that participants would choose to be
tested for cancer at various levels of risk. Three contrasting cancers were chosen - colorectal, lung,
and pancreas – as they differ in terms of symptoms, type of test, treatment, and prognosis. The main
question of what proportion of the population would opt for investigation at each risk level was
addressed using a simple ‘yes/no’ alternative. The survey was administered using an electronic touch
screen tablet computer (iPad).
Survey design
We developed twelve separate vignettes (excerpts in Table 1). These were refined in two rounds of
cognitive interviewing using the verbal probing method (ref Willis) with 18 members of 3 GP practice
patient groups: participants (n=13) were asked for their understanding of each question and
information screen. Responses were recorded systematically, collated. Following redesign, the
questionnaire was tested again (n=5) and this was followed by a full week of piloting. Check
numbers in green plus add ref for willis. There were four vignettes for each of the three cancers,
portraying different risk levels (1, 2, 5, and 10%). The content was informed by NICE guidelines,
qualitative interviews with patients referred for diagnostic tests for the three cancers,16 and clinical
experience.17-19 Each contained a description of symptoms, the risk that these might indicate cancer
(both numerically and pictorially), information about the relevant diagnostic test, likely treatment,
possible alternative diagnoses, and an indication of the prognosis, if cancer were identified. The
vignette culminated in a brief summary of information and asked the respondent whether they
would opt for diagnostic testing at that point, or defer or avoid investigation (the exact wording
being ‘YES – I would choose to be tested’ or NO - I would not want to be tested now’). After this
choice, participants were asked for the main reason for their decision, using a list of options that
were informed by qualitative interviews,16 questionnaires previously used in cancer research20 and
the cognitive interviewing phase. Participants could complete up to three vignettes. The first
vignette was randomly generated from all 12 possibilities, the second from the two remaining
cancers (eight possibilities), and the third from the remaining cancer (four possibilities). We also
collected participant characteristics, including age, sex, income, education, employment status,
ethnicity, experience of cancer, and convenience of the nearest main hospital.
Participants
4
Twenty-six general practices in three areas of England (Bristol & South Gloucestershire, Devon, and
the East of England) were recruited to include a broad range of urban and rural locations and varying
levels of socio-economic status. The practices had a mean list size of 11,615 patients (range 4,155 to
19,666) compared to an England mean of 6,919; their mean Index of Multiple Deprivation score was
18.2 (4.0-36.6) with an England mean of 21.5; and mean percentage of non-white British ethnicity of
4.7% (0.7-12.8) compared to an England and Wales figure of 12.1% (means from National Public
Health Observatory 2011, apart from ethnicity which is from the Office of National Statistics 2009).
In these practices, researchers in general practice waiting areas recruited attenders aged ≥40 at
different times of the day and week between December 2011 and September 2012. We conducted a
test-retest exercise in one additional practice using 48 similar volunteers who agreed to return two
weeks later, to complete identical vignettes to their first exercise. These participants were offered
£10 shopping vouchers.
Analysis
In addition to descriptive statistics, for the main question – whether or not to be tested – logistic
regression was used, with opting for investigation as the outcome variable. The explanatory
variables were cancer site, risk level (as a continuous variable), age group, sex, ethnicity, income
band, education, employment, previous diagnosis of cancer, cancer diagnosis in a family member or
close friend, convenience of hospital, and travel time to hospital. This analysis used only the first
completed vignette from each participant, since this was available for all participants and thus
avoided possible differential selection bias for subsequent vignettes.
Separate models were developed for each cancer, using all (first, second or third) responses for that
cancer. As participants completing multiple vignettes always had a different cancer for the later
vignettes, concerns about selection bias in the analysis of each cancer separately were eliminated.
Initially, each possible explanatory variable entered univariable analysis to establish the strength of
the relationship between it and opting for investigation, and those with a p-value<0·2 were retained
for multivariable analysis. The first multivariable model contained only those variables with a
univariable p-value<0·05; we then added the other variables sequentially, repeating the process
until only variables with p<0·05 were present, after adjusting for all other variables in the model. A
supplementary analysis used k-fold cross validation with risk level as the only predictor variable in
the base model and all four of the other explanatory variables in Table 4 as additional predictors.
We tested these sequentially, omitting variables in turn that did not appear to contribute to the
model. We considered the impact of missing data by omitting from the regression models any
variables with more than an extremely small percentage of missing values. We used intracluster
5
correlation coefficients to investigate the degree of clustering of the outcome variable across the 26
practices and the six researchers involved in data collection.
The test-retest analysis was undertaken on the first vignettes and used percentage comparisons for
participant characteristics and Kappa statistics for the vignette components.
