B‐cell non‐Hodgkin's lymphoma and hepatitis C virus infection: A systematic review
Bibliographic record
Abstract
A high prevalence of hepatitis C virus (HCV) infection in patients with B-cell non-Hodgkin's lymphoma (B-NHL) has been reported in some, but not all, studies, and the association showed a strong regional variation. We conducted a systematic review of the prevalence of HCV infection in case series of B-NHL and, when an appropriate control group was available, of the odds ratio of B-NHL associated with HCV infection. A high HCV prevalence in B-NHL was found in southern and eastern Europe, Japan and the southern United States, but not in central and northern Europe, Canada, northern United States, or a few Asian countries. Possible sources of heterogeneity and bias are discussed. The odds ratio of B-NHL for HCV infection was relatively weak, ranging from 2 to 4 in most studies. Thus, even if the observed association were causal, the percentage of cases of B-NHL attributable to HCV infection would be relatively low (10%) also in countries with a high prevalence of HCV infection in the general population, and extremely low in other countries. This may explain apparent inconsistencies between studies. Potential mechanisms of action are also discussed.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".