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Power and sample size for dose-finding studies with survival endpoints under model uncertainty
Qiqi Deng1, Xiaofei Bai1, Dacheng Liu1
1Biostatistics and Data Science, Boehringer Ingelheim Pharmaceuticals Inc., 900 Ridgebury Rd, Ridgefield, Connecticut 06811, U.S.A.
Biometrics
|September 12, 2018
Summary
This study introduces new power and sample size formulas for dose-finding studies using multiple comparison procedures combined with modeling techniques (MCP-Mod) with survival endpoints. The derived formulas accurately estimate sample sizes for robust statistical analysis.
Area of Science:
- Biostatistics
- Clinical Trial Design
- Pharmacometrics
Background:
- Multiple comparison procedures combined with modeling techniques (MCP-Mod) is a robust statistical method for dose-finding studies.
- MCP-Mod requires covariance matrix for power and sample size calculations, which is challenging for survival endpoints.
Purpose of the Study:
- To derive analytic formulas for power and sample size calculations in MCP-Mod studies with survival endpoints.
- To provide accurate and practical tools for designing dose-finding clinical trials.
Main Methods:
- Derived an analytic form of the covariance matrix for log hazard ratio estimators based on the total number of events.
- Utilized the closed-form covariance matrix to develop power and sample size formulas for MCP-Mod with survival data.
Main Results:
- Developed novel power and sample size formulas for MCP-Mod using survival endpoints.
- Simulation studies confirmed the accuracy of the proposed formulas for practical application.
Conclusions:
- The derived formulas offer a practical solution for sample size determination in dose-finding studies with survival outcomes.
- This methodology enhances the efficiency and robustness of clinical trial design in pharmaceutical research.
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