  Incorporating historical data or real-world evidence has a great potential to
improve the efficiency of phase I clinical trials and to 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 the Bayesian optimal
interval (BOIN), keyboard, and modified toxicity probability interval (mTPI)
designs. This has led to the misconception that model-assisted designs cannot
incorporate prior information. In this paper, we propose a unified framework
that allows for incorporating historical data or real-world evidence into
model-assisted designs. The proposed approach uses the well-established
"skeleton" approach, combined with the concept of prior effective sample size,
thus it is easy to understand and use. More importantly, our approach maintains
the hallmark of model-assisted designs: simplicity---the dose
escalation/de-escalation rule can be tabulated prior to the trial conduct.
Extensive simulation studies show that the proposed method can effectively
incorporate prior information to improve the operating characteristics of
model-assisted designs, similarly to model-based designs.
