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Update - Issue 13, 2017
Curated by Peter Lansberg,
a Dutch lipidologist and educator, and
reviewed by prof. Philip Barter, Past President of the
International Atherosclerosis Society.

The IAS Statin Newsletter will keep you up-to-date with all recent statin publications, using a curated approach to select relevant articles.

Key publications

Issue 13

Under treatment of very high risk patients in CEPHEUS Egypt study
The CEPHEUS program is a global initiative to evaluate if patients receive adequate statin dosage, based on level of risk and European Society of Cardiology 2011 treatment targets. In this Egyptian CEPHEUS analysis, an open-label, observational, multicenter, cross-sectional survey, 90 investigators enrolled 1127 patients receiving lipid-lowering drugs for at least 3 months (April 2014 - August 2015). Analysis was possible in 896 patients. No less than 65.2% of the patients were classified as high risk, goal achievement of was observed in 22.3% of these patients. Secondary prevention patients constituted 34.4% of the total population and 90.1% used lipid lowering agents as mono therapy, 9.9% a combination treatment. Goals were achieved in 34% and 38% of the respective groups. Statins were used by 86.9% of the patients, (rosuvastatin 47.1%; atorvastatin 36.0%, simvastatin 31.7%). Treatment goals were reached in 34.2%, 36% and 31.7% and average dosages used were: 14.6 mg; 24.8 mg and 25.7 mg. respectively. Ezetimibe was prescribed in 63 patients with an average dose of 15 mg! Only a minimal difference in statin dosage, when comparing the low risk to very high risks patients, was noted. Sub-optimal dosing of the high intensity statins of 13.8 mg, 25.8 mg 21.0 mg in the low risk patients and 14.6 mg, 25.1 mg and 31 mg of Rosuvastatin, Atorvastatin and simvastatin respectively. Majority of patients used Rosuvastatin and Atorvastatin; only 52/584 (8.9%) used simvastatin in the high-risk group and 12/111(10.8%) in the low risk group. The results of the CEPHEUS Egypt study re-affirms that physicians are embracing statins for CVD risk reduction but fail to prescribe the guideline dictated dosage (ACC/AHA 2013 guidelines) or are achieving guideline dictated LDL-C targets (ESC/EAS 2011 guidelines).
Reda A, Etman A, Abdel-Rahim A et al. Centralized Pan-Middle East Survey on the Under-Treatment of Hypercholesterolemia: Results from the CEPHEUS II Study in Egypt. Cardiology and therapy 2017. http://www.ncbi.nlm.nih.gov/pubmed/?term=28357773
Comparing US and European risk scores for primary prevention
For the comparison of the US Pooled Cohort Equation (PCE) and the European SCORE risk calculator, 44 889 participants of the Copenhagen General Population Study were used to observe real-world outcomes based on their risk profile. They were recruited between 2003-2009 and through 2014 overall 2 217 ASCVD events and 199 fatal events were recorded. When Class I recommendations were evaluated, 42% qualified for statins based on PCE and only 6% with SCORE. Using PCE increased sensitivity 62% for any ASCVD event and 76% for fatal events. Specificity was reduced to lesser degree by -35% and -36% respectively. Similar results were observed for men and women separately and for Class IIa recommendations. A PCE risk of 5% was equivalent to a SCORE risk of 1.4% and a  PCE risk of 7.5% equated to a SCORE risk of 2.4%.
The PCE was reliable with 1-year risk <10% and good calibration at the threshold levels of 5% and 7.5%. The SCORE overestimated fatal ASCVD events across all deciles but with a hefty overestimation at the critical threshold levels of 5% (high risk) and 10% (very high risk). Of serious concern is that using the SCORE in people aged 40–75, only <15% of those who later developed a first any or fatal ASCVD event qualified at baseline for a Class I recommendation for primary prevention with statin. The authors concluded that the PCE outperformed the SCORE In primary prevention of ASCVD fatal and non-fatal events, patients using the PCE were more likely to be prescribed statins.
Mortensen MB, Nordestgaard BG, Afzal S, Falk E. ACC/AHA guidelines superior to ESC/EAS guidelines for primary prevention with statins in non-diabetic Europeans: the Copenhagen General Population Study. Eur Heart J 2017; 38:586-594. http://www.ncbi.nlm.nih.gov/pubmed/?term=28363217
Who will (and who will not) stop statins, that is the question!
Adherence is one of, if not the biggest, challenges we face when aiming to reduce cardiovascular risk by statins. How to recognize non-adherent patient was the evaluated in this elaborate study in. Using data collected in a large US insurer medical and pharmacy administrative claims database of 99 377 individuals. Adherence to statins was observed in 58.4% of the participants. Three models of adherence were evaluated: Pre-index adherence parameters, Investigator-specified and empirically selected pharmacy, medical, and demographic variables and post index parameters. Combining the 1st and 2nd model using 3 pre-index and 3 post-index adherence predictors provided the most reliable predictions with a C-statistic of 0.78. The 2nd model was least reliable and achieved a C statistic of 0.57-0.60). Adherence filling behavior before and immediately after and index prescription fill provided the best predictive power to forecast non-adherence and outperformed the more complex demographic parameters. This dataset can be extracted in a fairly simple manner from and administrative claims database and would make this an easy to use instrument to anticipate non-adherence.
