Phase I/II adaptive design for drug combination oncology trials

Existing statistical methodology on dose finding for combination chemotherapies has focused on toxicity considerations alone in finding a maximum tolerated dose combination to recommend for further testing of efficacy in a phase II setting. Recently, there has been increasing interest in integrating...

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Bibliographic Details
Published in:Statistics in medicine 2014-05, Vol.33 (12), p.1990-2003
Main Authors: Wages, Nolan A., Conaway, Mark R.
Format: Article
Language:English
Subjects:
adaptive randomization
Algorithms
Antineoplastic Combined Chemotherapy Protocols - administration & dosage
Antineoplastic Combined Chemotherapy Protocols - adverse effects
Chemotherapy
Clinical trials
Clinical Trials, Phase I as Topic
Clinical Trials, Phase II as Topic
continual reassessment method
dose finding
Dose-Response Relationship, Drug
drug combination
Drug dosages
Humans
Maximum Tolerated Dose
Models, Statistical
Neoplasms - drug therapy
Oncology
phase II
R&D
Research & development
Research Design
Simulation
Toxicity
Treatment Outcome
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Summary:Existing statistical methodology on dose finding for combination chemotherapies has focused on toxicity considerations alone in finding a maximum tolerated dose combination to recommend for further testing of efficacy in a phase II setting. Recently, there has been increasing interest in integrating phase I and phase II trials in order to facilitate drug development. In this article, we propose a new adaptive phase I/II method for dual‐agent combinations that takes into account both toxicity and efficacy after each cohort inclusion. The primary objective, both within and at the conclusion of the trial, becomes finding a single dose combination with an acceptable level of toxicity that maximizes efficacious response. We assume that there exist monotone dose–toxicity and dose–efficacy relationships among doses of one agent when the dose of other agent is fixed. We perform extensive simulation studies that demonstrate the operating characteristics of our proposed approach, and we compare simulated results to existing methodology in phase I/II design for combinations of agents. Copyright © 2014 John Wiley & Sons, Ltd.
ISSN:0277-6715
1097-0258
DOI:10.1002/sim.6097