Persistent risk of hepatocellular carcinoma despite improvement of liver stiffness in patients with chronic HBV with advanced fibrosis
Bibliographic record
Abstract
Background & Aims Chronic hepatitis B (CHB) patients with advanced fibrosis are at high risk for hepatocellular carcinoma (HCC). Liver stiffness measurement (LSM) correlates with fibrosis in untreated patients, and is used to monitor changes in severity of liver disease. However, the association between on-treatment LSM and HCC risk is controversial. Methods We conducted an international multicenter retrospective cohort study of CHB patients with advanced fibrosis and assessed the association between on-treatment LSM, HCC development and decompensation events. Results We analyzed 562 patients (62.8% F4, 69.2% Asian). During antiviral therapy, the on-treatment LSM decreased to <6 kPa in 209 (37.2%), to 6-9 kPa in 174 (31.0%) and remained >9 kPa in 179 (31.9%) patients. During a median follow-up of 6.8 years after the on-treatment LSM, 56 patients developed HCC, 18 (32.2%) had an on-treatment LSM <6 kPa. The 5-year cumulative HCC incidence was comparable across on-treatment LSM strata; 4.4% for <6 kPa, 5.5% for 6-9 kPa and 5.8% for >9 kPa (p=0.300). In multivariable analysis, older age (adjusted Hazard Ratio [aHR] 1.058, 95% CI 1.026 – 1.091, p<0.001) and lower platelet count (aHR 0.992, 95% CI 0.992 – 0.998, p=0.005) were associated with HCC development, whereas on-treatment LSM was not (aHR 0.974, p=0.974). In contrast, patients with an LSM decrease to ≤9 kPa had a negligible risk of decompensation (0% vs 1.8% at 5 years, p=0.017). Conclusions Most chronic hepatitis B patients with advanced fibrosis decrease in liver stiffness measurement during antiviral therapy. Although a decrease in liver stiffness was associated with a lower risk of decompensation, an improvement in liver stiffness was not associated with a reduction in hepatocellular carcinoma risk.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".