Drug Evaluation Committee Causal Inference for Understanding ICH E9(R1)
Data Science Subcommittee
July 2022
It is increasingly recognized that it is important to understand the concept of causal inference when setting the estimand in clinical trials.
Moreover, discussing estimand using the framework of causal inference will deepen our 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 Task Force 1 of the Data Science Subcommittee of the Drug Evaluation Committee of the Japan Pharmaceutical Manufacturers Association (JPMA), explained the basics of causal inference and each analysis method, and then provided examples of the application of causal inference to clinical trial data.
The subteam also touched on the relationship between estimand and causal inference in clinical trials, including the impact of COVID-19 on estimand as a recent topic.
We hope this document will help you to understand ICH-E9(R1) and to plan, conduct, and interpret the results of clinical trials.
Japan Pharmaceutical Manufacturers Association, Committee on Drug Evaluation
DS Subcommittee 2020 Ongoing Issues Team 1
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