Optimal two-stage log-rank test for randomized phase II clinical trials
Minjung Kwak1, Sin-Ho Jung2,3
1a Department of Statistics , Yeungnam University , Gyeongsan , Gyeongbuk , Republic of Korea.
Journal of Biopharmaceutical Statistics
|April 7, 2016
Summary
This study introduces optimal two-stage clinical trial designs to minimize sample size. These designs allow early stopping for futility or efficacy, improving efficiency in survival analysis.
Area of Science:
- Clinical Trials
- Biostatistics
- Survival Analysis
Background:
- Randomized controlled trials (RCTs) evaluate new treatments against standard therapies.
- Survival time with right censoring is a common endpoint in clinical trials.
- The log-rank test is standard for comparing survival distributions.
Purpose of the Study:
- To present optimal two-stage clinical trial designs for survival endpoints.
- To minimize maximal or expected sample size under specified error rates.
- To facilitate early stopping for futility or both futility and efficacy.
Main Methods:
- Development of two-stage adaptive designs for RCTs.
- Optimization criteria focus on minimizing sample size (maximal or expected).
- Incorporation of early stopping rules for futility and/or efficacy.
Main Results:
- Tabulated optimal designs for various parameters.
- Simulation-based evaluation of proposed designs.
- Demonstrated reduction in sample size compared to traditional designs.
Conclusions:
- The proposed two-stage designs offer efficient planning for clinical trials with survival endpoints.
- These designs balance statistical power with resource optimization.
- Early stopping rules enhance trial efficiency and ethical considerations.
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