Assessment of the effect of occupational exposure to formaldehyde on the risk of lung cancer in two Canadian population-based case–control studies
Bibliographic record
Abstract
OBJECTIVE: This study aimed to explore the possible association between formaldehyde exposure and lung cancer risk. METHODS: Data were collected in two population-based case-control studies conducted in Montreal, Canada. Cases were individuals diagnosed with incident, histologically-confirmed lung cancer. Controls were randomly selected from electoral lists and frequency-matched to cases by age, sex, and electoral district of residence. Interviews for the two studies were conducted in 1979-1986 and 1996-2002, using a virtually identical questionnaire to obtain lifetime occupational and smoking history and several lifestyle covariates. Experts reviewed the detailed work history for each participant to assess exposure to several occupational agents, including formaldehyde. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (95% CI) for the associations between several metrics of formaldehyde exposure and lung cancer, adjusting for smoking and occupational and sociodemographic factors. RESULTS: In all, 2060 lung cancer cases and 2046 population controls were interviewed and assessed for exposure. About 25% of subjects had ever been occupationally exposed to formaldehyde. The adjusted OR for lung cancer was 1.06 (95% CI 0.89-1.27) comparing ever versus never exposure to formaldehyde. Analyses for age at first exposure, average, and peak intensity of exposure also suggested an absence of association between formaldehyde exposure and lung cancer risk. Results did not vary by sex, lifetime smoking intensity, or histological subtype. CONCLUSIONS: No marked increases in lung cancer risk related to workplace formaldehyde exposure were observed. Study participants were mainly exposed at low concentration levels, which should be considered in the interpretation of our findings.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".