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European Journal of Heart Failure 2006 8(4):390-399; doi:10.1016/j.ejheart.2005.10.004
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© 2006 European Society of Cardiology

Accuracy of B-type natriuretic peptide levels in the diagnosis of left ventricular dysfunction and heart failure: A systematic review

Jaime Latour-Péreza,b,*, Francisco Javier Coves-Ortsa, Carmen Abad-Terradoa, Víctor Abrairac,d and Javier Zamorac,d

a Servei de Medicina Intensiva, Hospital General Universitari d'Elx. Elx Spain
b Departament d'Infermeria Comunitaria, Medicina Preventiva i Salut Pública i Història de la Ciència, Universitat d'Alacant Sant Vicent del Raspeig, Spain
c Unidad de Bioestadística Clínica. Hospital Ramón y Cajal, Node of R_MBE research network (G03/90) Madrid, Spain
d Departamento de Matemática Aplicada (Biomatemática), Universidad Complutense. Madrid, Spain

* Corresponding author. Hospital General Universitari d'Elx. Servei de Medicina Intensiva, Camí Vell de l'Almàssera 11, 03203 Elx, Spain. Tel.: +34 96 667 9511; fax: +34 96 667 9108. E-mail address: jlatour{at}ua.es


   Abstract
Top
 Abstract
1. Introduction
 2. Methods
 3. Results
 4. Discussion
 Appendix A. Supplementary data
 References
 
Objectives: To evaluate the accuracy of B-type natriuretic peptide levels (BNP) in the diagnosis of heart failure and left ventricular dysfunction.

Data sources: Electronic search in Medline, Embase, Cochrane Library and Medion database, and hand search of reference lists.

Review methods: We have included published studies on the accuracy of BNP which had both sufficient information to construct the 2x2 diagnostic cross table and an appropriate spectrum of patients.

Results: Fifty five studies (16,730 patients) were analyzed. The main determinants of diagnostic accuracy were the reference standard analyzed (clinical heart failure versus left ventricular dysfunction), and the methodological quality of the study. BNP levels were highly accurate for the diagnosis of clinical heart failure (diagnostic OR=41; 95% CI 23–74). The negative likelihood ratios were homogeneous, and useful for excluding the existence of heart failure (pooled negative likelihood ratio=0.11; 95% CI 0.08–0.16). The studies focused on the identification of left ventricular dysfunction were heterogeneous, with indications of publication bias, and showed less overall diagnostic accuracy than studies focused on heart failure.

Conclusions: BNP levels are useful for ruling out heart failure. The accuracy of BNP for identifying patients with systolic dysfunction is more limited.

Key Words: Heart failure • Natriuretic peptides • Sensitivity and specificity • ROC curve • Systematic review • Meta-analysis

Received March 28, 2005; Revised June 15, 2005; Accepted October 3, 2005


   1. Introduction
Top
 Abstract
 1. Introduction
2. Methods
 3. Results
 4. Discussion
 Appendix A. Supplementary data
 References
 
The clinical diagnosis of heart failure (HF) or left ventricular dysfunction is complex, especially in the presence of other pathologies such as respiratory diseases or obesity [1,2]. Echocardiography is considered the gold standard for diagnosis of left ventricular dysfunction; however, limited availability and high cost prohibit its use as a general screening test [3,4].

The availability of commercial tests for B-type natriuretic peptide (BNP) for the diagnosis of HF or left ventricular dysfunction has raised expectations. In a recent pivotal study (Breathing Not Properly Multinational Study) the diagnostic accuracy of BNP for identifying patients with dyspnoea secondary to heart failure was greater than that of clinicians [5]. In this study, adding BNP to clinical judgment enhanced diagnostic accuracy from 74% to 81% [6]. Even more recently, Mueller et al. [7] showed that the rapid measurement of BNP in patients with acute dyspnoea in the emergency room reduces length of stay and total cost of treatment.

The value of the assessment of BNP levels for the diagnosis of heart failure or ventricular dysfunction has been analyzed in a number of studies [8]. However, despite all the available information about the diagnostic utility of BNP, some uncertainty still exists due to inconsistencies between studies. The explanation for these differences is not straightforward. We hypothesized that this heterogeneity in the accuracy of BNP may be related to several factors, these are the clinical setting (patients with dyspnoea versus asymptomatic patients), the reference standard (clinical heart failure versus left ventricular dysfunction), the type of assay used (point-of-care immunofluorometric test versus other) and the methodological quality of the study.

