Precision Dose-finding Cancer Clinical Trials in the Setting of Broadened Eligibility
Rebecca B. Silva, Bin Cheng, Richard D. Carvajal, Shing M. Lee

TL;DR
This paper introduces a novel precision dose-finding design for phase I cancer trials that accounts for unknown patient heterogeneity, enabling more accurate dose recommendations across diverse patient subgroups.
Contribution
It proposes a two-in-one approach that simultaneously identifies relevant patient criteria and estimates subgroup-specific maximum tolerated doses using marginal models.
Findings
Design recommends multiple doses when heterogeneity exists.
Design suggests a single dose when no heterogeneity is detected.
Simulation shows improved dose recommendations over naive methods.
Abstract
Broadening eligibility criteria in cancer trials has been advocated to represent the true patient population more accurately. While the advantages are clear in terms of generalizability and recruitment, novel dose-finding designs are needed to ensure patient safety. These designs should be able to recommend precise doses for subpopulations if such subpopulations with different toxicity profiles exist. While dose-finding designs accounting for patient heterogeneity have been proposed, all existing methods assume the source of heterogeneity is known and thus pre-specify the subpopulations or only allow inclusion of a few patient characteristics. We propose a precision dose-finding design to address the setting of unknown patient heterogeneity in phase I cancer clinical trials where eligibility is expanded, and multiple eligibility criteria could potentially lead to different optimal doses…
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Taxonomy
TopicsStatistical Methods in Clinical Trials · Health Systems, Economic Evaluations, Quality of Life · Advanced Causal Inference Techniques
