Smoking cessation by combined medication and counseling in lung cancer patients – effectiveness in a high prevalence real life setting

Study type

• Study topic:
  Human medicinal product
• Study type:
  Non-interventional study
• Scope of the study:
  Effectiveness study (incl. comparative)
• Data collection methods:
  Primary data collection

Non-interventional study

• Non-interventional study design:
  Other
• Non-interventional study design, other:
  Prospective, observational, non-comparative trial

Study drug and medical condition

• Medicinal product name, other:
  Nicotinell
• Anatomical Therapeutic Chemical (ATC) code:
  (N07BA03) varenicline

  varenicline

Population studied

• Short description of the study population:
  Patients with verified diagnosis of lung cancer.; Inclusion criteria were as follows:; - Newly diagnosed lung cancer of all stages within 14 day of study enrollment; - Active smoking or smoking up to 4 weeks before study enrollment; - Age > 18 years
• Age groups:
  • Adults (18 to < 46 years)
  • Adults (46 to < 65 years)
  • Adults (65 to < 75 years)
  • Adults (75 to < 85 years)
  • Adults (85 years and over)
• Special population of interest:
  Hepatic impaired

  Immunocompromised

  Renal impaired
• Estimated number of subjects:
  80

Study design details

• Main study objective:
  To show that smoking cessation can be effectively and succesfully implemented in treatmend of patients with newly diagnosed lung cancer.
• Outcomes:
  Main abstinace rate at week 12 after smoking cessation, verified via measurement of exhaled carbon monoxide. Secondary endpoints will be 26-week abstinace rate as well as quality of life and depression.
• Data analysis plan:
  Descriptive statistics of baseline variables will be generated. Abstinence rate at week 12 will be estimated and reported with exact 95% confidence intervals (Clopper/Pearson 1934). The analysis of the secondary endpoint 26-week abstinence rate will follow the same lines. The impact of depression on 12-week abstinence rates will be explored by calculating various trajectories of the longitudinal depression score, which will be included as independent variables in logistic regression models with 12-week abstinence rate as dependent variable. Similarly the association between depression and withdrawal symptoms will be investigated through linear models. Standard diagnostics will be applied to check adequate model fit. Regression coefficients will be reported with 95% confidence intervals and p-values testing the null hypothesis of no effect.