Skip to main content
SpringerLink
Log in

A Discrete-Event Simulation of Smoking-Cessation Strategies Based on Varenicline Pivotal Trial Data

  • Original Research Article
  • Published:
PharmacoEconomics Aims and scope Submit manuscript

Abstract

Background

Smoking is the leading cause of preventable death in the US. While one in five individuals smoke, and 70% of these indicate a desire to quit, <5% of unaided quit attempts succeed. Cessation aids can double or triple the odds of successfully quitting. Models of smoking-cessation behaviour can elucidate the implications of individual abstinence patterns to allow better tailoring of quit attempts to an individual’s characteristics.

Objective

The objectives of this study were to develop and validate a discrete-event simulation (DES) to evaluate the benefits of smoking abstinence using data from the pooled pivotal clinical trials of varenicline versus bupropion or placebo for smoking cessation and to provide a foundation for the development of a lifetime smoking-cessation model.

Methods

The DES model simulated the outcome of a single smoking-cessation attempt over 1 year, in accordance with the clinical trial timeframes. Pharmaceutical costs were assessed from the perspective of a healthcare payer. The model randomly sampled patient profiles from the pooled varenicline clinical trials. All patients were physically and mentally healthy adult smokers who were motivated to quit abruptly. The model allowed for comparisons of up to five distinct treatment approaches for smoking cessation. In the current analyses, three interventions corresponding to the clinical trials were evaluated, which included brief counselling plus varenicline 1.0 mg twice daily (bid) or bupropion SR 150mg bid versus placebo (i.e. brief counselling only). The treatment periods in the clinical trials were 12 weeks (target quit date: day 8), with a 40-week non-treatment follow-up, and counselling continuing over the entire 52-week period in all treatment groups. The main outcome modelled was the continuous abstinence rate (CAR; defined as complete abstinence from smoking and confirmed by exhaled carbon monoxide ≤10 ppm) at end of treatment (weeks 9–12) and long-term follow-up (weeks 9–52), and total time abstinent from smoking over the course of 52 weeks. The model also evaluated costs and cost-effectiveness outcomes.

Results

For the varenicline, bupropion and placebo cohorts, respectively, the model predicted CARs for weeks 9–12 of 44.3%, 30.4% and 18.6% compared with observed rates of 44.0%, 29.7% and 17.7%; over weeks 9–52, predicted CARs in the model compared with observed rates in the pooled clinical studies were 22.9%, 16.4% and 9.4% versus 22.4%, 15.4% and 9.3%, respectively. Total mean abstinence times accrued in the model varenicline, bupropion and placebo groups, respectively, were 3.6, 2.6 and 1.5 months and total pharmaceutical treatment costs were $US261, $US442 and $US0 (year 2008 values) over the 1-year model period. Using cost per abstinent-month achieved as a measure of cost effectiveness, varenicline dominated bupropion and yielded an incremental cost-effectiveness ratio of $US124 compared with placebo.

Conclusion

The model accurately replicated abstinence patterns observed in the clinical trial data using individualized predictions and indicated that varenicline was more effective and may be less costly than bupropion. This simulation incorporated individual predictions of abstinence and relapse, and provides a framework for lifetime modelling that considers multiple quit attempts over time in diverse patient populations using a variety of quit attempt strategies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Centers for Disease Control and Prevention (CDC). Annual smoking-attributable mortality, years of potential life lost, and economic costs: United States, 1995–1999. MMWR Morb Mortal Wkly Rep 2002 Apr 12; 51 (14): 300–3

    Google Scholar 

  2. Centers for Disease Control and Prevention (CDC). State-specific smoking-attributable mortality and years of potential life lost: United States, 2000–2004. MMWR Morb Mortal Wkly Rep 2009 Jan 23; 58 (2): 29–33

    Google Scholar 

  3. Centers for Disease Control and Prevention (CDC). Smoking-attributable mortality, years of potential life lost, and productivity losses: United States, 2000–2004. MMWR Morb Mortal Wkly Rep 2008 Nov 14; 57 (45): 1226–8

