Atopic Disease and Risk of Non–Hodgkin Lymphoma: An InterLymph Pooled Analysis
Bibliographic record
Abstract
We performed a pooled analysis of data on atopic disease and risk of non-Hodgkin lymphoma (NHL) from 13 case-control studies, including 13,535 NHL cases and 16,388 controls. Self-reported atopic diseases diagnosed 2 years or more before NHL diagnosis (cases) or interview (controls) were analyzed. Pooled odds ratios (OR) and 95% confidence intervals (95% CI) were computed in two-stage random-effects or joint fixed-effects models, and adjusted for age, sex, and study center. When modeled individually, lifetime history of asthma, hay fever, specific allergy (excluding hay fever, asthma, and eczema), and food allergy were associated with a significant reduction in NHL risk, and there was no association for eczema. When each atopic condition was included in the same model, reduced NHL risk was only associated with a history of allergy (OR, 0.80; 95% CI, 0.68-0.94) and reduced B-cell NHL risk was associated with history of hay fever (OR, 0.85; 95% CI, 0.77-0.95) and allergy (OR, 0.84; 95% CI, 0.76-0.93). Significant reductions in B-cell NHL risk were also observed in individuals who were likely to be truly or highly atopic-those with hay fever, allergy, or asthma and at least one other atopic condition over their lifetime. The inverse associations were consistent for the diffuse large B-cell and follicular subtypes. Eczema was positively associated with lymphomas of the skin; misdiagnosis of lymphoma as eczema is likely, but progression of eczema to cutaneous lymphoma cannot be excluded. This pooled study shows evidence of a modest but consistent reduction in the risk of B-cell NHL associated with atopy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".