Abstract
Background
Individuals with metabolic syndrome (MetS) are at increased risk of cardiovascular disease (CVD), often requiring combination drug therapy for control of risk factors and subsequent risk reduction. This study aims to compare the long-term effectiveness and cost effectiveness of the polypill (a multi-component tablet), and its components (alone or in combination), in a MetS population.
Methods and Results
A Markov state transition model, using individual subject data from the Australian Diabetes, Obesity and Lifestyle study, was constructed to simulate the effects of the treatment versus no treatment on CVD events, and costs over 10 years. In 1,991 individuals classified as MetS and free of existing diabetes mellitus or CVD, treatment with the polypill (or its components) was effective at reducing cardiovascular events [statin: 171, aspirin (actetylsalicylic acid): 201, antihypertensive: 186 per 1,000 individuals]. The more drug therapies employed the greater the reduction, with the polypill reducing up to 351 cardiovascular events per 10,000 individuals. Cost-effectiveness analyses were sensitive to drug treatment costs and effectiveness of treatment. At a cost of AUD$42 per person per annum, aspirin was considered cost saving. All other treatment strategies, including the polypill, were not cost effective.
Conclusion
The polypill is likely to be effective in the reduction of cardiovascular events in a MetS population. It is, however, not cost effective. Nevertheless, in a high-risk population, among whom combination therapy is often prescribed, the polypill is likely to be more cost effective than antihypertensive therapy alone or dual therapy with a statin and antihypertensive combination.
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References
Wald NJ, Law MR. A strategy to reduce cardiovascular disease by more than 80%. BMJ. 2003;326:1419-25.
Lonn E, Bosch J, Teo KK, et al. The polypill in the prevention of cardiovascular diseases: key concepts, current status, challenges, and future directions. Circulation. 2010;122:2078–88.
Yusuf S, Pais P, Afzal R, et al. Effects of a polypill (Polycap) on risk factors in middle-aged individuals without cardiovascular disease (TIPS): a phase II, double-blind, randomised trial. Lancet. 2009;373:1341–51.
Manson JE, Skerrett PJ, Greenland P, et al. The escalating pandemics of obesity and sedentary lifestyle. A call to action for clinicians. Arch Intern Med. 2004;164:249–58.
Grundy SM. Metabolic syndrome: a multiplex cardiovascular risk factor. J Clin Endocrinol Metab. 2007;92:399–404.
Sun X, Faunce T. Decision-analytical modeling in health-care economic evaluations. Eur J Health Econ. 2008;9:313–23.
Pauker SG, Kassirer JP. Decision analysis. N Engl J Med. 1987;316:250–8.
O’Hagen A, McCabe C, Akehurst R, et al. Incorporation of uncertainty in health economic modeling studies. Pharmacoeconomics. 2005;23:529–36.
Dunstan DW, Zimmet PZ, Welborn TA, et al. The Australian Diabetes, Obesity and Lifestyle Study (AusDiab)—methods and response rates. Diabetes Res Clin Pract. 2002;57:119–29.
Alberti KG, Zimmet P, Shaw J. The metabolic syndrome—a new worldwide definition. Lancet. 2005;366:1059–62.
Anderson KM, Odell PM, Wilson PWF, et al. Cardiovascular disease risk profiles. Am Heart J. 1990;121:293–8.
Zomer E, Liew D, Owen A, et al. Cardiovascular risk prediction in a population with the metabolic syndrome: Framingham vs. UKPDS algorithms. Eur J Prev Cardiol 2012. doi:10.1177/2047487312449307 (Epub ahead of print).
Australian Institute of Health and Welfare 2011. National GRIM books. AIHW, 2011. http://www.aihw.gov.au/national-grim-books.
Steg PG, Bhatt DL, Wilson PWF, for the REACH Registry Investigators, et al. One-year cardiovascular event rates in outpatients with atherothrombosis. JAMA. 2007;297(11):1197–206.