Sample size
We estimated 80% of participants given a 10% risk vignette would opt for investigation, and 60% of
those at the 1% risk would do so. Using a two-sided 5% alpha and 90% power, this would require 119
participants in each group, or 1428 in total. In practice, the study was extremely popular, recruiting
at a much higher rate than expected: as our estimated effect sizes were very uncertain, we
continued the study to use our full researcher time.
Ethics approval
Ethics approval was given by NRES Committee South West – Southmead (ref 11/SW/0055).
Role of the funding source
This paper presents independent research funded by the National Institute for Health Research
(NIHR) Programme Grants for Applied Research programme, RP-PG-0608-10045. The views
expressed are those of the authors and not necessarily those of the NHS, the NIHR or the
Department of Health. The funders of this study had no role in: study design; data collection,
analysis, and interpretation; or the writing of this research paper. The corresponding author had full
access to all data and final responsibility for the decision to submit for publication.
Results
A total of 3,469 participants took part, completing 6,930 vignettes; 1415 (29%) declined to
participate. The characteristics of the participants are shown in Table 2. The age/sex profile of
responders is similar to that of the consulting population in England, though compared with the
population of England as a whole the sample was low on men aged 40-59 (17% versus 27% ), high on
women aged 60-69 (15% versus 11%), and high on all aged 70 and over (29% versus 24%). The
respondents were largely white British, nearly half were retired, and 15% had previously been
diagnosed with cancer, which compares with an estimate of 13% of the over-65 UK population.21
Missing data were minimal; most categories were between <1%-2% with the only exception being
income at 15%.
Table 3 gives the proportion of respondents who indicated that they would opt for investigation,
given the scenario presented to them. Overall, 88% of participants opted for investigation; this was
slightly lower in the lowest risk (1%) group and higher in the highest risk (10%) group, but the
difference was small and largely explained by a risk gradient in colorectal cancer. This pattern was
consistent across responses to the first, second, and third vignettes.
6
The results of the logistic regression analysis, combining all three cancers and controlling for
participant characteristics, confirmed these findings. The overall odds ratio (OR) for a one
percentage point increase in risk was 1·02 (95% CI: 0·998 to 1·06; p=0·189): participants were, in
general, only slightly more likely to opt for investigation the higher the risk that the symptoms
indicated cancer. For lung and pancreatic cancer, compared with colorectal, the odds ratios were
2·66 (95% CI: 1·99 to 3·56) and 1·96 (95% CI: 1·48 to 2·60) respectively, indicating that participants
were more likely to opt for investigation for lung and pancreatic cancers than for colorectal cancer.
There was no evidence of an overall interaction between risk and cancer site (p value = 0·183) but
the models for the individual cancers (Table 4) indicate that in the case of colorectal cancer risk did
have an effect on whether to opt for investigation (OR 1·08; 95% CI:1·03 to 1·13; p=0.001). Age
appears in all three models, with a similar influence: those aged 60-69 were more likely to opt for
investigation than those aged 40-59, and those in the oldest group (70+) least likely to opt for
investigation.
Further investigation into whether attitude to risk was affected by age revealed weak evidence of a
difference overall (p-value of interaction between risk and age 0·10), with notable variation across
the different cancers. For instance, in colorectal and pancreatic cancers, when controlling for all
other factors, participants in the youngest age group (40-59) were more likely to opt for
investigation the higher the risk (OR 1·07; 95% CI: 1·01 to 1·13 for colorectal and OR 1·10; 95% CI:
1·01 to 1·17 for pancreas). Conversely, participants in the oldest group (70+) were less likely to opt
for investigation the higher the risk for lung and pancreatic cancers (OR 0·96 95%; CI: 0·88 to 1·04 for
lung and OR 0·93; 95% CI: 0·87 to 1·01 for pancreas), though the latter confidence intervals were
wide, and include the null value. Other variables associated with increased likelihood of opting for
investigation were: shorter travel times to testing centre (colorectal and lung), a family history of
cancer (colorectal and lung), and higher household income (colorectal and pancreas).
The k-fold cross validation results for all three cancer sites produced final models including the same
variables as those in the original models, with almost identical regression coefficients (not shown,
but available from authors). Table 5 shows the distribution of participants’ responses for each of the
variables identified in the logistic regression. We examined the potential bias of missing data in
relation to income by omitting the variable from the two final models in Table 4 with almost
identical results for risk level and the other variables. We found negligible intracluster correlation of
the preference for investigation general practice and researcher for all vignettes overall and for
each cancer site separately.
