8287735 Independent exposure-response analysis of five lung carcinogens and lung cancer risk in a cohort of 2.2 million Ontario workers
Bibliographic record
Abstract
Objectives Several occupational exposures cause lung cancer, but few studies have examined sex-specific differences. We aim to investigate the independent exposure response effects of exposure to five carcinogens— asbestos, chromium VI, nickel, polycyclic aromatic hydrocarbons (PAHs), and silica — on lung cancer risk. Methods A prospective open cohort of Ontario workers was followed for lung cancer diagnoses from 1983 to 2019 in the Ontario Cancer Registry. Exposures were assessed using the Canadian job-exposure matrix, including measures for exposure status (exposed/non-exposed), intensity of exposure (low, medium/high) and frequency of exposure (<8h/week, 8-40h/week, 40+h/week) for each carcinogen. Cox proportional hazards models estimated independent associations of carcinogen exposure and lung cancer risk overall, by sex, and by subtype. Models were adjusted for age, sex, and birth-year. Results Overall, 36,125 lung cancer cases were identified among 2,223,408 workers. Exposed workers had significantly higher lung cancer risks for all carcinogens (HR_chomium VI=1.12, 95% CI:1.06–1.18; HR_nickel=1.05, 95% CI: 1.01–1.10; HR_PAHs=1.18, 95% CI: 1.16–1.21; HR_silica=1.10, 95% CI: 1.06–1.14) except asbestos (HR_asbestos=1.00, 95% CI: 0.97–1.03). Females had higher risks than males for all carcinogens, ranging from 3% (Silica: HR_females=1.12, 95% CI: 0.96–1.31; HR_males=1.09, 95% CI: 1.05–1.13) to 28% (Nickel: HR_females=1.31, 1.10–1.56; HR_males=1.03, 95% CI: 0.99–1.08). Positive exposure-response relationships for exposure frequency and intensity were observed for all carcinogens, with stronger associations among females. Results were similar for adenocarcinoma, squamous cell, and small cell lung cancer. Conclusion The independent findings are consistent with previous research and highlight potential sex differences in lung cancer risk due to occupational exposure to five carcinogens.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".