Global real‐world evidence of sofosbuvir/velpatasvir as simple, effective HCV treatment: Analysis of 5552 patients from 12 cohorts
Bibliographic record
Abstract
BACKGROUND AND AIMS: Achieving sustained virological response (SVR; cure) in hepatitis C patients using a simple regimen is key to making elimination by 2030 possible. In the largest real-world analysis to date, the effectiveness of pangenotypic, panfibrotic, single-tablet, sofosbuvir/velpatasvir (SOF/VEL) once-daily for 12 weeks was assessed in 12 clinical real-world cohorts from various geographical areas, settings and treatment practices. Factors affecting risk of not achieving SVR were assessed. METHODS: Adults treated with SOF/VEL 400/100 mg, without ribavirin, were included. All HCV patients reaching Week 12 or 24 post-treatment were assessed for SVR12/24. Factors associated with not achieving SVR12/24 for virological reasons were evaluated using logistic regression analysis. RESULTS: Overall, 5552 patients were included: 13.3% treatment-experienced; 20.7% compensated cirrhotic; 30.2% genotype 1; 29.5% genotype 2; 32.9% genotype 3; 4.7% genotype 4; 3.7% HIV coinfection; 13.4% current/former intravenous drug use. Of the 5196 patients evaluated for effectiveness, 98.9% achieved SVR12/24. High SVR12/24 rates occurred in all genotypes including genotype 3 (98.3%; 1649/1677) and in those with compensated cirrhosis (97.9; 1055/1078). Only 55 patients did not achieve SVR12/24 due to a virological reason; the only factor statistically significantly associated with an increased risk of not achieving SVR12/24 was compensated cirrhosis (P = .002). Overall, 6% (332/5552) of patients did not achieve SVR12/24 for non-virological reasons (67% lost to follow-up; 26.5% early treatment discontinuation). CONCLUSIONS: In this large cohort, representative of clinical practice, a simple 12-week regimen of SOF/VEL without ribavirin resulted in high SVR12/24 rates in diverse patient populations, even among those with compensated 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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".