7
The main reasons cited by participants (Table 6) opting for investigation in vignette 1 were: ‘peace of
mind’ (41%), ‘early detection’ (39%), and ‘family history’ (10%), with minimal variation across the
three cancers. The main reasons cited by those choosing not to be investigated were: ‘low risk of
cancer’ (26%), ‘low risk at my age’ (19%), and ‘rather not know’ (13%). There was much greater
variation across the cancers in the no responses, with much higher proportions citing ‘unpleasant
test’ and ‘harmful test’ for colorectal (19% and 11% respectively) compared with lung and pancreas,
which was ≤3% in both categories.
Test-retest
The primary research question of whether the participant chose to undergo diagnostic tests for
cancer showed excellent test-retest consistency, with a Kappa statistic of 0·878 (>0·75=excellent).
Participants’ reasons for their choice produced Kappa statistics of 0·584 (yes) and 0·667 (no), which
are both in the fair to good range (0·4-0·75).22 The social and economic status data demonstrated
reliable test-retest consistency: six out of 10 questions returned >90% agreement, three were
between 80% and 89% and the lowest (hospital travel time) was 69%.
Discussion
To our knowledge this is the first study of public preferences for cancer investigation. It showed that
88% of participants would opt for investigation given a realistic scenario of symptoms, along with
the risk of cancer these symptoms posed, plus a description of the relevant investigation and likely
outcomes. Despite the strong preference for testing, a risk gradient was still evident. Although this
risk gradient was identified in the analysis incorporating all three cancers, it was primarily driven by
the colorectal findings, where participants appeared to make a trade-off between the invasiveness
of the colonoscopy and the risk of cancer. Age was also influential, with the preference for
investigation highest in the age group 60-69 and lowest in those aged 70+.
The main results
The most striking finding was the appetite for testing. This far exceeds what is actually being offered
in the NHS, and bears comparison with Slevin et al who found that cancer patients were more likely
than clinicians to choose chemotherapy, even when benefits were minimal.23 It is possible
participants simply opted for a free test – why not? – with some evidence for this in the lack of
differentiated responses at low and high risks for lung and pancreas cancer. This could indicate that
the vignettes were insufficiently sensitive to different risk levels. However, the demonstrable
differences by risk gradient for colorectal cancer and by age group suggest that this was a considered
response. Our four examples for colorectal cancer all met current NICE guidance (because of the six
weeks of diarrhoea), though there are many low-risk (1-5%) symptoms that do not meet NICE
guidance.10, 11 For lung the position is similar, in that persistent cough (defined as three weeks or
8
greater) is recommended by NICE for a chest X-ray. Again, many symptoms of lung cancer fall into
the 1-5% bracket, but only meet NICE recommendations if present for three weeks.5,
18, 24
It is
debatable if any of the pancreas scenarios used in this study meet current NICE guidance (which
largely concentrates on jaundice). Even with these caveats, comparing most patients opting for
investigation at even a 1% risk of cancer with a conversion rate of 11%7 in the two-week clinics
leaves a considerable gap. Using the 11% figure is a little misleading, as an average conversion rate
means that some patients whose risk is below that figure have been selected for investigation.
Nonetheless, the current (unpublished) threshold risk figure for investigation of possible cancer
must be well in excess of 1%.
The survey is also instructive about the referral process and the GP-patient relationship. NICE
guidelines, as well as giving referral guidance, emphasise the value and importance of including the
patient in the decision-making process for referral and diagnostic testing for cancer – a recognition
that effective communication between GP and patient is a key dimension of an appropriate
referral.25 The way that participants engaged with this study, the subtle variations in participant
preferences, and the high participant numbers, suggest that GPs can have greater confidence in
engaging in a dialogue with patients about the meaning of symptoms and the risk of cancer. We
know that GPs can underestimate the degree to which patients want information and involvement
around decision-making26 and that decisions are sometimes made on a perception of patient
preference,27 but our data and experience show there is a willingness within a significant proportion
of the population to think about symptom meaning, personal risk and the possibility of cancer. It is
this kind of internal dialogue that could be used in the consulting room and turn aspirations about
patient involvement into a reality. Our experience shows that ‘fear of cancer’ does not necessarily
translate into a fear of talking about cancer.
Strengths and weaknesses
The use of hypothetical vignettes has methodological strengths and weaknesses. Much of the
debate around their use centres on the degree to which responses can be used as accurate
measures of views and behaviour, with the correlation between vignette response and actual
behaviour being questioned.28 Conversely, several studies have demonstrated that vignette
responses are useful indicators of behaviour and compare favourably with other methods of
assessing preferences and intentions e.g., Peabody and colleagues.29 The method has been widely
used in the investigation of medical choice and judgement e.g., Jiwa and colleagues.30 Many of the
participants had not experienced referral for cancer testing and the vignettes provided a means of
eliciting preferences in the absence of direct experience.
9
Any questionnaire survey is only useful if the questions are realistic, and the responses thoughtful.