The objectives of this study are therefore (1) to estimate the accuracy of plasma BNP levels in the diagnosis of cardiac failure and/or left ventricular dysfunction by means of a systematic review of the literature and (2) to explore the possible sources of heterogeneity between studies.


   2. Methods
Top
 Abstract
 1. Introduction
 2. Methods
3. Results
 4. Discussion
 Appendix A. Supplementary data
 References
 
2.1. Data sources
A search was conducted for articles on the diagnostic accuracy of BNP levels in Medline, Embase, Cochrane Library (3rd edition 2003), and Medion Database. A manual review of the cited references in the recovered primary studies and review articles was also performed. We did not search for unpublished literature. Authors were contacted as necessary for further study details, but no additional studies were requested.

The Medline search (between 1966 and October 2004) was made in PubMed, using the terms: natriuretic, heart failure and related terms (cardiac failure, ventricular dysfunction), and sensitivity or specificity and their related terms (ROC, receiver operating characteristic, likelihood ratio, predictive value or accuracy). The search in Embase (between 1993 and October 2003) was based upon the MeSH term brain natriuretic peptide and any of the following terms (as text words): sensitivity, specificity, likelihood ratio, ROC, predictive or accuracy. The Medion search (1998-2002) was simple, using the descriptor DR (diagnostic reviews).

2.2. Inclusion and exclusion criteria
We included all publications on the accuracy of BNP in the diagnosis of HF or left ventricular dysfunction that had sufficient information to construct 2x2 diagnostic cross tables and which were published in English, French, German, Italian, Norwegian, Portuguese or Spanish. Studies using NT-proBNP were not included in the review.

We excluded any duplicated studies and studies limited to very restrictive subgroups, such as patients with Duchenne disease, Chagas disease, or Brugada syndrome. We also excluded studies with an inappropriate spectrum of patients (an appropriate spectrum was the inclusion of patients in which it was sensible to suspect the target disorder). For example, studies that excluded patients with demonstrated systolic dysfunction were considered to have an inappropriate spectrum, and were excluded from the review.

2.3. Data extraction
Data on study identification, year of publication, diagnostic cross table, spectrum of patients and methodological aspects were extracted from the original studies. When the study presented sensitivity, specificity and predictive values data, but not prevalence data, the 2x2 table was reconstructed by means of an iterative process. In the event that one of the cells of the cross table contained a zero value, 0.5 points were added to all the cells. When the article provided information on diagnostic accuracy at several cut-points, the cut-point that minimized the sum of false positive and false negatives was chosen.

The study population data incorporated the inclusion/exclusion criteria, type of assay (extractive or not extractive RIA, IRMA, or immunofluorescence) and the reference standard evaluated (cardiac failure versus left ventricular systolic and/or diastolic dysfunction).

The methodological quality of the individual studies was appraised using the QUADAS tool [9] and a modified check list from the Lijmer study [10].

Data extraction was carried out independently by two researchers (CAT, FCO). In the event of mismatching, the coding was done by consensus and, in the event that consensus was not reached, by a third appraiser (JLP).

2.4. Statistical analysis
Sensitivity, specificity, positive and negative likelihood ratios (LR) and diagnostic odds ratio (DOR), as well as their corresponding standard errors and confidence intervals, were calculated for each study. The statistical heterogeneity of DOR and the existence of publication bias were statistically and graphically studied [11]. The indexes were pooled, when possible, using a random effects model.

The regression model described by Littenberg and Moses [12-14] was employed to construct the summary ROC (SROC) curves and to assess whether the DOR was independent of the selected cut-point of the test (threshold effect). Additionally, this model was used to explore the sources of heterogeneity.

The analyses were carried out using the statistical software StatsDirect (version 2.4.1), and Meta-DiSc (version 1.1.2) [15].


   3. Results
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
4. Discussion
 Appendix A. Supplementary data
 References
 
3.1. Study details
We identified 272 potentially suitable papers, of which 220 were excluded as follows: considered irrelevant (94 papers), not empirical articles (e.g. editorials tutorials or reviews) (59 papers), insufficient data to build 2x2 cross tables (44 papers), partial or complete duplicates of other studies included in the review (9 papers), addressed a very restricted subgroup of patients (4 papers) or because they selected patients according to ventricular function (10 papers). Finally 52 papers [4,5,16-65] with data from 16,730 patients were included in the review (Fig. 1, Table 1). (Details of all excluded studies are listed in Appendix A, see supplementary data). Three of the included articles provided separate results for women and men, so each of these papers was analyzed as two independent studies.


