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

  • James G. Xenakis

    (United BioSource Corporation, Lexington, Massachusetts, USA)

  • Elizabeth T. Kinter

    (United BioSource Corporation, Lexington, Massachusetts, USA)

  • K. Jack. Ishak

    (United BioSource Corporation, Montreal, Quebec, Canada)

  • Alexandra J. Ward

    (United BioSource Corporation, Lexington, Massachusetts, USA)

  • Jen P. Marton

    (Pfizer Inc, Primary Care Business Unit, New York, New York, USA)

  • Richard J. Willke

    (Pfizer Inc, Primary Care Business Unit, New York, New York, USA)

  • Simon Davies

    (Pfizer Inc, Primary Care Business Unit, New York, New York, USA)

  • J. Jaime. Caro

    (United BioSource Corporation, Lexington, Massachusetts, USA)

Registered author(s):

    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 150 mg 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.

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    Article provided by Springer Healthcare | Adis in its journal PharmacoEconomics.

    Volume (Year): 29 (2011)
    Issue (Month): 6 ()
    Pages: 497-510

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    Handle: RePEc:wkh:phecon:v:29:y:2011:i:6:p:497-510
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