Occupational benzene exposure and colorectal cancer: A systematic review and meta-analysis
Bibliographic record
Abstract
Recent reports suggest that benzene exposure may be associated with solid cancers, such as lung and bladder cancers. Instead, evidence on the association between benzene and colorectal cancer (CRC) is sparse. Thus, we aimed to summarize current literature on the association between occupational benzene exposure and CRC. We searched Pubmed, Embase (through Ovid), and Scopus to retrieve cohort and nested case-control studies on the association between occupational benzene exposure and solid cancers. The search was initially completed in December 2022 and later updated in April 2024. We assessed quality of included studies using a modified version of Newcastle-Ottawa Scale. We computed pooled relative risks (RRs) and corresponding 95% confidence intervals (CIs) of CRC according to occupational benzene exposure, using the Paule-Mandel method. Twenty-eight studies were included in the meta-analysis. Most of them were conducted in Europe or North America (82.1%) and were industry-based (89.3%). Pooled RRs comparing workers exposed to benzene with those who were unexposed for incidence and mortality were 1.10 (95% CI: 1.06, 1.15) and 1.04 (95% CI: 0.97, 1.11) for CRC, 1.12 (95% CI: 1.01, 1.24) and 1.08 (95% CI: 0.99, 1.19) for colon cancer, and 1.04 (95% CI: 0.94, 1.14) and 1.05 (95% CI: 0.92, 1.19) for rectal cancer, respectively. Only one study supported the occurrence of a dose-response relationship between occupational benzene exposure and CRC, while others found no increase in risk according to dose of exposure or duration of employment. Our findings suggest that occupational benzene exposure may be associated with CRC. Further research with detailed assessment of individual-level exposure is warranted to confirm our results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".