Figure 1
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  		Fig. 1 Flow chart of included/excluded studies.

 


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  		Table 1 Description of included studies

 
Inter-observer agreement in the initial assessment of the methodological quality of the studies ranged between 67% and 98% with a mean overall concordance of 87%. After appraising the methodological quality of the individual studies, we found, as was expected [9], that some items were related to a low DOR whereas others were associated with a high DOR. Consequently, we did not summarize the individual items into an overall quality score; instead, we selected the four items that were related to the strength of the DOR: adequate description of the study population, adequate description of the test, prospective study and no case-control design. The studies that did not fulfil these four items were considered of low-quality (12 studies).

3.2. Sources of heterogeneity
Our initial analysis included all 55 studies (Table 1). Diagnostic odds ratios were highly heterogeneous even after the studies were stratified according the reference standard. The sources of heterogeneity identified by the regression model were the methodological quality of the study (low quality studies overestimated the DOR by a factor of 3.7) and the reference standard: the accuracy of the test in identifying patients with heart failure was much greater than for the identification of left ventricular systolic dysfunction (Relative DOR=6.4). Neither the clinical setting (studies in patients with acute dyspnoea, stable heart disease or screening), nor the prevalence of cardiac dysfunction, nor the type of BNP assay were independently associated with the DOR after controlling for the effect of the reference standard and study quality. According to these findings, we decided to summarize diagnostic accuracy stratifying by the reference standard after exclusion of low quality studies.

3.3. Heart failure
Sixteen studies [5,20,22,24,26,28,32-34,37,40,48,49,61,63] assessed the diagnostic accuracy of BNP against a clinical diagnosis of heart failure. Five studies [24,28,32,49,63] were excluded due to low methodological quality; therefore we analyzed data from only 11 studies. All but two of the studies [20,48] used Triage BNP® test. There were no indications of a threshold effect (p=0.5489) or publication bias (p=0.1813) (Table 2). The DOR showed statistical heterogeneity (p=0.001). After excluding the two studies [22,61] with higher values, this heterogeneity vanished. Even after the exclusion of these outliers, BNP levels were highly accurate for identifying patients with heart failure (DOR=28.94, AUC=0.93).


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  		Table 2 Diagnostic accuracy of BNP according to the reference standard

 
Fig. 2A shows the SROC curve and the pooled negative LR for these 11 studies. It is worth noting that the straight line, representing the pooled negative LR, also fits the data points in the ROC space, indicating that, despite the wide range of cutoff points used in the studies, negative LR was relatively homogeneous (pooled LR=0.11; 95% CI 0.08-0.16; p value for heterogeneity=0.09). The point with the largest area corresponds to the Breathing Not Properly study, which included 56% of all of the patients in this group [5]. It is noteworthy, however, that exclusion of this study did not significantly change the estimated accuracy of the test (data not shown).


Figure 2
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  		Fig. 2 SROC curves. The pooled diagnostic odds ratios (DOR), estimated by the Moses' model, were used to plot the curves and to compute the area under the curves. SROC curves are plotted with their confidence intervals. The area of the circles is proportional to the size of the studies. (A): Studies of clinical heart failure. The straight line represents the summary negative LR; (B): Studies of systolic/diastolic dysfunction; (C): Studies of systolic dysfunction.

 
3.4. Systolic and/or diastolic dysfunction
Ten studies [19,25,27,35,36,41,42,47,53,62] assessed the diagnostic accuracy of BNP in identifying patients with systolic and/or diastolic dysfunction, however, three studies [19,35,62] were excluded due to low methodological quality. The seven included studies showed a high degree of heterogeneity (p<0.0001), with sensitivities ranging between 0.92 [47] and 0.28 [41] and specificities between 0.97 [36] and 0.44 [53]. The funnel plot was highly suspicious of publication bias (p=0.0624). Although the AUC was acceptable (0.85) (Fig. 2B and Table 2), the estimation of pooled measures with this degree of heterogeneity is problematic. The DOR is shown in Table 2 only for the sake of completeness.

