Association of allergic diseases and epilepsy with risk of glioma, meningioma and acoustic neuroma: results from the INTERPHONE international case–control study
Bibliographic record
Abstract
We investigated the association of allergic diseases and epilepsy with risk of brain tumours, in Interphone, a 13-country case-control study. Data were obtained from 2693 glioma cases, 2396 meningioma cases, and 1102 acoustic neuroma cases and their 6321 controls. Conditional logistic regression models were used to estimate pooled odds ratios (ORs) and their respective 95% confidence intervals (CIs), adjusted for education and time at interview. Reduced ORs were observed for glioma in relation to physician-diagnosed asthma (OR = 0.73; CI 0.58-0.92), hay fever (OR 0.72; CI 0.61-0.86), and eczema (OR 0.78, CI 0.64-0.94), but not for meningioma or acoustic neuroma. Previous diagnosis of epilepsy was associated with an increased OR for glioma (2.94; CI 1.87-4.63) and for meningioma (2.12; CI 1.27-3.56), but not for acoustic neuroma. This large-scale case-control study adds to the growing evidence that people with allergies have a lower risk of developing glioma, but not meningioma or acoustic neuroma. It also supports clinical observations of epilepsy prior to the diagnosis of glioma and meningioma.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".