Download Accuracy of natriuretic peptides levels in the diagnosis of left

Accuracy of natriuretic peptides levels in the
diagnosis of left ventricular dysfunction –
Systematic review
Pontes J.,
[email protected]
Almendra R.,
[email protected]
Carvalho J.,
[email protected]
Moreira C.,
[email protected]
Martins A.,
[email protected]
Afonso A.,
[email protected]
Leitão M. A.,
[email protected]
Rodrigues G.,
[email protected]
Gaspar R.,
[email protected]
Lima S.,
[email protected]
Martinho C.,
[email protected]
Correia F.
[email protected]
Adviser: Almeida F., [email protected] Class: 11
Oporto medical faculty, 2007
Abstract
Introduction Echocardiography is a common tool in the diagnosis of left ventricular
dysfunction (LVD) but recent clinical and experimental studies also report the role of
Brain Natriuretic Peptides in the diagnosis of this pathology.
Aim To evaluate the accuracy of the brain natriuretic peptide levels in the diagnosis of
systolic LVD when compared to echocardiography.
Methods A standard systematic review methodology was followed. Published literature
was searched through the PubMed and Cochrane Library electronic databases.
Inclusion and exclusion criteria were applied. 23 articles (12,082 patients) were
analyzed.
Results In BNP studies, 11 of 16 had sensitivities lower than 71% and 6 of 16 studies
had specificities lower than 77%. 5 of 10 NT-proBNP studies had sensitivities lower
than 88% and 4 of 10 studies had specificities inferior to 68%. In 9 articles analysing
BNP, with an interval of cut-offs from 19.2 to 100pg/ml, it was verified significant
differences in what concerns to specificity. In a cut-off’s interval from 20 to 75pg/ml, the
accuracy was inconsistent. The pooled of LR- were heterogeneous (p<0.05).
Discussion Our results suggest that the diversity of cut-off points is a source of
heterogeneity in the accuracy of both tests.
Conclusion BNP and NT-proBNP tests appear to have high sensitivity and they might be
helpful in the ruling out of systolic LVD.
Key words Left Ventricular Dysfunction, Brain Natriuretic Peptide, Sensitivity and
Specificity
Introduction
Heart failure (HF) is a pathophysiologic state in which the heart is unable to pump
blood at a rate commensurate with the requirements of the metabolizing tissues [1].
Nowadays, heart failure, such as left ventricular dysfunction (LVD), is a major health
problem, especially in developed countries, where it is associated with coronary artery
disease, obesity and hypertension [2]. HF is the most common cause of hospitalization
due to cardiovascular disease in patients over 65 years [3] and the number of HF deaths
has increased steadily despite advances in treatment. The clinical diagnosis of heart
failure or left ventricular dysfunction is complex, especially in the presence of other
pathologies such as respiratory disease or obesity [4, 5]
The echocardiography is the common test used to diagnosis LVD, but the access to
.
population is limited, especially in primary care [6] Its restricted availability and high
costs prohibit its use as a general screening test [7]. Electrocardiogram (ECG) is an
alternative method to diagnosis HF, but it is insensitive and non-specific.
Most recently, a new diagnostic test has been used for LVD: the measurement of the
blood levels of Brain Natriuretic Peptides (BNP) [8]. The BNP is the most relevant in
the diagnosis of HF, because it’s secreted rapidly and has a longer half-time in
circulation [8]. BNP is synthesized as a larger inactive molecule, the proBNP, which is
cleaved in two molecules: an active hormone, BNP, and a biologically inactive Nterminal peptide fragment, NT-proBNP [9]. BNP is produced constantly by ventricular
cells in response to heart normal function, but an increased myocardial wall stress
induces the production of higher concentrations of BNP [10].
The aim of this study is to evaluate the accuracy of brain natriuretic peptides in the
diagnosis of systolic LVD when compared to echocardiography or radionuclide
ventriculography.
Methods
Data search
We conducted a systematic review of studies on the diagnosis accuracy of BNP and
NT-proBNP levels in the Cochrane Central Register of Controlled Trials (CENTRAL) at
The Cochrane Library and in the Medline database.
