Benzene exposure increases the risk of non-Hodgkin’s lymphoma: a systematic review and meta-analysis of observational studies
Bibliographic record
Abstract
Background: Although there is sufficient evidence that benzene exposure increases the risk of leukemia, whether benzene exposure increases the risk of non-Hodgkin’s lymphoma (NHL) remains controversial. The method of meta-analysis can reduce the uncertainty in evidence-based medicine (EBM) evidence decision-making caused by the bias between studies by systematically searching, evaluating, and combining all relevant literatures. Methods: PubMed, Embase, ScienceDirect and other databases were searched according to the population exposure comparison outcome principles: whether the general population exposed to benzene has a higher risk of developing NHL than the population without benzene exposure. Two independent researchers extracted the main endpoint indicators from the included literature, including the odds ratio (OR) or relative risk (RR) of benzene exposure to the risk of NHL. Risk of bias was assessed for each study using the Newcastle-Ottawa scale (NOS). Heterogeneity between studies was evaluated using the Cochrane Q test and I2 statistics, and combined risk estimates were calculated with the random-effects and fixed-effect models. Meanwhile, source of heterogeneity was evaluated by subgroup analysis. Publication bias was evaluated by funnel plot and Egger’s test, and the stability of results was evaluated by sensitivity analysis. All results with P<0.05 were considered statistically significant. Results: A total of 14 articles were included in this study for meta-analysis, including 9 cohort studies and 5 case-control studies with NOS scores between 5 and 9. Four of the articles were at low risk of bias, and 10 were at moderate risk of bias. Of 492,719 people with benzene exposure, there were 1,994 cases of NHL. The OR of NHL in the benzene-exposed population compared with nonexposed population was 1.23 (P=0.03), with moderate heterogeneity (I2=63.47%). People with high exposure to benzene showed a higher risk of NHL (OR =1.81) and there was a low degree of heterogeneity (I2=27.56%). The risk of benzene exposure in China (OR =2.48) was higher than that in Europe (OR =1.19), the United Kingdom (OR =1.07), and the United States (OR =1.24). Conclusions: Benzene exposure was positively correlated with the incidence of NHL.
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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 | 0.021 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.042 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".