A trivariate continual reassessment method for phase I/II trials of toxicity, efficacy, and surrogate efficacy

• Published in: Statistics in medicine Vol. 31; no. 29; pp. 3885 - 3895
• Main Authors: Zhong, Wei, Koopmeiners, Joseph S., Carlin, Bradley P.
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 20.12.2012; Wiley Subscription Services, Inc
• Subjects: Algorithms; Antineoplastic Agents - adverse effects; Antineoplastic Agents - therapeutic use; Bayes Theorem; Bayesian adaptive methods; Biomarkers; Cancer; Clinical Trials, Phase I as Topic - statistics & numerical data; Clinical Trials, Phase II as Topic - statistics & numerical data; continual reassessment method (CRM); Dose-Response Relationship, Drug; Humans; Lymphoma - drug therapy; Maximum Tolerated Dose; maximum tolerated dose (MTD); Medical statistics; phase I/II clinical trial; Research Design - statistics & numerical data; Simulation; surrogate efficacy; Toxicity
• ISSN: 0277-6715; 1097-0258
• DOI: 10.1002/sim.5477

Recently, many Bayesian methods have been developed for dose finding when simultaneously modeling both toxicity and efficacy outcomes in a blended phase I/II fashion. A further challenge arises when all the true efficacy data cannot be obtained quickly after the treatment so that surrogate markers are instead used (e.g., in cancer trials). We propose a framework to jointly model the probabilities of toxicity, efficacy, and surrogate efficacy given a particular dose. Our trivariate binary model is specified as a composition of two bivariate binary submodels. In particular, we extend the bivariate continual reassessment method (CRM), as well as utilize a particular Gumbel copula. The resulting trivariate algorithm utilizes all the available data at any given time point and can flexibly stop the trial early for either toxicity or efficacy. Our simulation studies demonstrate that our proposed method can successfully improve dosage targeting efficiency and guard against excess toxicity over a variety of true model settings and degrees of surrogacy. Copyright © 2012 John Wiley & Sons, Ltd.