Trial Sequential Analysis (TSA) is a methodology that combines a required information size (RIS) calculation for a meta-analysis with the threshold for statistical significance [1719]. TSA is used to quantify the statistical reliability of the data in cumulative meta-analysis adjusting P values for sparse data and for repetitive testing on accumulating data thus controlling the risks of type I and type II errors [1719]. We calculated the diversity-adjusted required information size (DARIS, i.e. number of participants required to detect or reject effects in meta-analyses), and used TSA for our primary outcome at end of treatment. If the TSA did not find a significant finding before the RIS was reached (no Z curve crossing of the trial sequential monitoring boundaries), we could conclude that either more trials were needed to reject or accept an intervention effect or the anticipated effect could be rejected. If the cumulated Z curve enters the futility area, the anticipated intervention effect can be rejected.

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