Night work and prostate cancer risk: results from the EPICAP Study
Bibliographic record
Abstract
OBJECTIVE: To investigate the role of night work in prostate cancer based on data from the EPICAP Study. METHODS: EPICAP is a French population-based case-control study including 818 incident prostate cancer cases and 875 frequency-matched controls that have been interviewed face to face on several potential risk factors including lifetime occupational history. Detailed information on work schedules for each job (permanent or rotating night work, duration, total number of nights, length of the shift, number of consecutive nights) as well as sleep duration and chronotype, was gathered. Prostate cancer aggressiveness was assessed by Gleason Score. RESULTS: Night work was not associated with prostate cancer, whatever the aggressiveness of prostate cancer, while we observed an overall increased risk among men with an evening chronotype (OR=1.83, 95% CI 1.05 to 3.19). A long duration of at least 20 years of permanent night work was associated with aggressive prostate cancer (OR=1.76, 95% CI 1.13 to 2.75), even more pronounced in combination with a shift length >10 hours or ≥ 6 consecutive nights (OR=4.64, 95% CI 1.78 to 12.13; OR=2.43, 95% CI 1.32 to 4.47, respectively). CONCLUSION: Overall, ever night work, either permanent or rotating, was not associated to prostate cancer. Nevertheless, our results suggest that a long duration of permanent night work in combination with a long shift length or at least six consecutive nights may be associated with prostate cancer, particularly with aggressive prostate cancer. Further studies are needed to confirm those 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".