Medical History, Lifestyle, and Occupational Risk Factors for Hairy Cell Leukemia: The InterLymph Non-Hodgkin Lymphoma Subtypes Project
Bibliographic record
Abstract
BACKGROUND: Little is known about the etiology of hairy cell leukemia (HCL), a rare B-cell lymphoproliferative disorder with marked male predominance. Our aim was to identify key risk factors for HCL. METHODS: A pooled analysis of individual-level data for 154 histologically confirmed HCL cases and 8834 controls from five case-control studies, conducted in Europe and Australia, was undertaken. Age-, race and/or ethnicity-, sex-, and study-adjusted odds ratios (OR) and 95% confidence intervals (CI) were estimated using unconditional logistic regression. RESULTS: The usual patterns for age and sex in HCL were observed, with a median age of 55 years and sex ratio of 3.7 males to females. Cigarette smoking was inversely associated with HCL (OR = 0.51, 95% CI = 0.37 to 0.71) with dose-response relationships observed for duration, frequency, and lifetime cigarette smoking (P(trend) < .001). In contrast, occupation as a farmer was positively associated with HCL (OR = 2.34, 95% CI = 1.36 to 4.01), with a dose-response relationship observed for duration (OR = 1.82, 95% CI = 0.85 to 3.88 for ≤ 10 years vs never; and OR = 2.98, 95% CI = 1.50 to 5.93 for >10 years vs never; P(trend) = .025). Adult height was also positively associated with HCL (OR = 2.69, 95% CI = 1.39 to 5.29 for upper vs lower quartile of height). The observed associations remained consistent in multivariate analysis. CONCLUSIONS: Our observations of an increased risk of HCL from farming exposures and decreased risk from smoking exposures, independent of one another, support a multifactorial origin and an etiological specificity of HCL compared with other non-Hodgkin lymphoma subtypes. The positive association with height is a novel finding that needs replication.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".