Evidence map›Paper›PMID 26342964›Full record

ArticleJournal of biomedical informatics2015

Leveraging MEDLINE indexing for pharmacovigilance - Inherent limitations and mitigation strategies.

Rainer Winnenburg, Alfred Sorbello, Anna Ripple, Rave Harpaz, Joseph Tonning, Ana Szarfman, Henry Francis, Olivier Bodenreider

Abstract read
In one paragraph

Article in Journal of biomedical informatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Impact of literature reports on drug safety signals.Wiener klinische Wochenschrift · 2021
    Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Finding medication doses in the liteature.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018
    Article
  8. Toward multimodal signal detection of adverse drug reactions.Journal of biomedical informatics · 2017
    Article
  9. Article
  10. Article
  11. Article
  12. Automated Summarization of Publications Associated with Adverse Drug Reactions from PubMed.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2016
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Rainer WinnenburgLister Hill National Center for Biomedical Communications, U.S. National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894, USA.
Alfred SorbelloUS Food and Drug Administration, Center for Drug Evaluation and Research, Office of Translational Sciences, 10903 New Hampshire Avenue, Silver Spring, MD 20993, USA.
Anna RippleLister Hill National Center for Biomedical Communications, U.S. National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894, USA.
Rave HarpazOracle Health Sciences GBU, 100 Crosby Drive, Bedford, MA 01730, USA.
Joseph TonningUS Food and Drug Administration, Center for Drug Evaluation and Research, Office of Translational Sciences, 10903 New Hampshire Avenue, Silver Spring, MD 20993, USA.
Ana SzarfmanUS Food and Drug Administration, Center for Drug Evaluation and Research, Office of Translational Sciences, 10903 New Hampshire Avenue, Silver Spring, MD 20993, USA.
Henry FrancisUS Food and Drug Administration, Center for Drug Evaluation and Research, Office of Translational Sciences, 10903 New Hampshire Avenue, Silver Spring, MD 20993, USA.
Olivier BodenreiderLister 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.

Funding

National Biomedical Information ServicesZIHLM200888 · NLM · NATIONAL LIBRARY OF MEDICINE · PI PALTOO, DINA · 2009 to 2025
$5200.7M
STANFORD COMPOSITE(RMI)U54HG004028 · NHGRI · STANFORD UNIVERSITY · PI MUSEN, MARK A · 2005 to 2014
$36.2M
Interpretable deep learning models for translational medicine RenewalR01LM012011 · NLM · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Tanner J. Freeman, XINGHUA LU · 2015 to 2026
$3.6M
Drug terminology at NLM - Integration, dissemination, quality assurance and applicationsZIALM010007 · NLM · NATIONAL LIBRARY OF MEDICINE · PI BODENREIDER, OLIVIER · 2016 to 2020
$3.1M
Mining health data for drug safety profilesR01GM101430 · NIGMS · STANFORD UNIVERSITY · PI SHAH, NIGAM H · 2013 to 2017
$2.9M
Intramural NIH HHS Z99 LM999999NHGRI NIH HHS U54 HG004028NIGMS NIH HHS R01 GM101430NLM NIH HHS R01 LM012011
6 · The paper itself

Abstract

backgroundTraditional 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.

objectives(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.

methodsWe 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.

resultsOur 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.

conclusionsIn 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.

Indexed as

Drug-Related Side Effects and Adverse ReactionsMedical Subject HeadingsMEDLINEPharmacovigilanceAdverse Drug Reaction Reporting SystemsData MiningHumansInformation Storage and RetrievalUnited StatesUnited States Food and Drug AdministrationAdverse drug eventsMEDLINE indexingPharmacovigilance

Identifiers

PMID26342964
PMCPMC4775467

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.