Assessment and management of statin-associated muscle symptoms (SAMS): A clinical perspective from the National Lipid Association
Open accessAbstract
Statin-associated muscle symptoms (SAMS) are the most common form of statin intolerance and are associated with increased risk of cardiovascular events that manifest from statin underutilization and discontinuation. The reported frequencies of SAMS are divergent in the literature. The writing group estimates the prevalence of SAMS, namely all muscle symptoms temporally related to statin use but without regard to causality, to be about 10% (range 5% to 25%), and the prevalence of pharmacological SAMS, specifically muscle symptoms resulting from pharmacological properties of the statin, to be about 1-2% (range 0.5% to 4%). In clinical practice, SAMS are likely to result from a combination of pharmacological and nonpharmacological effects, however this does not make the symptoms any less clinically relevant. Regardless of the etiology, SAMS need to be addressed in accordance with patients' preferences and experiences. This clinical perspective reviews the epidemiology and underlying pathophysiology of SAMS, and the cardiovascular consequences resulting from statin discontinuation. We present patient-centered clinical and communication strategies to mitigate SAMS and improve medication adherence and outcomes among statin users. Treatment strategies include 1) optimizing lifestyle interventions, 2) modulating risk factors that may contribute to muscle symptoms, 3) optimizing statin tolerability by dose reduction, decreased dosing frequency, or use of an alternate statin with more favorable pharmacokinetic properties, and 4) use of non-statins, emphasizing those with evidence for atherosclerotic risk reduction, either in combination with or in place of statin therapy depending on the patient's circumstances. The focus of this clinical perspective is sustainable lipoprotein goal achievement, which is important for cardiovascular risk reduction.
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Recent narrative reviews on the management of SAMS found that further research is needed to close the knowledge gap.
“Recent narrative reviews on the management of SAMS found that further research is needed to close the knowledge gap [19].”
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- Authors
- Warden, B. A., Guyton, J. R., Kovacs, A. C., Durham, J. A., Jones, L. K., Dixon, D. L., Jacobson, T. A., & Duell, P. B.
- Affiliations
- Oregon Health & Science University (US)
- Duke Medical Center (US)
- Virginia Commonwealth University (US)
- Emory University (US)
- Corresponding author
- Warden, Bruce A.
- Guyton, John R.
- Kovacs, Adrienne C.
- Durham, Jessica A.
- Jones, Laney K.
- Dixon, Dave L.
- Jacobson, Terry A.
- Duell, P. Barton
- Venue
- Journal of Clinical Lipidology
- Publisher
- Elsevier BV
- Published
- 2023-01
- Volume
- 17
- Issue
- 1
- Pages
- 19-39
- ISSN
- 1876-4789 (ISSN-L)
- 1933-2874
- OpenAlex
- W4295221059
- Cited by
- 111
- References
- 82
- Citations by year
- 2026: 24 · 2025: 40 · 2024: 24 · 2023: 21 · 2022: 2
- FWCI
- 20.88
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of clinical lipidology (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Surgery › Lipoproteins and Cardiovascular Health
- Health Sciences › Medicine › Family Practice › Medication Adherence and Compliance
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Lipids, and Metabolism
- Keywords
- statin-associated muscle symptoms, statin intolerance, statin discontinuation, cardiovascular risk, medication adherence, lifestyle intervention, statin dose reduction, non-statin therapy, cardiovascular risk reduction
- MeSH terms
- Humans, Lipids, Muscles, Muscular Diseases, Risk Factors, Hydroxymethylglutaryl-CoA Reductase Inhibitors
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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