Literature DB >> 23821436

Smoking cessation treatment and outcomes patterns simulation: a new framework for evaluating the potential health and economic impact of smoking cessation interventions.

Denis Getsios1, Jenő P Marton, Nikhil Revankar, Alexandra J Ward, Richard J Willke, Dale Rublee, K Jack Ishak, James G Xenakis.   

Abstract

BACKGROUND: Most existing models of smoking cessation treatments have considered a single quit attempt when modelling long-term outcomes.
OBJECTIVE: To develop a model to simulate smokers over their lifetimes accounting for multiple quit attempts and relapses which will allow for prediction of the long-term health and economic impact of smoking cessation strategies.
METHODS: A discrete event simulation (DES) that models individuals' life course of smoking behaviours, attempts to quit, and the cumulative impact on health and economic outcomes was developed. Each individual is assigned one of the available strategies used to support each quit attempt; the outcome of each attempt, time to relapses if abstinence is achieved, and time between quit attempts is tracked. Based on each individual's smoking or abstinence patterns, the risk of developing diseases associated with smoking (chronic obstructive pulmonary disease, lung cancer, myocardial infarction and stroke) is determined and the corresponding costs, changes to mortality, and quality of life assigned. Direct costs are assessed from the perspective of a comprehensive US healthcare payer ($US, 2012 values). Quit attempt strategies that can be evaluated in the current simulation include unassisted quit attempts, brief counselling, behavioural modification therapy, nicotine replacement therapy, bupropion, and varenicline, with the selection of strategies and time between quit attempts based on equations derived from survey data. Equations predicting the success of quit attempts as well as the short-term probability of relapse were derived from five varenicline clinical trials.
RESULTS: Concordance between the five trials and predictions from the simulation on abstinence at 12 months was high, indicating that the equations predicting success and relapse in the first year following a quit attempt were reliable. Predictions allowing for only a single quit attempt versus unrestricted attempts demonstrate important differences, with the single quit attempt simulation predicting 19 % more smoking-related diseases and 10 % higher costs associated with smoking-related diseases. Differences are most prominent in predictions of the time that individuals abstain from smoking: 13.2 years on average over a lifetime allowing for multiple quit attempts, versus only 1.2 years with single quit attempts. Differences in abstinence time estimates become substantial only 5 years into the simulation. In the multiple quit attempt simulations, younger individuals survived longer, yet had lower lifetime smoking-related disease and total costs, while the opposite was true for those with high levels of nicotine dependence.
CONCLUSION: By allowing for multiple quit attempts over the course of individuals' lives, the simulation can provide more reliable estimates on the health and economic impact of interventions designed to increase abstinence from smoking. Furthermore, the individual nature of the simulation allows for evaluation of outcomes in populations with different baseline profiles. DES provides a framework for comprehensive and appropriate predictions when applied to smoking cessation over smoker lifetimes.

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Year:  2013        PMID: 23821436     DOI: 10.1007/s40273-013-0070-5

Source DB:  PubMed          Journal:  Pharmacoeconomics        ISSN: 1170-7690            Impact factor:   4.981


  39 in total

1.  Prevalence and predictors of transitions in smoking behavior among college students.

Authors:  David W Wetter; Susan L Kenford; Samuel K Welsch; Stevens S Smith; Rachel T Fouladi; Michael C Fiore; Timothy B Baker
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2.  Individual-level predictors of cessation behaviours among participants in the International Tobacco Control (ITC) Four Country Survey.

Authors:  A Hyland; R Borland; Q Li; H-H Yong; A McNeill; G T Fong; R J O'Connor; K M Cummings
Journal:  Tob Control       Date:  2006-06       Impact factor: 7.552

Review 3.  Individual behavioural counselling for smoking cessation.

Authors:  T Lancaster; L F Stead
Journal:  Cochrane Database Syst Rev       Date:  2005-04-18

Review 4.  Economic evaluation of smoking-cessation therapies: a critical and systematic review of simulation models.

