Histological benefits of virological response to peginterferon alfa‐2a monotherapy in patients with hepatitis C and advanced fibrosis or compensated cirrhosis
Bibliographic record
Abstract
BACKGROUND: Patients with chronic hepatitis C virus and advanced fibrosis or cirrhosis are at risk for disease progression and hepatic decompensation. AIM: To determine the effects on hepatic histology of treatment with peginterferon alfa-2a (90 or 180 mug/week) or interferon alfa-2a (3 million units three times weekly) for 48 weeks in patients with paired biopsies. METHODS: Liver biopsies were obtained at baseline and 6 months after end of treatment. Histological and virological responses were compared. RESULTS: Patients attaining sustained virological response (n = 40) demonstrated the greatest improvements in fibrosis (-1.0, P < 0.0001) and inflammation (-0.65, P < 0.0001). Patients who cleared hepatitis C virus during treatment, but later relapsed (n = 59), experienced less improvement in fibrosis (-0.04, P < 0.0001) and inflammation (-0.14, P = 0.0768). Nonresponders (n = 85) showed no significant improvement in inflammation or fibrosis. Multiple regression analysis showed that the only factors contributing to improvement in fibrosis were sustained virological response (vs. nonresponder, P = 0.0005; vs. relapse, P = 0.7525) and body mass index < or =30 kg/m2 (P = 0.0995). CONCLUSIONS: These findings indicate that virological response to peginterferon alfa-2a improves inflammation and fibrosis in hepatitis C virus patients with advanced fibrosis or cirrhosis. Improving virological response and maintaining ideal body weight are critical for achieving optimal histological outcomes in hepatitis C virus patients.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".