We tried to maximise realism in the vignettes, and to make the percentage risk understandable by
presenting it numerically and pictorially, using suggestions from our two rounds of cognitive
interviewing. Whether the overall high level of opting for investigation was driven by the symptom
burden (which worsened with higher risk levels) or by the risk level itself, or by the combination, we
cannot know, though the last of these interpretations appears closest to clinical reality. We were
realistic in our description of the three first-line investigations (colonoscopy, chest X-ray and CT
scanning), including their requirements and possible hazards (largely relevant to colonoscopy with
its need for bowel preparation and the very small risk of perforation). Since the study began, the
SIGGAR study31 has suggested CT colonography may be as accurate as colonoscopy: it is possible that
more participants would have opted for investigation had this been available. We made it clear that
earlier diagnosis may not reduce the chance of death from lung and pancreas cancers, emphasising
that most patients would die of their disease, though prompt diagnosis could allow benefit from
palliative care. As to the reliability of the responses, the test-retest analyses demonstrated
consistent responses. We would also point to the responses given around the reasons for choice as
indicating that participants responded reflectively; the subtle variations around the type of test, the
risk and the age of respondents demonstrated an engagement with the differing components of the
vignette.
This was a large study (which greatly exceeded its recruitment targets as the format proved
particularly popular with participants) which recruited from urban/rural and wealthy/deprived
locations. A recruitment rate of 71% is good for a questionnaire survey. Although our target
population was the general UK population susceptible to cancer (adults ≥40) we made a pragmatic
decision to recruit from general practice waiting areas. This enabled us to access a large group of
people face-to-face about a sensitive health-related subject; moreover, a health care setting
provided the time, space and privacy for respondents to complete the questionnaire thoughtfully.
There is little published data on the demographics of the primary care attending population. The
proportion with a past history of cancer in our sample (15%) is similar to the estimated proportion in
the UK population of >65s (13%), and as our sample over-represented >70s the figures may be very
similar. This was not the case for ethnicity, where the non-white proportion was clearly smaller.
There can be ethnic differences in cancer survival, but it was beyond the scope of the study to
examine this.
Implications for policy and practice
There is a large disparity between NICE recommendations and NHS provision in terms of cancer
diagnostic pathways, and patient preferences as elicited in this sample – which we recognise under-
10
represents non-white people. This should influence the ongoing revision of NICE guidance. In terms
of clinical practice our findings can also provide a springboard for thinking about the referral
decision-making. If more patients can be drawn into a full dialogue about preference, risk and
decision-making with their GP then this could go some way toward creating a more effective referral
pathway from primary care.
Contributors
JB, LB, WH, SH, TJP and FW had roles in the design, conduct and management of the study. JB, SH,
WH and TJP had roles in the analysis and interpretation of the data. JB, LB, SH and WH contributed
to the first drafts of the paper and TJP and FW made critical revisions.
The authors fulfil the four criteria for authorship in the ICMJE recommendations.
Conflicts of interest
WH is the clinical lead for the ongoing revision of the NICE 2005 guidance. His contribution to this
article is in a personal capacity, and is not to be interpreted as representing the view of the
Guideline Development Group, or of NICE itself. The remaining authors have no conflict of interest
relevant to this research paper.
Acknowledgments
The authors would like to acknowledge the contribution to the research presented in this paper
made by the Discovery Programme Steering Committee comprising: Roger Jones (chair); Clare
Bankhead; Alison Clutterbuck; Jon Emery; Ardiana Gjini; Joanne Hartland; Maire Justice; Jenny
Knowles; Helen Morris; Richard Neal; Peter Rose; Greg Rubin. We would also like to thank: Catherine
Stabb (Exeter), and East of England Primary Care Research Network, who recruited non-Bristol
participants; and Bristol Software Partners who developed the software for the iPad application used
to collect data.
Study protocol
http://www.discovery-programme.org/pdfs/PIVOT%20protocol%20version%201%2001.11.2010.pdf
Panel: Research in context
Systematic review
We searched the background literature for this study using OvidSP between 21.11.2011 and
12.12.2012 using the following MeSH terms ‘patient preference’, ‘decision making’, ‘cancer’,
‘primary health care’, and ‘early diagnosis’. We did not restrict our searches by date. We were
unable to find any studies which were directly comparable to our research and, therefore, much of
the literature that we have used to situate the rationale and contribution of our study is around the
early diagnosis of cancer literature which has developed in recent years. The Discovery team have
made a number of contributions to this literature and regularly monitor updates and there have
been no further relevant contributions since the original searches.
