Occupational exposure to asbestos and lung cancer in men: evidence from a population-based case-control study in eight Canadian provinces
Bibliographic record
Abstract
BACKGROUND: Asbestos is classified as a human carcinogen, and studies have consistently demonstrated that workplace exposure to it increases the risk of developing lung cancer. Few studies have evaluated risks in population-based settings where there is a greater variety in the types of occupations, and exposures. METHODS: This was a population based case-control study with 1,681 incident cases of lung cancer, and 2,053 controls recruited from 8 Canadian provinces between 1994 and 1997. Self-reported questionnaires were used to elicit a lifetime occupational history, including general tasks, and information for other risk factors. Occupational hygienists, who were blinded to case-control status, assigned asbestos exposures to each job on the basis of (i) concentration (low, medium, high), (ii) frequency (<5%, 5-30%, and >30% of the time in a normal work week), and (iii) reliability (possible, probable, definite). Logistic regression was used to estimate odds ratios (ORs) and their corresponding 95% confidence intervals (CI). RESULTS: Those occupationally exposed to (i) low, and (ii) medium or high concentrations of asbestos had ORs for lung cancer of 1.17 (95% CI=0.92 - 1.50) and 2.16 (95% CI=1.21-3.88), respectively, relative to those who were unexposed. Medium or high exposure to asbestos roughly doubled the risk for lung cancer across all three smoking pack-year categories. The joint relationship between smoking and asbestos was consistent with a multiplicative risk model. CONCLUSIONS: Our findings provide further evidence that exposure to asbestos has contributed to an increased risk of lung cancer in Canadian workplaces, and suggests that nearly 3% of lung cancers among Canadian men are caused by occupational exposure to asbestos.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".