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Bayesian Sequential Monitoring of Single-Arm Trials: A Comparison of Futility Rules Based on Binary Data
1Dipartimento di Scienze Statistiche, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy.
Summary
This study introduces Bayesian futility rules for early clinical trial termination in single-arm studies. These methods enhance decision-making by analyzing probabilities to determine if a treatment is unlikely to succeed.
Area of Science:
- Clinical Trials Methodology
- Bayesian Statistics
- Biostatistics
Background:
- Futility rules are crucial for monitoring clinical trials and enabling early termination.
- Ensuring experimental treatments meet efficacy targets is a primary goal in clinical research.
Purpose of the Study:
- To develop and evaluate Bayesian strategies for interim analyses in single-arm clinical trials.
- To modify futility rules for improved accuracy when using historical response rates.
Main Methods:
- Utilizing Bayesian approaches for interim analyses with binary response variables.
- Employing both posterior and predictive probabilities in trial monitoring.
- Modifying futility rules by incorporating prior distributions to account for uncertainty in standard treatment efficacy.
Main Results:
- Comparison of stopping boundaries for different Bayesian designs under identical trial conditions.
- Simulation studies assessing the operating characteristics of the proposed futility rules.
- Evaluation of probability cut-off calibration for decision-making.
Conclusions:
- Bayesian strategies offer a robust framework for interim analyses in single-arm trials.
- Modified futility rules can improve the reliability of early trial termination decisions.
- The proposed methods provide valuable tools for efficient clinical trial monitoring.
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