A flexible modeling approach to estimating the component effects of smoking behavior on lung cancer.

OBJECTIVE: Despite the established causal association between cigarette smoking and lung cancer, the relative contributions of age started, duration, years since quitting, and daily amount smoked have not been well characterized. We estimated the contribution of each of these aspects of smoking behavior. STUDY DESIGN AND SETTING: A case-control study was conducted in Montreal on the etiology of lung cancer. There were 640 cases and 938 control subjects for whom lifetime smoking histories were collected. We used generalized additive models, incorporating cubic smoothing splines to model nonlinear effects of various smoking variables. We adopted a multistep approach to deal with the multicollinearity among time-related variables. RESULTS: The main findings are that (1) risk increases independently by daily amount and by duration; (2) among current smokers, lung cancer risk doubles for every 10 cigarettes per day up to 30 to 40 cigarettes per day and tails off thereafter; (3) among ex-smokers, the odds ratio decreases with increasing time since quitting, the rate of decrease being sharper among heavy smokers than among light smokers; and (4) absolute risks demonstrate the dramatic public health benefits of long-term smoking cessation. CONCLUSION: Our results reinforce some previous findings on this issue.