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大流行平台试验的统计设计与分析:对未来的启示。

The statistical design and analysis of pandemic platform trials: Implications for the future.

作者信息

Lindsell Christopher J, Shotwell Matthew, Anstrom Kevin J, Berry Scott, Brittain Erica, Harrell Frank E, Geller Nancy, Grund Birgit, Hughes Michael D, Jagannathan Prasanna, Leifer Eric, Moser Carlee B, Price Karen L, Proschan Michael, Stewart Thomas, Thomas Sonia, Touloumi Giota, LaVange Lisa

机构信息

Duke University, Durham, NC, USA.

Vanderbilt University Medical Center, Nashville, TN, USA.

出版信息

J Clin Transl Sci. 2024 Oct 15;8(1):e155. doi: 10.1017/cts.2024.514. eCollection 2024.

Abstract

The Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Cross-Trial Statistics Group gathered lessons learned from statisticians responsible for the design and analysis of the 11 ACTIV therapeutic master protocols to inform contemporary trial design as well as preparation for a future pandemic. The ACTIV master protocols were designed to rapidly assess what treatments might save lives, keep people out of the hospital, and help them feel better faster. Study teams initially worked without knowledge of the natural history of disease and thus without key information for design decisions. Moreover, the science of platform trial design was in its infancy. Here, we discuss the statistical design choices made and the adaptations forced by the changing pandemic context. Lessons around critical aspects of trial design are summarized, and recommendations are made for the organization of master protocols in the future.

摘要

加速COVID-19治疗干预和疫苗(ACTIV)跨试验统计小组收集了负责11项ACTIV治疗主方案设计和分析的统计学家的经验教训,以为当代试验设计以及未来大流行的应对做准备。ACTIV主方案旨在快速评估哪些治疗方法可以挽救生命、避免人们住院,并帮助他们更快地康复。研究团队最初在不了解疾病自然史的情况下开展工作,因此缺乏用于设计决策的关键信息。此外,平台试验设计科学尚处于起步阶段。在此,我们讨论了所做出的统计设计选择以及不断变化的大流行背景所迫使的调整。总结了试验设计关键方面的经验教训,并对未来主方案的组织提出了建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9591/11557281/8176200a86e1/S2059866124005144_fig1.jpg

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