Rippin Gerd
IQVIA, Biostatistics, Frankfurt, Germany.
Front Drug Saf Regul. 2024 Feb 2;3:1332040. doi: 10.3389/fdsfr.2023.1332040. eCollection 2023.
The estimand framework as defined by the ICH E9(R1) addendum aims to clearly define "the treatment effect reflecting the clinical question posed by the trial objective". It intends to achieve this goal of a clear definition by specifying the 5 estimand attributes: treatment conditions, population, endpoints, handling of intercurrent events (IEs), and population-level summary. However, hybrid clinical/observational research like External Comparators (ECs) leads to new reflections on existing attributes and to considerations for additional ones. Specifically, treatment conditions and exposure may be more difficult to handle in the EC, and especially Standard of Care (SoC) treatment needs detailed attention. The external population typically cannot be based on the classical Intention-to-treat population and constitutes also an approximation only. Endpoints may not be comparable across cohorts, and IEs may be more different than in an RCT setting, such that the hypothetical treatment policy according to the ICH E9(R1) addendum may become of greater interest especially for long-term endpoints. Finally, the necessary assumptions for some population-level summaries (e.g., the proportional hazards assumption) can become more fragile when joining data from different sources due to induced heterogeneity. Finally, it is shown that the baseline definition and the marginal estimator are candidates for additional estimand attributes in case the estimand framework is revised to account for observational study needs.
国际人用药品注册技术协调会(ICH)E9(R1)增编所定义的估计量框架旨在明确界定“反映试验目的所提出临床问题的治疗效果”。它试图通过规定五个估计量属性来实现这一明确定义的目标:治疗条件、人群、终点、并发事件(IEs)的处理以及人群水平汇总。然而,像外部对照(ECs)这样的混合临床/观察性研究引发了对现有属性的新思考以及对其他属性的考量。具体而言,在外部对照中,治疗条件和暴露可能更难处理,尤其是标准治疗(SoC)需要详细关注。外部人群通常不能基于经典的意向性治疗人群,且也只是一种近似。不同队列间的终点可能不可比,并发事件可能比随机对照试验(RCT)环境中的更不同,以至于根据ICH E9(R1)增编的假设治疗策略可能对长期终点尤其更具意义。最后,由于诱导的异质性,在合并来自不同来源的数据时,一些人群水平汇总所需的假设(例如比例风险假设)可能变得更不可靠。最后,结果表明,在修订估计量框架以满足观察性研究需求时,基线定义和边际估计量是额外估计量属性的候选者。