科研之友
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摘要
Numerous models have been suggested for Phase I adaptive designs for identifying the maximum tolerated combination (MTC) of two agents. However, these designs have yet to be adopted as the standard approach to use in actual clinical trials, which we posit is mostly due to the complexity of the models that are used. Given that the continual reassessment method (CRM) is gradually being adopted as a standard for single-agent Phase I trials, we propose a generalized version of the CRM, which we denote by gCRM, in hopes of providing such a standard for two-agent trials. For each dose of one agent, we apply the traditional CRM to study doses of the other agent; each of these CRM designs assumes the same dose-toxicity model, as well as the value of the parameter used in the model. However, each model includes a second parameter that varies among the models in an effort to allow flexibility when modeling the probability of dose-limiting toxicity (DLT) of all combinations, yet borrow strength among neighboring combinations as well. We incorporate an adaptive Bayesian algorithm to sequentially assign each patient to the most appropriate dose combination, as well as focus patient assignments to a dose combination that has a DLT probability closest to a prespecified target rate. We test the performance of our method via extensive simulations in various scenarios that are likely to arise in two-agent Phase I trials. We also directly compare the operating characteristics of our model to the alternate published models.
- 出版日期2013-5
