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Use of health insurance claim patterns to identify patients using nonsteroidal anti‐inflammatory drugs for rheumatoid arthritis
Author(s) -
Bernard MarieAgnès,
Bénichou Jacques,
Blin Patrick,
Weill Alain,
Bégaud Bernard,
Abouelfath Abdelilah,
Moore Nicholas,
FourrierRéglat Annie
Publication year - 2012
Publication title -
pharmacoepidemiology and drug safety
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.023
H-Index - 96
eISSN - 1099-1557
pISSN - 1053-8569
DOI - 10.1002/pds.3221
Subject(s) - medicine , nonsteroidal , rheumatoid arthritis , logistic regression , pharmacoepidemiology , cohort , receiver operating characteristic , sample size determination , pharmacology , statistics , mathematics , medical prescription
Purpose To determine healthcare claim patterns associated using nonsteroidal anti‐inflammatory drugs (NSAIDs) for rheumatoid arthritis (RA). Methods The CADEUS study randomly identified NSAID users within the French health insurance database. One‐year claims data were extracted, and NSAID indication was obtained from prescribers. Logistic regression was used in a development sample to identify claim patterns predictive of RA and models applied to a validation sample. Analyses were stratified on the dispensation of immunosuppressive agents or specific antirheumatism treatment, and the area under the receiver operating characteristic curve was used to estimate discriminant power. Results NSAID indication was provided for 26 259 of the 45 217 patients included in the CADEUS cohort; it was RA for 956 patients. Two models were constructed using the development sample ( n = 13 143), stratifying on the dispensation of an immunosuppressive agent or specific antirheumatism treatment. Discriminant power was high for both models (AUC > 0.80) and was not statistically different from that found when applied to the validation sample ( n = 13 116). Conclusions The models derived from this study may help to identify patients prescribed NSAIDs who are likely to have RA in claims databases without medical data such as treatment indication. Copyright © 2012 John Wiley & Sons, Ltd.