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A Real-World Evaluation of Primary Medication Nonadherence in Patients with Nonvalvular Atrial Fibrillation Prescribed Oral Anticoagulants in the United States

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Abstract

Background

Nonadherence to oral anticoagulants (OACs) is a challenge to stroke risk reduction in patients with nonvalvular atrial fibrillation (NVAF). Data on primary medication nonadherence (PMN) in NVAF are lacking.

Objectives

Our aim was to assess the rates and predictors of PMN among NVAF patients who were newly prescribed an OAC.

Methods

This was a retrospective database analysis of linked healthcare claims and electronic health record data. Adult NVAF patients with a prescription order for an OAC (apixaban, rivaroxaban, dabigatran, or warfarin) between January 2016 and June 2019 were identified (date of first prescription order = index date). Patients had a 1-year baseline and a 6-month post-index period to assess the rates of PMN, defined as having a prescription order but no paid claim for any OAC on or within 30 days after the index date. Sensitivity analyses explored 60-, 90- and 180-day PMN thresholds. Logistic regression models were used to examine the predictors of PMN.

Results

Among 20,393 patients, the overall 30-day PMN rate was 28.4%; PMN rates decreased to 17% with a 180-day threshold. PMN was numerically lowest for warfarin among OACs and numerically lowest for apixaban among direct OACs. A CHA2DS2-VASc score of ≥ 3, commercial insurance, and African American race were associated with higher odds of PMN.

Conclusions

More than one-quarter of patients experienced PMN within 30 days of their initial prescription order. This rate decreased over a longer period, suggesting a delay in fills. Understanding the factors associated with PMN is warranted to develop effective interventions for improving OAC treatment rates in NVAF.

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References

  1. Farina GS, Kalil C, Gutiérrez JP, Barbosa ECD. Arterial stiffness: a possible predictor of atrial fibrillation. Rev Cardiovasc Med. 2022;23(1):32. https://doi.org/10.31083/j.rcm2301032.

    Article  PubMed  Google Scholar 

  2. Corban MT, Toya T, Ahmad A, et al. Atrial fibrillation and endothelial dysfunction: a potential link? Mayo Clin Proc. 2021;96(6):1609–21. https://doi.org/10.1016/j.mayocp.2020.11.005.

    Article  CAS  PubMed  Google Scholar 

  3. Colilla S, Crow A, Petkun W, et al. Estimates of current and future incidence and prevalence of atrial fibrillation in the US adult population. Am J Cardiol. 2013;112(8):1142–7. https://doi.org/10.1016/j.amjcard.2013.05.063.

    Article  PubMed  Google Scholar 

  4. Miyasaka Y, Barnes ME, Gersh BJ, et al. Secular trends in incidence of atrial fibrillation in Olmsted County, Minnesota, 1980 to 2000, and implications on the projections for future prevalence. Circulation. 2006;114(2):199–225. https://doi.org/10.1161/CIRCULATIONAHA.105.595140.

    Article  Google Scholar 

  5. Centers for Disease Control and Prevention. Heart Disease. Atrial Fibrillation. https://www.cdc.gov/heartdisease/atrial_fibrillation.htm. Accessed 16 Dec 2022.

  6. January CT, Wann LS, Calkins H, et al. 2019 AHA/ACC/HRS focused update of the 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society. J Am Coll Cardiol. 2019;74(1):104–32. https://doi.org/10.1016/j.jacc.2019.01.011.

    Article  PubMed  Google Scholar 

  7. Keider N, Elul Y, Schuster A, Yaniv Y. Visualizing and quantifying irregular heart rate irregularities to identify arterial fibrillation events. Front Physiol. 2021;12:637680. https://doi.org/10.3389/fphys.2021.637680.

    Article  Google Scholar 

  8. Hankey GJ. Non-valvular atrial fibrillation and stroke prevention. National Blood Pressure Advisory Committee of the National Heart Foundation. Med J Aust. 2001;174(5):234–9. https://doi.org/10.5694/j.1326-5377.2001.tb143246.x.

    Article  CAS  PubMed  Google Scholar 

  9. Seiffge DJ, Werring DJ, Paciaroni M, et al. Timing of anticoagulation after recent ischaemic stroke in patients with atrial fibrillation. Lancet Neurol. 2019;18(1):117–26. https://doi.org/10.1016/S1474-4422(18):30356-9.