Interpretation
Our study showed a clear preference by members of the public for cancer investigations across a
range of potential risk levels. Only in the case of colorectal cancer, with its invasive method of
testing, was there clear evidence of a gradient linking preference for testing to risk level: even then it
11
remained above 80%. This study brings the voice of the public and patients directly into the ongoing
redesign of diagnostic pathways into and out of primary care for cancer in the UK. At the
consultation level, the way that people engaged with the survey and the cancer symptom vignettes
highlight public willingness to discuss and contemplate risk of cancer and testing potentially allowing
a more patient-centred primary care consultation and decision-making process.
12
Table 1. The vignette symptom profiles
Colorectal
Lung
Pancreas
All symptoms are 6 weeks duration
1%
2%


Diarrhoea on most days
Diarrhoea and stomach pain
most days


Coughing most days
More tired than normal



Coughing most days
A little out of breath
walking up hills
You have lost a few
pounds In weight


5%


10%




Unusually tired for the last six
weeks
Your GP does a blood test
which shows you are anaemic


Coughing most days
You have coughed blood
once

Intermittent bleeding from
the back passage (rectal
bleeding)
Your GP does a blood test
which shows you are anaemic


Coughing most days
You have coughed blood a
few times
You have lost ½ stone in
weight


13


Some stomach pain on
most days
You’ve lost a few pounds
in weight
Continuous pain in your
stomach
You’ve lost ½ stone in
weight
Continuous pain in your
stomach
You’ve lost ½ stone in
weight
Continuous pain in your
stomach
You’ve lost 1 stone in
weight
Table 2. Participant characteristics (n=number of complete responses)
Age group (years)
n=3452
Sex
n=3461
Annual Income
n=2958
Ethnicity
n=3453
Education
n=3388
Employment
n=3446
Cancer diagnosis – self
n=3463
Cancer – family/ close
friend
n=3465
Convenience of hospital
n=3461
Travel time to hospital
n=3463
40-59
60-69
70+
missing
male
female
missing
<£10,000
£10,000 - £25,000
>£25,000
missing
White British
Other
missing
None
GCSE or equivalent
Vocational / ‘A’ level
Degree and higher
missing
Retired
Not in paid employment
Working part time
Working full time
missing
Yes
No
missing
Yes
No
missing
Very convenient
Quite convenient
Quite inconvenient
Very inconvenient
missing
<0·5 hour
0·5 – 1 hour
>1 hour
missing
14
Number
1519
945
988
17
1457
2004
8
720
1166
1072
511
3,096
357
16
1,001
781
850
756
81
1,673
379
607
787
23
522
2941
6
2597
868
4
1,388
1,621
323
129
8
1,759
1,458
246
6
Percentage
44
27
28
<1
42
58
<1
21
34
31
15
89
10
<1
29
23
25
22
2
48
11
17
23
1
15
85
<1
75
25
<1
40
47
9
4
<1
51
42
7
<1
Table 3. Number (%) choosing to be investigated by cancer and risk level
Colorectal
Lung
Pancreas
All three cancers (first
vignette only)
Risk
level
Number of
responses
Number (%)
choosing to
be tested
Number of
responses
Number (%)
choosing to
be tested
Number of
responses
Number (%)
choosing to
be tested
Number of
responses
Number (%)
choosing to
be tested
1%
572
462 (81%)
581
533 (92%)
582
525 (90%)
898
782 (87%)
2%
569
485 (85%)
571
531 (93%)
580
527 (91%)
838
738 (88%)
5%
580
496 (86%)
589
543 (92%)
572
526 (92%)
873
764 (88%)
10%
570
508 (89%)
582
537 (92%)
582
529 (91%)
860
768 (89%)
2291
1951 (85%)
2323
2144 (92%)
2316
2107 (91%)
3469
3052 (88%)
15
Table 4. Multivariable analysis for each cancer separately
Colorectal (colonoscopy)
Variable (reference category*)
OR
95% CI
p-value
Risk
1·08
(1·03 to 1·13)
0·0001
Age (40-59)*
1
Lung (chest x-ray)
OR
0·0347
95% CI
1
Pancreas (Ultrasound / CT scan)
p-value
OR
<0·0001
1
95% CI
<0·0001
60 – 69
1·29
(0·92 to 1·82)
1·32
(0·86 to 2·03)
2·56
(0·94 to 7·00)
70+
0·81
(0·59 to 1·11)
0·54
