Faculty, Staff and Student Publications

Publication Date

5-20-2022

Journal

Statistics in Medicine

Abstract

In the era of immunotherapies and targeted therapies, the focus of early phase clinical trials has shifted from finding the maximum tolerated dose to identifying the optimal biological dose (OBD), which maximizes the toxicity-efficacy trade-off. One major impediment to using adaptive designs to find OBD is that efficacy or/and toxicity are often late-onset, hampering the designs’ real-time decision rules for treating new patients. To address this issue, we propose the model-assisted TITE-BOIN12 design to find OBD with late-onset toxicity and efficacy. As an extension of the BOIN12 design, the TITE-BOIN12 design also uses utility to quantify the toxicity-efficacy trade-off. We consider two approaches, Bayesian data augmentation and an approximated likelihood method, to enable real-time decision making when some patients’ toxicity and efficacy outcomes are pending. Extensive simulations show that, compared to some existing designs, TITE-BOIN12 significantly shortens the trial duration while having comparable or higher accuracy to identify OBD and a lower risk of overdosing patients. To facilitate the use of the TITE-BOIN12 design, we develop a user-friendly software freely available at www.trialdesign.org.

Keywords

Bayes Theorem, Clinical Trials, Phase I as Topic, Clinical Trials, Phase II as Topic, Computer Simulation, Dose-Response Relationship, Drug, Humans, Immunotherapy, Maximum Tolerated Dose, Research Design, Bayesian adaptive design, risk-benefit trade-off, dose optimization, dose finding

DOI

10.1002/sim.9337

PMID

35098585

PMCID

PMC9199061

PubMedCentral® Posted Date

6-15-2022

PubMedCentral® Full Text Version

Author MSS

Published Open-Access

yes

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