Leveraging MEDLINE indexing for pharmacovigilance - Inherent limitations and mitigation strategies.
BACKGROUND
Traditional approaches to pharmacovigilance center on the signal detection from spontaneous reports, e.g., the U.S. Food and Drug Administration (FDA) adverse event reporting system (FAERS). In order to enrich the scientific evidence and enhance the detection of emerging adverse drug events that can lead to unintended harmful outcomes, pharmacovigilance activities need to evolve to encompass novel complementary data streams, for example the biomedical literature available through MEDLINE.


OBJECTIVE
(1) To review how the characteristics of MEDLINE indexing influence the identification of adverse drug events (ADEs); (2) to leverage this knowledge to inform the design of a system for extracting ADEs from MEDLINE indexing; and (3) to assess the specific contribution of some characteristics of MEDLINE indexing to the performance of this system.


METHODS
We analyze the characteristics of MEDLINE indexing. We integrate three specific characteristics into the design of a system for extracting ADEs from MEDLINE indexing. We experimentally assess the specific contribution of these characteristics over a baseline system based on co-occurrence between drug descriptors qualified by adverse effects and disease descriptors qualified by chemically induced.


RESULTS
Our system extracted 405,300 ADEs from 366,120 MEDLINE articles. The baseline system accounts for 297,093 ADEs (73%). 85,318 ADEs (21%) can be extracted only after integrating specific pre-coordinated MeSH descriptors and additional qualifiers. 22,889 ADEs (6%) can be extracted only after considering indirect links between the drug of interest and the descriptor that bears the ADE context.


CONCLUSIONS
In this paper, we demonstrate significant improvement over a baseline approach to identifying ADEs from MEDLINE indexing, which mitigates some of the inherent limitations of MEDLINE indexing for pharmacovigilance. ADEs extracted from MEDLINE indexing are complementary to, not a replacement for, other sources.
Lister Hill National Center for Biomedical Communications, U.S. National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894, USA.
Rainer
R
Winnenburg
US Food and Drug Administration, Center for Drug Evaluation and Research, Office of Translational Sciences, 10903 New Hampshire Avenue, Silver Spring, MD 20993, USA.
Alfred
A
Sorbello
Lister Hill National Center for Biomedical Communications, U.S. National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894, USA.
Anna
A
Ripple
Oracle Health Sciences GBU, 100 Crosby Drive, Bedford, MA 01730, USA.
Rave
R
Harpaz
US Food and Drug Administration, Center for Drug Evaluation and Research, Office of Translational Sciences, 10903 New Hampshire Avenue, Silver Spring, MD 20993, USA.
Joseph
J
Tonning
US Food and Drug Administration, Center for Drug Evaluation and Research, Office of Translational Sciences, 10903 New Hampshire Avenue, Silver Spring, MD 20993, USA.
Ana
A
Szarfman
US Food and Drug Administration, Center for Drug Evaluation and Research, Office of Translational Sciences, 10903 New Hampshire Avenue, Silver Spring, MD 20993, USA.
Henry
H
Francis
Lister Hill National Center for Biomedical Communications, U.S. National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894, USA. Electronic address: olivier.bodenreider@nih.gov.
Olivier
O
Bodenreider
D016907:Adverse Drug Reaction Reporting Systems; D057225:Data Mining; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D016247:Information Storage and Retrieval; D016239:MEDLINE; D046650:Medical Subject Headings; D060735:Pharmacovigilance; D014481:United States; D014486:United States Food and Drug Administration
Adverse drug events; MEDLINE indexing; Pharmacovigilance