(0·38 to 0·76)
0·35
(0·13 to 0·99)
Travel time (<0·5 hr)*
1
0·0004
1
0·0032
0·5 – 1 hr
0·78
(0·59 to 1·03)
0·93
(0·67 to 1·30)
>1 hour
0·39
(0·22 to 0·68)
0·41
(0·25 to 0·67)
Family cancer (yes)*
1
No
0·72
Household Income (<£10,000)*
1
£10,000 - £25,000
>£25,000
0·0266
(0·53 to 0·96)
1
0·55
0·0006
(0·40 to 0·77)
1
0·0025
0·0001
1·31
0·95 to 1·81)
2·63
(0·97 to 7·16)
1·85
(1·26 to 2·71
3·80
(1·09 to 13·26)
16
p-value
Table 5. Number (%) choosing to be investigated by cancer and participant characteristics (variables identified in the multivariable analysis)
Colorectal
Number
of
responses
Number
(%)
choosing
to be
tested
Lung
Number
of
responses
Pancreas
Number
(%)
choosing
to be
tested
Number
of
responses
Number
(%)
choosing
to be
tested
All three cancers (first
vignette only)
Number
Number
of
(%)
responses
choosing
to be
tested
Age group (years)
40-59
1,061
917 (86%)
1,076
1,004(93%)
1,083
1,002(93%)
1,519
1,372(90%)
60-69
641
563 (88%)
638
605(95%)
640
601(94%)
945
861(91%)
70+
580
463 (80%)
598
524 (88%)
583
496 (85%)
988
805 (81%)
2,282
1,943(85%)
2,312
2,133(92%)
2,306
2,099(91%)
3,452
3,038(88%)
1,204
1,052(87%)
1,224
1,143(93%)
1,220
1,126(92%)
1,759
1,586(90%)
0.5 – 1 hour
943
798(85%)
946
874(92%)
943
853(90%)
1,458
1,272(87%)
>1 hour
143
101(71%)
150
125(83%)
149
124(83%)
246
189(77%)
2,290
1,951(85%)
2,320
2,142(92%)
2,312
2,103(91%)
3,463
3,047(88%)
Travel time to hospital
<0.5 hour
Cancer – family/close friend
Yes
1,739
1,507(87%)
1,778
1,660(93%)
1,769
1,625(92%)
2,597
2,317(89%)
No
550
443 (81%)
545
484 (89%)
545
481 (88%)
868
733 (84%)
2,289
1,950(85%)
2,323
2,144(92%)
2,314
2,106(91%)
3,465
3,050(88%)
<£10,000
450
357 (79%)
445
403 (91%)
443
376 (85%)
720
595 (83%)
£10,000-£25,000
759
642 (85%)
770
715 (93%)
746
685 (92%)
1,166
1,035(89%)
>£25,000
806
721 (89%)
806
758 (94%)
825
777 (94%)
1,072
985 (92%)
2,015
1,720(85%)
2,021
1,876(93%)
2,014
1,838(91%)
2,958
2,615(88%)
Annual Income
17
Table 6 – Main reasons for choosing yes/no to testing
Main reason for answering yes:
n (%)
All cancers
Colorectal
Lung
Pancreas
723 (37)
872 (45)
212 (11)
63
(3)
47
(2)
10
(1)
20
(1)
4
(0)
1951 (100)
Colorectal
806
890
204
61
58
58
22
45
2144
Lung
(38)
(42)
(10)
(3)
(3)
(3)
(1)
(2)
(100)
832 (39)
877 (42)
195 (9)
66
(3)
62
(3)
43
(2)
21
(1)
11
(1)
2107 (100)
Pancreas
69
60
37
41
66
12
39
11
5
340
66
38
27
18
2
14
3
6
5
179
(37)
(21)
(15)
(10)
(1)
(8)
(2)
(3)
(3)
(100)
57
40
33
26
7
22
3
13
8
209
vignette 1 only
peace of mind
early detection
family history
my age puts me at risk
no reason given
test is straightforward
family/friend pressure
my lifestyle puts me at risk
Total
Main reason for answering no:
N (%)
1255 (41)
1191 (39)
306 (10)
107 (4)
77
(3)
56
(2)
34
(1)
26
(1)
3052 (100)
All cancers
low risk of cancer
low risk at my age
rather not know
no reason given
unpleasant test
early diagnosis would not help
harmful test
inconvenient
difficult to access hospital
Total
103
89
59
51
28
37
18
20
12
417
vignette 1 only
(25)
(21)
(14)
(12)
(7)
(9)
(4)
(5)
(3)
(100)
(20)
(18)
(11)
(12)
(19)
(4)
(11)
(3)
(1)
(100)
18
(27)
(19)
(16)
(12)
(3)
(11)
(1)
(6)
(4)
(100)
Web table 1 - Vignette content - all symptoms are six week duration
Lung
Pancreas
Colorectal
1% - Diarrhoea on most days
2% - Diarrhoea and stomach pain
most days
5% - Unusually tired for the last
six weeks
Your GP does a blood test
which shows you are
anaemic
10% - Intermittent bleeding
from the back passage
(rectal bleeding)
Your GP does a blood test
which shows you are
anaemic
Your GP tells you these symptoms could indicate bowel cancer. This type of cancer can respond well to treatment (usually an operation and chemotherapy) and
an early diagnosis can improve the outcome. A small number of patients need to have a colostomy (a bag on the abdomen) following treatment.
