Antiviral Treatment of Recurrent Hepatitis C After Liver Transplantation: Predictors of Response and Long-Term Outcome
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Efficacy and long-term outcome of antiviral therapy for recurrent hepatitis C after liver transplantation is poorly defined. AIM: This study aimed at assessing the efficacy of antiviral therapy regarding sustained hepatitis C virus (HCV) clearance, liver histology, and patient survival. METHODS: We retrospectively reviewed all 446 patients who received a liver allograft at our institution for HCV-related cirrhosis between January 1992 and December 2006. Two hundred thirty-two patients (52%) were eligible for antiviral therapy based on predefined criteria (Metavir stage > or =1 and/or grade > or =2; protocol biopsies). One hundred seventy-two patients (39%) had no contraindication for treatment, received more than or equal to 1 dose of interferon-alpha-based combination therapy, and form the basis of this analysis. Therapy was aimed for 48 weeks; median posttreatment follow-up was 68 months. RESULTS: The overall sustained virological response (SVR) rate was 50% (genotype 1/4: 40%; genotype 2/3: 76%). SVR was higher on cyclosporine A (CsA) (56%) than on tacrolimus (44%, P=0.05), largely because of a lower relapse rate (6% vs. 19%, P=0.01). In multivariate analysis, genotype 2/3, CsA use, donor age, and pretreatment necroinflammatory activity were independently associated with SVR. SVR significantly improved histology and long-term survival (actuarial 5-year survival 96% vs. 69% in nonresponders, P<0.0001). CONCLUSION: Antiviral therapy of recurrent hepatitis C after liver transplantation is able to clear HCV in half the patients, more likely on CsA than on tacrolimus, and markedly improves outcome.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it