Signal detection of rosuvastatin compared to other statins: data-mining study using national health insurance claims database.
OBJECTIVE
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 96 236 elderly outpatients who received rosuvastatin, or other statins, from January 2005 to September 2005, 40 304 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.
Choi
Nam-Kyong
NK
Department of Preventive Medicine, Seoul National University College of Medicine, Seoul 110-799, Korea.
Chang
Yoosoo
Y
Choi
Yu Kyong
YK
Hahn
Seokyung
S
Park
Byung-Joo
BJ
D016907:Adverse Drug Reaction Reporting Systems / Q000706:statistics & numerical data*; D000368:Aged; D000369:Aged, 80 and over; D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual / Q000706:statistics & numerical data; D005260:Female; D005464:Fluorobenzenes / Q000009:adverse effects*; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors / Q000009:adverse effects*; D007723:Korea; D008297:Male; D011743:Pyrimidines / Q000009:adverse effects*; D012306:Risk; D000068718:Rosuvastatin Calcium; D013449:Sulfonamides / Q000009:adverse effects*
D005464:Fluorobenzenes; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors; D011743:Pyrimidines; D013449:Sulfonamides; D000068718:Rosuvastatin Calcium