Krumme AA, Franklin JM, Isaman DL et al. Predicting 1-Year Statin Adherence Among Prevalent Users: A Retrospective Cohort Study. Journal of managed care & specialty pharmacy 2017; 23:494-502. http://www.ncbi.nlm.nih.gov/pubmed/?term=28345442
Drug-drug interaction observed in a large Estonian population using statins
Statins have an excellent safety profile; however caution is needed when statins are combined with certain type of drugs. In this retrospective analysis of a prescription database of the Estonian Health Insurance Fund, 203 646 patients aged >50 yrs. were evaluated. Statins use was noted in 29 367 participants. Only persons who had used at least one prescription medicine for a minimum of 7 days concomitantly with statins were analyzed. Simvastatin and Atorvastatin are metabolized by Cytochrome P450 3A4 iso-enzymes. Most Estonian statin users (64%) were prescribed one of these statins. Concomitant medications know to have interactions were used by 4.6% of the patients. The drugs most often concomitantly prescribed with simvastatin were warfarin (5.7%) and amiodarone (3.9%). Digoxin (1.2%) and ethinylestradiol (2%) were prescribed with atorvastatin. Simvastatin is associated with the highest risk of developing rhabdomyolysis when combined with fibrates, cyclosporine, digoxin, macrolide antibiotics, warfarin or azoles. In this study 10% of simvastatin users (4.3% of all statin users) were at risk of developing this complication. If simvastatin is combined with warfarin there is an increased risk of hemorrhage; 729 patients (7.8% of all statin users) were at risk for this complication as well. Switching from the less interactive prone atorvastatin and rosuvastatin to simvastatin occurred in 600 patients (2%). The authors noted that costs was most likely the driving force for this switch. They conclude that statin prescriptions should favor statin with a less likely chance to develop drug-drug interactions. For rosuvastatin, pravastatin and fluvastatin no potential interactions were detected. Fluvastatin is metabolized via CYP2C9, and potential interactions are rare. CYP450 enzymes do not contribute to the metabolism of pravastatin and rosuvastatin.
Gavronski M, Volmer D, Hartikainen S, Zharkovsky A. Potential drug interactions with statins: Estonian register-based study. Open medicine (Warsaw, Poland) 2015; 10:254-260. http://www.ncbi.nlm.nih.gov/pubmed/?term=28352703
Multi-modality risk score shows potential
Traditional risk-factors have been, and will be, first and foremost when calculating risk for ASCVD complications. In this analysis, based on the Multi Ethnic Study of Atherosclerosis (MESA) (N=6621) and the Dallas Heart Study (DHS) (N=2202), novel biomarkers, with ECG and imaging modalities were combined in a multi-modality risk assessment tool. Participants free from CVD had the following measurements performed: left ventricular hypertrophy (ECG-LVH), coronary artery calcium N-terminal pro B-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-cTnT) and high-sensitivity C-reactive protein (hs-CRP). A global composite CVD outcome (CVD death, myocardial infarction [MI], stroke, coronary or peripheral revascularization, incident heart failure or atrial fibrillation) and ASCVD risk (fatal or nonfatal MI or stroke) was calculated. The risk was determined by counting the number of abnormal test and comparing them with those who had no abnormal test. The global CVD 10-year risk was significantly increased in participants with 1 (adjusted HR 1.9, 95% CI 1.4-2.6), 2 (HR 3.2, 95% CI 2.3-4.4), 3 (HR 4.7, 95% CI 3.4-6.5) and >4 (HR 7.5, 95% CI 5.2-10.6) abnormal tests. This was evaluated in the MESA study and reproduced in the DHS. The proportion of individuals with scores of 0, 1, 2, 3 or > 4 was 20, 30, 27, 17, and 6 % in MESA and the proportion with scores of 0, 1, 2, and > 3 in DHS was 35, 42, 17, and 7 %. Individuals with scores >2, represented fewer than half of MESA participants and 1/4 of the younger DHS populations, but were associated for 79% and 58% of global CVD events, respectively. The authors suggest that this multimodality testing strategy may help to individualize and more efficiently target cardiovascular prevention efforts in primary care.
de Lemos JA, Ayers CR, Levine BD et al. A Multimodality Strategy for Cardiovascular Risk Assessment: Performance in Two Population-Based Cohorts. Circulation 2017. http://www.ncbi.nlm.nih.gov/pubmed/?term=28360032

