B ayesian bivariate meta‐analysis of sensitivity and specificity: summary of quantitative findings in 50 meta‐analyses

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.