An adaptive dose-finding design based on both safety and immunologic responses in cancer clinical trials.

Dose-finding in cancer clinical trials has been dominated by algorithmic designs on the principle that the highest tolerable dose is also the most effective dose. This assumption no longer applies to the biologic treatments that are characterized by different toxicity and/or efficacy profiles to the extent that the best therapeutic dose might be well below any dose that produces serious toxicity. As such, we propose a two-stage design with focus on immunotherapy trials, incorporating both safety and efficacy information. The 1st stage establishes the safety profile of each dose, with escalation decisions based on likelihood principles. Continuous immunologic outcomes are used to evaluate the relative efficacy of the doses. The 2nd stage employs an adaptive randomization to assign patients to doses showing higher efficacy. Safety is being continuously monitored throughout stage 2, where some doses may be 'closed' due to unacceptable toxicity. The proposed design is compared to the modified toxicity probability interval (mTPI) design using percent dose allocation and estimation of outcomes under different scenarios. We show that by using an efficacy-driven adaptive randomization with safety constraints, the allocation distribution is skewed towards more efficacious doses, and thus limit the number of patients exposed to toxic or non-therapeutic doses.