Reinfection and Risk Behaviors After Treatment of Hepatitis C Virus Infection in Persons Receiving Opioid Agonist Therapy
Bibliographic record
Abstract
BACKGROUND: Hepatitis C virus (HCV) reinfection after successful treatment may reduce the benefits of cure among people who inject drugs. OBJECTIVE: To evaluate the rate of HCV reinfection for 3 years after successful treatment among people receiving opioid agonist therapy (OAT). DESIGN: A 3-year, long-term, extension study of persons enrolled in the CO-STAR (Hepatitis C Patients on Opioid Substitution Therapy Antiviral Response) study (ClinicalTrials.gov: NCT02105688). SETTING: 55 clinical trial sites in 13 countries. PATIENTS: Aged 18 years and older with chronic HCV infection with genotypes 1, 4, or 6 receiving stable OAT. INTERVENTION: No treatments were administered. MEASUREMENTS: Serum samples were assessed for HCV reinfection. Urine drug screening was performed. RESULTS: Among 296 participants who received treatment, 286 were evaluable for reinfection and 199 were enrolled in the long-term extension study. The rate of HCV reinfection was 1.7 [95% CI, 0.8 to 3.0] per 100 person-years; 604 person-years of follow-up). A higher rate of reinfection was seen among people with recent injecting drug use (1.9 [95% CI, 0.5 to 4.8] per 100 person-years; 212 person-years). Ongoing drug use and injecting drug use were reported by 59% and 21% of participants, respectively, at the 6-month follow-up visit and remained stable during 3 years of follow-up. LIMITATIONS: Participants were required to be 80% adherent to OAT at baseline and may represent a population with higher stability and lower risk for HCV reinfection. Rate of reinfection may be underestimated because all participants did not continue in the long-term extension study; whether participants who discontinued were at higher risk for reinfection is unknown. CONCLUSION: Reinfection with HCV was low but was highest in the first 24 weeks after treatment completion and among people with ongoing injecting drug use and needle-syringe sharing. PRIMARY FUNDING SOURCE: Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".