Drug Safety Meta-Analysis: Promises and Pitfalls

Abstract

Meta-analysis has increasingly been used to identify adverse effects of drugs and vaccines, but the results have often been controversial. In one respect, meta-analysis is an especially appropriate tool in these settings. Efficacy studies are often too small to reliably assess risks that become important when a medication is in widespread use, so meta-analysis, which is a statistically efficient way to pool evidence from similar studies, seems like a natural approach. But, as the examples in this paper illustrate, different syntheses can come to qualitatively different conclusions, and the results of any one analysis are usually not as precise as they seem to be. There are three reasons for this: the adverse events of interest are rare, standard meta-analysis methods may not be appropriate for the clinical and methodological heterogeneity that is common in these studies, and adverse effects are not always completely or consistently reported. To address these problems, analysts should explore heterogeneity and use random-effects or more complex statistical methods, and use multiple statistical models to see how dependent the results are to the choice of models.