Medical History, Lifestyle, Family History, and Occupational Risk Factors for Mantle Cell Lymphoma: The InterLymph Non-Hodgkin Lymphoma Subtypes Project
Bibliographic record
Abstract
The etiology of mantle cell lymphoma (MCL), a distinctive subtype accounting for 2%–10% of all non-Hodgkin lymphoma, is not known. We investigated associations with self-reported medical history, lifestyle, family history, and occupational risk factors in a pooled analysis of 557 patients with MCL and 13766 controls from 13 case–control studies in Europe, North America, and Australia. Odds ratios (ORs) and 95% confidence intervals (CIs) associated with each exposure were examined using multivariate logistic regression models. The median age of the MCL patients was 62 years and 76% were men. Risk of MCL was inversely associated with history of hay fever (OR = 0.63, 95% CI = 0.48 to 0.82), and the association was independent of other atopic diseases and allergies. A hematological malignancy among first-degree relatives was associated with a twofold increased risk of MCL (OR = 1.99, 95% CI = 1.39 to 2.84), which was stronger in men (OR = 2.21, 95% CI = 1.44 to 3.38) than women (OR = 1.61, 95% CI = 0.82 to 3.19). A modestly increased risk of MCL was also observed in association with ever having lived on a farm (OR = 1.40, 95% CI = 1.03 to 1.90). Unlike some other non-Hodgkin lymphoma subtypes, MCL risk was not statistically significantly associated with autoimmune disorders, tobacco smoking, alcohol intake, body mass index, or ultraviolet radiation. The novel observations of a possible role for atopy and allergy and farm life in risk of MCL, together with confirmatory evidence of a familial link, suggest a multifactorial etiology of immune-related environmental exposures and genetic susceptibility. These findings provide guidance for future research in MCL etiology.
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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) | 0.000 | 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 | 0.001 |
| 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".