Piantadosi Steven
Brigham and Women's Hospital, Boston, MA, USA.
Clin Trials. 2020 Oct;17(5):483-490. doi: 10.1177/1740774520940227. Epub 2020 Jul 15.
The COVID-19 pandemic presents challenges for clinical trials including urgency, disrupted infrastructure, numerous therapeutic candidates, and the need for highly efficient trial and development designs. This paper presents design components and rationale for constructing highly efficient trials to screen potential COVID-19 treatments.
Key trial design elements useful in this circumstance include futility hypotheses, treatment pooling, reciprocal controls, ranking and selection, and platform administration. Assuming most of the many candidates for COVID-19 treatment are likely to be ineffective, these components can be combined to facilitate very efficient comparisons of treatments.
Simulations indicate such designs can reliably discard underperforming treatments using sample size to treatment ratios under 30.
Methods to create very efficient clinical trial comparisons of treatments for COVID-19 are available. Such designs might be helpful in the pandemic and should be considered for similar needs in the future.
新冠疫情给临床试验带来了诸多挑战，包括紧迫性、基础设施中断、众多治疗候选方案，以及对高效试验和研发设计的需求。本文介绍了构建高效试验以筛选潜在新冠治疗方法的设计要素及基本原理。
在此情况下有用的关键试验设计要素包括无效假设、治疗合并、相互对照、排序与选择以及平台管理。鉴于众多新冠治疗候选方案中多数可能无效，这些要素可结合起来以促进对治疗方法进行非常高效的比较。
模拟表明，此类设计能够以低于30的样本量与治疗比例可靠地摒弃表现不佳的治疗方法。
已有方法可对新冠治疗方法进行非常高效的临床试验比较。此类设计在疫情期间可能会有所帮助，未来类似需求时也应予以考虑。
