Direct-Acting Antiviral Initiation Among People With Hepatitis C Virus (HCV) and HIV on Antiretroviral Therapy in the United States and Canada: Factors Driving the HCV Treatment Gap
Bibliographic record
Abstract
Background: People with human immunodeficiency virus (HIV; PWH) are at increased risk of hepatitis C virus (HCV) coinfection and experiencing negative clinical outcomes. We evaluated direct-acting antiviral (DAA) initiation among PWH with HCV to identify factors associated with initiation. Methods: US and Canadian PWH ≥18 years with a detectable HCV RNA in the North American AIDS Cohort Collaboration on Research and Design were followed up from the latest of first detectable HCV viremia, antiretroviral therapy initiation, enrollment date, or 1 January 2014 until the first of DAA prescription, clearance of HCV viremia, loss to follow-up, death, or 31 December 2021. We estimated the cumulative incidence of DAA initiation accounting for the competing risks of death and HCV viral clearance. Cox proportional hazard models estimated crude and adjusted hazard ratios and 95% confidence intervals to identify factors associated with DAA initiation. Results: Among 6300 PWH with a detectable HCV RNA, 3672 (58%) initiated DAA. Accounting for the competing risks of death and HCV clearance, by 8 years after study entry 6% of eligible PWH had not initiated DAA. A lower rate of DAA initiation was identified among non-Hispanic black and Hispanic PWH compared with non-Hispanic white PWH. DAA initiation was lower among PWH reporting injection drug use as their HIV acquisition risk, at-risk alcohol use, smoking, detectable HIV viremia, or a history of AIDS. A higher Fibrosis-4 score was associated with increased DAA initiation. Conclusions: The DAA initiation gap among PWH engaged in care and eligible for treatment has greatly narrowed over time. Targeted approaches to increase equity in DAA initiation are needed to eliminate HCV among PWH.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 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".