Association between red blood cell transfusions and development of non-Hodgkin lymphoma: a meta-analysis of observational studies
Bibliographic record
Abstract
The incidence of non-Hodgkin lymphoma (NHL) has increased steadily for the past few decades. Previous studies have suggested an association between blood transfusions and NHL. The main objective of this study was to evaluate this relationship with a meta-analysis of observational studies. A literature search was undertaken, looking for case-control and cohort studies evaluating the risk of developing NHL in persons who received allogeneic blood transfusions; 14 studies were included. Outcome was calculated and reported as relative risk (RR). Heterogeneity was assessed with Cochrane Q and I(2) statistics. Dissemination bias was evaluated by funnel plot visualization and trim-and-fill analysis. Quality assessment was performed with the Newcastle-Ottawa scale. Our analysis showed a RR of developing NHL of 1.05 (95% CI, 0.89-1.25; P = .42) and 1.34 (95% CI, 1.15-1.55; P < .01) in case-control and cohort studies, respectively. When pooling all studies, RR was 1.2 (95% CI, 1.07-1.35; P < .01). In subset analysis, RR of chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) was 1.66 (95% CI, 1.08-2.56; P = .02). The RR of NHL was elevated in both men and women and in persons receiving transfusions either before or after 1992. Blood transfusions appear to increase the risk of developing NHL; however, the risk of CLL/SLL appears higher than for other NHL subtypes.
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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 | 0.022 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.047 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".