Methodology Working Group, College ter Beoordeling van Geneesmiddelen - Medicines Evaluation Board, Utrecht, The Netherlands.
Clinical Trial Methodology Department, Biostatistics and Research Support, Julius Center for Health Sciences and Primary Care, Biostatistics and Research Support, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Pharm Stat. 2022 Sep;21(5):1037-1057. doi: 10.1002/pst.2214. Epub 2022 Jun 9.
Estimands aim to incorporate intercurrent events in design, data collection and estimation of treatment effects in clinical trials. Our aim was to understand what estimands may correspond to efficacy analyses commonly employed in clinical trials conducted before publication of ICH E9(R1). We re-analysed six clinical trials evaluating a new anti-depression treatment. We selected the following analysis methods-ANCOVA on complete cases, following last observation carried forward (LOCF) imputation and following multiple imputation; mixed-models for repeated measurements without imputation (MMRM), MMRM following LOCF imputation and following jump-to-reference imputation; and pattern-mixture mixed models. We included a principal stratum analysis based on the predicted subset of the study population who would not discontinue due to adverse events or lack of efficacy. We translated each analysis into the implicitly targeted estimand, and formulated corresponding clinical questions. We could map six estimands to analysis methods. The same analysis method could be mapped to more than one estimand. The major difference between estimands was the strategy for intercurrent events, with other attributes mostly the same across mapped estimands. The quantitative differences in MADRS10 population-level summaries between the estimands were 4-8 points. Not all six estimands had a clinically meaningful interpretation. Only a few analyses would target the same estimand, hence only few could be used as sensitivity analyses. The fact that an analysis could estimate different estimands emphasises the importance of prospectively defining the estimands targeting the primary objective of a trial. The fact that an estimand can be targeted by different analyses emphasises the importance of prespecifying precisely the estimator for the targeted estimand.
效标旨在将伴随事件纳入临床试验的设计、数据收集和治疗效果评估中。我们的目的是了解在 ICH E9(R1) 发布之前进行的临床试验中，通常采用的疗效分析可能对应哪些效标。我们重新分析了六项评估新型抗抑郁治疗的临床试验。我们选择了以下分析方法：完全病例的协方差分析、末次观察值结转（LOCF）插补后的分析、以及多重插补后的分析；无插补的重复测量混合模型（MMRM）、LOCF 插补后的 MMRM 和跳至参照插补后的 MMRM；以及模式混合混合模型。我们进行了基于预测的不会因不良事件或疗效不佳而退出研究人群的主要分层分析。我们将每种分析转换为隐含的目标效标，并提出相应的临床问题。我们可以将六个效标映射到分析方法。同一种分析方法可以映射到多个效标。效标之间的主要区别在于伴随事件的策略，而映射效标之间的其他属性大多相同。MADRS10 人群水平汇总的效标之间的差异为 4-8 分。并非所有六个效标都具有临床意义的解释。只有少数分析会针对相同的效标，因此只有少数分析可以作为敏感性分析。同一种分析可以估计不同效标的事实强调了前瞻性定义针对试验主要目标的效标的重要性。一个效标可以被不同的分析所针对的事实强调了针对目标效标准确预设估计器的重要性。
