Global Real-World Evidence of Sofosbuvir/Velpatasvir as a Highly Effective Treatment and Elimination Tool in People with Hepatitis C Infection Experiencing Mental Health Disorders
Bibliographic record
Abstract
Hepatitis C virus (HCV) is prevalent in people with mental health disorders, a priority population to diagnose and cure in order to achieve HCV elimination. This integrated analysis pooled data from 20 cohorts in seven countries to evaluate the real-world effectiveness of the pangenotypic direct-acting antiviral (DAA) sofosbuvir/velpatasvir (SOF/VEL) in people with mental health disorders. HCV-infected patients diagnosed with mental health disorders who were treated with SOF/VEL for 12 weeks without ribavirin as part of routine clinical practice were included. The primary outcome was sustained virological response (SVR) in the effectiveness population (EP), defined as patients with an available SVR assessment. Secondary outcomes were reasons for not achieving SVR, characteristics of patients with non-virological failures, adherence, and time from HCV RNA diagnosis to SOF/VEL treatment initiation. A total of 1209 patients were included; 142 did not achieve an SVR for non-virological reasons (n = 112; 83 lost to follow-up, 20 early treatment discontinuations) or unknown reasons (n = 30). Of the 1067 patients in the EP, 97.4% achieved SVR. SVR rates in the EP were ≥95% when stratified by type of mental health disorder and other complicating baseline characteristics, including active injection drug use and antipsychotic drug use. Of 461 patients with data available in the EP, only 2% had an adherence level < 90% and 1% had an adherence level < 80%; all achieved SVR. Patients with mental health disorders can be cured of HCV using a well-tolerated, pangenotypic, protease inhibitor-free SOF/VEL regimen. This DAA allows the implementation of a simple treatment algorithm, with minimal monitoring requirements and fewer interactions with central nervous system drugs compared with protease-inhibitor DAA regimens.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".