Accounting for multiplicities in assessing drug safety: A three-level hierarchical mixture model
Accounting for multiplicities in assessing drug safety: A three-level hierarchical mixture model
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DOI：
10.1111/j.0006-341x.2004.00186.x
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发表时间：
2004-06-01
期刊：
影响因子：
1.9
通讯作者：
Berry, DA
中科院分区：
文献类型：
--
作者：
Berry, SM;Berry, DA
多重比较和其他多重性是统计学家、频率论者和贝叶斯学派面临的最困难的问题之一。一个例子是分析药物临床试验中记录的多种类型的不良事件（AE）。我们提出了一个三层分层混合模型。最基本的层次是AE类型。第二个层次是身体系统，每一个层次都包含许多类型的可能相关的AE。最高层次是所有身体系统的集合。我们的分析允许跨身体系统的借用，但根据实际数据，每个身体系统内的借用有更大的潜力。如果同一身体系统内几种类型AE的发生率升高，则药物导致某种类型AE的概率大于发生率升高的AE发生在不同身体系统中的概率。我们给出的例子来说明我们的方法，我们描述其应用程序的其他类型的问题。
Multiple comparisons and other multiplicities are among the most difficult of problems that face statisticians, frequentists, and Bayesians alike. An example is the analysis of the many types of adverse events (AEs) that are recorded in drug clinical trials. We propose a three-level hierarchical mixed model. The most basic level is type of AE. The second level is body system, each of which contains a number of types of possibly related AEs. The highest level is the collection of all body systems. Our analysis allows for borrowing across body systems, but there is greater potential-depending on the actual data-for borrowing within each body system. The probability that a drug has caused a type of AE is greater if its rate is elevated for several types of AEs within the same body system than if the AEs with elevated rates were in different body systems. We give examples to illustrate our method and we describe its application to other types of problems.