Medical History, Lifestyle, Family History, and Occupational Risk Factors for Sporadic Burkitt Lymphoma/Leukemia: The Interlymph Non-Hodgkin Lymphoma Subtypes Project
Bibliographic record
Abstract
BACKGROUND: The etiologic role of medical history, lifestyle, family history, and occupational risk factors in sporadic Burkitt lymphoma (BL) is unknown, but epidemiologic and clinical evidence suggests that risk factors may vary by age. METHODS: We investigated risk factors for sporadic BL in 295 cases compared with 21818 controls in a pooled analysis of 18 case-control studies in the International Lymphoma Epidemiology Consortium (InterLymph). Cases were defined to include typical BL or Burkitt-like lymphoma. Odds ratios (ORs) and 95% confidence intervals (CIs) for associations were calculated separately for younger (<50 years) and older (≥ 50 years) BL using multivariate logistic regression. RESULTS: Cases included 133 younger BL and 159 older BL (age was missing for three cases) and they were evenly split between typical BL (n = 147) and Burkitt-like lymphoma (n = 148). BL in younger participants was inversely associated with a history of allergy (OR = 0.58; 95% CI = 0.32 to 1.05), and positively associated with a history of eczema among individuals without other atopic conditions (OR = 2.54; 95% CI = 1.20 to 5.40), taller height (OR = 2.17; 95% CI = 1.08 to 4.36), and employment as a cleaner (OR = 3.49; 95% CI = 1.13 to 10.7). BL in older participants was associated with a history of hepatitis C virus seropositivity (OR = 4.19; 95% CI = 1.05 to 16.6) based on three exposed cases. Regardless of age, BL was inversely associated with alcohol consumption and positively associated with height. CONCLUSIONS: Our data suggest that BL in younger and older adults may be etiologically distinct.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".