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

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.

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.

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.

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

Clinical trials (London, England). 2026 May 30 [Epub ahead of print]

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

Department of Biostatistics, Virginia Commonwealth University, Richmond, USA., Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA., Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, USA.