With these symptoms there is a 1%/2%/5%/10% risk of bowel cancer. On average, if 100/50/20/10 people have these symptoms, 1 of them will have cancer.
For the other 99/49/19/9, the symptoms will probably be caused by a bowel infection and the symptoms will settle. [Graphical example of risk omitted for space]
The best test is a colonoscopy. The day before the test you take a medicine that clears out your bowel. This will usually mean you can’t go to work, or carry out
your normal activities as you need to be close to a toilet. The test itself has to be done in a main hospital. You would be given a short sedative; then a doctor
puts a long telescope into your rectum to see along your bowel. The test takes about 2 minutes. You would be able to go home later that day, though you would
not be able to drive. There is a small risk with this test. In about 1 in a 1000 cases the telescope damages the bowel and the patient needs an operation to repair
it.
1% - Some stomach pain on
2% - Some stomach pain on most 5% - Continuous pain in your
10% - Continuous pain in your
most days
days
stomach
stomach
You’ve lost a few pounds in
You’ve lost ½ a stone in
You’ve lost ½ stone in
You’ve lost 1 stone in
weight
weight
weight
weight
Your GP tells you these symptoms could indicate pancreas cancer. The pancreas is located behind the stomach. This type of cancer is particularly difficult to treat.
Early diagnosis of pancreas cancer does not tend to improve the outcome.
With these symptoms there is a 1%/2%/5%/10% risk of pancreas cancer. On average, if 100/50/20/10 people have these symptoms, 1 of them will have
cancer. For the other 99/49/19/9 the symptoms will probably be caused by a stomach infection or small ulcer and the symptoms will settle. [Graphical example
of risk omitted for space]
The best test for pancreas cancer is an ultrasound scan. This will involve a visit to the X-Ray department of your nearest main hospital. A small instrument is
pressed to your stomach; it only takes a few minutes and is painless. If this shows abnormalities then you will need to come back for a 2 nd test which will usually
take place within a few days ….
The 2nd test is a CT scan which will involve lying on a couch while a machine shaped like a giant Polo mint passes over your body. The whole procedure takes an
hour or so and is also painless.
1% - Coughing most days
2% - Coughing most days
5% - Coughing most days
10% - Coughing most days
More tired than normal
A little out of breath
You have coughed blood
You have coughed blood a
walking up hills
once
few times
You have lost a few pounds
You have lost ½ stone in
In weight
weight
Your GP tells you these symptoms could indicate lung cancer. This is a difficult cancer treat but current evidence indicates that early diagnosis can improve
outcome in some cases.
With these symptoms there is a 1%/2%/5%/10% risk of lung cancer. On average, if 100/50/20/10 people have these symptoms 1 of them will have cancer. For
the other 99/49/19/9 the symptoms will probably be caused by a chest infection and the symptoms will settle. [Graphical example of risk omitted for space]
The best test for lung cancer is a Chest X-ray. To have the X-ray you would need to go to your nearest main hospital for a short appointment at the X-ray
department. During the X-ray you would stand in front of a machine with no clothes on the upper half of your body for a few minutes. The procedure is
completely painless.
19
Web figure 1- vignette example (colorectal 5%)
20
References
1.
Thomson CS, Forman D. Cancer survival in England and the influence of early diagnosis: what
can we learn from recent EUROCARE results[quest]. Br J Cancer 2009; 101(S2): S102-S9.
2.
Department of Health. Cancer Reform Strategy: Department of Health, 2007.
3.
Richards MA. The size of the prize for earlier diagnosis of cancer in England. Br J Cancer
2009; 101(S2): S125-S9.
4.
Hamilton W. Cancer diagnosis in UK primary care
Nature Clinical Oncology 2012; 9:
251-2.
5.
NICE. Referral Guidelines for suspected cancer. London: NICE; 2005.
6.
Weller D, Vedsted P, Rubin G, et al. The Aarhus statement: improving design and reporting
of studies on early cancer diagnosis. British Journal of Cancer 2012; 106(7): 1262-7.
7.
National Audit Office. Delivering the cancer reform strategy. London, 2010.
8.
Elliss-Brookes L, McPhail S, Ives A, et al. Routes to diagnosis for cancer - determining the
patient journey using multiple routine data sets. Br J Cancer 2012; 107: 1220-6.
9.
Meechan D, Gildea C, Hollingworth L, Richards MA, Riley D, Rubin G. Variation in use of the
2-week referral pathway for suspected cancer: A cross-sectional analysis. British Journal of General
Practice 2012; 62(602): e590-e7.
