Adaptive Randomization for Multiarm Comparative Clinical Trials Based on Joint Efficacy/Toxicity Outcomes
2009
Ji, Yuan | Bekele, B Nebiyou
We present an outcomeâadaptive randomization (AR) scheme for comparative clinical trials in which the primary endpoint is a joint efficacy/toxicity outcome. Under the proposed scheme, the randomization probabilities are unbalanced adaptively in favor of treatments with superior joint outcomes characterized by higher efficacy and lower toxicity. This type of scheme is advantageous from the patients' perspective because on average, more patients are randomized to superior treatments. We extend the approximate Bayesian timeâtoâevent model in Cheung and Thall (2002,âBiometricsâ58, 89–97) to model the joint efficacy/toxicity outcomes and perform posterior computation based on a latent variable approach. Consequently, this allows us to incorporate essential information about patients with incomplete followâup. Based on the computed posterior probabilities, we propose an AR scheme that favors the treatments with larger joint probabilities of efficacy and no toxicity. We illustrate our methodology with a leukemia trial that compares three treatments in terms of their 52âweek molecular remission rates and 52âweek toxicity rates.
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