Dose Individualization for Phase I Cancer Trials With Broadened Eligibility

ABSTRACT Broadening eligibility criteria in cancer trials has been advocated to represent the intended patient population more accurately. The advantages are clear in terms of generalizability and recruitment, however there are some important considerations in terms of design for efficiency and pati...

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Veröffentlicht in:Statistics in medicine 2024-12, Vol.43 (29), p.5534-5547
Hauptverfasser: Silva, Rebecca B., Cheng, Bin, Carvajal, Richard D., Lee, Shing M.
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container_end_page 5547
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container_start_page 5534
container_title Statistics in medicine
container_volume 43
creator Silva, Rebecca B.
Cheng, Bin
Carvajal, Richard D.
Lee, Shing M.
description ABSTRACT Broadening eligibility criteria in cancer trials has been advocated to represent the intended patient population more accurately. The advantages are clear in terms of generalizability and recruitment, however there are some important considerations in terms of design for efficiency and patient safety. While toxicity may be expected to be homogeneous across these subpopulations, designs should be able to recommend safe and precise doses if subpopulations with different toxicity profiles exist. Dose‐finding designs accounting for patient heterogeneity have been proposed, but existing methods assume that the source of heterogeneity is known. We propose a broadened eligibility dose‐finding design to address the situation 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 for patient subgroups. The design offers a two‐in‐one approach to dose‐finding by simultaneously selecting patient criteria that differentiate the maximum tolerated dose (MTD), using stochastic search variable selection, and recommending the subpopulation‐specific MTD if needed. Our simulation study compares the proposed design to the naive approach of assuming patient homogeneity and demonstrates favorable operating characteristics across a wide range of scenarios, allocating patients more often to their true MTD during the trial, recommending more than one MTD when needed, and identifying criteria that differentiate the patient population. The proposed design highlights the advantages of adding more variability at an early stage and demonstrates how assuming patient homogeneity can lead to unsafe or sub‐therapeutic dose recommendations.
doi_str_mv 10.1002/sim.10264
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The design offers a two‐in‐one approach to dose‐finding by simultaneously selecting patient criteria that differentiate the maximum tolerated dose (MTD), using stochastic search variable selection, and recommending the subpopulation‐specific MTD if needed. Our simulation study compares the proposed design to the naive approach of assuming patient homogeneity and demonstrates favorable operating characteristics across a wide range of scenarios, allocating patients more often to their true MTD during the trial, recommending more than one MTD when needed, and identifying criteria that differentiate the patient population. 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The design offers a two‐in‐one approach to dose‐finding by simultaneously selecting patient criteria that differentiate the maximum tolerated dose (MTD), using stochastic search variable selection, and recommending the subpopulation‐specific MTD if needed. Our simulation study compares the proposed design to the naive approach of assuming patient homogeneity and demonstrates favorable operating characteristics across a wide range of scenarios, allocating patients more often to their true MTD during the trial, recommending more than one MTD when needed, and identifying criteria that differentiate the patient population. 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source Wiley Online Library - AutoHoldings Journals; MEDLINE
subjects Antineoplastic Agents - administration & dosage
Antineoplastic Agents - adverse effects
Antineoplastic Agents - therapeutic use
Bayesian variable selection
Cancer
Clinical outcomes
Clinical trials
Clinical Trials, Phase I as Topic - methods
Computer Simulation
dose selection
Dose-Response Relationship, Drug
Drug dosages
Humans
Maximum Tolerated Dose
Models, Statistical
Neoplasms - drug therapy
patient heterogeneity
Patient Selection
phase I
Research Design
Toxicity
title Dose Individualization for Phase I Cancer Trials With Broadened Eligibility
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