Relevant publications
Issue 13
  1. Mirjanic-Azaric B, Jelic-Ivanovic Z, Zeljkovic A et al. The Pleiotropic Effects of Atorvastatin on Stable Angina Patients: Evidence by Analysis of High-Density Lipoprotein Size and Subclasses, and Plasma mRNA. Journal of medical biochemistry 2015; 34:314-322. http://www.ncbi.nlm.nih.gov/pubmed/?term=28356842
  2. Chee YR, Watson RW, McCarthy J et al. High dose statin prophylaxis in cardiopulmonary bypass related surgery: clinical utility. Journal of cardiothoracic surgery 2017; 12:20. http://www.ncbi.nlm.nih.gov/pubmed/?term=28359339
  3. Kuiper JG, Sanchez RJ, Houben E et al. Use of Lipid-Modifying Therapy and LDL-C Goal Attainment in a High-Cardiovascular-Risk Population in the Netherlands. Clinical therapeutics 2017. http://www.ncbi.nlm.nih.gov/pubmed/?term=28347514
  4. Jiang F, Choi JY, Lee JH et al. The influences of SLCO1B1 and ABCB1 genotypes on the pharmacokinetics of simvastatin, in relation to CYP3A4 inhibition. Pharmacogenomics 2017; 18:459-469. http://www.ncbi.nlm.nih.gov/pubmed/?term=28350522
  5. He XX, Zhang R, Zuo PY et al. The efficacy advantage of evolocumab (AMG 145) dosed at 140mg every 2weeks versus 420mg every 4weeks in patients with hypercholesterolemia: Evidence from a meta-analysis. Eur J Intern Med 2017; 38:52-60. http://www.ncbi.nlm.nih.gov/pubmed/?term=28341307
  6. Frohlich H, Raman N, Tager T et al. Statins attenuate but do not eliminate the reverse epidemiology of total serum cholesterol in patients with non-ischemic chronic heart failure. Int J Cardiol 2017. http://www.ncbi.nlm.nih.gov/pubmed/?term=28342630
  7. Cariou B, Leiter LA, Muller-Wieland D et al. Efficacy and safety of alirocumab in insulin-treated patients with type 1 or type 2 diabetes and high cardiovascular risk: Rationale and design of the ODYSSEY DM-INSULIN trial. Diabetes Metab 2017. http://www.ncbi.nlm.nih.gov/pubmed/?term=28347654
  8. Yu Y, Zhu C, Liu C, Gao Y. Effect of Prior Atorvastatin Treatment on the Frequency of Hospital Acquired Pneumonia and Evolution of Biomarkers in Patients with Acute Ischemic Stroke: A Multicenter Prospective Study. BioMed research international 2017; 2017:5642704. http://www.ncbi.nlm.nih.gov/pubmed/?term=28357403
  9. Shean KE, McCallum JC, Soden PA et al. Regional variation in patient selection and treatment for carotid artery disease in the Vascular Quality Initiative. Journal of vascular surgery 2017. http://www.ncbi.nlm.nih.gov/pubmed/?term=28359719
  10. Rubba P, Gentile M, Marotta G et al. Causative mutations and premature cardiovascular disease in patients with heterozygous familial hypercholesterolaemia. Eur J Prev Cardiol 2017:2047487317702040. http://www.ncbi.nlm.nih.gov/pubmed/?term=28353356
  11. Nakagawa I, Park HS, Yokoyama S et al. Pretreatment with and ongoing use of omega-3 fatty acid ethyl esters reduce the slow-flow phenomenon and prevent in-stent restenosis in patients undergoing carotid artery stenting. Journal of vascular surgery 2017. http://www.ncbi.nlm.nih.gov/pubmed/?term=28359716
  12. Hausner H, Derving Karsbol J, Holst AG et al. Effect of Semaglutide on the Pharmacokinetics of Metformin, Warfarin, Atorvastatin and Digoxin in Healthy Subjects. Clinical pharmacokinetics 2017. http://www.ncbi.nlm.nih.gov/pubmed/?term=28349387
  13. Hackett G, Jones PW, Strange RC, Ramachandran S. Statin, testosterone and phosphodiesterase 5-inhibitor treatments and age related mortality in diabetes. World J Diabetes 2017; 8:104-111. http://www.ncbi.nlm.nih.gov/pubmed/?term=28344753
  14. de la Pena A, Cui X, Geiser J, Loghin C. No Dose Adjustment is Recommended for Digoxin, Warfarin, Atorvastatin or a Combination Oral Contraceptive When Coadministered with Dulaglutide. Clinical pharmacokinetics 2017. http://www.ncbi.nlm.nih.gov/pubmed/?term=28357715
  15. Choudhary NS, Saigal S, Saraf N, Soin AS. Acute Onset Significant Muscle Weakness in a Patient Awaiting Liver Transplantation: Look for Statins. J Clin Exp Hepatol 2017; 7:66-67. http://www.ncbi.nlm.nih.gov/pubmed/?term=28348473
  16. Alizadeh J, Zeki AA, Mirzaei N et al. Mevalonate Cascade Inhibition by Simvastatin Induces the Intrinsic Apoptosis Pathway via Depletion of Isoprenoids in Tumor Cells. Scientific reports 2017; 7:44841. http://www.ncbi.nlm.nih.gov/pubmed/?term=28344327

