Shift Work and Prostate Cancer: An Updated Systematic Review and Meta-Analysis
Bibliographic record
Abstract
The International Agency of Research in Cancer (IARC) has recently confirmed shift work as a type 2A carcinogen. The results presented in published epidemiological studies regarding prostate cancer are inconsistent and the association remains controversial. The aims of this study were: (a) to investigate the possible association between shift work and prostate cancer incidence, identifying possible sources of heterogeneity; and (b) to analyze the potential effect of publication bias. A search for cohort and case-control studies published from January 1980 to November 2019 was conducted. The quality of the articles was assessed using the Newcastle–Ottawa Scale. Pooled OR were calculated using random-effects models. Heterogeneity was evaluated using Cochran’s Q test and data were stratified by potential sources of heterogeneity. Publication bias was analyzed. Eighteen studies were included. No association was found between rotating/night-shift work and prostate cancer, pooled OR 1.07 (95%CI 0.99 to 1.15), I2 = 45.7%, p = 0.016. Heterogeneity was eliminated when only cohort studies (pooled OR 1.03; 95%CI 0.96 to 1.10; I2 = 18.9%, p = 0.264) or high-quality studies (pooled OR 0.99; 95%CI 0.89 to 1.08; I2 = 0.0%, p = 0.571) were considered. A publication bias was detected. An association between shift work and prostate cancer cannot be confirmed with the available current data. Future analytical studies assessing more objective homogeneous exposure variables still seem necessary.
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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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.034 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".