Literature DB >> 15680751

Health plan administrative databases can efficiently identify serious myopathy and rhabdomyolysis.

Susan E Andrade1, David J Graham, Judy A Staffa, Stephanie D Schech, Deborah Shatin, Lois La Grenade, Michael J Goodman, Richard Platt, Jerry H Gurwitz, K Arnold Chan.   

Abstract

OBJECTIVE: We evaluated the positive predictive values (PPVs) of specific criteria based upon International Classification of Diseases, 9th revision (ICD-9-CM) codes documented in health plan administrative databases for identification of cases of serious myopathy and rhabdomyolysis. STUDY DESIGN AND
SETTING: We conducted a retrospective study among patients enrolled in 11 geographically dispersed managed care organizations. Cohorts of new users of specific statins and fibrates were identified by selecting patients with an initial dispensing of the drug during the period 1 January 1998 to 30 June 2001. Potential cases of serious myopathy or rhabdomyolysis were identified using specific criteria based upon ICD-9-CM codes suggesting a muscle disorder or acute renal failure.
RESULTS: A total of 194 hospitalizations meeting the criteria for chart review selection were identified among 206,732 new users of statins and 15,485 new users of fibrates. Overall, 31 cases of serious, clinically important myopathy or rhabdomyolysis (18%) were confirmed through chart review. Of these, 26 (84%) had a claim including codes for myoglobinuria (ICD-9-CM 791.3) or other disorders of muscle, ligament, and fascia (ICD-9-CM 728.89). A PPV of 74% (26 of 35 patients meeting criteria) was found for a composite definition that included (1) a primary or secondary discharge code for myoglobinuria, (2) a primary code for "other disorders of muscle," or (3) a secondary code for "other disorders of muscle" accompanied by a claim for a CK test within 7 days of hospitalization or a discharge code for acute renal failure.
CONCLUSION: For rare adverse events such as serious myopathy or rhabdomyolysis, large population-based databases that include diagnosis and laboratory test claims data can facilitate epidemiologic research.

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Year:  2005        PMID: 15680751     DOI: 10.1016/j.jclinepi.2004.10.004

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  16 in total

1.  A pharmacoepidemiological network model for drug safety surveillance: statins and rhabdomyolysis.

Authors:  Ben Y Reis; Karen L Olson; Lu Tian; Rhonda L Bohn; John S Brownstein; Peter J Park; Mark J Cziraky; Marcus D Wilson; Kenneth D Mandl
Journal:  Drug Saf       Date:  2012-05-01       Impact factor: 5.606

2.  Cerivastatin, genetic variants, and the risk of rhabdomyolysis.

Authors:  Kristin D Marciante; Jon P Durda; Susan R Heckbert; Thomas Lumley; Ken Rice; Barbara McKnight; Rheem A Totah; Bani Tamraz; Deanna L Kroetz; Hisayo Fukushima; Rüdiger Kaspera; Joshua C Bis; Nicole L Glazer; Guo Li; Thomas R Austin; Kent D Taylor; Jerome I Rotter; Cashell E Jaquish; Pui-Yan Kwok; Russell P Tracy; Bruce M Psaty
Journal:  Pharmacogenet Genomics       Date:  2011-05       Impact factor: 2.089

3.  Comparative Effectiveness of Statin Therapy in Chronic Kidney Disease and Acute Myocardial Infarction: A Retrospective Cohort Study.

Authors:  David H Smith; Eric S Johnson; Denise M Boudreau; Andrea E Cassidy-Bushrow; Stephen P Fortmann; Robert T Greenlee; Jerry H Gurwitz; David J Magid; Catherine J McNeal; Kristi Reynolds; Steven R Steinhubl; Micah Thorp; Jeffrey O Tom; Suma Vupputuri; Jeffrey J VanWormer; Jessica Weinstein; Xiuhai Yang; Alan S Go; Stephen Sidney
Journal:  Am J Med       Date:  2015-07-11       Impact factor: 4.965

4.  Use of administrative data to estimate the incidence of statin-related rhabdomyolysis.

Authors:  James S Floyd; Susan R Heckbert; Noel S Weiss; David S Carrell; Bruce M Psaty
Journal:  JAMA       Date:  2012-04-18       Impact factor: 56.272

5.  Racial/Ethnic and gender gaps in the use of and adherence to evidence-based preventive therapies among elderly Medicare Part D beneficiaries after acute myocardial infarction.

Authors:  Julie C Lauffenburger; Jennifer G Robinson; Christine Oramasionwu; Gang Fang
Journal:  Circulation       Date:  2013-12-10       Impact factor: 29.690

6.  Unintended effects of statins in men and women in England and Wales: population based cohort study using the QResearch database.

Authors:  Julia Hippisley-Cox; Carol Coupland
Journal:  BMJ       Date:  2010-05-20

7.  Validation of acute myocardial infarction in the Food and Drug Administration's Mini-Sentinel program.

Authors:  Sarah L Cutrona; Sengwee Toh; Aarthi Iyer; Sarah Foy; Gregory W Daniel; Vinit P Nair; Daniel Ng; Melissa G Butler; Denise Boudreau; Susan Forrow; Robert Goldberg; Joel Gore; David McManus; Judith A Racoosin; Jerry H Gurwitz
Journal:  Pharmacoepidemiol Drug Saf       Date:  2012-06-29       Impact factor: 2.890

Review 8.  Gemfibrozil in Combination with Statins-Is It Really Contraindicated?

Authors:  Barbara S Wiggins; Joseph J Saseen; Pamela B Morris
Journal:  Curr Atheroscler Rep       Date:  2016-04       Impact factor: 5.113

9.  Prevalent but moderate variation across small geographic regions in patient nonadherence to evidence-based preventive therapies in older adults after acute myocardial infarction.

Authors:  Gang Fang; Jennifer G Robinson; Julie Lauffenburger; Mary T Roth; Maurice Alan Brookhart
Journal:  Med Care       Date:  2014-03       Impact factor: 2.983

10.  Effect of SLCO1B1 T521C on Statin-Related Myotoxicity With Use of Lovastatin and Atorvastatin.

Authors:  Brian Lu; Laura Sun; Manuel Seraydarian; Thomas J Hoffmann; Marisa W Medina; Neil Risch; Carlos Iribarren; Ronald M Krauss; Akinyemi Oni-Orisan
Journal:  Clin Pharmacol Ther       Date:  2021-07-23       Impact factor: 6.903

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