SFU: Surface-Free Utility-Based Design for Dose Optimization in Cancer Drug Combination Trials

Jingyi Zhang, Nolan A. Wages and Ruitao Lin ()
Additional contact information
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
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s12561-024-09424-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:stabio:v:16:y:2024:i:3:d:10.1007_s12561-024-09424-x

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/12561

DOI: 10.1007/s12561-024-09424-x

Access Statistics for this article

Statistics in Biosciences is currently edited by Hongyu Zhao and Xihong Lin

More articles in Statistics in Biosciences from Springer, International Chinese Statistical Association
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().