U.S. Preventive Services Task Force. Aspirin for the prevention of cardiovascular disease: recommendation statement. Ann Intern Med. 2009;150:396–404.
Clarke P, Gray A, Holman R. Estimating utility values for health states of type 2 diabetic patients using the EQ-5D (UKPDS 62). Med Decis Making. 2002;22:340–9.
Greving JP, Buskens E, Koffijberg H, et al. Cost-effectiveness of aspirin treatment in the primary prevention of cardiovascular disease events in subgroups based on age, gender, and varying cardiovascular risk. Circulation. 2008;117:2875–83.
Encyclopedia of Biostatistics 2nd ed. New York: Wiley; 2005.
Woloshin S, Schwartz LM, Moncur M, et al. Assessing values for health: numeracy matters. Med Decis Making. 2001;21:382–90.
Australian Government: Department of Health and Ageing. Pharmaceutical benefits scheme (PBS). http://www.pbs.gov.au. Viewed 5 Sept 2011.
Salkeld G, Phongsavan P, Oldenberg B, et al. The cost-effectiveness of a cardiovascular risk reduction program in general practice. Health Policy. 1997;41(2):105–19.
Walker A, Butler JR. Economic model system of chronic diseases in Australia; a novel approach initially focusing on diabetes and cardiovascular disease. Int J Simul Process Model. 2010;6:137–51.
Huynh T. Convenience care: a patient-centered mode duling. Physician Exec. 2004;30:56–8.
Sassi F. Calculating QALYs, comparing QALY and DALY calculations. Helath Policy Plan. 2006;21:402–8.
Severens JL, Milne RJ. Discounting health outcomes in economic evaluation; the ongoing debate. Value Health. 2004;7:397–401.
Sonnenberg FA, Beck JR. Markov models in medical decision making: a practical guide. Med Decis Making. 1993;13:322–38.
Li R, Zhang P, Barker LE, et al. Cost-effectiveness of interventions to prevent and control diabetes mellitus: a systematic review. Diabet Care. 2010;33:1872–94.
World Health Organization. Choosing interventions that are cost effective (WHO-CHOICE). Geneva: World Health Organization; 2005.
Vos T, Carter R, Barendregt J, et al. for the ACE-Prevention team. Assessing cost-effectiveness in prevention: ACE-prevention. Final report. University of Queensland, Brisbane and Deakin University, Melbourne 2010.
Sorensen HT, Mellemkjaer L, Blot WJ, et al. Risk of upper gastrointestinal bleeding associated with use of low-dose aspirin. Am J Gastroenterol. 2000;95:2218–24.
Kelly JP, Kaufman DW, Jurgelon JM, et al. Risk of aspirin-associated major upper-gastrointestinal bleeding with enteric-coated or buffered product. Lancet. 1996;348:1413–6.
Claxton AJ, Cramer J, Pierce C. A systematic review of the associations between dose regimens and medication compliance. Clin Ther. 2001;23:1296–310.
Author Contributions
EZ developed the epidemiological model, performed the statistical analysis, and drafted the manuscript. AO participated in the design of the model and revised the manuscript. DJM participated in data and subject selection and revised the manuscript. ZA revised the manuscript. CMR participated in the design of the model and revised the manuscript. DL assisted in development of the epidemiological model and revised the manuscript.
Acknowledgments
The authors wish to thank the AusDiab Steering Committee for providing data from the AusDiab study.
Funding
This research was supported by grants from the Australian Research Council (ARC) and sanofi-aventis australia.
Conflicts of Interest
The authors have no potential conflicts of interest to disclose.
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Zomer, E., Owen, A., Magliano, D.J. et al. Predicting the Impact of Polypill Use in a Metabolic Syndrome Population: An Effectiveness and Cost-Effectiveness Analysis. Am J Cardiovasc Drugs 13, 121–128 (2013). https://doi.org/10.1007/s40256-013-0019-2
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DOI: https://doi.org/10.1007/s40256-013-0019-2