3.5. Systolic dysfunction
The accuracy of BNP in the identification of systolic dysfunction was addressed in 29 studies [4,16-18,21,23,29-31,38,39,43-46,50-52,54-60,64,65], however, four studies were excluded from subsequent analysis due to poor methodological quality [4,39,56,58]. The results were statistically (p<0.0001) and clinically heterogeneous, with apparent asymmetry of the funnel plot (p=0.0005) suggesting the existence of publication bias. There were no indications of a threshold effect in the included studies (p=0.6844). Even after taking into consideration the heterogeneity and probable selection bias, the diagnostic accuracy was poorer than that of studies of heart failure (Fig. 2C and Table 2).


   4. Discussion
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
Appendix A. Supplementary data
 References
 
The diagnostic accuracy of BNP levels for heart failure has been recently reviewed by Doust et al. [8]. In this systematic review, based on 20 studies, BNP levels were highly accurate in the diagnosis of heart failure, but there was considerable variation among studies, and this variation could not be accounted for by differences in the clinical setting or type of test used. Our systematic review, based on 55 studies, provides complementary information about the diagnostic accuracy of BNP in different subgroups of patients, and helps to explain the heterogeneity observed among studies.

Firstly, the current review shows that BNP is a good test for the diagnosis of heart failure. Despite the wide range of cutoff points (for the Triage test the range was 80-300 pg/mL) employed in studies focusing on this reference standard, negative LRs show no evidence of significant heterogeneity. Moreover, according to the pooled negative LR, the existence of low BNP levels provides reasonably convincing evidence for ruling out heart failure. Conversely, positive LRs are highly heterogeneous and calculation of a pooled estimate is therefore problematic, making the reliability of BNP in confirming the existence of heart failure debatable. This statement is in agreement with the guidelines of the European Society of Cardiology [66] and the NICE [67], which recommend the use of BNP for ruling out a diagnosis of heart failure.

The ability of BNP to discriminate between patients with and without ventricular dysfunction is only moderate. This is consistent with the physiopathology of natriuretic peptide secretion, with higher levels of BNP in patients with overt heart failure — with high ventricular diastolic pressure and ventricular distension, than in patients with asymptomatic compensated ventricular dysfunction.

The accuracy of BNP for diagnosing diastolic dysfunction could not be formally assessed in our review, because many of the relevant studies had an inappropriate spectrum of patients (exclusion of patients according to their ejection fraction). However, the fact that the accuracy of BNP was greater when the definition of disease included patients with heart failure but with preserved left ventricular systolic function suggests that BNP levels can be useful for the diagnosis of diastolic dysfunction [8,68,69].

Secondly, our study suggests that part of the heterogeneity observed among the studies is attributable to their methodological quality, as studies of low quality overestimate the DOR by a factor of 3.74.

Thirdly, the asymmetrical funnel plot suggests that overall DOR is overestimated due to publication bias and/or small studies effect [70,71], especially in studies of systolic dysfunction.

In contrast with our previous hypothesis, neither the clinical setting (patients with dyspnoea, stable heart disease or screening) nor the type of assay contributed significantly to explaining heterogeneity, once the effects of the reference standard and study quality were controlled. However, the spectrum of patients, the type of assay and the outcome analyzed were strongly associated in our data and then colinearity could be an issue. The tendency for authors of individual studies to adjust the cut-off points to optimize accuracy might also explain this finding. Moreover, these results must be interpreted with caution since, given the limited number of available studies, the existence of interactions (for example the interaction between clinical settings and cut-point) could not be addressed and the possibility of a type II error cannot be excluded.

We could not properly assess the relationship between sex or age and the accuracy of BNP, due to the lack of disaggregated data. The results of three studies that separated the results by sex [34,54,60] were inconsistent.

We conclude that BNP levels are useful for ruling out heart failure as the cause of symptoms. The capacity of BNP levels to confirm the existence of cardiac failure or to identify patients with ventricular systolic dysfunction is limited. The observed heterogeneity among studies is partially explained by the methodological quality of the studies and the existence of publication bias and/or small studies effect.


   Appendix A. Supplementary data
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 Appendix A. Supplementary data
References
 
Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.ejheart.2005.10.004.


   Acknowledgements
 
To Drs. A. Hammerer-Lercher, G. Misuraca and S. Waku, who provided original data from their studies. To Dr. R. Carbonell for careful reading of a previous version of this manuscript. To Dr. J. F. Sánchez for his comments on laboratory methods. To Sarah White and Kathleen Seley, for their help with translation.


   References
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 Appendix A. Supplementary data
 References
 

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