Paper Info
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.
Year
Venue
Keywords
2012
AMIA
pharmacovigilance
Field
DocType
Volume
High Level Term,MedDRA,Information retrieval,Detection theory,Precision and recall,Pharmacovigilance,Medicine,Statistical hypothesis testing
Conference
2012
ISSN
Citations 
PageRank 
1942-597X
0
0.34
References 
Authors
3
6
Name
Order
Citations
PageRank
Julien Souvignet173.77
Gunnar Declerck2115.00
Béatrice Trombert3113.74
Jean Marie Rodrigues47422.79
Marie-Christine Jaulent537568.72
Cédric Bousquet610922.59