Explanation of trial sequential analysis: using a post-hoc analysis of meta-analyses published in Korean Journal of Anesthesiology

Background: Trial sequential analysis (TSA) is a recent cumulative meta-analysis method used to weigh type I and II errors and to estimate when the effect is large enough to be unaffected by further studies. The aim of this study was to illustrate possible TSA scenarios and their significance using meta-analyses published in the Korean Journal of Anesthesiology (KJA) as working material. Methods: We performed a systematic medical literature search for meta-analyses published in the KJA. TSA was performed on each main outcome, estimating the required sample size on the calculated effect size for the intervention, considering a type I error of 5% and a power of 90% or 99%. Results: Six meta-analyses with a total of ten main outcomes were included in the analysis. Seven TSAs confirmed the results of the meta-analyses. However, only three of them reached the required sample size. In the two TSAs, the cumulative z-lines were not statistically significant. One TSA boundary for effect was reached with the 90% analysis, but not with the 99% analysis. Conclusions: In TSA, a meta-analysis pooled effect may be established to assess if the cumulative sample size is large enough. TSA can be used to add strength to the conclusions of meta-analyses; however, pre-registration of the TSA protocol is of paramount importance. This study could be useful to better understand the use of TSA as an additional statistical tool to improve meta-analysis quality.

Automated summary

This study used meta-analyses published in the Korean Journal of Anesthesiology to demonstrate possible TSA scenarios and their significance. Results showed that while most TSAs confirmed the meta-analyses' results, only a few met the required sample size, indicating TSA can strengthen meta-analysis conclusions but require proper pre-registration to ensure validity.