Occupational risk factors for low grade and high grade glioma: Results from an international case control study of adult brain tumours
Bibliographic record
Abstract
The majority of suspected occupational risk factors for adult brain tumours have yet to be confirmed as etiologically relevant. Within an international case-control study on brain tumours, lifelong occupational histories and information on exposures to specific substances were obtained by direct interviews to further investigate occupational risk factors for glioma. This is one of the largest studies of brain tumours in adults, including 1,178 cases and 1987 population controls from 8 collaborating study centres matched for age, gender and centre. All occupational information, was aggregated into 16 occupational categories. In a pooled analysis, odds ratios (OR), adjusted for education, were estimated separately for men and women and for high-grade glioma (HGG) and low-grade glioma (LGG), focusing especially on 6 categories defined a priori: agricultural, chemical, construction, metal, electrical/electronic and transport. For men, an elevated OR of glioma associated with the category "metal" (OR = 1.24, 95% CI 0.96-1.62) was seen, which appeared to be largely accounted for by LGG (OR = 1.59, 95% CI 1.00-2.52). For the other 5 occupational categories, no elevated risks for glioma were observed. For women the only noteworthy observation for the 6 a priori categories was an inverse association with the "agriculture" category (OR = 0.60, 95% CI 0.36-0.99). Apart from the 6 major categories, women working in food production or food processing (category "food") showed an increased OR of 1.95 (95% CI 1.04-3.68). None of the 20 substance groups was positively associated with glioma risk. Although some other point estimates were elevated, they lacked statistical significance. The results do not provide evidence of a strong association between occupational exposures and glioma development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".