The Medline search was made in Pubmed using the MESH terms: "Ventricular
Dysfunction, Left", "Heart Failure, Congestive"; "Natriuretic Peptide, Brain";
"Sensitivity and Specificity"; "ROC Curve" "clinical trials"; and the terms (as text
words): "Cardiac failure"; "Cardiac dysfunction"; "Heart dysfunction"; "BNP"; "NTproBNP"; "Accuracy"; "Likelihood ratio" and "Predictive value".
The search in the Cochrane Library was made using the same MESH terms and text
words used in the Pubmed search. Both searches were concluded until February 2007.
Inclusion and exclusion criteria – articles selection
2
In an initial phase the titles and abstracts of the articles were reviewed to identify all
potential studies, without making restrictions to the time of publication. Full text
versions were obtained, if considered necessarily. This task was performed by six groups
of two reviewers bearing in mind the following inclusion criteria: (1) Being written in
English, Portuguese, French or Spanish; (2) Publications on the accuracy or sensitivity
and specificity of BNP levels in the diagnosis of systolic left ventricular dysfunction; (3)
To compare the diagnostic accuracy of NTproBNP or BNP to the gold standard for
diagnosing
the
heart
failure,
such
as
echocardiography
and
radionuclide
ventriculography.
In the second phase we performed the exclusion of studies. This task was realized by
two groups of three reviewers, having read the methods section of each study and
applied the exclusion criteria. These were: (A) To evaluate diastolic dysfunction; (B) To
be limited to very restrictive study groups such as patients with Duchenne disease;
Chagas disease or Brugada syndrome; (C) To be performed in non human population;
(D) To associate the cardiac failure to congenital or hereditary diseases.
The selection of the articles was only made under the overall reviewers’ approval. In
case of disagreement, a third reviewer would interview.
The articles which the complete text was not found were excluded.
Assessment of study quality
Two reviewers assessed the quality of each included trial according to the QUADAS
tool [11]: (I) To compare with an independent appropriate gold standard, (II) To include
patients who cover a wide patient spectrum likely to be encountered in a usual clinical
practice setting, (III) To interpret the index test result without the knowledge of gold
standard, and vice-versa, (IV) To prospectively recruit consecutive patients suspected to
have the disease of interest.
Data Extraction
For each study selected, two reviewers extracted data independently. Data on year of
publications, spectrum of patients, sensitivity, specificity and predictive values,
diagnosis accuracy and type of assay were extracted from original articles. The
information was then reunited in order to confirm the data extracted.
Data aggregation and analysis
3
We used SPSS 14.0 Data Editor statistical software to calculate mean of ages,
sensitivity, specificity, positive and negative predict values and scatters plots, as well as
measures of dispersion for this variables and a linear regression between accuracy and
patients’ age. We made SROC curves, Forest plots and calculated Likelihood ratios
using Metadisc software, in order to make an aggregation of the data.
Concordance test- Kappa’s test
In order to calculate the agreement between reviewers in the articles’ selection, we
used the Kappa’s test. This test measures the quality of the method in what concerns to
objectivity and impartiality in the article’s selection. This test is useful as it allow us to
understand if the criteria defined were well chosen and also if the methodology followed
was the most appropriated [12].
Results
Articles characteristics
Of 789 potentially relevant publications, 34 met our inclusion criteria. 6 were
excluded as they were not found and other 5 had missing data. So, 23 articles were
included in this systematic review (Figure 1).
The main characteristics of the studies selected are summarized in table 1. All
publications were written in English.
14 studies were cohorts, 5 were transversals, 4 were randomized controlled trials and
1 was a prospective study. The studies ranged from 41 to 2193 patients. A total of
12,082 participants were included in our study.
4
789 Articles identified and screened for retrieval
686 Articles
without all
inclusion criteria
103 Articles retrieved for more detailed evaluation
69 Articles with an
exclusion criteria
Potentially apropriate 34 articles to be included
6 Articles not
found
28 Full articles read
5 Articles
excluded
(missing data)
Analized and extracted data from 23 included articles
Figure 1 - Flow diagram for the selection of studies included in this systematic review.
