Age-period-cohort analysis of Swiss lung cancer mortality trends since 1969, with prediction to 2041.

AIMS: Using more than five decades of national data, we examine how age, period and cohort factors influence lung cancer mortality in Switzerland, and forecast future death counts to the early 2040s.

METHODS

Lung cancer deaths were extracted from Swiss vital statistics. We applied age-period-cohort (APC) modelling to lung cancer mortality rates using substantiated assumptions about the age-mortality relationship as model constraints. To account for the uncertainty in the age-mortality relationship, boundary constraints were applied to the line of APC solutions, yielding a range of plausible results. In an alternative model, we replaced the cohort terms with smoking prevalence estimates from Swiss health surveys, enabling unconstrained modelling of age and period effects. Predictions are based on modelled age trends, and linearly extrapolated period and cohort trends.

RESULTS

Plausible age, period and cohort effects indicated that age-specific mortality risks decline at the oldest ages, that period effects were minimal, while cohort effects showed distinct peak risks for men born around 1909 and women born around 1954. Among women, birth cohorts with the highest mortality closely aligned with those exhibiting the highest smoking prevalence. The models predicted a decline in the number of lung cancer deaths among men beginning in the mid-2020s, and among women from the mid-2030s onwards.

CONCLUSIONS

This population-based analysis of lung cancer mortality not only highlights declining mortality rates in men of all ages, but reveals an emerging downward trend among younger women. We predict that the total number of lung cancer deaths in women will begin to decrease by the mid-2030s.