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The Finkelstein-Schoenfeld Test: A Note on Some Overlooked Issues Concerning Power
Rong Tang1, Wei-Chen Chen2, Heng Li2
1Center for Devices and Radiological Health, Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD, 20993, USA. rong.tang@fda.hhs.gov.
Therapeutic Innovation & Regulatory Science
|February 5, 2024
Summary
This study explores power considerations for clinical trial design using hierarchical composite endpoints and the Finkelstein-Schoenfeld test through simulations. Findings aid in optimizing study planning for robust statistical power.
Area of Science:
- Biostatistics
- Clinical Trial Design
- Statistical Power Analysis
Background:
- Hierarchical composite endpoints are increasingly used in clinical studies to assess multiple outcomes efficiently.
- The Finkelstein-Schoenfeld test is a statistical method suitable for analyzing time-to-event data with composite endpoints.
- Accurate power considerations are crucial for designing clinical studies that yield statistically significant and reliable results.
Purpose of the Study:
- To provide insights into power considerations for clinical study designs.
- To evaluate the performance of the Finkelstein-Schoenfeld test in the context of hierarchical composite endpoints.
- To inform optimal clinical trial design strategies through simulation studies.
Main Methods:
- The study employed simulation studies to investigate power considerations.
- Hierarchical composite endpoints were utilized in the simulated clinical study designs.
- The Finkelstein-Schoenfeld test was applied to analyze the simulated data.
Main Results:
- Simulation results highlight the impact of various factors on statistical power.
- The study provides a viewpoint on achieving adequate power in complex clinical study designs.
- Specific recommendations regarding parameter choices for power calculations are discussed.
Conclusions:
- Careful consideration of power is essential when designing clinical studies with hierarchical composite endpoints.
- Simulation studies are valuable tools for understanding power dynamics and optimizing the Finkelstein-Schoenfeld test application.
- The findings contribute to the methodological advancements in clinical trial design and statistical analysis.
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