EPID-12. DEMOGRAPHICS AND LIFESTYLE FACTORS IN GLIOMA RISK: A REPORT FROM THE GLIOMA INTERNATIONAL CASE-CONTROL STUDY
Bibliographic record
Abstract
Although previous studies have examined the role of demographic and lifestyle factors in glioma etiology, there are few established associations between such factors and glioma risk. The incidence of glioma is 2-3 times higher among non-Hispanic whites compared to blacks, Asians, or other racial/ethnic groups, but the reasons behind this remain unclear. As one of the largest glioma study populations available, the Glioma International Case-Control Study (GICC) provides an unprecedented opportunity to explore the associations between glioma risk and a number of lifestyle and demographic factors, stratified by race/ethnicity. The GICC is a 14-site consortium with data on 4533 cases and 4171 controls collected from five countries. Using these data, we examined following exposures of interest: birth order, family history of glioma, birth season, dexterity, “usual adult” BMI, physical activity levels, smoking history, and alcohol consumption. We calculated age- and sex-adjusted meta-analysis ORs (mOR), using two-stage random-effects restricted maximum likelihood modeling. In our case-case comparisons, we found that there was a preponderance of younger cases among racial/ethnic minorities compared to non-Hispanic whites, and this trend persisted even among glioblastoma cases. With regard to family history, a positive family history of glioma increased glioma risk across all races/ethnicities, though not always significantly. By contrast, the association between body mass index (BMI) and glioma risk was not consistent across all racial/ethnic groups. Among African-American cases and controls, being overweight was associated with a significantly increased glioma risk compared to being normal/underweight (pOR: 2.36, 95% CI: 1.09-5.10); yet among the other races/ethnicities, being overweight was not significantly associated with glioma risk. Overall, this study adds new information to the literature on whether potential associations with our factors of interest (i.e., family history, physical activity, BMI) were consistent by race/ethnicity. Although our analyses were exploratory, they contribute new information to the existing epidemiologic literature.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.008 |
| 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) | 0.005 | 0.001 |
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".