Exploration of occupations as risk factors for lung cancer in hierarchical and penalization penalized regression models accounting for multiple known exposures
Year: 2022
Type: conference-abstract
Abstract: Background and aim: Traditional occupational epidemiological analysis typically emphasize on disease risks associated with specific single exposures or single occupations. We used hierarchical and regularization models to explore occupational risks at the job-title level associated with lung cancer while accounting for exposures to multiple known lung carcinogens. Methods: We pooled lung cancer case-control study subjects from 14 European and Canadian studies. Associations between ever employment in 1,288 five-digit ISCO-68 occupations and lung cancer were screened using two approaches: Bayesian hierarchical and LASSO penalized regressions. Both modeling approaches account for age, smoking, sex, study, and fully quantitative exposures to six known occupational lung carcinogens: asbestos, chromium, diesel engine exhaust, nickel, PAHs, and silica. False positive findings in the Bayesian hierarchical and LASSO models were controlled using horseshoe priors and stability selection, respectively. Lung cancer odds ratios for selected occupations were estimated using unconditional logistic regression model with identical covariates. Results: Our final analyses included 16,901 lung cancer cases and 20,965 controls. There were notable overlaps in jobs selected by the hierarchical and penalization modeling approaches. Occupations selected by both modeling approaches with positive associations with lung cancer after controlling for known exposures include carpenters (OR: 1.77; 95CI: 1.36, 2.33) and construction bricklayers (OR: 1.40; 95CI: 1.17, 1.67). Similarly selected occupations but with negative associations with lung cancer include secondary school teachers (OR: 0.36; 95CI: 0.23, 0.55), production managers (OR: 0.65; 95CI: 0.53, 0.79), and government executive officials (OR: 0.7; 95% CI: 0.61, 0.79). Conclusion: We demonstrated viable agnostic approaches in identifying employment risk factors for lung cancer. Future work involves investigations of factors that contribute to the observed elevated or lower cancer risks, which may involve gaps in current exposure assessment and modeling framework, and/or exposures to other lung carcinogens yet to be elucidated.
Source: ISEE Conference Abstracts
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4320066326