Abstract
A number of novel model-based and model-assisted designs have been proposed to find the MTD in phase I clinical trials, but their differences and relative pros and cons are not clear to many practitioners. We review three model-based designs, including the continual reassessment method (CRM), dose escalation with overdose control (EWOC), and Bayesian logistic regression model (BLRM), and three model-assisted designs, including the modified toxicity probability interval (mTPI), Bayesian optimal interval (BOIN), and keyboard (equivalently mTPI-2) designs. We conduct numerical studies to assess their accuracy, safety, and reliability and the practical implications of various empirical rules used in some designs, such as skipping a dose and imposing overdose control. Our results show that the CRM outperforms EWOC and BLRM with higher accuracy of identifying the MTD. For the CRM, skipping a dose is not recommended, as it substantially increases the chance of overdosing patients while providing limited gain for identifying the MTD. EWOC and BLRM appear excessively conservative. They are safe but have relatively poor accuracy of finding the MTD. The BOIN and keyboard (equivalently mTPI-2) designs have similar operating characteristics, outperforming the mTPI, but the BOIN is more intuitive and transparent. The BOIN yields competitive performance comparable with the CRM but is simpler to implement and free of the issue of irrational dose assignment caused by model misspecification, thereby providing an attractive approach for designing phase I trials. Clin Cancer Res; 24(18); 4357-64. ©2018 AACR.
Highlights
Most phase I oncology clinical trials are designed to identify the MTD of a new drug, which is defined as the dose with a dose-limiting toxicity (DLT) probability that is closest to the target DLT probability
The poor accuracy of the Bayesian logistic regression model (BLRM) can be addressed by removing the overdose control rule; the BLRM-NOC has the highest average percentage of correct selection (PCS)
The BLRM and escalation with overdose control (EWOC) perform the worst, and BLRM-NOC and continual reassessment method (CRM)-DS perform well, with the highest average percentage of patients treated at the MTD
Summary
Most phase I oncology clinical trials are designed to identify the MTD of a new drug, which is defined as the dose with a dose-limiting toxicity (DLT) probability that is closest to the target DLT probability. The 3 þ 3 design [1] has been dominant in phase I clinical trials for decades despite its poor ability to identify the MTD and tendency to treat patients at low doses that are potentially subtherapeutic [2]. Novel phase I trial designs that have been proposed to improve the efficiency of identifying the MTD include model-based designs and model-assisted designs. The continual reassessment method (CRM) is a typical example of a model-based design that assumes a parametric model for the dose–toxicity curve and based on the accumulating trial data, continuously updates the estimate of the curve to guide the dose assignment and MTD selection [3]. Various extensions of the CRM have been proposed, including dose escalation with
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