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Understanding the causes and consequences of low statin adherence: evidence from UK Biobank primary care data
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Abstract
Background: Statins are prescribed to lower LDL cholesterol. Clinical guidelines recommend 30–50% reduction within 3 months, yet many patients do not achieve this. We investigated predictors of LDL-c reduction, treatment adherence, and adverse clinical outcomes in a sample of UK Biobank participants. Methods: We analysed 76,000 UK Biobank participants prescribed atorvastatin or simvastatin in primary care: 41,000 had LDL-c measurements before statin initiation (median = 16 days prior, IQR = 28) and within a year of starting treatment (median = 89 days, IQR = 125). Adherence was defined as the “proportion of days covered” (PDC). We estimated associations between PDC within 1 year of statin initiation, genetic factors, post-treatment LDL-c reduction, and clinical adverse outcomes. For 13,000 patients with ≥ 3 LDL-c measures, we used inverse probability of treatment weighting methods to estimate the effect of sustained adherence intervention on LDL-c reduction longitudinally. Results: LDL-c reduction following statin initiation was predicted by time until the 1st measurement (up to 26% greater reduction if returned ≤ 3 months vs > 3 months), PDC (up to 38% reduction when PDC > 95% [high] vs. 15% when PDC < 50% [low]), and the pharmacogenetic variant SLCO1B1 *5 (lowest reduction in CC-allele: 37% versus TT-allele: 39.5%). Longitudinal causal modelling showed that the most recent PDC measure exerted the largest influence on overall LDL-c reduction, followed by the initial PDC. Genetic predictors of reduced PDC included liability to schizophrenia (Coef top 20% − 1.94, 95%CI − 2.69 to − 1.19), while genetic liability to cardiovascular diseases increased PDC (Coef top 20% 1.30, 95%CI 0.55 to 2.05). High PDC was associated with increased risk of incident iron deficiency anaemia (HR 1.30, 95%CI 1.09–1.54) and cataract (HR 1.20, 95%CI 1.07–1.34), and decreased risk of incident coronary heart disease (HR 0.78, 95%CI 0.73–0.84). Conclusions: We identify substantial variability in the time to first on-treatment LDL-c measurements and also in adherence to statin medication, highlighting a gap between NHS guidelines, LDL-c monitoring, and statin adherence. We show its subsequent impact on long-term health, demonstrating the potential effect of targeted interventions to improve adherence. We identify important predictors of reduced statin effectiveness, including pharmacogenetic variants, polygenic scores, but most of all, adherence. Tailored statin therapy strategies with patient education on statin indication and adherence could optimize treatment efficacy, safety, and long-term clinical outcomes.
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Many patients do not achieve guideline-recommended LDL-C targets due to inadequate response, intolerance, or high residual risk.
“many patients do not achieve guideline-recommended LDL-C targets due to inadequate response, intolerance, or high residual risk.2”
From Small Interfering RNA for LDL-Cholesterol Reduction (2026) · cites this paper as [2]
The Background (page not provided) says many people with detected hypercholesterolaemia do not achieve guideline LDL-C targets. The Results (page not provided) report that only 31% of the secondary-prevention group reached the stated target. The paper discusses adherence and reduced statin effectiveness, but does not establish inadequate response, intolerance, or high residual risk as the three reasons for missing those targets. (LLM, conf=0.87)
Experimental — accuracy not yet measuredStatins remain first-line therapy for lowering LDL-C.
“While statins remain first-line therapy”
From Small Interfering RNA for LDL-Cholesterol Reduction (2026) · cites this paper as [2]
The Background (page unavailable) says statins lower LDL-C and discusses guideline targets and follow-up after statin initiation. It does not establish that statins are first-line therapy rather than another treatment option. (LLM, conf=0.78)
Experimental — accuracy not yet measured
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Computationally efficient whole-genome regression for quantitative and binary traits
Mbatchou, J., Barnard, L., Backman, J., Marcketta, A., Kosmicki, J. A., Ziyatdinov, A., Benner, C., O’Dushlaine, C., Barber, M., Boutkov, B., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00870-7 · Cited by 1,502
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Bosworth, H. B., Granger, B. B., Mendys, P., Brindis, R., Burkholder, R., Czajkowski, S. M., Daniel, J. G., Ekman, I., Ho, M., Johnson, M., et al. (2011) · American Heart Journal · doi:10.1016/j.ahj.2011.06.007 · Cited by 448
An overview of the common methods used to measure treatment adherence
Anghel, L. A., Farcas, A. M., & Oprean, R. N. (2019) · Medicine and Pharmacy Reports · doi:10.15386/mpr-1201 · Cited by 335
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“We also included polygenic scores (PGS) derived by Genomics PLC [25] (UKB category 301): 8 PGS for relevant biomarkers and patient characteristics (e.g. LDL-c, BMI) and 28 PGS for genetic liability to disease (e.g. CVD, schizophrenia).”
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Small Interfering RNA for LDL-Cholesterol Reduction
Batista, F., Mamede, I., & Dacoregio, M. (2026) · JACC: Advances · doi:10.1016/j.jacadv.2026.102932
Metadata
- Authors
- Türkmen, D., Liang, X., Masoli, J. A. H., Gill, D., Pilling, L. C., & Bowden, J.
- Affiliations
- University of Exeter (GB)
- Imperial College London (GB)
- Corresponding author
- Bowden, Jack
- Venue
- BMC Medicine
- Published
- 2025-07-22
- Volume
- 23
- Issue
- 1
- Pages
- 436-436
- ISSN
- 1741-7015 (ISSN-L)
- PMC
- PMC12285031
- OpenAlex
- W4412572587
- Cited by
- 6
- References
- 6
- Citations by year
- 2026: 6
- FWCI
- 8.10
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- BMC Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Royal Devon and Exeter Research Repository (Royal Devon and Exeter) (submittedVersion)
- Funders
- UK Medical Research Council research grant (MR/X011372/1)
- National Institute for Health Research Fellowship (NIHR301445)
- Topics
- Health Sciences › Medicine › Family Practice › Medication Adherence and Compliance
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Blood Pressure and Hypertension Studies
- Keywords
- statin adherence, LDL cholesterol lowering, atorvastatin, simvastatin, proportion of days covered, pharmacogenetics, iron deficiency anemia, cataract, coronary artery disease, statin adverse effects, primary care prescribing, UK Biobank, causal models, inverse probability of treatment weighting
- MeSH terms
- Atorvastatin, UK Biobank, Aged, Female, United Kingdom, Humans, Cholesterol, LDL, Male, Middle Aged, Primary Health Care, Biological Specimen Banks, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Simvastatin, Medication Adherence
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