Design and validation of an automated method to detect known adverse drug reactions in MEDLINE: a contribution from the EU-ADR project

Paul Avillach, JC Dufour, G Diallo, Francesco Salvo, M Joubert, F Thiessard, F Mougin, Gianluca Trifiro, A Fourrier-Reglat, A Pariente, M Fieschi

Research output: Contribution to journalArticleAcademicpeer-review

54 Citations (Scopus)

Abstract

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.
Original languageUndefined/Unknown
Pages (from-to)446-452
Number of pages7
JournalJournal of the American Medical Informatics Association
Volume20
Issue number3
DOIs
Publication statusPublished - 2013

Research programs

  • EMC NIHES-03-77-02

Cite this