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

J Clin Epidemiol. 2008 Aug;61(8):763-9. doi: 10.1016/j.jclinepi.2007.10.007. Epub 2008 Apr 14.


Objectives: To 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 setting: We 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 (TSA(30%)), 15% (TSA(15%)), or a risk reduction suggested by low-bias risk trials of the meta-analysis corrected for heterogeneity (TSA(LBHIS)).

Results: A 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, TSA(30%) showed firm evidence in 61%. TSA(15%) and TSA(LBHIS) 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>or=0.05) meta-analyses, TSA(30%) showed absence of evidence in 80% (insufficient information size). TSA(15%) and TSA(LBHIS) found that 95% and 91% had absence of evidence. The remaining nonsignificant meta-analyses had evidence of lack of effect.

Conclusion: TSA reveals insufficient information size and potentially false positive results in many meta-analyses.

MeSH terms

  • Data Interpretation, Statistical
  • False Positive Reactions
  • Humans
  • Infant, Newborn
  • Meta-Analysis as Topic*
  • Randomized Controlled Trials as Topic*
  • Research Design / standards*
  • Review Literature as Topic
  • Sample Size