Documentation in pharmacovigilance: using an ontology to extend and normalize Pubmed queries

Autor: Delamarre, Denis, Lillo-Le Louët, Agnès, Guillot, Laetitia, Jamet, Anne, Sadou, Eric, Ouazine, Theo, Burgun, Anita, Jaulent, Marie-Christine
Přispěvatelé: Modélisation Conceptuelle des Connaissances Biomédicales, Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Centre Régional de Pharmacovigilance ( CRPV ), Assistance publique - Hôpitaux de Paris (AP-HP)-Hôpital Européen Georges Pompidou [APHP] ( HEGP ), Laboratoire de Santé Publique et Informatique Médicale ( SPIM ), Institut National de la Santé et de la Recherche Médicale ( INSERM ), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Centre Régional de Pharmacovigilance (CRPV), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Laboratoire de Santé Publique et Informatique Médicale (SPIM), Institut National de la Santé et de la Recherche Médicale (INSERM), Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)
Jazyk: angličtina
Rok vydání: 2010
Předmět:
MESH: Terminology as Topic
PubMed
Drug-Related Side Effects and Adverse Reactions
Adverse drug reaction reporting
Adverse drug reaction
MESH: Documentation
Documentation
MESH: Drug Toxicity
MESH: Natural Language Processing
MESH : Database Management Systems
Terminology as Topic
MESH : Vocabulary
Controlled
Data Mining
Humans
Information retrieval
[ SDV.IB ] Life Sciences [q-bio]/Bioengineering
Natural Language Processing
MESH: Humans
Ontology
MESH : Data Mining
MESH: Data Mining
MESH : Humans
MESH : Drug Toxicity
MESH: PubMed
MESH: Vocabulary
Controlled
MESH : Natural Language Processing
MESH : PubMed
MESH : Terminology as Topic
Vocabulary
Controlled
Database Management Systems
[SDV.IB]Life Sciences [q-bio]/Bioengineering
MESH : Documentation
Databases bibliographic
MESH: Database Management Systems
Zdroj: Studies in Health Technology and Informatics
Studies in Health Technology and Informatics, IOS Press, 2010, 160 (Pt 1), pp.518-22. 〈10.3233/978-1-60750-588-4-518〉
Studies in Health Technology and Informatics, 2010, 160 (Pt 1), pp.518-22. ⟨10.3233/978-1-60750-588-4-518⟩
Studies in Health Technology and Informatics, IOS Press, 2010, 160 (Pt 1), pp.518-22. ⟨10.3233/978-1-60750-588-4-518⟩
ISSN: 0926-9630
1879-8365
DOI: 10.3233/978-1-60750-588-4-518〉
Popis: International audience; OBJECTIVES: To assess and understand adverse drug reactions (ADRs), a systematic review of reference databases like Pubmed is a necessary and mandatory step in Pharmacovigilance. In order to assist pharmacovigilance team with a computerized tool, we performed a comparative study of 4 different approaches to query Pubmed through ADR-drug terms. The aim of this study is to assess how an ontology of adverse effects, used to normalize and extend queries, could improve this search. MATERIAL AND METHOD: The ontological resource OntoEIM contains 58,000 classes and integrates MedDRA terminology. The entry point is a ADR-Drug term and the four methods are (i) a direct search on Pubmed (ii) a search with a normalized query enhanced with domain-specific Mesh Heading criteria, (iii) a search with the same elaborated query extended to the MeSH sub-hierarchy of the adverse effect entry and (iv) a search with a set of MedDRA terms grouped by subsomption in the OntoEIM ontology. For each of the 16 queries performed and analysed, relevant publications are selected "manually" by two pharmacovigilant experts. RESULTS: The recall is respectively of 63%, 50%, 67% and 74%, the precision of 13%, 26%, 29% and 4%. The best recall is provided by the ontology-based method, for 4 cases out of 16 this method returns relevant publications when the others return no results. CONCLUSION: Results show that an ontology-based search tool improves the recall performance, but other tools and methods are needed to raise the precision.
Databáze: OpenAIRE
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