Miscellaneous publications
Issue 13
  1. Zijah V, Salehi R, Aghazadeh M et al. Towards optimization of odonto/osteogenic bioengineering: in vitro comparison of simvastatin, sodium fluoride, melanocyte-stimulating hormone. In vitro cellular & developmental biology. Animal 2017. http://www.ncbi.nlm.nih.gov/pubmed/?term=28342024
  2. Mahmoud MO, Aboud HM, Hassan AH et al. Transdermal delivery of atorvastatin calcium from novel nanovesicular systems using polyethylene glycol fatty acid esters: Ameliorated effect without liver toxicity in poloxamer 407-induced hyperlipidemic rats. J Control Release 2017. http://www.ncbi.nlm.nih.gov/pubmed/?term=28344015
  3. Lee WS, Lee EG, Sung MS et al. Atorvastatin inhibits osteoclast differentiation by suppressing NF-kappaB and MAPK signaling during IL-1beta-induced osteoclastogenesis. The Korean journal of internal medicine 2017. http://www.ncbi.nlm.nih.gov/pubmed/?term=28352062
  4. Kerr AG, Tam LC, Hale AB et al. A genomic DNA reporter screen identifies squalene synthase inhibitors which act cooperatively with statins to upregulate the low-density lipoprotein receptor. J Pharmacol Exp Ther 2017. http://www.ncbi.nlm.nih.gov/pubmed/?term=28360334
  5. Huang Z, Zhang L, Feng X et al. A new in vivo method to retard progression of intervertebral disc degeneration through stimulation of endogenous stem cells with simvastatin. Medical hypotheses 2017; 101:65-66. http://www.ncbi.nlm.nih.gov/pubmed/?term=28351496

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