Occupational Benzene Exposure and Hepatobiliary and Pancreatic Cancers: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Evidence on the association between benzene and hepatobiliary and pancreatic cancers is scarce. Hence, we aimed to summarize current literature on the association between occupational benzene exposure and these cancers. We conducted a systematic review and meta-analysis by searching Pubmed, Embase, and Scopus through April 2024 to identify cohort and nested case-control studies. We evaluated study quality with the Newcastle–Ottawa Scale and estimated pooled relative risks (RRs) and 95% confidence intervals (CIs) using Paule–Mandel method. Twenty-nine studies were included in the meta-analysis. Occupational benzene exposure was associated with hepatobiliary cancer incidence (RR: 1.14; 95% CI: 1.04-1.24; I 2 = 0.0%, p = 0.707), but not with mortality (RR: 0.89; 95% CI: 0.69-1.15; I 2 = 66.7%, p < 0.001). Pooled RRs for incidence and mortality were 1.13 (95% CI: 0.93-1.36; I 2 = 0.0%, p = 0.729) and 0.79 (95% CI: 0.65-0.96; I 2 = 0.0%, p = 0.539) for liver cancer, 1.16 (95 % CI: 0.73-1.82; I 2 = 34.6%, p = 0.164) and 2.00 (95% CI: 0.96-4.19; I 2 = 67.7%, p = 0.015) for gallbladder cancer, and 0.95 (95% CI: 0.78-1.16; I 2 = 13.5%, p = 0.316) and 1.00 (95% CI: 0.87-1.14; I 2 = 29.6%, p = 0.100) for pancreatic cancer, respectively. Occupational benzene exposure might be associated with hepatobiliary cancer. Further studies, with detailed exposure assessment and control for potential confounders, are needed to clarify this relationship.
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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 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.040 |
| Bibliometrics | 0.008 | 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) | 0.003 | 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".