Multivariate random-effects approach: for meta-analysis of cancer staging studies

Meta-analyses of diagnostic accuracy studies produce summary estimates of sensitivity and specificity. Cancer staging relies on staging systems and meta-analysis is often performed after dichotomization of the staging results. For each dichotomization, summary estimates of sensitivity and specificity can be calculated by repeated bivariate random-effects analyses. In this process, staging information is lost and under- and overstaging can not be adequately expressed.

We propose a new multivariate random-effects approach, which is an extension of the bivariate random-effects approach. To illustrate the principles and outcomes of both approaches, we used data from a meta-analysisevaluating endoluminal ultrasonography in staging of rectal cancer. In the multivariate approach, results on correct staging and under- and overstaging were calculated. In addition, the results from this analysis were used to calculate sensitivity and specificity estimates for each dichotomization and these estimates were compared with the results of the repeated bivariate analyses.

By the multivariate analysis, results on correct staging and under- and overstaging were obtained. The sensitivity and specificity estimates for the dichotomizations, calculated from the results of this multivariate approach, were also comparable with the sensitivity and specificity estimates obtained by the repeated bivariate analyses.

The multivariate random-effects approach can be a useful meta-analytic method for summarizing cancer staging data presented in diagnostic accuracy studies.