Bayesian optimal interval design for phase I oncology clinical trials
Bryan M. Fellman and
Stata Journal, 2015, vol. 15, issue 1
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.
Keywords: Research; Methods/; Statistical; Methods (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:stataj:271687
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