Literature DB >> 24828853

Bayesian bivariate meta-analysis of sensitivity and specificity: summary of quantitative findings in 50 meta-analyses.

Jan Menke1.   

Abstract

RATIONALE, AIMS AND
OBJECTIVES: Meta-analyses of diagnostic test accuracy are important elements in evidence-based medicine. However, currently there is no overview of related quantitative findings that were obtained in a large number of real meta-analyses. This study aimed at providing such empirical summary.
METHODS: From the literature 50 meta-analyses were randomly selected that had reported their 2 × 2 count data of sensitivity and specificity. Descriptive statistics, assessment of between-study heterogeneity and bivariate random-effects meta-analysis of sensitivity and specificity were performed with a novel Bayesian program code. The bivariate model parameters were also converted to the parameters of the closely related hierarchical summary receiver operating characteristic (HSROC) model.
RESULTS: Among the 50 meta-analyses, the studies per meta-analysis ranged from 5 to 45 and the disease prevalence from 2.3 to 71%. Significant between-study heterogeneity was found in 43 of 50 meta-analyses, favouring a random-effects model over a fixed-effects model. Empirical distributions of sensitivity and specificity, positive and negative likelihood ratios, and other model results are presented in the full text numerically and graphically.
CONCLUSIONS: Studies of diagnostic test accuracy can be well meta-analysed within a Bayesian framework, and the presented quantitative findings provide an orientation when interpreting the results of the standard bivariate/HSROC model.
© 2014 John Wiley & Sons, Ltd.

Keywords:  Bayesian meta-analysis; Monte Carlo method, sensitivity and specificity; diagnostic accuracy; meta-analysis

Mesh:

Year:  2014        PMID: 24828853     DOI: 10.1111/jep.12173

Source DB:  PubMed          Journal:  J Eval Clin Pract        ISSN: 1356-1294            Impact factor:   2.431


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