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Design and validation of an automated method to detect known adverse drug reactions in MEDLINE: a contribution from

Paul Avillach1, Jean-Charles Dufour, Gayo Diallo

  • 1LESIM, ISPED, University of Bordeaux, Bordeaux, France. avillach@mac.com

Journal of the American Medical Informatics Association : JAMIA
|December 1, 2012
PubMed
Abstract

Insights

This study developed an automated method to identify adverse drug reactions (ADR) in medical literature. The approach achieved high accuracy, demonstrating a valid way to find drug/event associations using MEDLINE and MeSH terms.

Area of Science:

  • Biomedical Informatics
  • Pharmacovigilance
  • Medical Literature Analysis

Background:

  • Adverse drug reactions (ADR) pose a significant public health challenge.
  • Efficiently identifying and confirming drug-event associations in scientific literature is crucial for patient safety.

Purpose of the Study:

  • To automate the search for publications related to adverse drug reactions (ADR).
  • To define optimal search queries and publication thresholds for confirming drug/event associations in MEDLINE.
  • To develop a reliable method for mining established drug-adverse event relationships.

Main Methods:

  • Utilized Medical Subject Headings (MeSH) descriptor and supplementary concept records.
  • Incorporated 'chemically induced' and 'adverse effects' subheadings with 'pharmacological action' knowledge.
  • Validated the approach using an expert-curated dataset of 61 drug/adverse event associations.

Main Results:

  • Achieved 90% sensitivity and 100% specificity with a threshold of three or more publications.
  • Demonstrated recall ranging from 24% to 64% and precision from 93% to 48% for selected drug/event pairs.
  • The automated search effectively filters signals using a MeSH approach.

Conclusions:

  • Presents a validated method for identifying established drug-adverse event relationships in literature.
  • Confirms MEDLINE searching with a MeSH approach as a viable strategy for ADR detection.
  • The developed method is available as a web service for integration into automated systems like the EU-ADR project.

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