Disparities in uptake of direct‐acting antiviral therapy for hepatitis C among people who inject drugs in a Canadian setting
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND & AIMS: Despite the high burden of hepatitis C virus (HCV) infection among people who inject drugs (PWID), uptake of interferon-based therapies has been extremely low. Increasing availability of direct-acting antiviral (DAA)-based therapies offers the possibility of rapid treatment expansion with the goal of controlling the HCV epidemic. We evaluated DAA-based treatment uptake among HCV-positive PWID in Vancouver after introduction of DAAs in the government drug formulary. METHODS: Using data from three cohorts of PWID in Vancouver, Canada, we investigated factors associated with DAA-therapies uptake among participants with HCV between April 2015 and November 2017. RESULTS: Of the 915 HCV-positive PWID, 611 (66.8%) were recent PWID and 369 (40.3%) had HIV coinfection. During the study period, 146 (16.0%) initiated DAA-therapies, a rate of 6.0 per 100 person-year, with higher initiation rates among non-recent PWID and an increasing trend over time. In multivariable analysis, HIV coinfection (Adjusted Odds Ratio [AOR] = 2.29, 95% Confidence Interval [CI]: 1.55-3.40), white race (AOR = 1.56, 95% CI: 1.05-2.35), and engagement in HCV care (AOR = 1.94, 95% CI: 1.31-2.90) were positively associated with DAA-therapies uptake, while high-risk drinking (AOR = 0.47, 95% CI: 0.23-0.88) and daily crack use were negatively associated (AOR = 0.41, 95% CI: 0.17-0.85). Among recent PWID, engagement in opioid agonist therapy emerged as an independent correlate of DAA uptake. CONCLUSIONS: Despite increases in HCV treatment uptake among PWID after the introduction of DAAs in our setting, disparities in access remain. Social-structural and behavioural barriers to HCV care should be addressed for the success of any HCV elimination strategy.
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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 | 0.001 | 0.000 |
| 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 it