14 articles used BNP test to diagnoses LVD, while 5 used NT-proBNP and 4 used
both peptides. 22 studies compared the natriuretic peptides with echocardiography and 1
compared with radionuclide ventriculography.
Patients’ characteristics
The sum of female patients, from 21 articles of the 23 included, was 6383 (53%) and
that of male patients was 4608. Patients´ mean age, of the 21 studies which provided
information about their participants’ mean age, ranged from 45 to 75 years old. Among
these, 4 studies had a mean age below 60 years old, which corresponds to 17% of the
participants involved in these studies.
In 14 studies that provided the data about the participants with HF, 1933 patients
were ill and 3959 weren’t. The most common symptom was dyspnoea, diagnosed in 7
studies, affecting, in mean, 71% of the participants. Some studies addressed the
prevalence of comorbilities, especially hypertension that affected 38% of the patients
(19 studies), ischemic heart disease affecting 12% of the patients (5 studies), 17% of
the patients had diabetes mellitus (16 studies) and 34% of patients smoked (8 studies).
5
References
Nº of
Nº of
participants
female
participants
Nº of
Nº of
Mean
patients
patients with
age
with
antecedents of
dyspnoea
hypertension
Nº of
patients
smokers
Nº of
patients with
antecedents
of diabetes
Anguita M. et al
247
116
70
247
158
125
68
Fuat A. et al
246
104
65,7
NR
NR
NR
NR
Steg PG. et al
709
392
66,44
709
469
NR
193
Nakamura M. et al
993
513
58
NR
460
128
82
Nakamura M., Sakai T. et al
856
485
65
NR
17
NR
NR
Bal L. et al
41
NR
NR
NR
NR
NR
NR
Gustafsson F. et al
367
198
68,8
326
68
NR
7
Zaphiriou A. Et al
306
176
74
NR
168
NR
58
Nueller T. et al
251
17
73
NR
141
NR
58
Hedberg P. et al
407
205
75
NR
115
215
31
Dokainish H. et al
122
60
56
52
60
49
54
Nielsen LS. et al
345
169
65
283
NR
NR
NR
Groenning BA. et al
672
382
68,1
219
169
237
43
Ng LL. et al
1331
579
63
NR
322
261
63
Sim V. et al
83
43
72
NR
NR
NR
NR
Vay M. et al
2193
2152
73
NR
26
42
12
Balli N. et al
167
48
53,72
NR
26
NR
NR
Wright SP. et al
305
198
72
149
159
NR
71
Wieczorek SG. et al
1050
NR
NR
NR
246
NR
NR
Hobds FD. et al
591
275
45
NR
232
351
68
Maisel A. et al
200
11
65,32
NR
130
NR
68
Yakamoto et al
466
210
65
NR
252
NR
70
Mcclure S. et al
134
50
67
NR
51
NR
24
NR, not reported
Table 1 - Patients’ demographics of the studies included.
Specificity and sensitivity
The specificity ranged from 35% to 98%. In 9 articles analysing BNP with an
interval from 19.2 to 100pg/ml, it was demonstrated significant differences in what
concerns to specificity. 2 of them demonstrated specificity below 45%, while 3 of them
presented specificity above 98%. 6 of 16 studies had specificities lowest than the mean,
77%. In more extreme values of cut-off, above 200pg/ml, the specificity was superior
in comparison with lower values of cut-off (beneath 50pg/ml).
The sensitivity of the BNP test decreased as the cut-off value erased in a general
way. 11 of 16 BNP studies had sensitivities higher than the mean, 76%. The value of
sensitivity ranged from 26% to 95%.
In the NT-proBNP test, the highest value of sensitivity was 100% and the minimum
was 73%. 4 of 10 NT- proBNP studies had sensitivities lowest than the mean, 88%, and
6
in 5 studies which provided the cut-off and the respective value of sensitivity, there’s
no constant reason between the augment of cut-off and the sensitivity of the test.
