Design and validation of an automated method to detect known adverse drug reactions in MEDLINE: a contribution from the EU-ADR project
Design and validation of an automated method to detect known adverse drug reactions in MEDLINE: a contribution from the EU-ADR project
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DOI：
10.1136/amiajnl-2012-001083
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发表时间：
2013-05-01
影响因子：
6.4
通讯作者：
Fieschi, Marius
中科院分区：
文献类型：
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作者：
Avillach, Paul;Dufour, Jean-Charles;Fieschi, Marius
目的本研究的目的是通过定义用于检索MEDLINE的查询和确定所需阈值的数量提取的出版物，以确认药物/事件associationinliterates.Methods我们定义了一种基于医学主题词（MeSH）的“描述符记录”和“补充概念记录”词库的方法，使用副标题“化学诱导”和“不良反应”与“药理作用"知识。一个专家建立的验证集的真阳性和真阴性药物/不良事件协会（n=61）被用来验证我们的methods.Results使用阈值的三个更提取的出版物，自动搜索方法提出了一个敏感性为90%，特异性为100%。对9种不同的药物/不良事件对，自动检索的召回率为24%~ 64%，准确率为93%~ 48%。结论本研究提供了一种在文献中寻找药物与不良事件关系的方法。使用MEDLINE，遵循MeSH方法过滤信号，是一个有效的选择。我们的贡献是作为一个网络服务，将被集成在最终的欧洲EU-ADR项目（探索和了解药物不良反应的临床记录和生物医学知识的综合挖掘）自动化系统。
Objectives The aim of this research was to automate the search of publications concerning adverse drug reactions (ADR) by defining the queries used to search MEDLINE and by determining the required threshold for the number of extracted publications to confirm the drug/event association in the literature.Methods We defined an approach based on the medical subject headings (MeSH) 'descriptor records' and 'supplementary concept records' thesaurus, using the subheadings 'chemically induced' and 'adverse effects' with the 'pharmacological action' knowledge. An expert-built validation set of true positive and true negative drug/adverse event associations (n=61) was used to validate our method.Results Using a threshold of three of more extracted publications, the automated search method presented a sensitivity of 90% and a specificity of 100%. For nine different drug/event pairs selected, the recall of the automated search ranged from 24% to 64% and the precision from 93% to 48%.Conclusions This work presents a method to find previously established relationships between drugs and adverse events in the literature. Using MEDLINE, following a MeSH approach to filter the signals, is a valid option. Our contribution is available as a web service that will be integrated in the final European EU-ADR project (Exploring and Understanding Adverse Drug Reactions by integrative mining of clinical records and biomedical knowledge) automated system.