Bayesian Optimal Design for Phase II Screening Trials
نویسندگان
چکیده
منابع مشابه
Bayesian optimal design for phase II screening trials.
Most phase II screening designs available in the literature consider one treatment at a time. Each study is considered in isolation. We propose a more systematic decision-making approach to the phase II screening process. The sequential design allows for more efficiency and greater learning about treatments. The approach incorporates a Bayesian hierarchical model that allows combining informati...
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Future progress in improving cancer therapy can be expedited by better prioritization of new treatments for phase III evaluation. Historically, phase II trials have been key components in the prioritization process. There has been a long-standing interest in using phase II trials with randomization against a standard-treatment control arm or an additional experimental arm to provide greater ass...
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Despite more than two decades of publications that offer more innovative model-based designs, the classical 3 + 3 design remains the most dominant phase I trial design in practice. In this article, we introduce a new trial design, the Bayesian optimal interval (BOIN) design. The BOIN design is easy to implement in a way similar to the 3 + 3 design, but is more flexible for choosing the target t...
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The Bayesian optimal interval (BOIN) design is a novel phase I trial design for finding the maximum tolerated dose (MTD). The BOIN design is motivated by top priority and concern of clinicians, which is to effectively treat patients and minimize the chance of exposing them to subtherapeutic or overly toxic doses. The most important advantage of the BOIN design is that it is easy to implement in...
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ژورنال
عنوان ژورنال: Biometrics
سال: 2007
ISSN: 0006-341X,1541-0420
DOI: 10.1111/j.1541-0420.2007.00951.x