Sensitivity of between-study heterogeneity in meta-analysis: proposed metrics and empirical evaluation

Several approaches are available for evaluating heterogeneity in meta-analysis. Sensitivity analyses are often used, but these are often implemented in various non-standardized ways.

We developed and implemented sequential and combinatorial algorithms that evaluate the change in between-study heterogeneity as one or more studies are excluded from the calculations. The algorithms exclude studies aiming to achieve either the maximum or the minimum final I(2) below a desired pre-set threshold. We applied these algorithms in databases of meta-analyses of binary outcome and >/=4 studies from Cochrane Database of Systematic Reviews (Issue 4, 2005, n = 1011) and meta-analyses of genetic associations (n = 50). Two I(2) thresholds were used (50% and 25%).