Computing the fragility index for randomized trials and meta-analyses using Stata

Abstract

In this article, I introduce two commands for computing the fragility index (FI): fragility, which is used for individual randomized controlled trials, and metafrag, which is used for meta-analyses. The FI for individual studies is defined as the minimum number of patients whose status would have to change from a nonevent to an event to nullify a statistically significant result. Correspondingly, the FI for meta-analyses is defined as the minimum number of patients from one or more trials included in the meta-analysis for which a modification of the event status (that is, changing events to nonevents or nonevents to events) would change the statistical significance of the pooled treatment effect to nonsignificant. Whether for an individual study or for a meta-analysis, a low FI indicates a more “fragile” study result, and a larger FI indicates a more robust result.