Variable selection on large case-crossover data: application to a registry-based study of prescription drugs and road traffic crashes
Variable selection on large case-crossover data: application to a registry-based study of prescription drugs and road traffic crashes
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DOI：
10.1002/pds.3539
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发表时间：
2014-02-01
影响因子：
2.6
通讯作者：
Lagarde, Emmanuel
中科院分区：
文献类型：
--
作者：
Avalos, Marta;Orriols, Ludivine;Lagarde, Emmanuel
目的在对大量暴露人群的药物流行病学数据的探索性分析中，概念和计算问题都是如何使用概率推理来筛选假设，选择最需要进一步进行假设检验的药物类别或单个药物。方法我们报告了使用收缩技术Lasso来探索性分析处方药和道路交通事故的数据，该方法是由Orriols和他的同事描述的病例交叉配对间隔方法(PLoS Med 2010；7：E1000366)产生的。为了防止假阳性结果，我们考虑使用套索的自举增强版本。结果抗癫痫药、苯二氮卓类催眠药、抗焦虑药、抗抑郁药、抗血栓药、矿物质补充剂、糖尿病药物、抗帕金森病治疗药物和几种心血管药物显示出与道路交通事故或事故责任的可疑关联。结论这些结果与文献中的其他发现相关联，提供了新的见解，并可能对处方药的使用与驾驶能力受损之间的联系产生新的假设。版权所有(C)2013 John Wiley&Sons，Ltd.
PurposeIn exploratory analyses of pharmacoepidemiological data from large populations with large number of exposures, both a conceptual and computational problem is how to screen hypotheses using probabilistic reasoning, selecting drug classes or individual drugs that most warrant further hypothesis testing.MethodsWe report the use of a shrinkage technique, the Lasso, in the exploratory analysis of the data on prescription drugs and road traffic crashes, resulting from the case-crossover matched-pair interval approach described by Orriols and colleagues (PLoS Med 2010; 7:e1000366). To prevent false-positive results, we consider a bootstrap-enhanced version of the Lasso. To highlight the most stable results, we extensively examine sensitivity to the choice of referent window.ResultsAntiepileptics, benzodiazepine hypnotics, anxiolytics, antidepressants, antithrombotic agents, mineral supplements, drugs used in diabetes, antiparkinsonian treatment, and several cardiovascular drugs showed suspected associations with road traffic accident involvement or accident responsibility.ConclusionThese results, in relation to other findings in the literature, provide new insight and may generate new hypotheses on the association between prescription drugs use and impaired driving ability. Copyright (c) 2013 John Wiley & Sons, Ltd.