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Table 2 Data parameters in model

From: Economic evaluation of an exercise-counselling intervention to enhance smoking cessation outcomes: The Fit2Quit trial

Model parameter Mean (se) Distribution Source
Male Female   
 24-week point prevalence rates
 a) intervention – adherent group (n = 236) 35.2% (4.7%) 29.8% (4.0%) Beta Trial
 b) usual care 24.2% (3.0%) 19.7% (2.5%) Beta Trial
 Relapse rate from 24 weeks (end of trial) to 12 months 21% a   [25]
 Relapse rates after 12 months 30% cumulative a   [26]
Lung cancer
 Annual incidence eg 0.00180b eg 0.00165b Beta [27]
 Proportion – early stage lung cancer (I&II) 20% a   [14]
 Proportion – adv stage lung cancer (III&IV) 80% a   [14]
 Relative risk of lung cancer in ex-smokers vs. general population eg 1.771 a   [14]
  15 years after quittingb    
 Annual incidence eg 0.03095b eg 0.01843b Beta [28]
 Relative risk of CVD in smokers vs. general population 1.42 (0.031) a LogNormal [29]
 Relative risk of CVD in ex-smokers vs. smokers 0.71 (0.036) a LogNormal [29]
 a) pre-hospital death given a CVD event 18.1% a   [30]
 b) post-hospital death given a CVD event (≤28 days) 7.1% a   [30]
 c) background mortality (annual) eg 0.01071b eg 0.00715b Beta [31]
Utility scores
 a) well (no lung cancer or CVD)
  baseline 0.800 a   Trial
  continue smoking after end of trial 0.800 a   Assumption
  abstain from smoking at end of trial 0.830 a   [11]
 b) early stage lung cancer 0.73 (0.020) a Beta [14]
  adv stage lung cancer 0.56 (0.043) a Beta [9]
 c) weighted average CVD 0.611    [9, 10]
Excess health system costs (NZ$)
 a) lung cancer, first year of diagnosis eg 23,970b eg 22,256b Gamma [13]
  lung cancer, subsequent annual costs before death eg 5,375b eg 4,341b Gamma [13]
  lung cancer, last six months before cancer death eg 16,615b eg 20,300b Gamma [13]
 b) CVD, first year of diagnosis if hospitalised eg 11,327b eg 10,189b Gamma [13]
  CVD, last six months before CVD death eg 17,573b eg 11,048b Gamma [13]
  1. NZ$1 = US$0.68 = €0.53
  2. aSame value for both sexes
  3. bAge/time-dependent values used in tables. If no other details are given, then the example is for a 65-year-old individual