Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

Providing patients with pharmacogenetic test results affects adherence to statin therapy: results of the Additional KIF6 Risk Offers Better Adherence to Statins (AKROBATS) trial

Abstract

Despite the clinical benefit of statin therapy and the numerous strategies used to improve adherence, no strategy has used direct communication of genetic test results to the patient as an adherence and persistence motivator. We investigated in a real-world setting the effect of a process of providing KIF6 test results and risk information directly to 647 tested patients on 6-month statin adherence (proportion of days covered (PDC)) and persistence compared with concurrent non-tested matched controls. Adjusted 6-month statin PDC was significantly greater in tested patients: 0.77 (95% confidence interval (CI) 0.72–0.82) vs controls 0.68 (95% CI 0.63–0.73), P<0.0001. Significantly more tested patients were adherent (PDC0.80) (63.4% (59.6–67.1%) vs 45.0% (41.1–48.8%), P<0.0001) and persisted on therapy (69.1% (65.4–72.5%) vs 53.3% (49.4–57.1%), P<0.0001). Similar results were observed in a secondary comparison with 779 unmatched patients who declined testing. The Additional KIF6 Risk Offers Better Adherence to Statins trial provides the first evidence that pharmacogenetic testing may modify patient adherence.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6

Similar content being viewed by others

References

  1. Roger VL, Go AS, Lloyd-Jones DM, Benjamin EJ, Berry JD, Borden WB et alon behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics—2012 update: a report from the American Heart Association. Circulation 2012; 125: e12–e230.

    Article  Google Scholar 

  2. Third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel iii) final report. Circulation 2002; 106: 3143–3421, ; PMID: 12485966.

  3. Grundy SM, Cleeman JI, Merz CNB, Brewer HB Jr., Clark LT, Hunninghake DB et alfor the Coordinating Committee of the National Cholesterol Education Program. Implications of recent clinical trials for the National Cholesterol Education Program Adult Treatment Panel III Guidelines. JACC 2004; 44: 720–732.

    Article  Google Scholar 

  4. American Diabetes Association. Standards of Medical Care in Diabetes—2012. Diabetes Care 2012; 35 (Suppl 1): S11–S63.

    Google Scholar 

  5. Smith SC Jr, Benjamin EJ, Bonow RO, Braun LT, Creagerm M, Franklin BA et al. AHA/ACCF secondary prevention and risk reduction therapy for patients with coronary and other atherosclerotic vascular disease: 2011 update: a guideline from the American Heart Association and American College of Cardiology Foundation. Circulation 2011; 124: 2458–2473.

    Article  Google Scholar 

  6. 2011 Top Therapeutic Classes by US Spending, IMS Health 2012 http://www.imshealth.com/deployedfiles/ims/Global/Content/Corporate/PressRoom/Top-LineMarketData&Trends/2011Top-lineMarketData/Top_Therapy_Classes_by_Sales.pdf Accessed 2012.

  7. 2011 Top Therapeutic Classes by U.S. Dispensed Prescriptions, IMS Health 2012 http://www.imshealth.com/deployedfiles/ims/Global/Content/Corporate/PressRoom/Top-LineMarketData&Trends/2011ToplineMarketData/Top_Therapy_Classes_by_RX.pdf Accessed on 2012.

  8. Sarawate CA, Cziraky MJ, Stanek EJ, Willey VJ, Corbelli JC, Charland SL . Achievement of optimal combined lipid values in a managed care setting: is a new treatment paradigm needed? Cin Ther 2007; 29: 196–209.

    CAS  Google Scholar 

  9. Jackevicius CA, Mamdani M, Tu JV . Adherence with statins in elderly patients with and without acute coronary syndromes. JAMA 2002; 288: 462–467.

    Article  Google Scholar 

  10. Simpson RJ, Mendys P . The effects of adherence and persistence on clinical outcomes in patients treated with statins: A systematic review. J Clin Lipidol 2010; 4: 462–471.

    Article  Google Scholar 

  11. Sokol MC, McGuigan KA, Verbrugge RR, Epstein RS . Impact of medication adherence on hospitalization risk and healthcare cost. Med Care 2005; 43: 521–530.

