Evidence map›Paper›PMID 42216813›Full record

ArticleClinical trials (London, England)2026

Phase I design for partially ordered groups with late-onset toxicity.

Rami Hawila, Susan Halabi, Ruitao Lin, Nolan A Wages

Abstract read
In one paragraph

Article in Clinical trials (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Rami HawilaDepartment of Biostatistics, Virginia Commonwealth University, Richmond, USA.ORCID 0009-0007-1360-7695
Susan HalabiDepartment of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.ORCID 0000-0003-4135-2777
Ruitao LinDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, USA.ORCID 0000-0003-2244-131X
Nolan A WagesDepartment of Biostatistics, Virginia Commonwealth University, Richmond, USA.ORCID 0000-0002-2190-4864

Funding

Bayesian Methods for Complex Precision Biotherapy Trials in OncologyR01CA261978 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LIN, RUITAO, THALL, PETER F · 2021 to 2024
$1.4M
Dose finding designs for late-onset toxicitiesR01CA247932 · NCI · VIRGINIA COMMONWEALTH UNIVERSITY · PI WAGES, NOLAN · 2021 to 2023
$1.0M
NCI NIH HHS R01 CA247932NCI NIH HHS R01 CA261978
6 · The paper itself

Abstract

backgroundIn this article, we introduce a Phase I clinical trial design that utilizes late-onset toxicity outcomes to determine group-specific doses when groups are partially ordered before the trial. By "partially ordered groups," we mean that the frailty order is known between some, but not all, groups. Previous research has addressed dose finding for partially ordered groups and for late-onset toxicity separately, but no solution has been proposed for dose finding that incorporates both aspects simultaneously.

methodsMotivated by a Phase Ib study involving heterogeneous groups with metastatic castration-resistant prostate cancer, we extend the continual reassessment method shift model framework to tackle the problem of dose finding in partially ordered groups with late-onset toxicity. Our simulations compare the proposed method with an approach that incorporates group information without considering late-onset toxicity. An alternative strategy could involve conducting independent parallel trials for each group; however, this approach risks dose reversals, where a more sensitive group is assigned a higher dose than a less sensitive group.

resultsIn comparison with a similar dose-finding method that does not incorporate late-onset toxicity, our proposed method shows similar performance in selecting the correct dose. Through an extensive simulation study, the generated results demonstrate good operating characteristics for the proposed method in terms of the proportion of correct dose selection within groups, while accounting for late-onset toxicities.

conclusionOur proposed method avoids dose reversals and demonstrates favorable operating characteristics in recommending appropriate doses for each group.

Indexed as

Antineoplastic AgentsClinical Trials, Phase I as TopicProstatic Neoplasms, Castration-ResistantResearch DesignComputer SimulationDose-Response Relationship, DrugHumansMaleMaximum Tolerated DoseAntineoplastic AgentscancerDose-finding designslate-onset toxicitiespatient heterogeneity

Identifiers

PMID42216813
PMCPMC13225609

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.