大流行病平台试验的统计设计与分析:对未来的影响。

IF 2.1 Q3 MEDICINE, RESEARCH & EXPERIMENTAL
Journal of Clinical and Translational Science Pub Date : 2024-10-15 eCollection Date: 2024-01-01 DOI:10.1017/cts.2024.514
Christopher J Lindsell, Matthew Shotwell, Kevin J Anstrom, Scott Berry, Erica Brittain, Frank E Harrell, Nancy Geller, Birgit Grund, Michael D Hughes, Prasanna Jagannathan, Eric Leifer, Carlee B Moser, Karen L Price, Michael Proschan, Thomas Stewart, Sonia Thomas, Giota Touloumi, Lisa LaVange
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引用次数: 0

摘要

Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Cross-Trial Statistics Group(ACTIV交叉试验统计小组)收集了负责设计和分析11个ACTIV治疗主方案的统计人员的经验教训,以便为当代试验设计提供参考,并为未来的大流行病做好准备。ACTIV 主方案旨在快速评估哪些治疗方法可以挽救生命,让人们远离医院,并帮助他们更快地恢复健康。研究团队最初在不了解疾病自然史的情况下开展工作,因此缺乏设计决策所需的关键信息。此外,平台试验设计科学也处于起步阶段。在此,我们将讨论所做的统计设计选择,以及在不断变化的大流行背景下被迫做出的调整。我们总结了试验设计关键环节的经验教训,并对未来主方案的组织提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The statistical design and analysis of pandemic platform trials: Implications for the future.

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.

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来源期刊
Journal of Clinical and Translational Science
Journal of Clinical and Translational Science MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
2.80
自引率
26.90%
发文量
437
审稿时长
18 weeks
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