title: Evaluation of automated term groupings for detecting anaphylactic shock signals for drugs.
abstract: Signal detection in pharmacovigilance should take into account all terms related to a medical concept rather than a single term. We built an OWL-DL file with formal definitions of MedDRA and SNOMED-CT concepts and performed two queries, Query 1 and 2, to retrieve narrow and broad terms within the Standard MedDRA Query (SMQ) related to 'anaphylactic shock' and the terms from the High Level Term (HLT) grouping related to 'anaphylaxis'. We compared values of the EB05 (EBGM) statistical test for disproportionality with 50 active ingredients randomly selected in the public version of the FDA pharmacovigilance database. Coefficient of correlation was R(2) = 1.00 between Query 1 and HLT; R(2) = 0.98 between Query 1 and SMQ narrow; R(2) = 0.89 between Query 2 and SMQ Narrow+Broad. Generating automated groupings of terms for signal detection is feasible but requires additional efforts in modeling MedDRA terms in order to improve precision and recall of these groupings.
authors.affiliation: INSERM U872, Eq. 20, Paris, France.
authors.forename: Julien
authors.initials: J
authors.lastname: Souvignet
authors.forename: Gunnar
authors.initials: G
authors.lastname: Declerck
authors.forename: Béatrice
authors.initials: B
authors.lastname: Trombert
authors.forename: Jean Marie
authors.initials: JM
authors.lastname: Rodrigues
authors.forename: Marie-Christine
authors.initials: MC
authors.lastname: Jaulent
authors.forename: Cédric
authors.initials: C
authors.lastname: Bousquet
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems; D000707:Anaphylaxis / Q000175:diagnosis*; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D060735:Pharmacovigilance; D018875:Vocabulary, Controlled