SFU: Surface-Free Utility-Based Design for Dose Optimization in Cancer Drug Combination Trials
Jingyi Zhang,
Nolan A. Wages and
Ruitao Lin ()
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Jingyi Zhang: China Pharmaceutical University
Nolan A. Wages: Virginia Commonwealth University
Ruitao Lin: The University of Texas MD Anderson Cancer Center
Statistics in Biosciences, 2024, vol. 16, issue 3, No 15, 854-881
Abstract:
Abstract Precision oncology has demonstrated the potential of drug combinations in effectively enhancing anti-tumor efficiency and controlling disease progression. Nonetheless, dose optimization in early-phase drug combination trials presents various challenges and is considerably more complex than single-agent dose optimization. To address this, we propose a surface-free design for exploring the optimal doses of combination therapy within the phase I–II framework. Rather than relying on parametric models to define the shape of toxicity and efficacy surfaces, our approach centers on characterizing dose-toxicity and dose-efficacy relationships between adjacent dose combinations using surface-free models. The proposed design encompasses a run-in phase, facilitating a swift exploration of the dose space, followed by a main phase where the dose-finding rule relies on the proposed surface-free model. Through extensive simulation studies, we have thoroughly examined the operating characteristics of this innovative design. The results demonstrate that our method exhibits desirable operating characteristics across a wide range of dose-toxicity and dose-efficacy relationships.
Keywords: Bayesian adaptive trial design; Drug combination; Model-free method; Phase I–II design; Risk-benefit tradeoff (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s12561-024-09424-x
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