Evolution of heterogeneity (I2) estimates and their 95% confidence intervals in large meta-analyses

Assessment of heterogeneity is essential in systematic reviews and meta-analyses of clinical trials. The most commonly used heterogeneity measure, I(2), provides an estimate of the proportion of variability in a meta-analysis that is explained by differences between the included trials rather than by sampling error. Recent studies have raised concerns about the reliability of I(2) estimates, due to their dependence on the precision of included trials and time-dependent biases. Authors have also advocated use of 95% confidence intervals (CIs) to express the uncertainty associated with I(2) estimates. However, no previous studies have explored how many trials and events are required to ensure stable and reliable I(2) estimates, or how 95% CIs perform as evidence accumulates.