    Article  Google Scholar 

  12. Aubert RE, Yao J, Xia F, Garavaglia SB . Is there a relationship between early statin compliance and a reduction in healthcare utilization? Am J Managed Care 2010; 16: 459–466.

    Google Scholar 

  13. Pittman DG, Chen W, Bowlin SJ, Foody JM . Adherence to statins, subsequent healthcare costs, and cardiovascular hospitalizations. Am J Cardiol. 2011; 107: 1662–1666.

    Article  Google Scholar 

  14. Loeppke R, Haufle V, Jinnett K, Parry T, Zhu J, Hymel P et al. Medication adherence, comorbidities, and health risk impacts on workforce absence and job performance. JOEM 2011; 53: 595–604.

    PubMed  Google Scholar 

  15. National council on patient information and education. Enhancing prescription medicine adherence: A National Action Plan. 2007 http://www.talkaboutrx.org/documents/enhancing_prescription_medicine_adherence.pdf Accessed on November 12, 2012.

  16. Bosworth HB, Granger BB, Mendys P, Brindis R, Burkholder R, Czajkowski SM et al. Medication adherence: a call for action. Am Heart J 2011; 162: 412–424.

    Article  Google Scholar 

  17. Ho PM, Bryson CL, Rumsfeld JS . Medication adherence. Its importance in cardiovascular disease. Circulation 2009; 119: 3028–3035.

    Article  Google Scholar 

  18. Haynes RB, Ackloo E, Sahota N, Mc Donald HP, Yao X . Interventions for enhancing medication adherence (Review). The Chocrane Database of Systematic Reviews 2008, (2): CD000011; doi:10.1002/14651858.CD000011.pub3.

  19. Kripalani S, Yao X, Haynes RB . Interventions to enhance medication adherence in chronic medical conditions. Arch Int Med 2007; 167: 540–545.

    Article  Google Scholar 

  20. Lee JK, Grace KA, Taylor AJ . Effect of a pharmacy care program on medication adherence and persistence, blood pressure, and low-density lipoprotein cholesterol. JAMA 2006; 296: 2563–2571.

    Article  CAS  Google Scholar 

  21. O’Donnell CJ, Nabel EG . Genomics of cardiovascular disease. N Engl J Med 2011; 365: 2098–2109.

    Article  Google Scholar 

  22. Wang L, McLeod HL, Weinshilboum RM . Genomics and drug response. N Engl J Med 2011; 364: 1144–1153.

    Article  CAS  Google Scholar 

  23. Li Y, Iakoubova OA, Shiffman D, Devlin JJ, Forrester JS, Superko HR . KIF6 polymorphism as a predictor of risk of coronary events and clinical event reduction by statins. Am J Cardiol 2010; 106: 994–998.

    Article  CAS  Google Scholar 

  24. Ference BA, Yoo W, Flack JM, Clarke M . A common KIF6 polymorphism increases vulnerability to low-density lipoprotein cholesterol: two meta-analyses and a meta-regression analysis. PloS One 6: e28834.

    Article  CAS  Google Scholar 

  25. Bloss CS, Madlensky L, Schork NJ, Topol EJ . Genomic information as a behavioral health intervention: can it work? Pers Med 2011; 8: 659–667.

    Article  Google Scholar 

  26. Heshka JT, Palleschi C, Howley H, Wilson B, Wells PS . A systematic review of perceived risks, psychological and behavioral impacts of genetic testing. Genet Med 2008; 10: 19–32.

    Article  Google Scholar 

  27. Marteau TM, French DP, Griffin SJ, Prevost AT, Sutton S, Watkinson C et al. Effects of communicating DNA-based disease risk estimates on risk-reducing behaviors. Cochrane Database of Systematic Reviews 2010, (10): CD007275; doi:10.1002/14651858.CD007275.pub2.

  28. Chao S, Roberts JS, Marteau TM, Silliman R, Cupples LA, Green RC . Health behavior changes after genetic risk assessment for Alzheimer Disease: The REVEAL Study. Alzheimer Dis Assoc Discord 2008; 22: 94–97.

    Article  Google Scholar 

  29. Ware JE, Kosiniski M, Keller SD . A 12-item Short Form health survey: Construction of scales and preliminary tests of reliability and validity. Med Care 1996; 34: 220–233.

