Association between metabolic associated fatty liver disease and HCC risk after SVR in HCV patients: A systematic review and meta-analysis
Bibliographic record
Abstract
Aim of the study: Chronic hepatitis C (CHC) infection remains one of the most prevalent chronic liver disease worldwide.A sustained virological response (SVR) can be achieved at high rates for CHC patients receiving direct-acting antivirals (DAAs).However, even small subsets of patients achieving SVR still have a risk of developing hepatocellular carcinoma (HCC).Metabolic-associated fatty liver disease (MAFLD) is associated with increased risk of HCC.We aimed to summarize the effect of MAFLD on HCC development on CHC patients, even after achieving SVR. Material and methods:We conducted a search of PubMed and Google Scholar from inception to July 7 th 2024, for studies assessing the association between the presence of MAFLD or metabolic dysfunction-associated steatotic liver disease (MASLD) or non-alcoholic fatty liver disease (NAFLD) and HCC risk in CHC patients who achieved SVR.The quality of included studies was evaluated using the Newcastle-Ottawa Scale (NOS).We analyzed the pooled hazard ratios (HRs) with 95% confidence intervals (CIs) using a fixed and random-effects model.Heterogeneity was assessed using I 2 .Results: Five studies with a total of 7,034 patients were included.The quality of studies ranged from 6 to 8 stars.Metabolic dysfunction is associated with increased risk of HCC after SVR in CHC patients (HR = 2.02, 95% CI: 1.61-2.54,p < 0.00).No heterogeneity was present.Conclusions: Metabolic dysfunction is associated with increased risk of HCC progression in CHC patients even after achieving SVR.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.028 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".