May 2024 Statistical Frameworks for Oncology Dose-Finding Designs with Late-Onset Toxicities: A Review
Tianjian Zhou, Yuan Ji
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Statist. Sci. 39(2): 243-261 (May 2024). DOI: 10.1214/23-STS895

Abstract

In oncology dose-finding trials, due to staggered enrollment, it might be desirable to make dose-assignment decisions in real time in the presence of pending toxicity outcomes, for example, when the dose-limiting toxicity is late onset. Patients’ time-to-event information may be utilized to facilitate such decisions. We review statistical frameworks for time-to-event modeling in dose-finding trials and summarize existing designs into two classes: TITE designs and POD designs. TITE designs are based on inference about toxicity probabilities, while POD designs are based on probabilities of dose-assignment decisions. These two classes of designs contain existing individual designs as special cases and also give rise to new designs. We discuss and study the theoretical properties of these designs, including large-sample convergence properties, coherence principles and the underlying decision rules. To facilitate the use of these designs in practice, we introduce efficient computational algorithms and review common practical considerations, such as safety rules and suspension rules. Finally, the operating characteristics of several designs are evaluated and compared through computer simulations.

Acknowledgments

The authors would like to thank the Editor (Sonia Petrone), the former Editor (Cun-Hui Zhang) and the anonymous Associate Editors and referees for their constructive comments that improved the quality of this paper.

Citation

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Tianjian Zhou. Yuan Ji. "Statistical Frameworks for Oncology Dose-Finding Designs with Late-Onset Toxicities: A Review." Statist. Sci. 39 (2) 243 - 261, May 2024. https://doi.org/10.1214/23-STS895

Information

Published: May 2024
First available in Project Euclid: 5 May 2024

Digital Object Identifier: 10.1214/23-STS895

Keywords: Clinical trial design , maximum tolerated dose , missing data , Survival analysis , time-to-event modeling

Rights: Copyright © 2024 Institute of Mathematical Statistics

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Vol.39 • No. 2 • May 2024
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