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Signal detection of rosuvastatin compared to other statins: data-mining study using national health insurance claims database

Cited 29 time in Web of Science Cited 30 time in Scopus
Authors
Choi, Nam-Kyong; Chang, Yoosoo; Choi, Yu Kyong; Hahn, Seokyung; Park, Byung-Joo
Issue Date
2010-03
Publisher
JOHN WILEY & SONS LTD
Citation
PHARMACOEPIDEMIOLOGY AND DRUG SAFETY; Vol.19 3; 238-246
Keywords
pharmacovigilancerosuvastatinrelative riskdata-mininghealth insurance claims database
Abstract
Purpose To detect adverse drug reaction (ADR) signals of rosuvastatin compared to other statins with a novel data-mining approach based on relative risk (RR) using the national health insurance claims database, and to evaluate the usefulness of this method as a tool for signal detection. Methods We used the Health Insurance Review & Assessment Service (HIRA) claims database (Seoul, Korea). Serious adverse events (SAE) were defined as any diagnostic code at the time of hospitalization within 12 weeks from a statin prescription date, regardless of causality. Among statin users, RRs were calculated to compare the proportion of rosuvastatin-specific SAE pairs for rosuvastatin users with the corresponding proportion of drug-SAE pairs for users of other statins. Any SAE for which the lower limit of the RR`s 95% confidence interval was greater than 1 was defined as a signal. All detected signals were reviewed to determine whether the signals corresponded with published adverse events (AEs) exclusive to rosuvastatin. Results Among 96236 elderly outpatients who received rosuvastatin, or other statins, from January 2005 to September 2005, 40304 drug-SAE pairs and 376 SAEs were observed. Twenty-five (6.6%) SAEs were detected as signals by the RR-based data-mining approach. Among the 13 references AEs published to be exclusive to rosuvastatin, 8 (61.5%) were found to correspond with the detected signals with a positive predictive value (PPV) of 32%. Conclusions The RR-based data-mining approach successfully detected signals for rosuvastatin using a national health insurance claims database. This approach could be useful for safety surveillance of marketed products. Copyright (C) 2010 John Wiley & Sons, Ltd.
ISSN
1053-8569
Language
English
URI
https://hdl.handle.net/10371/76913
DOI
https://doi.org/10.1002/pds.1902
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College of Medicine/School of Medicine (의과대학/대학원)Preventive Medicine (예방의학전공)Journal Papers (저널논문_예방의학전공)
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