Medical History, Lifestyle, Family History, and Occupational Risk Factors for Follicular Lymphoma: The InterLymph Non-Hodgkin Lymphoma Subtypes Project
Bibliographic record
Abstract
BACKGROUND: Follicular lymphoma (FL) has been linked with cigarette smoking and, inconsistently, with other risk factors. METHODS: We assessed associations of medical, hormonal, family history, lifestyle, and occupational factors with FL risk in 3530 cases and 22639 controls from 19 case-control studies in the InterLymph consortium. Age-, race/ethnicity-, sex- and study-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression. RESULTS: Most risk factors that were evaluated showed no association, except for a few modest or sex-specific relationships. FL risk was increased in persons: with a first-degree relative with non-Hodgkin lymphoma (OR = 1.99; 95% CI = 1.55 to 2.54); with greater body mass index as a young adult (OR = 1.15; 95% CI = 1.04 to 1.27 per 5 kg/m(2) increase); who worked as spray painters (OR = 2.66; 95% CI = 1.36 to 5.24); and among women with Sjögren syndrome (OR = 3.37; 95% CI = 1.23 to 9.19). Lower FL risks were observed in persons: with asthma, hay fever, and food allergy (ORs = 0.79-0.85); blood transfusions (OR = 0.78; 95% CI = 0.68 to 0.89); high recreational sun exposure (OR = 0.74; 95% CI = 0.65 to 0.86, fourth vs first quartile); who worked as bakers or millers (OR = 0.51; 95% CI = 0.28 to 0.93) or university/higher education teachers (OR = 0.58; 95% CI = 0.41 to 0.83). Elevated risks specific to women included current and longer duration of cigarette use, whereas reduced risks included current alcohol use, hay fever, and food allergies. Other factors, including other autoimmune diseases, eczema, hepatitis C virus seropositivity, hormonal drugs, hair dye use, sun exposure, and farming, were not associated with FL risk. CONCLUSIONS: The few relationships observed provide clues suggesting a multifactorial etiology of FL but are limited in the extent to which they explain FL occurrence.
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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 | 0.000 |
| 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".