Transfusion History and Risk of Non-Hodgkin Lymphoma (NHL): an Interlymph Pooled Analysis
Bibliographic record
Abstract
Abstract Background. A recent meta-analysis of 9 case-control and 5 cohort studies reported a positive association of transfusion history with risk of NHL (RR=1.20; 95% CI 1.07-1.35), which was only evident in cohort (RR=1.25) and not case-control (RR=1.05) studies (Castillo et al., Blood 2010;116:2897-2907). Risk was similar in men and women, and for transfusions before or after 1992. In subset analyses, elevated risk was only apparent for chronic lymphocytic leukemia (CLL) and not diffuse large B-Cell lymphoma (DLBCL) or follicular lymphoma, but power was low. To further investigate these findings, particularly from studies conducted after 1990, better assess confounding, and address heterogeneity by NHL subtypes, we conducted an individual-level, pooled analysis of 13 case-control studies in the InterLymph Consortium (including 11 studies conducted after 1990; 8 studies were not included in the published meta-analysis). Methods. There were a total of 10,805 cases and 14,026 controls with transfusion data from 13 studies conducted in Europe, North America, and Australia. Transfusion history and other risk factors were self-reported in interviewer-administered or self-administered questionnaires. All risk factor data were harmonized centrally, and cases were grouped into NHL subtypes according to the WHO classification using guidelines from the InterLymph Pathology Working Group. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using logistic regression, adjusted for age, sex, and study center. Results. The median age at diagnosis was 60 years for cases (range, 18-97) and 59 years for controls (range, 16-97). The overall prevalence of a history of any transfusion in controls was 15.5%, was higher in women (18.6%) than men (13.0%), and increased with age, but was not associated with race/ethnicity (Asian, Black, Hispanic, White, other) or geographic region after adjusting for age and sex. Among whites, history of any transfusion was inversely associated with NHL risk among men (OR=0.74; 95% CI 0.65-0.83) but not women (OR=0.92; 95% CI 0.83-1.03); there were no significant results for other race/ethnicity groups, and ORs were highly variable and imprecise due to small sample sizes. Thus analyses were restricted to white men, where there was no trend with the number of transfusions, time since first transfusion, age at first transfusion, or decade of first transfusion. Further adjustment for socioeconomic status, body mass index, smoking, alcohol use or hepatitis C virus (HCV) seropositivity did not alter these results. The associations were stronger in hospital-based (OR=0.56; 95% CI 0.45-0.70) than population-based (OR=0.84; 95% CI 0.72-0.98) studies, and were stronger in studies from Southern Europe (OR=0.53; 95% CI 0.36-0.79) than northern Europe (OR=0.67; 95% CI 0.53-0.83) or North America (OR=0.82; 95% CI 0.70-0.98). For NHL subtypes, statistically significant inverse associations were observed for follicular lymphoma (OR=0.70; 95% CI 0.56-0.88), DLBCL (OR=0.72; 95% CI 0.59-0.87), and CLL/SLL (OR=0.67; 95% CI 0.52-0.87), whereas weaker and non-statistically significant associations were observed for mantle cell (OR=0.81; 95% CI 0.54-1.23), marginal zone (OR=0.78; 95% CI 0.54-1.15), lymphoplasmacytic (OR=0.82; 95% CI 0.47-1.42) and peripheral T-cell (OR=0.83; 95% CI 0.49-1.40) lymphomas. Conclusion. Contrary to earlier results, transfusion history was inversely associated with risk of NHL and the common subtypes of follicular lymphoma, DLBCL and CLL/SLL among white men, whereas associations were null among white women and other racial/ethnic groups. These results were not explained by confounding by lifestyle factors or HCV seropositivity, era of first transfusion, hospital versus population-based study design, or geographic location. Despite dramatic changes in transfusion practice over the past 40 years, results were similar for decade of first transfusion, suggesting secular trends are a less likely explanation. Our results are unexpected and bias cannot be ruled out. Further studies, particularly cohort studies, are needed to clarify the role of transfusion history in NHL risk. Disclosures No relevant conflicts of interest to declare.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".