title: Simultaneous evaluation of abstinence and relapse using a Markov chain model in smokers enrolled in a two-year randomized trial.
abstract: BACKGROUND
  GEE and mixed models are powerful tools to compare treatment effects in longitudinal smoking cessation trials. However, they are not capable of assessing the relapse (from abstinent back to smoking) simultaneously with cessation, which can be studied by transition models.
  
  
  METHODS
  We apply a first-order Markov chain model to analyze the transition of smoking status measured every 6 months in a 2-year randomized smoking cessation trial, and to identify what factors are associated with the transition from smoking to abstinent and from abstinent to smoking. Missing values due to non-response are assumed non-ignorable and handled by the selection modeling approach.
  
  
  RESULTS
  Smokers receiving high-intensity disease management (HDM), of male gender, lower daily cigarette consumption, higher motivation and confidence to quit, and having serious attempts to quit were more likely to become abstinent (OR = 1.48, 1.66, 1.03, 1.15, 1.09 and 1.34, respectively) in the next 6 months. Among those who were abstinent, lower income and stronger nicotine dependence (OR = 1.72 for ≤ vs. > 40 K and OR = 1.75 for first cigarette ≤ vs. > 5 min) were more likely to have relapse in the next 6 months.
  
  
  CONCLUSIONS
  Markov chain models allow investigation of dynamic smoking-abstinence behavior and suggest that relapse is influenced by different factors than cessation. The knowledge of treatments and covariates in transitions in both directions may provide guidance for designing more effective interventions on smoking cessation and relapse prevention.
authors: Department of Biostatistics, The University of Kansas Medical Center, Kansas City, KS 66160, USA. hyeh@kumc.edu
authors: Hung-Wen
authors: HW
authors: Yeh
authors: Edward F
authors: EF
authors: Ellerbeck
authors: Jonathan D
authors: JD
authors: Mahnken
mesh_terms: D000328:Adult; D003131:Combined Modality Therapy; D003376:Counseling; D019468:Disease Management; D006801:Humans; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D008390:Markov Chains; D008875:Middle Aged; D009042:Motivation; D012424:Rural Population; D055502:Secondary Prevention; D020377:Self Efficacy; D017678:Sex Distribution; D012907:Smoking / Q000453:epidemiology / Q000628:therapy; D016540:Smoking Cessation / Q000523:psychology* / Q000706:statistics & numerical data; D000074606:Smoking Prevention; D012959:Socioeconomic Factors; D013269:Stochastic Processes; D011795:Surveys and Questionnaires; D014029:Tobacco Use Disorder / Q000453:epidemiology / Q000628:therapy*; D016896:Treatment Outcome