All Times EDT
Keywords: dose finding; Bayesian design; utility; risk-benefit; phase I/II trials
For immunotherapy such as checkpoint inhibitors and CAR-T cell therapy, as the efficacy does not necessarily increase with the dose, the maximum tolerated dose (MTD) may not be the optimal dose for treating patients. For these novel therapies, the objective of dose-finding trials is to identify the optimal biological dose (OBD) that optimizes patients’ risk-benefit tradeoff. We propose a simple and flexible Bayesian optimal interval phase I/II (BOIN12) trial design to find the OBD that optimizes the risk-benefit tradeoff. The BOIN12 design makes the decision of dose escalation and de-escalation by simultaneously taking account of efficacy and toxicity, and adaptively allocates patients to the dose that optimizes the toxicity-efficacy tradeoff. We perform simulation studies to evaluate the performance of the BOIN12 design. Compared to existing phase I/II dose-finding designs, the BOIN12 design is simpler to implement, has higher accuracy to identify the OBD, and allocates more patients to the OBD. One of the most appealing features of the BOIN12 design is that its adaptation rule can be pre-tabulated and included in the protocol. During the trial conduct, clinicians can simply look up the decision table to allocate patients to a dose without complicated computation. The BOIN12 design is simple to implement and yields desirable operating characteristics. It overcomes the computational and implementation complexity that plagues existing Bayesian phase I/II designs, and provides a useful design to optimize the dose of immunotherapy and targeted therapy. User-friendly software will be freely available to facilitate the application of the BOIN12 design.