Stallard Nigel, Hampson Lisa, Benda Norbert, Brannath Werner, Burnett Thomas, Friede Tim, Kimani Peter K, Koenig Franz, Krisam Johannes, Mozgunov Pavel, Posch Martin, Wason James, Wassmer Gernot, Whitehead John, Williamson S Faye, Zohar Sarah, Jaki Thomas
Statistics and Epidemiology, Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK.
Advanced Methodology and Data Science, Novartis Pharma AG, Basel, Switzerland.
Stat Biopharm Res. 2020 Jul 29;12(4):483-497. doi: 10.1080/19466315.2020.1790415.
The COVID-19 pandemic has led to an unprecedented response in terms of clinical research activity. An important part of this research has been focused on randomized controlled clinical trials to evaluate potential therapies for COVID-19. The results from this research need to be obtained as rapidly as possible. This presents a number of challenges associated with considerable uncertainty over the natural history of the disease and the number and characteristics of patients affected, and the emergence of new potential therapies. These challenges make adaptive designs for clinical trials a particularly attractive option. Such designs allow a trial to be modified on the basis of interim analysis data or stopped as soon as sufficiently strong evidence has been observed to answer the research question, without compromising the trial's scientific validity or integrity. In this article, we describe some of the adaptive design approaches that are available and discuss particular issues and challenges associated with their use in the pandemic setting. Our discussion is illustrated by details of four ongoing COVID-19 trials that have used adaptive designs.
新型冠状病毒肺炎（COVID-19）大流行引发了临床研究活动方面前所未有的响应。这项研究的一个重要部分聚焦于随机对照临床试验，以评估针对COVID-19的潜在疗法。需要尽快获取这项研究的结果。这带来了一些挑战，包括疾病自然史存在相当大的不确定性、受影响患者的数量和特征，以及新的潜在疗法的出现。这些挑战使得临床试验的适应性设计成为一个特别有吸引力的选择。此类设计允许根据期中分析数据对试验进行修改，或者一旦观察到足够有力的证据能够回答研究问题，就立即停止试验，而不会损害试验的科学有效性或完整性。在本文中，我们描述了一些可用的适应性设计方法，并讨论了在大流行背景下使用这些方法所涉及的特定问题和挑战。我们的讨论通过四项正在进行的采用了适应性设计的COVID-19试验的详细情况加以说明。
