Faculty Opinions recommendation of Real-world Effectiveness of Sofosbuvir/Velpatasvir for Treatment of Chronic Hepatitis C in British Columbia, Canada: A Population-Based Cohort Study.
Bibliographic record
Abstract
Background.Clinical trials show high efficacy of sofosbuvir/velpatasvir (SOF/VEL), but there are limited data from "realworld" settings.We aimed to evaluate SOF/VEL effectiveness for all hepatitis C virus (HCV) genotypes (GTs) in British Columbia (BC), Canada. Methods.We used the BC Hepatitis Testers Cohort, which includes all HCV cases in the province linked to administrative databases, including prescriptions to end of 2018.We measured sustained virologic response (SVR; negative RNA ≥10 weeks after treatment end) and identified characteristics associated with non-SVR.Conservatively, we excluded individuals with no assessment for SVR if their last RNA test after treatment initiation was negative (but included if positive).Results.Of 2821 eligible participants, most were infected with GT1 (1076, 38.1%) or GT3 (1072, 38.0%), and a minority (278, 9.9%) were treated with RBV.SVR was 94.6% (2670/2821) overall and 94.5% (1017/1076) for GT1, 96.4% (512/531) for GT2, and 93.7% (1004/1072) for GT3.When disaggregated by GT, treatment regimen, and cirrhosis/treatment experience, SVR was lowest (30/40, 75.0%) among treatment-experienced GT3 individuals treated with RBV.Characteristics associated with non-SVR in multivariable analysis included younger age, RBV addition, and being a person with HIV (PWH) or who injects/injected drugs (PWID).When treatment regimen (±RBV) was removed from multivariable model, treatment experience was associated with non-SVR for GT3.Of 151 non-SVR individuals, 56.3% were nonvirological failures (treatment incomplete/no assessment for SVR) and 43.7% were virological failures (nonresponse/relapse).A disproportionately high percentage of non-SVR among PWID was due to nonvirological failure.Conclusions.SOF/VEL was highly effective in this "real-world" population-based cohort.Additional support is required for PWID/PWH to reach SVR. Keywords. hepatitis C; treatment effectiveness; observational study; administrative data; sofosbuvir; velpatasvir; ribavirin.Hepatitis C virus (HCV) and its associated morbidity and mortality are a significant public health issue in Canada and globally [1, 2].In the absence of effective treatment, about 75% of individuals infected with HCV advance to chronic infection, and 10%-15% of chronically infected individuals develop liver cirrhosis within 20 years [3].People with cirrhosis are at higher risk of end-stage liver disease and death.Second-generation oral direct-acting antivirals (DAAs) are short course (8-24 weeks), have fewer adverse effects, and can cure >95% of people with HCV.This high cure rate and ease of use led the World Health Organization to issue the first Global Health Sector Strategy on Viral Hepatitis, with the aim of eliminating HCV as a major public health issue by 2030 [4].Sofosbuvir/velpatasvir (SOF/VEL) is the first of these DAAs to be pan-genotypic and require a single pill taken once daily.SOF/VEL clinical trials published in 2015 demonstrated sustained virologic response (SVR) rates exceeding 97% for all genotypes (GTs) except for GT3 (94.7%) [5-10].In 2016, SOF/ VEL was approved by regulatory agencies in the United States (Food and Drug Administration), Canada (Health Canada), and the European Union (European Commission) [11, 12].
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.041 | 0.014 |
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".