Extreme value modelling of laboratory safety data from clinical studies
Extreme value modelling of laboratory safety data from clinical studies
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DOI：
10.1002/pst.1510
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发表时间：
2012-09-01
影响因子：
1.5
通讯作者：
Heffernan, Janet E.
中科院分区：
文献类型：
--
作者：
Southworth, Harry;Heffernan, Janet E.
大多数临床研究收集了几个安全性相关的实验室变量。通常，这些变量的极值表明存在潜在的安全问题。我们说明了新的极端值模型的应用，这些数据的目的是预测严重的药物不良反应的发生率。通过将该方法应用于临床试验数据集，我们确定了剂量反应关系，并使用贝叶斯技术，通过从拟合模型进行预测来确定潜在的安全性问题，尽管样本量很小。版权所有（C）2012约翰威利父子有限公司
Most clinical studies collect several safety-related laboratory variables. Generally, it is the extreme values of these variables that indicate potential safety issues. We illustrate the novel application of extreme value modelling to such data, with the aim of predicting the incidence of severe adverse drug reactions. By applying the methods to a clinical trial data set, we identify a doseresponse relationship and use Bayesian techniques to identify a potential safety concern by making predictions from the fitted model, despite the small sample size. Copyright (C) 2012 John Wiley & Sons, Ltd.