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Investigating Different Priors in Bayesian Continual Reassessment Method

机译:调查贝叶斯连续重新评估方法的不同前瞻

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Clinical trials are studies that explore whether a treatment, drug or device is safe and effective for humans. These studies can show which medial method work best for certain diseases. A well-designed and a properly-analyzed clinical trial is a powerful tool for the development of new drugs. The first step in drug discovery (phase I) is very important to determine maximum tolerated dose (MTD).In the first part of the study, the classical 3+3 design, Continual Reassessment Method (CRM), and Bayesian Continual Reassessment Method (B-CRM) are compared in terms of selection probability of MTD and the number of treated patients. Among these designs, the B-CRM produced better results than the 3+3 and the CRM. In the second part of the study, we considered different model structures and priors in the B-CRM design. We evaluated power model, hyperbolic tanget model and logit model for gamma, uniform and lognormal prior. We found that if power or hyperbolic tangent model structure and uniform prior was selected, the MTD selection rates was the highest in B-CRM.
机译:临床试验是探索治疗,药物或装置是否对人类安全有效的研究。这些研究可以显示某些疾病最适合哪种内侧方法。精心设计和妥善分析的临床试验是开发新药的强大工具。药物发现的第一步(阶段I)非常重要,可以确定最大耐受剂量(MTD)。在研究的第一部分,经典3 + 3设计,连续重新评估方法(CRM)和贝叶斯连续重新评估方法(在MTD的选择概率和治疗患者的数量方面进行比较B-CRM。在这些设计中,B-CRM产生比3 + 3和CRM更好的结果。在研究的第二部分中,我们在B-CRM设计中考虑了不同的模型结构和前瞻。我们评估了伽玛,统一和逻辑的功率模型,双曲弯矩和Logit模型。我们发现,如果选择了功率或双曲线切线模型结构和均匀,则MTD选择速率在B-CRM中最高。

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