Although systematic reviews of randomized clinical trials (RCTs) are considered the pinnacle of evidence-based medicine, RCTs are often designed to reach a desired level of power for a pre-specified effect size, independent of the current body of evidence. Evidence indicates that sample size calculations for a new RCT should be conducted in the context of a systematic review and meta-analysis of the existing body of evidence. This paper presents a framework to estimate sample size and power for a future study, based on a prospective multivariate network metaanalysis (MNMA) of RCTs. The term “multivariate” refers to powering on (potentially) multiple outcomes. Specifically, a Bayesian MNMA is fit to the existing network and 1000 hypothetical trials are designed from the resultant posterior predictive distribution of effect sizes. Thus, the future RCT is designed in the context of the current network of evidence. The approach is applied to a systematic review of pharmacologic treatments for adult acute manic disorder. The analysis suggests that new trials should be designed/powered within the context of either a multivariate or univariate network meta-analysis, where the former is preferred if researchers are interested in multiple primary outcomes, or the network is subject to extensive missing outcomes.

中文翻译：

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使用贝叶斯多元网络元分析估计未来研究的样本量

尽管随机临床试验 (RCT) 的系统评价被认为是循证医学的顶峰，但 RCT 通常旨在达到预先指定的效应量所需的功效水平，独立于当前的证据。证据表明，新 RCT 的样本量计算应在对现有证据进行系统评价和荟萃分析的背景下进行。本文基于 RCT 的前瞻性多变量网络荟萃分析 (MNMA)，提出了一个框架，用于估计未来研究的样本量和功效。术语“多元”是指推动（潜在）多个结果。具体来说，贝叶斯 MNMA 适合现有网络，并且根据效果大小的后验预测分布设计了 1000 次假设试验。因此，未来的 RCT 是在当前证据网络的背景下设计的。该方法应用于成人急性躁狂症药物治疗的系统评价。分析表明，新试验应在多变量或单变量网络荟萃分析的背景下设计/有效，如果研究人员对多个主要结果感兴趣，或者网络受到广泛缺失结果的影响，则首选前者。