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A Bayesian Optimal Interval Design Considering Efficacy and Toxicity in Early Phase Basket Trials.
Tomoyuki Kakizume1, Kentaro Takeda2, Masataka Taguri3
1Japan Biostatistics & Data Management Department, Daiichi Sankyo Co. Ltd, Tokyo, Japan.
Pharmaceutical Statistics
|July 7, 2026
Summary
This study introduces a new oncology trial design for finding optimal biological doses. The BOIN-ETB design efficiently identifies the best dose by balancing toxicity and efficacy in basket trials across different cancer types.
Area of Science:
- Oncology
- Clinical Trial Design
- Biostatistics
Background:
- Oncology drug development increasingly focuses on optimal biological doses (ODs) over maximum tolerated doses (MTDs).
- Basket trials are efficient for evaluating treatments across multiple cancer types with shared molecular targets.
- Targeted therapies and immunotherapies often have complex dose-efficacy relationships.
Purpose of the Study:
- To propose the BOIN-ETB design for identifying optimal doses in phase I/II oncology basket trials.
- To incorporate both toxicity and efficacy endpoints for robust dose-finding.
- To address differential efficacy responses across cancer types within basket trials.
Main Methods:
- Developed a model-assisted dose-finding design (BOIN-ETB).
- Employed common toxicity boundaries and cancer-specific efficacy boundaries.
- Utilized utility functions for efficacy-toxicity trade-off quantification in optimal dose selection.
- Conducted comprehensive simulation studies across fourteen realistic scenarios.
Main Results:
- The BOIN-ETB design demonstrated robust performance in identifying true optimal doses.
- The design maintained acceptable safety profiles across diverse cancer populations.
- Showcased superior consistency compared to alternative approaches, especially with heterogeneous dose-efficacy relationships.
Conclusions:
- The BOIN-ETB design is well-suited for contemporary oncology dose-finding basket trials.
- It effectively balances efficacy and toxicity for optimal dose selection.
- Provides a reliable framework for evaluating novel oncology therapeutics in basket trial settings.
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