Clinical Outcomes After Treatment With Direct Antiviral Agents: Beyond The Virological Response in Patients With Previous HCV-Related Decompensated Cirrhosis
Bibliographic record
Abstract
Abstract Background In HCV-infected patients with advanced liver disease, the direct antiviral agents (DAAS)-associated clinical benefits remain debated. We compared the clinical outcome of patients with a previous history of decompensated cirrhosis following treatment or not with DAAs from the French ANRS CO22 HEPATHER cohort. Methods We identified HCV patients who had experienced an episode of decompensated cirrhosis. Study outcomes were all-cause mortality, liver-related or non-liver-related deaths, hepatocellular carcinoma, liver transplantation. Secondary study outcomes were sustained virological response (SVR) and its clinical benefits Results 559 patients met the identification criteria, of which 483 received DAA and 76 remained untreated after inclusion in the cohort. The median follow-up time was 39·7 (IQR: 22·7–51) months. After adjustment for multivariate analysis, exposure to DAAs was associated with a decrease in all-cause mortality (HR 0·45, 95% CI 0·24–0·84, p = 0·01) and non-liver-related death (HR 0·26, 95% CI 0·08–0·82, p = 0·02), and was not associated with liver-related death, decrease in hepatocellular carcinoma and need for liver transplantation. The SVR was 88%. According to adjusted multivariable analysis, SVR achievement was associated with a decrease in all-cause mortality (HR 0·29, 95% CI 0·15–0·54, p < 0·0001), liver-related mortality (HR 0·40, 95% CI 0·17–0·96, p = 0·04), non-liver-related mortality (HR 0·17, 95% CI 0·06–0·49, p = 0.001), liver transplantation (HR 0·17, 95% CI 0·05–0·54, p = 0.003), and hepatocellular carcinoma (HR 0·52, 95% CI 0·29–0·93, p = 0·03). Conclusion Treatment with DAAS is associated with reduced risk for mortality. Thus, DAA treatment should be considered for any patient with HCV-related decompensated cirrhosis.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".