Bayesian bivariate meta-analysis of sensitivity and specificity: summary of quantitative findings in 50 meta-analyses.
OBJECTIVE
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.
Radiology Center, University Hospital Goettingen, Goettingen, Germany.
Jan
J
Menke
D001499:Bayes Theorem; D005069:Evaluation Studies as Topic; D019317:Evidence-Based Medicine; D006801:Humans; D015201:Meta-Analysis as Topic; D009010:Monte Carlo Method; D012680:Sensitivity and Specificity
Bayesian meta-analysis; Monte Carlo method, sensitivity and specificity; diagnostic accuracy; meta-analysis