Occupational heat exposure and prostate cancer risk: a pooled analysis of case-control studies
Bibliographic record
Abstract
Background and aim: Heat exposures occur frequently in many indoor and outdoor occupations. In our previous work, we observed some evidence for a positive association of occupational heat exposure and breast cancer risk. Here we seek to examine potential associations with prostate cancer risk in a large multi-country study. Methods: We performed a pooled analysis of data from 3,175 histologically confirmed prostate cancer cases and 3,529 frequency-matched controls from studies in three different countries, Spain, France, and Canada. The Finnish job exposure matrix, FINJEM, was used to apply estimates of occupational heat exposure to the lifetime occupational history of participants. Three main exposure indices were used: ever vs. never exposed, lifetime cumulative exposure (heat stress years) and duration of exposure (years) with a lag period of 5 years. We estimated odds ratios (ORs) and 95% confidence intervals (CIs), using conditional logistic regression models stratified by 5-year age groups and study and adjusted for potential confounders. Results: A total of 32% of cases and 33% of controls were classified as being ever occupationally exposed to heat. Highest heat exposed occupations included ore and metal furnace operators, firefighters, and bakers. We found no evidence for an association of ever occupational heat exposure and prostate cancer risk (OR 0.92; 95% CI 0.83, 1.03). There were also no associations observed in the highest categories of lifetime cumulative exposure or duration, and there was no evidence for a trend. Results did not change when stratifying by Gleason scores. When analysing the Spanish case-control study separately using a Spanish job exposure matrix developed for local working conditions, some odds ratios were elevated, though results were imprecise. Conclusions: Findings from this pooled study have provided no strong evidence for an association between occupational heat exposure and prostate cancer risk. Keywords: prostate cancer, occupational exposures, heat, pooled analysis
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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 | 0.023 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.019 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".