Abstract

Very recently the new pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified and the coronavirus disease 2019 (COVID-19) declared a pandemic by the World Health Organization. The pandemic has a number of consequences for ongoing clinical trials in non-COVID-19 conditions. Motivated by four current clinical trials in a variety of disease areas we illustrate the challenges faced by the pandemic and sketch out possible solutions including adaptive designs. Guidance is provided on (i) where blinded adaptations can help; (ii) how to achieve Type I error rate control, if required; (iii) how to deal with potential treatment effect heterogeneity; (iv) how to use early read-outs; and (v) how to use Bayesian techniques. In more detail approaches to resizing a trial affected by the pandemic are developed including considerations to stop a trial early, the use of group-sequential designs or sample size adjustment. All methods considered are implemented in a freely available R shiny app. Furthermore, regulatory and operational issues including the role of data monitoring committees are discussed.

摘要

最近，新的病原体重症急性呼吸综合征冠状病毒2（SARS-CoV-2）被发现，世界卫生组织宣布2019年冠状病毒病（COVID-19）大流行。大流行对非COVID-19条件下正在进行的临床试验有许多后果。受当前在各种疾病领域进行的四项临床试验的启发，我们说明了大流行病面临的挑战，并概述了包括自适应设计在内的可能解决方案。在以下方面提供了指南：（i）盲目适应可以提供帮助；（ii）如有需要，如何实现I类错误率控制；（iii）如何处理潜在的治疗效果异质性；（iv）如何​​使用早期读数；（v）如何使用贝叶斯技术。更详细地研究了确定受大流行影响的试验的规模的方法，包括考虑尽早停止试验，使用组序设计或样本量调整。所有考虑的方法都在免费提供的R Shiny应用程序中实现。此外，还讨论了监管和运营问题，包括数据监控委员会的作用。