临床试验中最大耐受剂量的确定系统

IF 0.7 Q3 STATISTICS & PROBABILITY
K. Ye, Xiaobin Yang, Y. Ji, Min Wang
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引用次数: 0

摘要

毒性研究,特别是在I期临床试验中确定最大耐受剂量(MTD),是开发新的救命药物的重要一步。在实践中,毒性水平可以分为二级、多级,或者在更普遍的情况下,可以分为连续级。在这项研究中,我们提出了一个总体MTD框架,其中包括单一毒性结果(反应)的所有上述病例。确定MTD的机制涉及由用户预先确定的功能。研究了这种系统的分析性质,并对各种场景进行了模拟研究。该框架中还隐含了连续再评估方法(CRM)的概念,并使用贝叶斯分析,包括马尔可夫链蒙特卡罗(MCMC)方法来估计模型参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A system for determining maximum tolerated dose in clinical trial
Toxicity study, especially in determining the maximum tolerated dose (MTD) in phase I clinical trial, is an important step in developing new life-saving drugs. In practice, toxicity levels may be categorised as binary grades, multiple grades, or in a more generalised case, continuous grades. In this study, we propose an overall MTD framework that includes all the aforementioned cases for a single toxicity outcome (response). The mechanism of determining MTD involves a function that is predetermined by user. Analytic properties of such a system are investigated and simulation studies are performed for various scenarios. The concept of the continual reassessment method (CRM) is also implied in the framework and Bayesian analysis, including Markov chain Monte Carlo (MCMC) methods are used in estimating the model parameters.
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来源期刊
CiteScore
0.90
自引率
20.00%
发文量
21
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