PMID- 20049851
OWN - NLM
STAT- MEDLINE
DCOM- 20100518
LR  - 20151119
IS  - 1099-1557 (Electronic)
IS  - 1053-8569 (Linking)
VI  - 19
IP  - 3
DP  - 2010 Mar
TI  - Signal detection of rosuvastatin compared to other statins: data-mining study 
      using national health insurance claims database.
PG  - 238-46
LID - 10.1002/pds.1902 [doi]
AB  - 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 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.
FAU - Choi, Nam-Kyong
AU  - Choi NK
AD  - Department of Preventive Medicine, Seoul National University College of Medicine, 
      Seoul 110-799, Korea.
FAU - Chang, Yoosoo
AU  - Chang Y
FAU - Choi, Yu Kyong
AU  - Choi YK
FAU - Hahn, Seokyung
AU  - Hahn S
FAU - Park, Byung-Joo
AU  - Park BJ
LA  - eng
PT  - Comparative Study
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PL  - England
TA  - Pharmacoepidemiol Drug Saf
JT  - Pharmacoepidemiology and drug safety
JID - 9208369
RN  - 0 (Fluorobenzenes)
RN  - 0 (Hydroxymethylglutaryl-CoA Reductase Inhibitors)
RN  - 0 (Pyrimidines)
RN  - 0 (Sulfonamides)
RN  - 83MVU38M7Q (Rosuvastatin Calcium)
SB  - IM
MH  - Adverse Drug Reaction Reporting Systems/*statistics & numerical data
MH  - Aged
MH  - Aged, 80 and over
MH  - Data Mining/*methods
MH  - Databases, Factual/statistics & numerical data
MH  - Female
MH  - Fluorobenzenes/*adverse effects
MH  - Hospitalization/statistics & numerical data
MH  - Humans
MH  - Hydroxymethylglutaryl-CoA Reductase Inhibitors/*adverse effects
MH  - Korea
MH  - Male
MH  - Pyrimidines/*adverse effects
MH  - Risk
MH  - Rosuvastatin Calcium
MH  - Sulfonamides/*adverse effects
EDAT- 2010/01/06 06:00
MHDA- 2010/05/19 06:00
CRDT- 2010/01/06 06:00
PHST- 2010/01/06 06:00 [entrez]
PHST- 2010/01/06 06:00 [pubmed]
PHST- 2010/05/19 06:00 [medline]
AID - 10.1002/pds.1902 [doi]
PST - ppublish
SO  - Pharmacoepidemiol Drug Saf. 2010 Mar;19(3):238-46. doi: 10.1002/pds.1902.