UNLABELLED: We used a Bayesian hierarchical selection model to study publication bias in 1106 meta-analyses from the Cochrane Database of Systematic Reviews comparing treatment with either placebo or no treatment. For meta-analyses of efficacy, we estimated the ratio of the probability of including statistically significant outcomes favoring treatment to the probability of including other outcomes. For meta-analyses of safety, we estimated the ratio of the probability of including results showing no evidence of adverse effects to the probability of including results demonstrating the presence of adverse effects. RESULTS: In the meta-analyses of efficacy, outcomes favoring treatment had on average a 27% (95% Credible Interval (CI): 18% to 36%) higher probability to be included than other outcomes. In the meta-analyses of safety, results showing no evidence of adverse effects were on average 78% (95% CI: 51% to 113%) more likely to be included than results demonstrating that adverse effects existed. In general, the amount of over-representation of findings favorable to treatment was larger in meta-analyses including older studies. CONCLUSIONS: In the largest study on publication bias in meta-analyses to date, we found evidence of publication bias in Cochrane systematic reviews. In general, publication bias is smaller in meta-analyses of more recent studies, indicating their better reliability and supporting the effectiveness of the measures used to reduce publication bias in clinical trials. Our results indicate the need to apply currently underutilized meta-analysis tools handling publication bias based on the statistical significance, especially when studies included in a meta-analysis are not recent.
Stored only when both papers are in the corpus — 211 citations exist upstream.