Dupuch Marie, Lerch Magnus, Jamet Anne, Jaulent Marie-Christine, Fescharek Reinhard, Grabar Natalia
Université Pierre et Marie Curie - Paris 6, Paris F-75006, France.
Stud Health Technol Inform. 2011;169:794-8.
Pharmacovigilance is the activity related to the collection, analysis and prevention of adverse drug reactions (ADRs) induced by drugs or biologics. Besides other methods, statistical algorithms are used to detect previously unknown ADRs, and it was noted that groupings of ADR terms can further improve safety signal detection. Standardised MedDRA Queries are developed to assist retrieval and evaluation of MedDRA-coded ADR reports. Dependent on the context of their application, different SMQs show varying degrees of specificity and sensitivity; some appear to be over-inclusive, some might miss relevant terms. Moreover, several important safety topics are not yet fully covered by SMQs. The objective of this work is to propose an automatic method for the creation of groupings of terms. This method is based on the application of the semantic distance between MedDRA terms. Several experiments are performed, showing a promising precision and an acceptable recall.
药物警戒是与收集、分析和预防药物或生物制品引起的药物不良反应（ADR）相关的活动。除其他方法外，统计算法用于检测先前未知的ADR，并且注意到ADR术语分组可以进一步改善安全信号检测。已开发标准化的MedDRA查询以协助检索和评估用MedDRA编码的ADR报告。根据其应用背景，不同的SMQ显示出不同程度的特异性和敏感性；有些似乎包容性过强，有些可能会遗漏相关术语。此外，一些重要的安全主题尚未被SMQ完全涵盖。这项工作的目的是提出一种自动创建术语分组的方法。该方法基于MedDRA术语之间语义距离的应用。进行了多项实验，显示出有前景的精确率和可接受的召回率。
