Occupational exposure to benzene, toluene, xylene and styrene and risk of prostate cancer in a population-based study
Bibliographic record
Abstract
OBJECTIVES: While several monocyclic aromatic hydrocarbons are classified as definite or possible carcinogens to humans, little data exist on their role in prostate cancer (PCa). We examined occupational exposure to benzene, toluene, xylene (BTX) and styrene and PCa risk in a population-based case-control study in Montreal, Canada. METHODS: Cases aged ≤75 years diagnosed with PCa in 2005-2009 (n=1920) and population controls frequency-matched on age (n=1989) provided detailed work histories. Experts evaluated the certainty, frequency and concentration of exposure to monocyclic aromatic hydrocarbons in each job lasting ≥2 years. Logistic regression estimated OR and 95% CIs for PCa risk, adjusting for potential confounders. RESULTS: Exposures to BTX were highly intercorrelated, except for durations of exposure at substantial levels. Ever exposure to any BTX was associated with overall PCa (OR 1.27, 95% CI 1.05 to 1.53), while the OR for styrene was 1.19. However, increases in risk were largely confined to low-grade tumours, with ORs of 1.33 (95%CI 1.08 to 1.64) and 1.41 (95% CI 0.85 to 2.31) for ever exposure to any BTX and styrene, respectively, and a duration response pattern for any BTX. Risks for low-grade tumours were elevated among men exposed ≥25 years at substantial levels of benzene (OR 2.32) and styrene (OR 2.44). Some cumulative exposure categories showed increased risks but without clear trends. CONCLUSION: Exposure to any BTX was associated with higher risks of overall PCa. Prolonged exposures at the substantial level to benzene and styrene increased risks of low-grade tumours. These novel findings were independent from PCa screening.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".