The specificity of the NT-proBNP test ranges from 35% to 92%. In 5 studies which
describes the cut-off value and the associated specificity, the value of specificity
increases with the augment of the cut-off, except in 1 study. 3 of 10 studies had
specificities inferior to the mean, 68%. The sensitivities and specificities for both tests
are described in the Table 3.
Positive and negative predictive value
5 of 10 BNP studies had a negative predictive value inferior to the mean, 85%, and
2 of 8 studies had a positive predictive value inferior to the mean, 92%. 5 of 9 NTproBNP studies had a negative predictive value lowest than the mean, 54%, and 5 of 9
studies had positive predictive value lowest than the mean, 37% (Table 3).
Negative
predictive
value
Positive
predictive
value
Specificity
Sensitivity
Type of peptide
BNP
NT-proBNP
Mean
N
0.75663
0.87950
16
10
Std. Deviation 0.175893
Mean
N
0.099176
0.76619
0.68150
16
10
Std. Deviation 0.188721
0.193018
0.54091
11
0.37433
9
Std. Deviation 0.361079
0.343924
0.84934
10
0.92125
8
Std. Deviation 0.149808
0.121589
Mean
N
Mean
N
Table 3 - Mean of positive and negative predictive values, sensitivity, specificity and their ranges.
More than one SROC curve was needed to describe the relationship between the
sensitivity and the 1-specificity, because the studies values of sensitivity and specificity
for the BNP test were heterogeneous (Figure 2). For the NT-proBNP test no SROC
curve was adjusted to the pooling of studies, due to the data’s heterogeneity (Figure 3).
7
Sensitivity
1
SROC Curve
Sensitivity
1
Symmetric SROC
AUC = 0,8271
SE(AUC) = 0,0491
Q* = 0,7600
SE(Q*) = 0,0446
0,9
0,8
0,8
0,7
0,6
0,6
0,5
0,5
0,4
0,4
0,3
0,3
0,2
0,2
0,1
0,1
0
0,2
0,4
0,6
0,8
0
1
Symmetric SROC
AUC = 0,5000
SE(AUC) = 0,0000
Q* = 0,5000
SE(Q*) = 0,0000
0,9
0,7
0
SROC Curve
0
0,2
1-specificity
0,4
0,6
0,8
1
1-specificity
Figure 2 – SROC curve of BNP test.
Figure 3 - SROC curve for NT-proBNP.
Negative Likelihood ratios were heterogeneous (p<0.05), indicating that the wide
range of cut-off points are a source of heterogeneity to the evaluation of the accuracy of
both BNP and NT-proBNP tests in the diagnosis of LVD (Table 4).
Type of
Pooled LR-(CI 95%)
peptide
P value of
Pooled LR+ (CI
P value of
heterogeneity*
95%)
heterogeneity*
NT-proBNP
0.283 (0.124 - 0.643)
0.000
2.079 (1.250 -3.458)
0.000
BNP
0.386 (0.246 – 0.606)
0.000
4.143 (1.995 – 8,604)
0.000
*p<0.05- statistically significant; CI- confidence interval; REM- random effects model; LR(-) – Negative Likelihood
ratio; LR (+) – Positive Likelihood ratio
Table 4 – Positive and Negative likelihood ratio of NT-proBNP and BNP tests.
An asymmetrical funnel plot is described in the forest plots of both diagnostic odds
ratio (DOR) for the BNP and NT-proBNP tests, which suggests the heterogeneity of
this tools in the diagnosis of systolic LVD (Figures 4 and 5).
Figures 4 and 5- Forest plots of the DOR for BNP and NT-proBNP tests.
8
Accuracy
The accuracy of BNP test was calculated in 8 studies. The accuracy ranged from a
minimum of 46% to a maximum of 92%. In a cut-off’s interval from 20 to 75pg/ml, the
accuracy is inconsistent: 71% (cut-off= 20pg/ml), 46% (cut-off= 50pg/ml), 80% (cutoff=52pg/ml) and 53% (cut off= 75pg/ml). For cut-off values higher than this interval,
the values for accuracy were greater and more approached (Figure 6).
Figure 6- Scatter plot between accuracy and the cut-off value.
