Meta‐Analysis of the Relationship Between Occupational/Environmental Exposure to Wood Dust and Laryngeal Cancer
Bibliographic record
Abstract
ABSTRACT Objective Wood dust is a human carcinogen. However, studies examining the relationship between wood dust exposure and laryngeal cancer have yielded inconsistent findings. Therefore, we systematically reviewed relevant studies examining the relationship between wood dust exposure and laryngeal cancer development, followed by a meta‐analysis. Methods Publications in the following databases were searched: PubMed, Medline, Embase, Cochrane Library, and China National Knowledge Infrastructure (CNKI). The Newcastle–Ottawa scale was used to evaluate the study quality. A random‐effects model was used for the meta‐analysis. Results Eighteen case–control studies and one cohort study, involving a total of 4426 patients with laryngeal cancer and 319,129 control participants, were identified. The association between occupational/environmental exposure to wood dust and laryngeal cancer, if any, was unclear (adjusted combined OR: 1.11; 95% CI: 0.94–1.31). However, subgroup analyses according to the number of cases, geographic region, publication year, and follow‐up duration revealed correlations between wood dust exposure correlated and laryngeal cancer, as follows: number of cases > 200 (OR: 1.14; 95% CI: 1.01–1.25 [n = 10]); studies conducted in the US (OR: 1.21; 95% CI: 1.07–1.37 [n = 5]); follow‐up time > 5 years (OR: 1.19; 95% CI: 1.07–1.32 [n = 10]); and publication after the year 2000 (OR: 1.15; 95% CI: 1.04–1.28 [n = 8]). A high heterogeneity in the results was observed (I2 = 42.5%, p = 0.024). The results were stable, and no publication bias existed, according to sensitivity analysis. Conclusions This meta‐analysis suggests that wood dust exposure is associated with laryngeal cancer. Additional large‐scale studies are warranted to clarify the relationship between wood dust exposure and laryngeal cancer.
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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 | 0.016 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.051 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".