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

BACKGROUND: In 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. METHODS: Motivated 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. RESULTS: In 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. CONCLUSION: Our proposed method avoids dose reversals and demonstrates favorable operating characteristics in recommending appropriate doses for each group.

Authors

Institutions

Publication Details

Journal
Clinical Trials
Published
2026-05-30
DOI
https://doi.org/10.1177/17407745261448830
Primary Topic
Statistical Methods in Clinical Trials
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Nolan A. Wages, Ruitao Lin, Rami Hawila, Susan Halabi
Clinical Trials
Statistical Methods in Clinical Trials
article

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

Nolan A. Wages, Ruitao Lin, Rami Hawila, Susan Halabi
article en

Abstract

BACKGROUND: In 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. METHODS: Motivated 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. RESULTS: In 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. CONCLUSION: Our proposed method avoids dose reversals and demonstrates favorable operating characteristics in recommending appropriate doses for each group.

Clinical Trials
The University of Texas MD Anderson Cancer Center (US), Duke University (US), Virginia Commonwealth University (US)
National Institutes of Health
Good health and well-being
Openalex Percentile: Top 4%
Statistical Methods in Clinical Trials
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.