O-303 The role of occupational exposures in lung cancer risk among women: preliminary results from a pooled case-control study of lung cancer
Bibliographic record
Abstract
Introduction Lung cancer is the most common cause of cancer death among women. However, little is known regarding occupational risk factors for lung cancer in women. Objective To investigate possible associations between selected occupational agents and lung cancer risk among women. Methods We pooled data from ten case-control studies of lung cancer with detailed lifetime occupational and smoking history. The current analysis was restricted to working women, including 3040 cases and 4186 controls. To assess occupational exposure, we used the Canadian Job-Exposure Matrix (CANJEM). Linking participants’ jobs to the CANJEM allows the estimation of probability, and frequency of exposure to a list of 258 agents. This analysis was restricted to 36 most prevalent occupational agents in our sample of women. The association between lung cancer risk and lifetime ever exposure, duration of exposure, and cumulative exposure for each agent was estimated in separate logistic regression models, adjusted for smoking and other selected covariates. Results Most agents we examined were not associated with lung cancer. We observed an increased risk of lung cancer among women occupationally exposed to cooking fumes for over 10 years (OR(95%CI)=1.73(1.09–2.82)). Statistically significant decreased risks of lung cancer were observed among women exposed to various textile fibres, especially among long-duration workers. The results regarding the various textile agents have not been mutually controlled yet. When restricting to never smokers, increased risks of lung cancer were observed among women exposed to metallic dust, isopropanol, and aliphatic alcohols, with OR point estimates for ever exposure ranging from 1.5 to 1.7. Conclusion Our preliminary results indicate that occupational exposure to cooking fumes is associated with an increased lung cancer risk in women, while exposures to various textile fibres seem to be associated with a decreased lung cancer risk.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".