8292418 Lung cancer risk among 2.2 million Ontario workers: joint effects of co-exposure to five occupational carcinogens by sex

<h3>Objectives</h3> Several occupational exposures cause lung cancer, but few studies have examined co-exposure effects. We aim to investigate the joint effects of exposure to five carcinogens— asbestos, chromium VI, nickel, polycyclic aromatic hydrocarbons (PAHs) and benzo-a-pyrene (BaP) as a surrogate of PAH exposure, and silica— on lung cancer risk. <h3>Methods</h3> Lung cancer cases were identified from the Ontario Cancer Registry between 1983 to 2019 from a large cohort of Ontario workers. Exposure status (exposed/non-exposed) was assigned to workers based on their occupation using the Canadian job-exposure matrix for each carcinogen. Cox proportional hazards models estimated associations of carcinogen exposure on lung cancer risk overall, by sex, and by subtype, controlling for age, sex, and birth-year. Joint effects were analyzed using pairwise interaction models assessed on multiplicative and additive scales using the relative excess risk due to interaction (RERI). <h3>Results</h3> Overall, 36,125 lung cancer cases were identified among 2,223,408 workers. In preliminary analysis, joint effects of co-exposure to asbestos/silica (RERI= 0.27, 95% CI: 0.15, 0.39), BaP/silica (RERI=0.28, 95% CI: 0.17, 0.39), PAHS/silica (RERI=0.14, 95% CI: 0.05, 0.23), and chromium/BaP (RERI= 0.20, 95% CI: 0.01, 0.42) were more than additive. Conversely, joint effects of asbestos/PAHs (RERI: -0.44, 95% CI: -0.68, -0.24), BaP/nickel (RERI= -0.11, 95% CI: -0.21, -0.01), and chromium/PAHs (RERI=-0.38, 95% CI: -0.60, -0.18) were less than additive. The remaining pairwise joint effects did not significantly depart from additivity. The pattern of results was similar among male workers, but no pairwise joint effects significantly departed from additivity for females. Differences by lung cancer sub-type and additional analyses to follow. <h3>Conclusion</h3> Significant interaction effects were observed. Ongoing joint effects analysis may help identify high-risk occupations/industries by discovering the most impactful exposure combinations.