Trial sequential analysis reveals insufficient information size and potentially false positive results in many meta-analyses

ObjectivesTo evaluate meta-analyses with trial sequential analysis (TSA). TSA adjusts for random error risk and provides the required number of participants (information size) in a meta-analysis. Meta-analyses not reaching information size are analyzed with trial sequential monitoring boundaries analogous to interim monitoring boundaries in a single trial.Study Design and SettingWe applied TSA on meta-analyses performed in Cochrane Neonatal reviews. We calculated information sizes and monitoring boundaries with three different anticipated intervention effects of 30% relative risk reduction (TSA30%), 15% (TSA15%), or a risk reduction suggested by low-bias risk trials of the meta-analysis corrected for heterogeneity (TSALBHIS).ResultsA total of 174 meta-analyses were eligible; 79 out of 174 (45%) meta-analyses were statistically significant (P < 0.05). In the significant meta-analyses, TSA30% showed firm evidence in 61%. TSA15% and TSALBHIS found firm evidence in 33% and 73%, respectively. The remaining significant meta-analyses had potentially spurious evidence of effect. In the 95 statistically nonsignificant (P ≥ 0.05) meta-analyses, TSA30% showed absence of evidence in 80% (insufficient information size). TSA15% and TSALBHIS found that 95% and 91% had absence of evidence. The remaining nonsignificant meta-analyses had evidence of lack of effect.ConclusionTSA reveals insufficient information size and potentially false positive results in many meta-analyses.