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Bayesian penalized log-likelihood ratio approach for dose response clinical trial studies
Yuanyuan Tang1, Chunyan Cai2, Liangrui Sun3
1a Cardiovascular Research, Saint Luke's Mid America Heart Institute , Saint Luke's Hospital of Kansas City, Saint Luke's Health System , Kansas City , Missouri , USA.
Journal of Biopharmaceutical Statistics
|March 21, 2017
Summary
A new Bayesian approach offers a flexible and efficient method for estimating target doses in drug development. This method improves upon existing techniques, providing comparable or better results across various dose-response relationships.
Area of Science:
- Biostatistics
- Clinical Trial Design
- Pharmacometrics
Background:
- Unified approaches for proof-of-concept testing and target dose estimation are limited.
- Existing methods include modeling-based multiple comparison procedures and permutation approaches.
Purpose of the Study:
- To develop and evaluate a novel Bayesian approach for target dose estimation.
- To compare the performance of the proposed Bayesian method against existing unified approaches.
Main Methods:
- Developed a Bayesian framework utilizing the posterior distribution of a penalized log-likelihood ratio test statistic.
- Compared operating characteristics with modeling and permutation approaches.
- Evaluated performance using extensive simulations and Phase II clinical trial data.
Main Results:
- The proposed Bayesian approach demonstrates flexibility for linear and nonlinear dose-response relationships.
- It is more efficient than the permutation approach.
- Operating characteristics are comparable or superior to existing methods across various scenarios.
Conclusions:
- The Bayesian approach provides a robust and adaptable tool for target dose estimation.
- It offers credible intervals and predictive distributions for enhanced decision-making.
- The method is extensible to diverse response types (continuous, categorical, time-to-event).
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