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Sample sizes for phase ii clinical trials derived from Bayesian decision theory

机译：基于贝叶斯决策理论的II期临床试验样本量

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AbstractIn early phase clinical trials of a new medical treatment, patients are treated to decide whether there is sufficient promise to justify additional studies. A decision theoretic approach is proposed to help determine the number of patients that should be treated. The optimal sample size is obtained by maximizing a utility function which incorporates both the number of ‘gained successes’ and the costs of treatment. The method extends work of Sylvester and Staquet, and adopts a Bayesian formulation. Numbers of patients in later studies and in eventual routine use of the treatment are taken into account. We allow for the possibility that a later study might lead to an erroneous conclusion. The effects of these various influences on the recommended sampling plan for the early phase clinical trial are explo
机译：摘要在一种新疗法的早期临床试验中，对患者进行治疗以决定是否有足够的希望来证明其他研究的合理性。提出了一种决策理论方法，以帮助确定应治疗的患者数量。最佳样本量是通过最大化效用函数获得的，该函数包含“获得的成功”数量和治疗成本。该方法扩展了 Sylvester 和 Staquet 的工作，并采用了贝叶斯公式。考虑了后期研究和最终常规使用治疗的患者数量。我们允许后来的研究可能导致错误结论的可能性。这些不同的影响因素对早期临床试验推荐的抽样计划的影响是爆炸性的

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