Matthew K Ito1, Kevin C Maki2, Eliot A Brinton3, Jerome D Cohen4, Terry A Jacobson5. 1. Oregon State University/Oregon Health & Science University College of Pharmacy, 3303 SW Bond Avenue, Portland, OR 97239, USA. Electronic address: itom@ohsu.edu. 2. Biofortis Clinical Research, Addison, IL 60101, USA. 3. Utah Foundation for Biomedical Research, Salt Lake City, UT 84106, USA. 4. St. Louis University School of Medicine, St. Louis, MO 63105, USA. 5. Emory University School of Medicine, Atlanta, GA 30322, USA.
Abstract
BACKGROUND: Drug interactions have been identified as a risk factor for muscle-related side effects in statin users. OBJECTIVES: The aim was to assess whether use of medications that inhibit cytochrome P450 (CYP450) isozymes, organic anion transporting polypeptide 1B1 (OATP1B1), or P-glycoprotein (P-gp) are associated with muscle-related symptoms among current and former statin users. METHODS: Persons (n = 10,138) from the Understanding Statin Use in America and Gaps in Education (USAGE) internet survey were categorized about whether they ever reported new or worsening muscle pain while taking a statin (n = 2935) or ever stopped a statin because of muscle pain (n = 1516). Univariate and multivariate logistic regression models were used to assess associations between use of concomitant therapies that inhibit CYP450 isozymes, OATP1B1, P-gp, or a combination and muscle-related outcomes. RESULTS: In multivariate analyses, concomitant use of a CYP450 inhibitor was associated with increased odds for new or worse muscle pain (odds ratio [OR] = 1.42; P < .001) or ever having stopped a statin because of muscle pain (OR = 1.28; P = .037). Concomitant use of medication known to inhibit both OATP1B1 and P-gp was also associated with increased odds (OR = 1.80; P = .030) of ever having stopped a statin because of muscle pain. CONCLUSIONS: Concomitant use of medication(s) that inhibit statin metabolism was associated with increased odds of new or worse muscle pain while taking a statin and having previously stopped a statin because of muscle symptoms. These data emphasize the importance of enhancing the capabilities of clinicians and health systems for identifying and reducing statin drug interactions.
BACKGROUND: Drug interactions have been identified as a risk factor for muscle-related side effects in statin users. OBJECTIVES: The aim was to assess whether use of medications that inhibit cytochrome P450 (CYP450) isozymes, organic anion transporting polypeptide 1B1 (OATP1B1), or P-glycoprotein (P-gp) are associated with muscle-related symptoms among current and former statin users. METHODS:Persons (n = 10,138) from the Understanding Statin Use in America and Gaps in Education (USAGE) internet survey were categorized about whether they ever reported new or worsening muscle pain while taking a statin (n = 2935) or ever stopped a statin because of muscle pain (n = 1516). Univariate and multivariate logistic regression models were used to assess associations between use of concomitant therapies that inhibit CYP450 isozymes, OATP1B1, P-gp, or a combination and muscle-related outcomes. RESULTS: In multivariate analyses, concomitant use of a CYP450 inhibitor was associated with increased odds for new or worse muscle pain (odds ratio [OR] = 1.42; P < .001) or ever having stopped a statin because of muscle pain (OR = 1.28; P = .037). Concomitant use of medication known to inhibit both OATP1B1 and P-gp was also associated with increased odds (OR = 1.80; P = .030) of ever having stopped a statin because of muscle pain. CONCLUSIONS: Concomitant use of medication(s) that inhibit statin metabolism was associated with increased odds of new or worse muscle pain while taking a statin and having previously stopped a statin because of muscle symptoms. These data emphasize the importance of enhancing the capabilities of clinicians and health systems for identifying and reducing statin drug interactions.
Authors: Kenjiro Imai; Takehiro Sugiyama; Mitsuru Ohsugi; Masafumi Kakei; Kazuo Hara Journal: Int J Environ Res Public Health Date: 2022-05-17 Impact factor: 4.614
Authors: Veronique Suttels; Eric Florence; John Leys; Marc Vekemans; Jef Van den Ende; Erika Vlieghe; Chris Kenyon Journal: J Med Case Rep Date: 2015-09-08