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On a Type of Probability Stopping Rule for Toxicity Study

机译:关于毒性研究的一种概率终止规则

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In early phase cancer clinical trials where toxicity events follow independent and identical Bernoulli distributions indexed by patients, the Bayesian stopping rule has been used for continuous monitoring of toxicity along with an affordable maximum sample size (N). This article studies some properties of an heuristic procedure where the trial will stop at the first time that the posterior probability that the toxicity rate (p) is greater than a threshold (η) is greater than certain probability threshold (τ). Specifically, we study the pattern formed by stopping times and regions, recursive stopping probability computation, and toxicity rate estimation. Some relevant theoretical results are given. The presented results are potentially useful for guiding toxicity clinical trial designs.
机译:在毒性事件遵循患者索引的独立且相同的伯努利分布的早期癌症临床试验中,贝叶斯停止规则已用于连续监测毒性以及可承受的最大样本量(N)。本文研究了启发式程序的一些属性,其中,当毒性率(p)大于阈值(η)的后验概率大于特定概率阈值(τ)时,试验将在第一次停止。具体来说,我们研究了由停药时间和区域,递归停药概率计算和毒性估计所形成的模式。给出了一些相关的理论结果。提出的结果可能对指导毒性临床试验设计有用。

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