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Mining Safety Signals in Spontaneous Reports Database Using Concept Analysis

机译:使用概念分析在自发报告数据库中挖掘安全信号

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In pharmacovigilance, linking the adverse reactions by patients to drugs they took is a key activity typically based on the analysis of patient reports. Yet generating potentially interesting pairs (drug, reaction) from a record database is a complex task, especially when many drugs are involved. To limit the generation effort, we exploit the frequently occurring patterns in the database and form association rules on top of them. Moreover, only rules of minimal premise are considered as output by concept analysis tools, which are then filtered through standard measures for statistical significance. We illustrate the process on a small database of anti-mv drugs involved in the HAART therapy while larger-scope validation within the database of the French Medicines Agency is also reported.
机译:在药物警戒中,将患者的不良反应与他们服用的药物联系起来是一项关键活动,通常是基于对患者报告的分析。然而,从记录数据库生成潜在有趣的对(药物,反应)是一项复杂的任务,尤其是在涉及许多药物时。为了限制生成工作,我们利用数据库中频繁发生的模式并在它们之上形成关联规则。此外,概念分析工具仅将最小前提规则视为输出,然后通过标准量度对其进行过滤以提高统计意义。我们在一个与HAART疗法有关的抗mv药物的小型数据库上说明了这一过程,同时还报道了法国药品管理局数据库内的更大范围的验证。

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