    Google Scholar 

  4. US Department of Health and Human Services. Office of the Surgeon General. The health consequences of involuntary exposure to tobacco smoke: a report of the Surgeon General. 2006 Jun 27 [online]. Available from URL: http://www.surgeongeneral.gov/library/secondhandsmoke/ [Accessed 2010 Sep 6]

  5. Kaper J, Wagena EJ, Willemsen MC, et al. Reimbursement for smoking cessation treatment may double the abstinence rate: results of a randomized trial. Addiction 2005 Jul; 100 (7): 1012–20

    Article  PubMed  CAS  Google Scholar 

  6. Centers for Disease Control and Prevention (CDC). Cigarette smoking among adults: United States, 2006. MMWR 2007 Nov 9; 56 (44): 1157–61

    Google Scholar 

  7. Taylor T, Lader D, Bryant A, et al. Smoking-related behaviour and attitudes, 2005: a report on research using the National Statistics Omnibus Survey produced on behalf of the Department of Health and the Information Centre for Health and Social Care. 2006 [online]. Available from URL: http://www.statistics.gov.uk/downloads/theme_health/Smoking2005.pdf [Accessed 2010 Sep 6]

  8. Hughes JR, Keely J, Naud S. Shape of the relapse curve and long-term abstinence among untreated smokers. Addiction 2004 Jan; 99 (1): 29–38

    Article  PubMed  Google Scholar 

  9. Nides M. Update on pharmacologic options for smoking cessation treatment. Am J Med 2008 Apr; 121 (4 Suppl. 1): S20–31

    Article  PubMed  CAS  Google Scholar 

  10. Hajek P, Stead LF, West R, et al. Relapse prevention interventions for smoking cessation. Cochrane Database System Rev 2009 Jan 21; (1): CD003999

    Google Scholar 

  11. Cahill K, Stead LF, Lancaster T. Nicotine receptor partial agonists for smoking cessation. Cochrane Database Syst Rev 2007 Jan 24; (1): CD006103

    Google Scholar 

  12. Fiore MC, Jaén CR, Baker TB, et al. Treating tobacco use and dependence: quick reference guide for clinicians, 2008 update. Rockville (MD): US Department of Health and Human Services, 2009 Apr [online]. Available from URL: http://www.ahrq.gov/clinic/tobacco/tobaqrg.pdf [Accessed 2010 Sep 6]

    Google Scholar 

  13. Hughes JR, Stead LF, Lancaster T. Antidepressants for smoking cessation. Cochrane Database Syst Rev 2007 Jan 24; (1): CD000031

    Google Scholar 

  14. Stead LF, Perera R, Bullen C, et al. Nicotine replacement therapy for smoking cessation. Cochrane Database Syst Rev 2008 Jan 23; (1): CD000146

    Google Scholar 

  15. Armour BS, Finkelstein EA, Fiebelkorn IC. State-level Medicaid expenditures attributable to smoking. Prev Chronic Dis 2009 Jul; 6 (3): A84

    PubMed  Google Scholar 

  16. Foulds J, Burke M, Steinberg M, et al. Advances in pharmacotherapy for tobacco dependence. Expert Opin Emerg Drugs 2004 May; 9 (1): 39–53

    Article  PubMed  CAS  Google Scholar 

  17. Ranney L, Melvin C, Lux L, et al. Systematic review: smoking cessation intervention strategies for adults and adults in special populations. Ann Int Med 2006 Dec 5; 145 (11): 845–56

    PubMed  Google Scholar 

  18. Joyce GF, Niaura R, Maglione M, et al. The effectiveness of covering smoking cessation services for medicare beneficiaries. Health Serv Res 2008 Dec; 43 (6): 2106–23

    Article  PubMed  Google Scholar 

  19. Centers for Disease Control and Prevention (CDC). State medicaid coverage for tobacco-dependence treatments: United States, 2009. MMWR Morb Mortal Wkly Rep 2010 Oct 22; 59 (41): 1340–3

    Google Scholar 

  20. Gonzales D, Rennard SI, Nides M, et al. Varenicline, an α4β2 nicotinic acetylcholine receptor partial agonist, vs sustained-release bupropion and placebo for smoking cessation: a randomized controlled trial. JAMA 2006 Jul 5; 296 (1): 47–55

