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当前确认性篮子、伞式和平台试验规划的统计考虑因素和监管观点。

Current Statistical Considerations and Regulatory Perspectives on the Planning of Confirmatory Basket, Umbrella, and Platform Trials.

机构信息

Competence Centre in Methodology and Statistics, Luxembourg Institute of Health, Strassen, Luxembourg.

AGES - Österreichische Agentur für Gesundheit und Ernährungssicherheit/Austrian Agency for Health and Food Safety, Vienna, Austria.

出版信息

Clin Pharmacol Ther. 2020 May;107(5):1059-1067. doi: 10.1002/cpt.1804. Epub 2020 Apr 1.

Abstract

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.

摘要

近年来,主方案受到越来越多的关注。通过将患者分配到特定的子研究中,它们旨在针对和加速临床开发。鉴于其复杂性,篮子、伞式和平台设计提出了具有挑战性的监管和统计问题,特别是确认性试验中多重性的控制。在篮子试验中,对汇总人群的获益/风险进行监管评估以及选择治疗指征具有挑战性。我们在此提供对这些主题的看法。在主方案中,只要不同子研究之间测试的统计假设是独立的,那么就不需要针对不同子研究进行多重性的额外调整。此外,在伞式或平台试验中,对不同药物进行研究时,共享一个对照臂不需要对第一类错误率进行校正,而应认识到多个假阳性监管决策的可能性。在篮子试验中,需要有支持预期适应证的基本原理来进行子研究的汇总,并且应该预先计划。汇总目标人群的获益/风险评估可能会受到设计或子研究之间疗效/安全性信号差异的影响。虽然受主方案管理的试验可以提供后勤和财务优势,但需要更多经验才能更深入地了解这一新框架。

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