    Article  PubMed  Google Scholar 

  10. Bejot Y, Ben Salem D, Osseby GV, et al. Epidemiology of ischemic stroke from atrial fibrillation in Dijon, France, from 1985 to 2006. Neurology. 2009;72(4):346–53. https://doi.org/10.1212/01.wnl.0000341280.31919.bd.

    Article  CAS  PubMed  Google Scholar 

  11. Grau AJ, Weimar C, Buggle F, et al. Risk factors, outcome, and treatment in subtypes of ischemicstroke: the German stroke data bank. Stroke. 2001;32(11):2559–66. https://doi.org/10.1161/hs1101.098524.

    Article  CAS  PubMed  Google Scholar 

  12. Mozaffarian D, Benjamin EJ, Go AS, et al. Heart disease and stroke statistics—2015 update: a report from the American Heart Association. Circulation. 2015;131(4):e29-322. https://doi.org/10.1161/CIR.0000000000000152.

    Article  PubMed  Google Scholar 

  13. Salazar CA, del Aguila D, Cordova EG. Direct thrombin inhibitors versus vitamin K antagonists for preventing cerebral or systemic embolism in people with non-valvular atrial fibrillation. Cochrane Database Syst Rev. 2014. https://doi.org/10.1002/14651858.CD009893.pub2.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Bruins Slot KM, Berge E. Factor Xa inhibitors versus vitamin K antagonists for preventing cerebral or systemic embolism in patients with atrial fibrillation. Cochrane Database Syst Rev. 2018;3(3):CD008980. https://doi.org/10.1002/14651858.CD008980.pub3.

    Article  PubMed  Google Scholar 

  15. Raparelli V, Proietti M, Cangemi R, et al. Adherence to oral anticoagulant therapy in patients with atrial fibrillation. Thromb Haemost. 2017;117(2):209–18. https://doi.org/10.1160/TH16-10-0757.

    Article  PubMed  Google Scholar 

  16. Yao X, Abraham NS, Alexander GC, et al. Effect of adherence to oral anticoagulants on risk of stroke and major bleeding among patients with atrial fibrillation. J Am Heart Assoc. 2016;5(2):e003074. https://doi.org/10.1161/JAHA.115.003074.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Pharmacy Quality Alliance. PQA Measures Overview. https://www.pqaalliance.org/assets/Measures/PQA_Measures_Overview.pdf. Accessed 16 Dec 2022.

  18. Raebel M, Schmittdiel J, Karter A, Konieczny JL, Steiner JF. Standardizing terminology and definitions of medication adherence and persistence in research employing electronic databases. Med Care. 2013;51(8 Suppl 3):S11-21. https://doi.org/10.1097/MLR.0b013e31829b1d2a.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Cheetham TC, Niu F, Green K, et al. Primary nonadherence to statin medications in a managed care organization. J Manag Care Pharm. 2013;19(5):367–73. https://doi.org/10.18553/jmcp.2013.19.5.367.

    Article  PubMed  Google Scholar 

  20. Rodriguez-Bernal CL, Peiró S, Hurtado I, García-Sempere A, Sanfélix-Gimeno G. Primary nonadherence to oral anticoagulants in patients with atrial fibrillation: real-world data from a population-based cohort. J Manag Care Spec Pharm. 2018;24(5):440–8. https://doi.org/10.18553/jmcp.2018.24.5.440.

    Article  PubMed  Google Scholar 

  21. Shrank WH, Choudhry NK, Fischer MA, et al. The epidemiology of prescriptions abandoned at the pharmacy. Ann Intern Med. 2010;153(10):633–40. https://doi.org/10.7326/0003-4819-153-10-201011160-00005.

    Article  PubMed  Google Scholar 

  22. Derose SF, Green K, Marrett E, et al. Automated outreach to increase primary adherence to cholesterol-lowering medications. JAMA Intern Med. 2013;173(1):38–43. https://doi.org/10.1001/2013.jamainternmed.717.

    Article  PubMed  Google Scholar 

  23. Guo J, He M, Gabriel N, et al. Underprescribing vs underfilling to oral anticoagulation: an analysis of linked medical record and claims data for a nationwide sample of patients with atrial fibrillation. J Manag Care Spec Pharm. 2022;28(12):1400–9.

