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Defining Efficacy Estimands in Clinical Trials: Examples Illustrating ICH E9(R1) Guidelines
Bohdana Ratitch1, Niti Goel2,3, Craig Mallinckrodt4
1Eli Lilly, Montreal, Quebec, Canada.
Therapeutic Innovation & Regulatory Science
|February 20, 2020
Summary
This paper illustrates defining estimands in clinical trials for major depressive disorder, severe asthma, and rheumatoid arthritis, adhering to International Council for Harmonisation E9(R1) guidelines. It emphasizes linking study objectives with data analysis for robust trial design.
Area of Science:
- Clinical Trials Methodology
- Pharmaceutical Statistics
- Regulatory Science
Background:
- Defining estimands is crucial for aligning clinical trial objectives with statistical analysis.
- ICH E9(R1) provides updated guidance on estimand specification.
- Real-world application of these guidelines requires careful consideration of study context.
Purpose of the Study:
- To provide practical examples of defining estimands in diverse clinical trial scenarios.
- To illustrate the process of selecting estimands that support specific development decisions.
- To demonstrate how to handle intercurrent events consistently with study objectives.
Main Methods:
- Illustrating three case studies of increasing complexity: a proof-of-concept trial and two confirmatory trials.
- Discussing the identification and handling of intercurrent events within each scenario.
- Focusing on the linkage between study objectives, estimand definition, and data analysis.
Main Results:
- Demonstrated how to define specific estimands for proof-of-concept and confirmatory trials in major depressive disorder, severe asthma, and rheumatoid arthritis.
- Showcased methods for addressing intercurrent events to maintain consistency with trial goals.
- Highlighted the importance of a structured development process for estimand selection.
Conclusions:
- The presented examples facilitate understanding and application of ICH E9(R1) estimand principles.
- A coherent process linking objectives, estimands, and analysis is vital for avoiding disconnects in clinical trial design.
- The approach ensures that estimands effectively support sponsor decisions and regulatory requirements.
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