Real-world efficacy and safety of direct-acting antiviral drugs in patients with chronic hepatitis C and inherited blood disorders
Bibliographic record
Abstract
BACKGROUND: Patients with inherited blood disorders (IBLD) have a high risk of hepatitis C virus (HCV) infection. The aim of this work was to assess the efficacy and safety of HCV direct-acting antiviral (DAA)-based treatment in patients with IBLD and chronic HCV infection. METHODS: Twenty-seven patients (25 with sickle cell disease, 1 with β-thalassemia and 1 with hemoglobin D-Punjab), including 3 with compensated cirrhosis, were included. They were treated with sofosbuvir in combination with ribavirin, daclatasvir, ledipasvir, or velpatasvir or with grazoprevir/elbasvir for 8 or 12 weeks. In the case of treatment failure, in-vitro assessment of resistance-associated substitutions (RASs) and full-length genome sequence analysis by means of deep sequencing were performed. RESULTS: Treatment was safe and well-tolerated and there were no drug discontinuations due to DAA-related adverse events. Twenty-five out of the 27 patients (93%) achieved sustained virological response 12 weeks post-treatment. One patient discontinued after 18 days due to adverse events unrelated to the antiviral treatment. One patient infected with 'unusual' genotype 2 subtype 2m relapsed. Subtype 2m naturally carries the NS5A L31M RAS. In a genotype 2a subgenomic replicon model, L31M increased daclatasvir effective concentration 50% (EC50) by 97-fold, but velpatasvir EC50 by only 3-fold, without altering the replication capacity. This patient was successfully retreated with sofosbuvir/velpatasvir for 12 weeks. CONCLUSION: DAA-based regimens are well tolerated and highly efficacious in patients with chronic hepatitis C and IBLD in the real-world setting. Thus, DAA-based antiviral treatment should be prioritized in this thus far neglected population of HCV-infected 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 | 0.002 | 0.003 |
| 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 | 0.001 | 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".