Histological response in patients treated by interferon plus ribavirin for hepatitis C virus-related severe fibrosis
Bibliographic record
Abstract
BACKGROUND: Studies of viral hepatitis C have suggested that fibrosis can regress, at least in patients with sustained virological response. A recent study suggested that cirrhosis was reversible in sustained and non-virological responders. AIM: To study fibrosis progression rate and cirrhosis reversion in patients treated for severe fibrosis with interferon or interferon + ribavirin. PATIENTS AND METHODS: Ninety-nine patients were treated with interferon + ribavirin and 64 with interferon. The Metavir fibrosis score and the semiquantitative fibrosis score (SFS) were used to assess fibrosis. RESULTS: In sustained responders, fibrosis progression rate decreased from 0.26 Metavir unit (interquartile range: 0.19-0.34) to -0.67 (-0.67 to 0) (P < 0.0001) and from 0.81 SFS unit (0.48-1.13) to -1.33 (-3.67 to 0) (P < 0.0001). In non-responders, fibrosis progression rate decreased from 0.25 Metavir unit (0.17-0.33) before treatment to 0 (0-0) during treatment (P = 0.002) and from 0.63 SFS unit (0.49-1.12) to 0 (-2.67-1.33) (P = 0.18). Six out of 18 (33%) sustained virological responders and four of 43 (9%) non-responders regressed from cirrhosis (F4) to severe fibrosis (F3) (P = 0.058). No patient with cirrhosis had a decrease of Metavir fibrosis score of 2 points. CONCLUSION: Interferon can slow fibrosis progression in sustained virological responders with severe fibrosis. In patients with a non-virological response and treated for 12 months the fibrosis progression rate was nil, meaning that only fibrosis stabilization could be obtained in these patients. Then, longer treatment duration (3-4 years) could be evaluated in non-virological responders.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".