Estimands and their Estimators for Clinical Trials Impacted by the COVID-19 Pandemic: A Report from the NISS Ingram Olkin Forum Series on Unplanned Clinical Trial Disruptions
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受新冠疫情影响的临床试验：目标估计量及其估计方法
- 研究问题
- 疫情造成试验中断、感染和测量缺失后，如何重新明确临床研究的目标估计量，并选择与研究目的匹配的估计方法？
- 方法与思路
- 作者依托 ICH E9(R1) 框架提出假想的目标估计量策略，讨论因果推断、缺失数据及结合无偏与可能有偏估计的方法。
- 材料陈述的贡献
- 摘要称通过一个示例性试验说明疫情干扰如何改变目标估计量及估计方法，并提出未来试验应对意外中断的设计考虑。
- 阅读关注点
- 应核对不同中间事件对应的处理策略、目标估计量如何变化，以及因果推断和缺失数据方法分别依赖哪些识别条件。
- 阅读边界
- 这是 arXiv 预印本，同行评审及期刊接收未核验；摘要主要描述框架与假想试验，未提供具体方法的效果比较或适用条件。
原文摘要
The COVID-19 pandemic continues to affect the conduct of clinical trials globally. Complications may arise from pandemic-related operational challenges such as site closures, travel limitations and interruptions to the supply chain for the investigational product, or from health-related challenges such as COVID-19 infections. Some of these complications lead to unforeseen intercurrent events in the sense that they affect either the interpretation or the existence of the measurements associated with the clinical question of interest. In this article, we demonstrate how the ICH E9(R1) Addendum on estimands and sensitivity analyses provides a rigorous basis to discuss potential pandemic-related trial disruptions and to embed these disruptions in the context of study objectives and design elements. We introduce several hypothetical estimand strategies and review various causal inference and missing data methods, as well as a statistical method that combines unbiased and possibly biased estimators for estimation. To illustrate, we describe the features of a stylized trial, and how it may have been impacted by the pandemic. This stylized trial will then be re-visited by discussing the changes to the estimand and the estimator to account for pandemic disruptions. Finally, we outline considerations for designing future trials in the context of unforeseen disruptions.