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The European Medicines Agency (EMA) adopted the International Council for Harmonization (ICH) E9(R1) guideline on estimands and sensitivity analysis in clinical trials in early 2020. The ICH E9(R1) guideline has significantly influenced the design and analysis of confirmatory studies by providing a structured framework for addressing intercurrent events. Since its adoption, there has been a shift in how sponsors approach clinical trials for a wide range of therapeutic areas. This chapter discusses the EMA’s implementation of the estimand framework across various guideline documents, including treatments for diabetes mellitus, Alzheimer’s disease, chronic noninfectious liver diseases, gout, trials with recurrent event endpoints, and registry-based studies. In most of these guidelines, common intercurrent events in specific disease areas and estimand strategies were discussed, which inform trial design, data collection, and choice of analysis method.

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EMA Guidelines and Their Relationship to the Estimand Framework

  • 章节

  • 发表日期：

    2025年

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  • Jiawei Wei,
  • Frank Bretz,
  • Cui Xiong,
  • Zhiyue Huang,
  • Xiaoling Wei,
  • Alice Wang,
  • Xin Zhang,
  • Luyan Dai,
  • Mouna Akacha,
  • Chunquan Ou

摘要

The European Medicines Agency (EMA) adopted the International Council for Harmonization (ICH) E9(R1) guideline on estimands and sensitivity analysis in clinical trials in early 2020. The ICH E9(R1) guideline has significantly influenced the design and analysis of confirmatory studies by providing a structured framework for addressing intercurrent events. Since its adoption, there has been a shift in how sponsors approach clinical trials for a wide range of therapeutic areas. This chapter discusses the EMA’s implementation of the estimand framework across various guideline documents, including treatments for diabetes mellitus, Alzheimer’s disease, chronic noninfectious liver diseases, gout, trials with recurrent event endpoints, and registry-based studies. In most of these guidelines, common intercurrent events in specific disease areas and estimand strategies were discussed, which inform trial design, data collection, and choice of analysis method.