Bayesian optimal interval design for phase I oncology clinical trials
Abstract. The Bayesian optimal interval (BOIN) design is a novel phase I trial design for
finding the maximum tolerated dose (MTD). With the BOIN design, phase I trials
are conducted as a sequence of decision-making steps for assigning an
appropriate dose for each enrolled patient. The design optimizes the assignment
of doses to patients by minimizing incorrect decisions of dose escalation or
deescalation; that is, it decreases the chance of erroneously escalating or
de-escalating the dose when the current dose is higher or lower than the MTD.
This feature of the BOIN design strongly ensures adherence to ethical
standards. The most prominent advantage of the BOIN design is that it
simultaneously achieves design simplicity and superior performance in
comparison with similar methods. The BOIN design can be implemented in a simple
way that is similar to the 3 + 3 design, but it yields substantially better
operating characteristics. Compared with the well-known continual reassessment
method, the BOIN design yields average performance when selecting the MTD, but
it has a substantially lower risk of assigning patients to subtherapeutic or
overly toxic doses. In this article, we present a command (optinterval)
for implementing the BOIN design in a phase I clinical trial setting.
View all articles by these authors:
Bryan M. Fellman, Ying Yuan
View all articles with these keywords:
optinterval, Bayesian optimal interval, phase I clinical trial design, maximum tolerated dose, operating characteristic
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