10.
Hamilton W. Cancer diagnosis in primary care. Brit J Gen Pract 2010; 60(571): 121-8.
11.
Shapley M, Mansell G, Jordan JL, Jordan KP. Positive predictive values of >= 5% in primary
care for cancer: systematic review. British Journal of General Practice 2010; 60(578): 681-8.
12.
Hubbard G, Kidd L, Donaghy E. Preferences for involvement in treatment decision making of
patients with cancer: A review of the literature. European Journal of Oncology Nursing 2008; 12(4):
299-318.
13.
Marshall DA, Johnson FR, Phillips KA, Marshall JK, Thabane L, Kulin NA. Measuring Patient
Preferences for Colorectal Cancer Screening Using a Choice-Format Survey. Value in Health 2007;
10(5): 415-30.
14.
Bosompra K, Flynn BS, Ashikaga T, Rairikar CJ, Worden JK, Solomon LJ. Likelihood of
Undergoing Genetic Testing for Cancer Risk: A Population-Based Study. Preventive Medicine 2000;
30(2): 155-66.
15.
Bottorff JL, Ratner PA, Johnson JL, Lovato CY, Joab SA. Communicating cancer risk
information: the challenges of uncertainty. Patient Education and Counseling 1998; 33(1): 67-81.
16.
Birt L, Hall N, Mills K, Banks J, Emery J, Walter FM. Appraisal and help seeking decisions
among patients with symptoms suspicious of lung cancer: a qualitative investigation. Royal College
of General Practitioners Annual Conference. Harrogate; 2013.
17.
Hamilton W, Lancashire R, Sharp D, Peters TJ, Cheng KK, Marshall T. The risk of colorectal
cancer with symptoms at different ages and between the sexes: a case-control study. BMC Medicine
2009; 7.
18.
Hamilton W, Peters TJ, Round A, Sharp D. What are the clinical features of lung cancer
before the diagnosis is made? A population based case-control study. Thorax 2005; 60: 1059-65.
19.
Stapley S, Peters TJ, Neal RD, Rose PW, Walter FM, Hamilton W. The risk of pancreatic
cancer in symptomatic patients in primary care: a large case-control study using electronic records.
British journal of cancer 2012; 106(12): 1940-4.
20.
Avery KN, Metcalfe C, Vedhara K, et al. Predictors of attendance for prostate-specific antigen
screening tests and prostate biopsy. European urology 2012; 62(4): 649-55.
21.
Maddams J, Brewster D, Gavin A, et al. Cancer prevalence in the United Kingdom: estimates
for 2008. Br J Cancer 2009; 101(3): 541-7.
22.
Landis J, Koch G. The measurement of interobserver agreement for categorical data.
Biometrics 1977; 33: 159-74.
23.
Slevin ML, Stubbs L, Plant HJ, et al. Attitudes to chemotherapy: comparing views of patients
with cancer with those of doctors, nurses, and general public. Brit Med J 1990; 300: 1458-60.
21
24.
Hippisley-Cox J, Coupland C. Identifying patients with suspected lung cancer in primary care:
derivation and validation of an algorithm. Br J Gen Pract 2011; 61(592): e715-23.
25.
Jiwa M. Referral from primary to secondary care. Brit Med J 2010; 341.
26.
Elwyn G, Edwards A, Kinnersley P. Shared decision-making in primary care: the neglected
second half of the consultation. Brit J Gen Pract 1999; 49: 477-82.
27.
Little P, Dorward M, Warner G, Stephens K, Senior K, Moore M. Importance of patient
pressure and perceived pressure and perceived medical need for investigations, referral, and
prescribing in primary care: nested observational study. Brit Med J 2004; 328.
28.
Morrell DC, Roland MO. Analysis of Referral Behaviour - Responses to Simulated CaseHistories May Not Reflect Real Clinical Behavior. Brit J Gen Pract 1990; 40(334): 182-5.
29.
Peabody JW, Luck J, Glassman P, Dresselhaus TR, Lee M. Comparison of vignettes,
standardized patients, and chart abstraction - A prospective validation study of 3 methods for
measuring quality. Jama-J Am Med Assoc 2000; 283(13): 1715-22.
30.
Jiwa M, Gordon M, Arnet H, Ee H, Bulsara M, Colwell B. Referring patients to specialists: A
structured vignette survey of Australian and British GPs. Bmc Fam Pract 2008; 9.
31.
Atkin W, Dadswell E, Wooldrage K, et al. Computed tomographic colonography versus
colonoscopy for investigation of patients with symptoms suggestive of colorectal cancer (SIGGAR): a
multicentre randomised trial. The Lancet 2013; 381(9873): 1194-202.
22