Risk of Hepatocellular Carcinoma After Spontaneous Clearance of Hepatitis C Virus and in Noncirrhosis Chronic Hepatitis C Patients With Sustained Virological Response: A Systematic Review
Bibliographic record
Abstract
In a hepatitis C virus (HCV)-controlled human infection model (CHIM), healthy volunteers are inoculated with HCV and then treated. Residual hepatocellular carcinoma (HCC) risk after viral clearance is an important consideration when evaluating the CHIM. We estimate HCC risk in spontaneously cleared HCV and in noncirrhosis after sustained virological response (SVR) to HCV treatment in a systematic review and using data from 3 cohorts: German anti-D, Taiwan, and US Veterans Affairs (VA). For noncirrhosis SVR, the overall HCC rate is 0.33 per 100 patient-years in meta-analysis. HCC rates for the German, Taiwan, and US Veterans Affairs cohorts are 0, 0.14, and 0.02 per 100 patient-years, respectively. Past hepatitis B virus exposure was not accounted for in the Taiwan cohort, while VA patients were likely tested based on liver disease/risk factors, which may confound HCC outcomes. The German cohort with no HCC after 44 years is most comparable to the CHIM participants. Although it is difficult to precisely estimate HCC risk from an HCV CHIM, the data suggest the risk to be very low or negligible.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".