Medical History, Lifestyle, Family History, and Occupational Risk Factors for Lymphoplasmacytic Lymphoma/Waldenstrom's Macroglobulinemia: The InterLymph Non-Hodgkin Lymphoma Subtypes Project
Bibliographic record
Abstract
BACKGROUND: Lymphoplasmacytic lymphoma/Waldenström's macroglobulinemia (LPL/WM), a rare non-Hodgkin lymphoma subtype, shows strong familial aggregation and a positive association with chronic immune stimulation, but evidence regarding other risk factors is very limited. METHODS: The International Lymphoma Epidemiology Consortium (InterLymph) pooled data from 11 predominantly population-based case-control studies from North America, Europe, and Australia to examine medical history, lifestyle, family history, and occupational risk factors for LPL/WM. Age-, sex-, race/ethnicity-, and study-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression for a total of 374 LPL/WM cases and 23 096 controls. RESULTS: In multivariate analysis including all putative risk factors, LPL/WM risk was associated with history of Sjögren's syndrome (OR = 14.0, 95% CI = 3.60 to 54.6), systemic lupus erythematosus (OR = 8.23, 95% CI = 2.69 to 25.2), hay fever (OR = 0.73, 95% CI = 0.54 to 0.99), positive hepatitis C serology (OR = 2.51, 95% CI = 1.03 to 6.17), hematologic malignancy in a first-degree relative (OR = 1.64, 95% CI = 1.02 to 2.64), adult weight (OR = 0.61, 95% CI = 0.44 to 0.85 for highest vs. lowest quartile), duration of cigarette smoking (OR = 1.46, 95% CI = 1.04 to 2.05 for ≥ 40 years vs. nonsmokers), and occupation as a medical doctor (OR = 5.54, 95% CI = 2.19 to 14.0). There was no association with other medical conditions, lifestyle factors, or occupations. CONCLUSIONS: This pooled analysis confirmed associations with immune conditions and family history of hematologic malignancy, and identified new associations with hay fever, weight, smoking, and occupation, and no association with other lifestyle factors. These findings offer clues to LPL/WM biology and prevention.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".