    Article  PubMed  CAS  Google Scholar 

  21. Jorenby DE, Hays JT, Rigotti NA, et al. Efficacy of varenicline, an α4β2 nicotinic acetylcholine receptor partial agonist, vs placebo or sustained-release bupropion for smoking cessation: a randomized controlled trial. JAMA 2006 Jul 5; 296(1): 56–63

    Article  PubMed  CAS  Google Scholar 

  22. Caro JJ. Pharmacoeconomic analyses using discrete event simulation. Pharmacoeconomics 2005; 23 (4): 323–32

    Article  PubMed  Google Scholar 

  23. Caro JJ, Möller J, Getsios D. Discrete event simulation: the preferred technique for health economic evaluations? Value Health 2010 Dec; 13 (8): 1056–60

    Article  PubMed  Google Scholar 

  24. Simpson KN, Strassburger A, Jones WJ, et al. Comparison of Markov model and discrete-event simulation techniques for HIV. Pharmacoeconomics 2009; 27 (2): 159–65

    Article  PubMed  Google Scholar 

  25. Weinstein MC. Recent developments in decision-analytic modelling for economic evaluation. Pharmacoeconomics 2006; 24 (11): 1043–53

    Article  PubMed  Google Scholar 

  26. Bolin K, Wilson K, Benhaddi H, et al. Cost-effectiveness of varenicline compared with nicotine patches for smoking cessation: results from four European countries. Eur J Public Health 2009 Dec; 19 (6): 650–4

    Article  PubMed  Google Scholar 

  27. Hoogendoorn M, Welsing P, Rutten-van Molken MP. Cost-effectiveness of varenicline compared with bupropion, NRT, and nortriptyline for smoking cessation in the Netherlands. Curr Med Res Opin 2008 Jan; 24 (1): 51–61

    PubMed  Google Scholar 

  28. Howard P, Knight C, Boler A, et al. Cost-utility analysis of varenicline versus existing smoking cessation strategies using the BENESCO simulation model: application to a population of US adult smokers. Pharmacoeconomics 2008; 26 (6): 497–511

    Article  PubMed  CAS  Google Scholar 

  29. Knight C, Howard P, Baker CL, et al. The cost-effectiveness of an extended course (12+12 weeks) of varenicline compared with other available smoking cessation strategies in the United States: an extension and update to the BENESCO model. Value Health 2010 Mar; 13 (2): 209–14

    Article  PubMed  Google Scholar 

  30. Law AM, Kelton WD. Simulations modeling and analysis. Boston (MA): McGraw-Hill, 2000

    Book  Google Scholar 

  31. Babad H, Sanderson C, Naidoo B, et al. The development of a simulation model of primary prevention strategies for coronary heart disease. Health Care Manag Sci 2002 Nov; 5 (4): 269–74

    Article  PubMed  Google Scholar 

  32. Bozzette SA, Boer R, Bhatnagar V, et al. A model for a smallpox-vaccination policy. N Eng J Med 2003 Jan 30; 348 (5): 416–25

    Article  Google Scholar 

  33. Cahill W, Render M. Dynamic simulation modeling of ICU bed availability. In: Farrington PA, Nembhard HB, Sturrock DT, et al., editors. Proceedings of the 1999 Winter Simulation Conference (WSC’99); 1999 Dec 5–8; Phoenix (AZ). Piscataway (NJ): IEEE Standards Office, 1999: 1573–6

    Google Scholar 

  34. Caro J, Ward A, Moller J. Modelling the health benefits and economic implications of implanting dual-chamber vs. single-chamber ventricular pacemakers in the UK. Europace 2006 Jun; 8 (6): 449–55

    Article  PubMed  Google Scholar 

  35. Cooper K, Davies R, Roderick P, et al. The development of a simulation model of the treatment of coronary heart disease. Health Care Manag Sci 2002 Nov; 5 (4): 259–67

    Article  PubMed  Google Scholar 

  36. Davies R, Roderick P, Canning C, et al. The evaluation of screening policies for diabetic retinopathy using simulation. Diabet Med 2002 Sep; 19 (9): 762–70

