Master protocols have received a growing interest during the last years. By assigning patients to specific substudies, they aim at targeting and accelerating clinical development. Given their complexity, basket, umbrella, and platform designs have raised challenging regulatory and statistical questions, especially the control of multiplicity in confirmatory trials. In basket trials, regulatory assessment of the benefit/risk in pooled populations and choice of the treatment indication is challenging. We provide here our perspectives on these topics. In master protocols, as long as the statistical hypotheses tested between the different substudies are independent, no supplementary adjustment for multiplicity over the different substudies should be required. Moreover, sharing a control arm within an umbrella or a platform trial investigating different drugs would not require a correction for the type I error rate, whereas the chance of multiple false positive regulatory decisions should be recognized. In basket trials, pooling across substudies requires a rationale supporting the intended indication and should be preplanned. Assessment of the benefit/risk in pooled target populations can be complicated by differences in design or in efficacy/safety signals between the substudies. While trials governed by a master protocol can offer logistic and financial advantages, more experience is needed to gain a deeper insight into this novel framework.

中文翻译：

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有关确认篮，雨伞和平台试验计划的最新统计考虑和监管观点。

在过去的几年中，主协议越来越引起人们的兴趣。通过将患者分配到特定的子研究中，他们旨在瞄准并加速临床发展。考虑到它们的复杂性，篮子，保护伞和平台设计提出了具有挑战性的监管和统计问题，尤其是在验证性试验中如何控制多重性。在篮子试验中，对合并人群的获益/风险以及治疗适应症的选择进行监管评估具有挑战性。我们在此提供对这些主题的观点。在主协议中，只要在不同子研究之间测试的统计假设是独立的，就不需要对不同子研究的多重性进行补充调整。此外，在研究不同药物的保护伞或平台试验中共享一个控制机构，无需对I型错误率进行校正，而应认识到可能出现多个错误的阳性监管决定。在篮子试验中，跨子研究的合并需要支持预期适应症的基本原理，并且应预先计划。由于子研究之间设计或功效/安全性信号的差异，可能会使合并目标人群的收益/风险评估变得复杂。虽然由主协议控制的试验可以提供后勤和财务优势，但需要更多经验才能对这种新颖的框架有更深入的了解。子研究之间的合并需要支持预期适应症的基本原理，并且应预先计划。由于子研究之间设计或功效/安全性信号的差异，可能会使合并目标人群的收益/风险评估变得复杂。虽然由主协议控制的试验可以提供后勤和财务优势，但需要更多经验才能对这种新颖的框架有更深入的了解。子研究之间的合并需要支持预期适应症的基本原理，并且应预先计划。由于子研究之间设计或功效/安全性信号的差异，可能会使合并目标人群的收益/风险评估变得复杂。虽然由主协议控制的试验可以提供后勤和财务优势，但需要更多经验才能对这种新颖的框架有更深入的了解。