    Article  Google Scholar 

  30. Morisky DE, Green LW, Levine DM . Concurrent predictive validity of a self-reported measure of medication adherence. Med Care 1986; 24: 67–74.

    Article  CAS  Google Scholar 

  31. Germer S, Holland MJ, Higuchi R . High-throughput SNP allele frequency determination in pooled DNA samples by kinetic PCR. Genome Res 2000; 10: 258–266.

    Article  CAS  Google Scholar 

  32. Karve S, Cleves MA, Helm M, Hudson TJ, West DS, Martin BC . As empirical bases for standardizing adherence measures derived from administrative claims data among diabetic patients. Med Care 2008; 46: 1125–1133.

    Article  Google Scholar 

  33. Kareter AJ, Parker MM, Moffet HH, Ahmed AM, Schmittdel JA, Selby JV . New prescription medication gaps: a comprehensive measure of adherence to new prescriptions. Health Services Res 2009; 44: 1640–1661.

    Article  Google Scholar 

  34. Karve S, Cleves MA, Helm M, Hudson TJ, West DS, Martin BC . Good and poor adherence: optimal cut-point for adherence measures using administrative claims data. CMRO 2009; 25: 2303–2310.

    Google Scholar 

  35. McBride CM, Bepler G, Lipkus IM, Lyna P, Samsa G, Albright J et al. Incorporating genetic suseptability feedback into a smoking cessation program for African-American smokers with low income. Cancer Epi Biomark Prev 2002; 11: 521–528.

    Google Scholar 

  36. Bloss CS, Schork NJ, Topol EJ . Effect of direct-to-consumer genomewide profiling to assess disease risk. NEJM 2011; 364: 524–534.

    Article  CAS  Google Scholar 

  37. Foster MW, Mulvihill JJ, Sharp RR . Evaluating the utility of personal genomic information. Genet Med 2009; 11: 570–574.

    Article  Google Scholar 

  38. Benner JS, Tiece JC, Ballantyne CM, Prasad C, Bullano MF, Willey VJ et al. Follow-up lipid tests and physician visits are associated with improved adherence to statin therapy. Pharmacoeconomics 2004; 22 (Suppl 3): 13–23.

    Article  Google Scholar 

  39. Smith DH, Kramer JM, Perrin N, Platt R, Roblin DW, Land K et al. A randomized trial of direct-to-patient communication to enhance adherence to β-blocker therapy following myocardial infarction. Arch Int Med 2008; 168: 477–483.

    Article  Google Scholar 

  40. Shiffman D, O'Meara ES, Bare LA, Rowland CM, Louie JZ, Arellano AR et al. Association of gene variants with incident myocardial infarction in the Cardiovascular Health Study. Arterioscler Thromb Vasc Biol 2008; 28: 173–179.

    Article  CAS  Google Scholar 

  41. Iakoubova OA, Tong CH, Rowland CM, Kirchgessner TG, Young BA, Arellano AR et al. Association of the Trp719Arg polymorphism in kinesin-like protein 6 with myocardial infarction and coronary heart disease in 2 prospective trials: the CARE and WOSCOPS trials. J Am Coll Cardiol 2008; 51: 435–443.

    Article  CAS  Google Scholar 

  42. Iakoubova OA, Sabatine MS, Rowland CM, Tong CH, Catanese JJ, Ranade K et al. Polymorphism in KIF6 gene and benefit from statins after acute coronary syndromes: results from the PROVE IT-TIMI 22 study. J Am Coll Cardiol 2008; 51: 449–455.

    Article  CAS  Google Scholar 

  43. Shiffman D, Sabatine MS, Louie JZ, Kirchgessner TG, Iakoubova OA, Campos H et al. Effect of pravastatin therapy on coronary events in carriers of the KIF6 719Arg allele from the cholesterol and recurrent events trial. Am J Cardiol 2010; 105: 1300–1305.

    Article  CAS  Google Scholar 

  44. Assimes TL, Hólm H, Kathiresan S, Reilly MP, Thorleifsson G, Voight BF et al. Lack of association between the Trp719Arg polymorphism in kinesin-like protein-6 and coronary artery disease in 19 case-control studies. JACC 2010; 56: 1552–1563.

