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Background  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.    Methodology/Principal Findings  To assess the stability and reliability of  I 2   estimates and their 95% CIs, in relation to the cumulative number of trials and events in meta-analysis, we looked at 16 large Cochrane meta-analyses - each including a sufficient number of trials and events to reliably estimate  I 2   - and monitored the  I 2   estimates and their 95% CIs for each year of publication. In 10 of the 16 meta-analyses, the  I 2   estimates fluctuated more than 40% over time. The median number of events and trials required before the cumulative  I 2   estimates stayed within +/−20% of the final  I 2   estimate was 467 and 11. No major fluctuations were observed after 500 events and 14 trials. The 95% confidence intervals provided good coverage over time.    Conclusions/Significance    I 2   estimates need to be interpreted with caution when the meta-analysis only includes a limited number of events or trials. Confidence intervals for  I 2   estimates provide good coverage as evidence accumulates, and are thus valuable for reflecting the uncertainty associated with estimating  I 2  .

Evolution of Heterogeneity (I2) Estimates and Their 95% Confidence Intervals in Large Meta-Analyses