Evaluation of phase I clinical trial designs for combinational agents along with guidance based on simulation studies

Shu Wang, Elias Sayour and Ji-Hyun Lee

Journal of Applied Statistics, 2023, vol. 50, issue 9, 2055-2078

Abstract: Combinational therapy that combines two or more therapeutic agents is very common in cancer treatment. Currently, many clinical trials aim to assess feasibility, safety and activity of combinational therapeutics to achieve synergistic response. Dose-finding for combinational agents is considerably more complex than single agent, because only partial order of dose combinations' toxicity is known. Prototypical phase I designs may not adequately capture this complexity thus limiting identification of the maximum tolerated dose (MTD) of combinational agents. In response, novel phase I clinical trial designs for combinational agents have been extensively proposed. However, with so many available designs, studies that compare their performances and explore the impact of design parameters, along with providing recommendations are limited. We are evaluating available phase I designs that identify a single MTD for combinational agents using simulation studies under various conditions. We are also exploring the influences of different design parameters and summarizing the risks/benefits of each design to provide general guidance in design selection.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:50:y:2023:i:9:p:2055-2078

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DOI: 10.1080/02664763.2022.2105827

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