Abstract
The relationship between smoking and lung cancer is well established and cohort studies provide estimates of risk for individual cohorts. While population trends are qualitatively consistent with smoking trends, the rates do not agree well with results from analytical studies. Four carcinogenesis models for the effect of smoking on lung cancer mortality were used to estimate lung cancer mortality rates for U.S. males: two-stage clonal expansion and multistage models using parameters estimated from two Cancer Prevention Studies (CPS I and CPS II). Calibration was essential to adjust for both shift and temporal trend. The age-period-cohort model was used for calibration. Overall, models using parameters derived from CPS I performed best, and the corresponding two-stage clonal expansion model was best overall. However, temporal calibration did significantly improve agreement with the population rates, especially the effect of age and cohort.