Lung cancer mortality attributable to smoking: a multi-scenario analysis with variable lag periods

The estimation of smoking-attributable mortality (SAM) is subject to the acceptance of different assumptions that may influence the estimates. We aimed to assess lung cancer mortality attributable to smoking by using both a prevalence-independent method (PIM) and a prevalence-dependent method (PDM) with different lags between exposure (smoking prevalence) and outcome (lung cancer mortality).

We estimated the population attributable fractions (PAF) and the lung cancer SAM by sex and age group (35-64, 65-84 years), year-by-year from 2011 to 2020, in four scenarios in Spain. In three of these scenarios, a PDM was applied using different lags: no lag, a 15-year lag and a 20-year lag. In the fourth scenario, a PIM was applied.

In the period 2011-2020 in Spain, the SAM was higher when the 20-year lag PDM was considered (173,526 deaths) and lower when no lag PDM or a PIM was applied (161,249 and 157,390 deaths, respectively). In men, the PAFs were similar between the no lag PDM and the PIM (86.7 % and 87.3 %, respectively). However, when a PDM 15-year or 20-year lag was considered, the PAF increased to 91.0 % and 92.3 %, respectively. In women, the lowest PAF was obtained with the PIM (57.3 %), and the highest with the PDM 20-year lag (79.4 %).

SAM estimates differ depending on the methods and lags used. Applying a 15-year or 20-year lag PDM yields higher SAM estimates than when no lag PDM or a PIM is used. Therefore, when feasible, smoking prevalence data that incorporate a lag of 15 or 20 years between exposure and result should be used for accurate estimates.