    Article  PubMed  CAS  Google Scholar 

  37. Guest JF, Cookson RF. Cost of schizophrenia to UK society: an incidence-based cost-of-illness model for the first 5 years following diagnosis. Pharmacoeconomics 1999 Jun; 15(6): 597–610

    Article  PubMed  CAS  Google Scholar 

  38. Huybrechts KF, Caro JJ, Wilson DA, et al. Health and economic consequences of sevelamer use for hyperphos-phatemia in patients on hemodialysis. Value Health 2005 Sep–Oct; 8 (5): 549–61

    Article  PubMed  Google Scholar 

  39. Kelton WD, Sadowski RP, Sadowski DA. Simulation with ARENA. 3rd ed. Boston (MA): McGraw-Hill, 2003

    Google Scholar 

  40. McEwan P, Peters JR, Bergenheim K, et al. Evaluation of the costs and outcomes from changes in risk factors in type 2 diabetes using the Cardiff stochastic simulation cost-utility model (DiabForecaster). Curr Med Res Opin 2006 Jan; 22 (1): 121–9

    Article  PubMed  Google Scholar 

  41. Ward A, Bozkaya D, Fleischmann J, et al. Modeling the economic and health consequences of managing chronic osteoarthritis pain with opioids in Germany: comparison of extended-release oxycodone and OROS hydromorphone. Curr Med Res Opin 2007 Oct; 23 (10): 2333–45

    Article  PubMed  CAS  Google Scholar 

  42. Warner KE, Smith RJ, Smith DG, et al. Health and economic implications of a work-site smoking-cessation program: a simulation analysis. J Occup Environ Med 1996 Oct; 38 (10): 981–92

    Article  PubMed  CAS  Google Scholar 

  43. Arias E. United States life tables, 2004. Natl Vital Stat Rep 2007; 56 (9): 1–39

    PubMed  Google Scholar 

  44. Nides M, Glover ED, Reus VI, et al. Varenicline versus bupropion SR or placebo for smoking cessation: a pooled analysis. Am J Health Behav 2008 Nov–Dec; 32 (6): 664–75

    Article  PubMed  Google Scholar 

  45. Doll R, Hill AB. The mortality of doctors in relation to their smoking habits: a preliminary report. 1954. BMJ 2004 Jun 26; 328 (7455): 1529–33; discussion 1533

    Article  PubMed  Google Scholar 

  46. Doll R, Peto R, Boreham J, et al. Mortality in relation to smoking: 50 years’ observations on male British doctors. BMJ 2004 Jun 26; 328 (7455): 1519

    Article  PubMed  Google Scholar 

  47. Hoogenveen RT, van Baal PH, Boshuizen HC, et al. Dynamic effects of smoking cessation on disease incidence, mortality and quality of life: the role of time since cessation. Cost Eff Resour Alloc 2008 Jan 11; 6: 1

    Article  PubMed  Google Scholar 

  48. Caro JJ, Getsios D, Möller J. Regarding probabilistic analysis and computationally expensive models: necessary and required? Value Health 2007 Jul–Aug; 10 (4): 317–8; author reply 319

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. United BioSource Corporation, Lexington, Massachusetts, USA

    James G. Xenakis, Elizabeth T. Kinter, Alexandra J. Ward & J. Jaime Caro

  2. United BioSource Corporation, Montreal, Quebec, Canada

    K. Jack Ishak

  3. Pfizer Inc, Primary Care Business Unit, East 42nd Street, New York, New York, 10017, USA

    Jenő P. Marton, Richard J. Willke & Simon Davies

Authors
  1. James G. Xenakis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Elizabeth T. Kinter
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. K. Jack Ishak
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Alexandra J. Ward
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jenő P. Marton
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Richard J. Willke
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Simon Davies
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. J. Jaime Caro
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jenő P. Marton.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Xenakis, J.G., Kinter, E.T., Ishak, K.J. et al. A Discrete-Event Simulation of Smoking-Cessation Strategies Based on Varenicline Pivotal Trial Data. Pharmacoeconomics 29, 497–510 (2011). https://doi.org/10.2165/11589230-000000000-00000

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.2165/11589230-000000000-00000

Keywords

Search

Navigation