摘要：Typical phase I dose-finding clinical trials, notably in cancer, are characterized by a small number of patients (less than 40), a relatively high number of dose levels (4 to 6) and sequential dose allocation rules. In this setting, the Continual Reassessment Method (CRM) has been recommended as a dose allocation rule that provides a consistent method to converge to the maximal tolerated dose (MTD), possibly based on likelihood (CRML). In this adaptive design setting, we derived a Relevance Weighted Likelihood to propose a robust estimation of the MTD. The main idea is to weight the individual contributions to likelihood using a decreasing function of rank. We compare this method to the CRML throughout simulations.
