Bayesian decision procedures based on logistic regression models for dose-finding studies.
Bayesian decision procedures based on logistic regression models for dose-finding studies.
复制标题
DOI：
10.1080/10543409808835252
复制
发表时间：
1998-07-01
影响因子：
1.1
通讯作者：
Williamson, D
中科院分区：
文献类型：
--
作者：
Whitehead, J;Williamson, D
考虑早期临床试验，以确定实验药物的适当剂量，以进行后期试验。目的是找到与不良事件低概率相关的剂量。贝叶斯模型，并得出一个决策理论的程序，找到最佳剂量的一系列队列的受试者。这一程序很灵活，可以很容易地使用标准统计软件进行。给出了研究该过程特性的模拟结果。
Early-phase clinical trials, conducted to determine the appropriate dose of an experimental drug to take forward to later trials, are considered. The objective is to find the dose associated with some low probability of an adverse event. A Bayesian model is presented, and a decision-theoretic procedure for finding the optimal doses for each of a series of cohorts of subjects is derived. The procedure is flexible and can easily be conducted using standard statistical software. The results of simulations investigating the properties of the procedure are presented.