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Keywords: Phase I, Bayesian adaptive design, model-assisted, historical information, effective sample size,
Incorporating historical data or real-world evidence has a great potential to improve the efficiency of phase I clinical trials and accelerate drug development. For model-based designs such as the continuous reassessment method (CRM), this can be conveniently carried out by specifying a ``skeleton", i.e., the prior estimate of dose limiting toxicity (DLT) probability at each dose. In contrast, little work has been done to incorporate historical data or real-world evidence into model-assisted designs, such as mTPI, keyboard and BOIN designs, which has led to the misconception that model-assisted designs cannot incorporate prior information. In this paper, we propose a unified framework that allows incorporating historical data or real-world evidence into model-assisted designs. The proposed approach utilizes the well-established ``skeleton" approach, combined with the notion of effective sample size, thus it is easy to be understood and accepted. More importantly, our approach maintains the hallmark of the model-assisted design: simplicity---the dose escalation/de-escalation rule can be tabulated prior to the trial conduct. Extensive simulation study shows that the proposed method can effectively incorporate prior information to improve the operating characteristics of model-assisted designs in a similar way as model-based designs.