    Article  CAS  Google Scholar 

  45. Hopewell JC, Parish S, Clarke R, Armitage J, Bowman L, Hager J et alMRC/BHF Heart Protection Study Collaborative Group. No impact of KIF6 genotype on vascular risk and statin response among 18,348 randomized patients in the heart protection study. J Am Coll Cardiol 2011; 57: 2000–2007.

    Article  CAS  Google Scholar 

  46. Ridker PM, MacFadyen JG, Glynn RJ, Chasman DI, Ridker PM, MacFadyen JG et al. Kinesin-like protein 6 (KIF6) polymorphism and the efficacy of rosuvastatin in primary prevention. Circ Cardiovasc Genet 2011; 4: 312–317.

    Article  CAS  Google Scholar 

  47. Arsenault BJ, Boekholdt SM, Hovingh GK, Hyde CL, Demicco DA, Chatterjee A et alon behalf of the TNT and IDEAL Investigators. The 719Arg variant of KIF6 and cardiovascular outcomes in statin-treated, stable coronary patients of the treating to new targets and incremental decrease in end points through aggressive lipid-lowering prospective studies. Circ Cardiovasc Genet 2012; 5: 51–57.

    Article  CAS  Google Scholar 

  48. Raebel MA, Carrolll NM, Schroeder EB, Bayliss EA . Importance of including early nonadherence in estimates of medication adherence. Ann Pharmacother 2011; 45: 1053–1060.

    Article  Google Scholar 

Download references

Acknowledgements

We thank the following individuals for their contributions to AKROBATS: Bryan Dechairo, PhD, MBA, for facilitating the partnership with Celera; the Medco Research Institute nursing staff whose efforts made this trial possible; Eryn Bilynsky, RN and Dmitri Kekos for providing clinical support and data quality assurance; and Ghada Hamid for trial management. This research was funded by Medco Health Solutions. Celera Corporation provided genetic testing services, but did not contribute to funding. The sponsors provided review and approval of the manuscript.

Author contributions

Drs Herrera and Charland had access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. The authors were responsible for the design and conduct of the study; for collection, management, analysis, and interpretation of the data; and for preparation and review of the manuscript. Study concept and design: Charland, Agatep, Herrera, Frueh, Devlin, Superko and Stanek. Acquisition of data: Charland, Agatep, Herrera, Ryvkin and Shabbeer. Analysis and interpretation of data: Charland, Agatep, Herrera, Schrader, Ryvkin, Shabbeer and Stanek. Drafting of manuscript: Charland, Agatep, Schrader and Stanek. Critical revision of the manuscript for important intellectual content: Charland, Agatep, Herrera, Schrader, Frueh, Ryvkin, Devlin, Superko, Shabbeer and Stanek. Statistical analysis: Herrera, Ryvkin, Charland, Agatep and Stanek. Obtaining funding: Charland, Frueh, Devlin, Superko and Stanek. Administrative, technical, or material support: Charland, Agatep, Herrera, Schrader, Ryvkin and Stanek. Supervision: Charland, Agatep and Stanek.

Author information

Authors and Affiliations

Authors

Ethics declarations

Competing interests

Dr Charland has received research grants regarding lipid management from Abbott Laboratories, received consulting fees from Mountain Solutions and was employed by Medco Research Institute, LLC/An Express Scripts Company. Drs Herrera, Schrader, Frueh and Stanek and Ms Agatep and Ryvkin were employed by Medco Research Institute, LLC/An Express Scripts Company. Drs Devlin and Superko are employed by Celera Corporation, which markets the KIF6 test used in this study and is available by physician order. Dr Shabbeer was previously employed by Celera Corporation and is currently employed by Ariosa Diagnostics.

Additional information

Previous meeting presentation: The data in this article were presented as a moderated poster at the ACC.12 61st Annual Scientific Session and Expo Meeting, 26 March 2012, Chicago, IL, USA.

Supplementary Information accompanies the paper on the The Pharmacogenomics Journal website

Supplementary information

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Cite this article

Charland, S., Agatep, B., Herrera, V. et al. Providing patients with pharmacogenetic test results affects adherence to statin therapy: results of the Additional KIF6 Risk Offers Better Adherence to Statins (AKROBATS) trial. Pharmacogenomics J 14, 272–280 (2014). https://doi.org/10.1038/tpj.2013.27

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/tpj.2013.27

Keywords

This article is cited by

Search

Quick links