Correlations
When relating the aging of patients to the accuracy of BNP test, there was a slightest
increase in the accuracy, however the results are relatively heterogeneous (Figure 7 and
Table 5).
Regression between age and accuracy
R
Adjusted R Std. Error of the
Model
R
Square
Square
Estimate
1
a
Figure 7 - Linear regression
0.500a
0.25
0.167
0.12943
-Predictors: (Constant), mean of ages of the participants
Table 5 - Output data.
of the relation between the
increase of patients’ age and
the accuracy of BNP test.
9
Degree of Concordance
According to the Kappa’s test result, the degree of concordance between the
reviewers ranged from 60% to 95%. In mean, the overall agreement surrounded the
78%.
Discussion
The diagnostic accuracy of BNP levels for systolic LVD has been recently reviewed
by Jaime et al [13]. In this systematic review, based on 52 studies, no tests analyzing
the accuracy of the NT-proBNP test were included, no gold standard was demanded as
base of comparison for the BNP test and studies with a wide variety of settings were
included, such as the emergency department. The studies included in this systematic
review were divided according to their reference standard and when this was the
systolic LVD, the conclusion was that the diagnostic accuracy of BNP test was poorer
than that of studies of heart failure. Jaime et al attributed this to the publication bias
which would be the explanation for the heterogeneity of the results and asymmetry of
the funnel plots. On the other hand, our systematic review included studies analyzing
the NT-proBNP test and the comparison of BNP or NT-proBNP tests to an appropriated
gold standard was a criteria required for the inclusion of the study. Our results suggest
that the variety of cut-off points is a source of heterogeneity in the accuracy of both
tests, as the pooled of negative LR is heterogeneous (p<0.05), which is not considered
in the Jaime et al review.
Significant limitations of the BNP and NT-proBNP tests were found: there is a wide
range of cut-off values; there are considerable differences in the specificity, sensitivity
and accuracy values for the same test between studies. As only high and good quality
classified studies were included in our systematic review (according to the QUADAS
tool), the source of heterogeneity which might explain the variety of sensitivities and
specificities for the BNP and NT-proBNP tests possibly can be in the low quality of the
methodology used by these studies in points that are not criteria of quality in the
QUADAS tool. We can also hypothesize that the main gold standard used,
echocardiography, it has itself limitations: it’s dependent on the user, on the patient’s
biotype and on the piece of equipment.
However it’s worth noting that both BNP and NT-proBNP, as tools for the diagnosis
of systolic LVD, appear to have high sensitivity (in mean, 76% for BNP and 88% for
10
NT-proBNP) and negative predictive values (in mean, 92% for the NT-proBNP and
84% for BNP), despite the heterogeneity. These results suggest that both natriuretic
peptides might be useful in the ruling out of systolic LVD. Although the number of
studies analysing the accuracy of NT-proBNP test it’s lower than those evaluating
BNP, NT-proBNP seems to be more sensitive and specific than the BNP test.
Our systematic review also faced difficulties: some studies didn’t present all the
information necessary for our statistical analysis, making more difficult the carry on of
a meta-analysis.
This review represents an up-to-date and comprehensive review of primary research
investigating the diagnostic accuracy of the natriuretic peptides (BNP and NTproBNP). It describes the problems associated with the conduction of studies heading
the evaluation of the accuracy of BNP test in the diagnosis of LVD, when trying to
synthesize primary research in this area as a result of clinical and methodological
heterogeneity.
Conclusion
We concluded that there is no consensus in what concerns to the most appropriated
value of cut-off. The degree of heterogeneity present in all but a few small sub-groups
of our included studies would mean that both the BNP and the NT-proBNP test are not
good diagnostic tests to the discrimination between patients with systolic LVD and
patients with no systolic LVD, when compared to echocardiography and radionuclide
ventriculography. However both BNP and NT-proBNP might be useful in the ruling out
of systolic left ventricular dysfunction. Further studies evaluating the accuracy and
limitations of brain natriuretic peptides, BNP and NT-proBNP, in the systolic LVD
would be necessary to understand these tools’ usefulness in the diagnosis of systolic
LVD.
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