Prostate Cancer Incidence and Mortality Linked to Metalworking Fluid Exposure: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction: Prostate cancer is a significant health concern, and occupational exposures, including metalworking fluid (MWF) exposure, have been implicated as potential risk factors. This protocol outlines a systematic review and meta-analysis methodology to investigate the association between MWF exposure and prostate cancer risk among male workers. Methods: Eligible studies include cohort, case-control, and cross-sectional studies published until between 1990 and 2023 focusing on MWF exposure and prostate cancer risk in male workers. Two independent reviewers will screen studies, extract data using a standardized form, conduct a meta-analysis using random-effects models, and assess study quality using the Newcastle-Ottawa Scale. Heterogeneity will be assessed, and sensitivity analyses will be conducted to explore sources of bias. Results: Anticipated outcomes include a comprehensive list of eligible studies, a synthesized analysis using random-effects meta-analysis models to estimate the association between MWF exposure and prostate cancer risk, and a quality assessment report of included studies. Subgroup analyses based on MWF type, exposure duration, and study design will be performed to explore heterogeneity. Conclusion: This systematic review and meta-analysis protocol aim to provide robust evidence on the association between MWF exposure and prostate cancer risk among male workers. The anticipated findings will have implications for occupational health practices and may guide future research and intervention strategies.
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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 | 0.015 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.033 |
| Bibliometrics | 0.009 | 0.009 |
| 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) | 0.004 | 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".