Ma Yong, Haddad Jonathan, Liu Wei, Snyder Ellen, Bennett Dimitri, Mayo Susan
Office of Biostatistics, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD, 20993, USA.
GlaxoSmithKline Plc, London, UK.
Ther Innov Regul Sci. 2025 May 27. doi: 10.1007/s43441-025-00780-4.
The ICH E9(R1) estimand framework provides a systematic approach to ensure alignment among clinical trial objectives, trial conduct, statistical analyses, and interpretation of results, however, whether it can be readily utilized for the pharmacoepidemiologic safety studies has not been established. We selected articles on drug safety published in the Journal Pharmacoepidemiology and Drug Safety (PDS), during 2020 to investigate whether estimand attributes were well defined in the study design and reporting. We found that among twenty-five articles selected, nineteen were cohort studies and six were nested case-control studies. All studies had well-defined exposure, outcome, target population, and population level summary. The term intercurrent event (ICE) was not mentioned in any of the studies; however, many cohort studies discussed drug discontinuation, treatment modification and terminal events, and strategies to handle them. All studies used methods to control for confounding: propensity score methods or covariate adjustment, or both for cohort studies; matching and covariate adjustment for the nested case-control studies. We conclude that while the estimand framework can serve to add clarity and precision to pharmacoepidemiologic safety studies, more detailed considerations are required for bias assessment to compensate for the lack of randomization and other shortcomings in observational studies. Recent pharmacoepidemiology frameworks, such as Target Trial Emulation, STaRT-RWE, HARPER could be combined with the complementary principals from the estimand framework to help achieve the study objectives.
国际人用药品注册技术协调会（ICH）的E9（R1）估计量框架提供了一种系统方法，以确保临床试验目标、试验实施、统计分析和结果解释之间保持一致。然而，其是否能轻易用于药物流行病学安全性研究尚未确定。我们选取了2020年发表在《药物流行病学与药物安全》（PDS）杂志上的关于药物安全性的文章，以调查估计量属性在研究设计和报告中是否得到明确界定。我们发现，在所选的25篇文章中，19篇为队列研究，6篇为巢式病例对照研究。所有研究都明确界定了暴露、结局、目标人群和人群水平汇总。所有研究均未提及并发事件（ICE）一词；然而，许多队列研究讨论了药物停用、治疗调整和终末事件以及处理这些事件的策略。所有研究都使用了控制混杂因素的方法：队列研究采用倾向评分法或协变量调整，或两者兼用；巢式病例对照研究采用匹配和协变量调整。我们得出结论，虽然估计量框架可为药物流行病学安全性研究增添清晰度和精确性，但在偏倚评估方面需要更详细的考量，以弥补观察性研究中缺乏随机化及其他缺陷。近期的药物流行病学框架，如目标试验模拟、STaRT -真实世界证据、HARPER等，可以与估计量框架中的互补原则相结合，以帮助实现研究目标。
