B‐cell non‐Hodgkin's lymphoma and hepatitis C virus infection: A systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it