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A Biomarker-Based Dose-Schedule Optimization Design for Immunotherapy Trials.
Yingjie Qiu1,2, Yan Han3, Beibei Guo4
1Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Statistics in Medicine
|January 23, 2026
Summary
Optimizing immunotherapy drug dose and schedule is crucial. This study proposes a tailored strategy using immune response, efficacy, and toxicity data for biomarker subgroups, improving clinical trial decision-making.
Area of Science:
- Immunotherapy
- Clinical Trial Design
- Biostatistics
Background:
- Drug dose and schedule significantly impact immunotherapy efficacy by modulating immune responses.
- Integrating immune response measures into clinical trials aids decision-making due to their link with efficacy and toxicity.
- Biomarker data can identify patient subgroups with improved treatment efficacy.
Purpose of the Study:
- To develop a dose-schedule optimization strategy for immunotherapy clinical trials.
- To tailor treatment optimization to specific biomarker-defined patient subgroups.
- To leverage immune response, toxicity, and efficacy data for enhanced decision-making.
Main Methods:
- A joint modeling framework was developed to simultaneously evaluate immune response, toxicity, and efficacy.
- Utility functions were elicited to capture patient-specific risk-benefit tradeoffs.
- Parsimonious yet flexible models were employed to handle small sample sizes in early-phase trials.
Main Results:
- The proposed joint modeling framework enables information sharing across different outcome types and patient subgroups.
- Simulation studies demonstrated desirable operating characteristics for the dose-schedule optimization design.
- The approach effectively informs dose-schedule optimization tailored to biomarker subgroups.
Conclusions:
- A novel dose-schedule optimization strategy enhances immunotherapy clinical trial design.
- Tailoring treatment based on biomarker subgroups and integrated outcome modeling improves risk-benefit assessment.
- The proposed methods are suitable for early-phase trials with limited sample sizes.
Keywords:
Bayesian adaptive designbiomarkerimmunotherapyoptimal treatment regimephase I/II trialrisk‐benefit tradeoffsubgroupsMore Related Videos
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