A multivariate method for meta-analysis and comparison of diagnostic tests

We present here an extension of the classic bivariate random effects meta-analysis for the log-transformed sensitivity and specificity that can be applied for two or more diagnostic tests. The advantage of this method is that a closed-form expression is derived for the calculation of the within-studies covariances. The method allows the direct calculation of sensitivity and specificity, as well as, the diagnostic odds ratio, the area under curve and the parameters of the summary receiver operator's characteristic curve, along with the means for a formal comparison of these quantities for different tests. There is no need for individual patient data or the simultaneous evaluation of both diagnostic tests in all studies. The method is simple and fast; it can be extended for several diagnostic tests and can be fitted in nearly all statistical packages. The method was evaluated in simulations and applied in a meta-analysis for the comparison of anti-cyclic citrullinated peptide antibody and rheumatoid factor for discriminating patients with rheumatoid arthritis, with encouraging results. Simulations suggest that the method is robust and more powerful compared with the standard bivariate approach that ignores the correlation between tests. Copyright (c) 2016 John Wiley & Sons, Ltd.