Occupational Benzene Exposure and Risk of Male Genital Cancers: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
BACKGROUND: Benzene is an established Group 1 carcinogen due to its leukemogenic properties. Recent studies suggest that occupational benzene exposure may be associated with solid cancers. However, little is known about its association with male genital cancers. We aimed to summarize the scientific evidence on occupational benzene exposure and the risk of male genital cancers. METHODS: We searched for relevant articles in three electronic databases. Methodological quality and the certainty of evidence were evaluated using a modified version of the Newcastle-Ottawa Scale (NOS) and Grading of Recommendations Assessment, Development and Evaluation (GRADE) assessment tool. We performed pooled and stratified meta-analyses, as well as meta-regressions to explore potential sources of heterogeneity. RESULTS: Thirty-one publications were included. Pooled results of incidence and mortality for prostate and testis cancer did not indicate a significant association with occupational benzene exposure. A borderline association was found for the incidence of prostate cancer (standardized incidence ratio (SIR): 1.07, 95% CI 0.97-1.19). Subgroup analyses stratified by study design and study quality revealed significant heterogeneity, with case-control (relative risk (RR): 1.19, 95% CI 1.04-1.36) and high-quality studies (RR: 1.22, 95% CI 1.14-1.31) showing an increased risk. Both NOS and GRADE assessments yielded mostly low to very low-quality results. CONCLUSIONS: This review provides no clear evidence of an association between occupational exposure to benzene and the risk of male genital cancers. Subgroup analysis suggests an increased risk of prostate cancer in high-quality studies. Nevertheless, it is important to acknowledge the methodological limitations of the available studies. Further analyses including methodologically sound studies are needed to corroborate these 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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.032 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| 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".