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Journal:  Pharmacoeconomics       Date:  2012-07-01       Impact factor: 4.981

5.  Survival and cause of death after myocardial infarction: the Danish MONICA study.

Authors:  H Brønnum-Hansen; T Jørgensen; M Davidsen; M Madsen; M Osler; L U Gerdes; M Schroll
Journal:  J Clin Epidemiol       Date:  2001-12       Impact factor: 6.437

6.  Smoking, smoking cessation and smoking relapse patterns: a web-based survey of current and former smokers in the US.

Authors:  K Yeomans; K A Payne; J P Marton; E P Merikle; I Proskorovsky; K H Zou; Q Li; R J Willke
Journal:  Int J Clin Pract       Date:  2011-10       Impact factor: 2.503

7.  Efficacy of varenicline, an alpha4beta2 nicotinic acetylcholine receptor partial agonist, vs placebo or sustained-release bupropion for smoking cessation: a randomized controlled trial.

Authors:  Douglas E Jorenby; J Taylor Hays; Nancy A Rigotti; Salomon Azoulay; Eric J Watsky; Kathryn E Williams; Clare B Billing; Jason Gong; Karen R Reeves
Journal:  JAMA       Date:  2006-07-05       Impact factor: 56.272

8.  Sex differences in mortality in patients with COPD.

Authors:  J P de Torres; C G Cote; M V López; C Casanova; O Díaz; J M Marin; V Pinto-Plata; M M de Oca; H Nekach; L J Dordelly; A Aguirre-Jaime; B R Celli
Journal:  Eur Respir J       Date:  2008-12-01       Impact factor: 16.671

9.  Current cigarette smoking among adults - United States, 2011.

Authors: 
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2012-11-09       Impact factor: 17.586

10.  State-specific smoking-attributable mortality and years of potential life lost--United States, 2000-2004.

Authors: 
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2009-01-23       Impact factor: 17.586

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  7 in total

1.  Smoking Cessation: A Comparison of Two Model Structures.

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Journal:  Pharmacoeconomics       Date:  2018-09       Impact factor: 4.981

2.  Operational Modeling with Health Economics to Support Decision Making for COPD Patients.

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Journal:  Health Serv Res       Date:  2021-03-22       Impact factor: 3.402

3.  Budgetary impact analysis on funding smoking-cessation drugs in patients with COPD in Spain.

Authors:  Carlos A Jiménez-Ruiz; Segismundo Solano-Reina; Jaime Signes-Costa; Eva de Higes-Martinez; José I Granda-Orive; José J Lorza-Blasco; Juan A Riesco-Miranda; Neus Altet-Gomez; Miguel Barrueco; Itziar Oyagüez; Javier Rejas
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2015-09-24

4.  Cost-Effectiveness Analysis of Smoking Cessation Interventions in Japan Using a Discrete-Event Simulation.

Authors:  Ataru Igarashi; Rei Goto; Kiyomi Suwa; Reiko Yoshikawa; Alexandra J Ward; Jörgen Moller
Journal:  Appl Health Econ Health Policy       Date:  2016-02       Impact factor: 2.561

5.  Risk of community-acquired pneumonia in chronic obstructive pulmonary disease stratified by smoking status: a population-based cohort study in the United Kingdom.

Authors:  Dionne Cw Braeken; Gernot Gu Rohde; Frits Me Franssen; Johanna Hm Driessen; Tjeerd P van Staa; Patrick C Souverein; Emiel Fm Wouters; Frank de Vries
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2017-08-14

Review 6.  Application of discrete event simulation in health care: a systematic review.

Authors:  Xiange Zhang
Journal:  BMC Health Serv Res       Date:  2018-09-04       Impact factor: 2.655

7.  If at first you don't succeed, when should you try again? A prospective study of failed quit attempts and subsequent smoking cessation.

Authors:  Sarah E Jackson; Robert West; Jamie Brown
Journal:  Addict Behav       Date:  2020-02-28       Impact factor: 3.913

  7 in total

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