Extending the methods used to screen the WHO drug safety database towards analysis of complex associations and improved accuracy for rare events
Extending the methods used to screen the WHO drug safety database towards analysis of complex associations and improved accuracy for rare events
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DOI：
10.1002/sim.2473
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发表时间：
2006-11-15
影响因子：
2
通讯作者：
Edwards, I. Ralph
中科院分区：
文献类型：
--
作者：
Noren, G. Niklas;Bate, Andrew;Edwards, I. Ralph
上市后的药物安全数据集通常是海量的，并带来异质性和选择偏差的问题。然而，定量方法已被证明是非常有用的帮助，帮助临床专家在这些数据集中筛选以前未知的关联。世卫组织国际药物安全数据库是世界上最大的同类数据库，有300多万份关于疑似药物不良反应事件的报告。自1998年以来，探索性数据分析方法已被常规用于筛选该数据集中的定量关联。这种方法最初基于大样本近似，仅限于两两关联，但在本文中，我们提出了更准确的可信度区间估计，并对该方法进行了扩展，以允许分析更复杂的数量关联。通过与精确的蒙特卡罗模拟进行比较，评估了所提出的可信度区间的准确性。此外，我们提出了Mantel-Haen szel类型的调整来控制可疑的混杂因素。版权所有(C)2005 John Wiley&Sons，Ltd.
Post-marketing drug safety data sets are often massive, and entail problems with heterogeneity and selection bias. Nevertheless, quantitative methods have proven a very useful aid to help clinical experts in screening for previously unknown associations in these data sets. The WHO international drug safety database is the world's largest data set of its kind with over three million reports on suspected adverse drug reaction incidents. Since 1998, an exploratory data analysis method has been in routine use to screen for quantitative associations in this data set. This method was originally based on large sample approximations and limited to pairwise associations, but in this article we propose more accurate credibility interval estimates and extend the method to allow for the analysis of more complex quantitative associations. The accuracy of the proposed credibility intervals is evaluated through comparison to precise Monte Carlo simulations. In addition, we propose a Mantel-Haen szel -type adjustment to control for suspected confounders. Copyright (c) 2005 John Wiley & Sons, Ltd.