    PubMed  Google Scholar 

  24. Charlton A, Vidal X, Sabaté M, et al. Factors associated with primary nonadherence to newly initiated direct oral anticoagulants in patients with nonvalvular atrial fibrillation. J Manag Care Spec Pharm. 2021;27(9):1210–20. https://doi.org/10.18553/jmcp.2021.27.9.1210.

    Article  PubMed  Google Scholar 

  25. Sabaté M, Vidal X, Ballarin E, et al. Adherence to direct oral anticoagulants in patients with non-valvular atrial fibrillation: a cross-national comparison in six European Countries (2008–2015). Front Pharmacol. 2021;12:682890. https://doi.org/10.3389/fphar.2021.682890.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Tibshirani R. Regression shrinkage and selection via the Lasso. J R Stat Soc Series B Stat Methodol. 1996;58(1):267–88.

    Google Scholar 

  27. Efron B, Hastie T, Johnstone I, Tibshirani R. Least angle regression. Ann Stat. 2004;32(2):407–99.

    Article  Google Scholar 

  28. Ozaki AF, Choi AS, Le QT, et al. Real-world adherence and persistence to direct oral anticoagulants in patients with atrial fibrillation: a systematic review and meta-analysis. Circ Cardiovasc Qual Outcomes. 2020;13(3):e005969. https://doi.org/10.1161/CIRCOUTCOMES.119.005969.

    Article  PubMed  Google Scholar 

  29. Shore S, Ho PM, Lambert-Kerzner A, et al. Site-level variation in and practices associated with dabigatran adherence. JAMA. 2015;313(14):1443–50. https://doi.org/10.1001/jama.2015.2761.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

The authors would like to acknowledge Katharine Coyle, Senior Consultant at IQVIA, for medical writing assistance in the preparation of this paper.

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Authors and Affiliations

  1. University of California, San Diego, La Jolla, CA, USA

    Inmaculada Hernandez

  2. IQVIA, Falls Church, VA, USA

    Victoria Divino, Mitch DeKoven & Wanjiku Kariuki

  3. Pfizer, New York, NY, USA

    Lin Xie, David W. Hood, Griffith Bell, Cristina Russ, Matthew Cato & Dionne M. Hines

  4. Bristol Myers Squibb, Lawrenceville, NJ, USA

    Dong Cheng & Nipun Atreja

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  1. Inmaculada Hernandez
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Corresponding author

Correspondence to Dionne M. Hines.

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Funding

This study was sponsored by Pfizer and Bristol Myers Squibb.

Conflict of interest

Inmaculada Hernandez was a paid consultant to Pfizer and Bristol Myers Squibb in connection with this study. Victoria Divino, Mitch DeKoven, and Wanjiku Kariuki are employees of IQVIA, which was a paid consultant to Pfizer and Bristol Myers Squibb. Dong Cheng and Nipun Atreja are employees and shareholders of BMS. Lin Xie, David W. Hood, and Matthew Cato were employees of Pfizer at the time of this study. Griffith Bell, Cristina Russ, and Dionne M. Hines are employees and shareholders of Pfizer.

Data availability

The data used in this analysis were obtained through a licensure agreement with Optum and are not publicly available. Interested researchers may contact Optum to apply to gain access to their data.

Ethics approval

Because this study was conducted using only de-identified data and did not involve the collection, use or transmittal of individually identifiable data, Institutional Review Board approval to conduct this study was not necessary. Analysis of commercially available de-identified secondary data sources is considered exempt from the requirements for ‘human subjects research’ in the US. The datasets meet the requirements of the Health Insurance Portability and Accountability Act of 1996.

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Author contributions

All authors have met the following authorship criteria: (1) substantial contributions to the conception and design of the work, or the acquisition, analysis or interpretation of data; (2) drafting the article or revising it critically for important intellectual content; (3) final approval of the version to be published; and (4) agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All authors contributed to the study conception and design. Data analysis was performed by David Hood and quality checks were conducted by Lin Xie. All authors were involved in interpretation of the data. The first draft of the manuscript was written by Victoria Divino and Dionne M. Hines. All authors were involved in critical revision of the manuscript, and all authors read and approved the final manuscript.

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Hernandez, I., Divino, V., Xie, L. et al. A Real-World Evaluation of Primary Medication Nonadherence in Patients with Nonvalvular Atrial Fibrillation Prescribed Oral Anticoagulants in the United States. Am J Cardiovasc Drugs 23, 559–572 (2023). https://doi.org/10.1007/s40256-023-00588-3

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