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Borrowing historical information to improve phase I clinical trials using meta-analytic-predictive priors
Xin Chen1, Jingyi Zhang1, Qian Jiang1
1Department of Biostatistics, China Pharmaceutical University, Nanjing, Jiangsu, China.
Journal of Biopharmaceutical Statistics
|May 20, 2022
Summary
This study introduces Meta-Analytic-Predictive (MAP) priors to improve maximum tolerated dose (MTD) estimation in early phase clinical trials by borrowing historical data. The novel approach enhances dose-finding accuracy and statistical performance.
Area of Science:
- Clinical Pharmacology
- Biostatistics
- Oncology
Background:
- Phase I clinical trials aim to determine maximum tolerated doses (MTD) for specific patient populations or cancer types.
- Estimating MTD accurately can be challenging due to limited data in individual trials.
- Leveraging historical clinical trial data can potentially improve MTD estimation and trial efficiency.
Purpose of the Study:
- To propose and evaluate Meta-Analytic-Predictive (MAP) priors for incorporating historical information into phase I clinical trials.
- To enhance the accuracy of toxicity rate estimation and MTD targeting.
- To integrate MAP priors into established dose-finding designs like CRM, Keyboard, and BOIN.
Main Methods:
- Development of Meta-Analytic-Predictive (MAP) priors to quantify heterogeneity across historical trials.
- Application of MAP priors within the Continual Reassessment Method (CRM), Keyboard design, and Bayesian Optimal Interval (BOIN) design.
- Validation through a clinical trial example and extensive simulation studies.
Main Results:
- The proposed MAP prior approach effectively estimates heterogeneity between historical trials.
- MAP priors facilitate a balanced borrowing of information, improving MTD estimation.
- Simulations and a clinical example demonstrate robust and efficient statistical performance compared to methods ignoring historical data.
Conclusions:
- Meta-Analytic-Predictive (MAP) priors offer a statistically sound method for utilizing historical data in phase I dose-finding studies.
- This approach enhances the precision and reliability of MTD determination.
- MAP priors represent a significant advancement for optimizing early-phase clinical trial designs.
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