Drug Evaluation Committee Causal Reasoning for Understanding ICH E9(R1)
July 2022
I believe there is a growing recognition that it is important to understand the concepts of causal inference when defining an estimand in clinical trials.
Furthermore, discussing estimands using a causal inference framework is expected to deepen understanding of ICH E9(R1) and lead to the planning and analysis of clinical trials that implement ICH E9(R1).
Therefore, we—the Causal Inference Subteam of the 2020 Continuing Task Force 1 of the Data Science Working Group, Drug Evaluation Committee, Japan Pharmaceutical Manufacturers Association (JPMA)—explained the fundamentals of causal inference and various analytical methods, followed by examples of applying causal inference to clinical trial data.
Furthermore, we addressed the relationship between the estimand and causal inference in clinical trials, including a discussion of the impact of COVID-19 on the estimand as a recent topic.
We hope this document will contribute to the understanding of ICH E9(R1) and assist in the planning, conduct, and interpretation of clinical trial results.
Japan Pharmaceutical Manufacturers Association, Drug Evaluation Committee,
DS Subcommittee, FY2020 Ongoing Issues Response Team 1