Impact of direct‐acting antiviral treatment on health utility in patients with chronic hepatitis C in hospital and community settings
Bibliographic record
Abstract
BACKGROUND: Direct-acting antiviral agents (DAAs) have transformed chronic hepatitis C (CHC) treatment. Continued affordable access to DAAs requires updated cost-effectiveness analyses (CEA). Utility is a preference-based measure of health-related quality of life (HRQoL) used in CEA. This study evaluated the impact of DAAs on utilities for patients with CHC in two clinical settings. METHODS: This prospective longitudinal study included patients aged ≥18 years, diagnosed with CHC and scheduled to begin DAA treatment, from two tertiary care hospital clinics and four community clinics in Toronto, Calgary, and Montreal. Patients completed two utility instruments (EQ-5D-5L and Health Utilities Index 2/3 (HUI2/3)) before treatment, 6 weeks after treatment initiation, and 12 weeks and 1 year after treatment completion. We measured utilities for all patients, and for hospital-based and community-based groups. RESULTS: Between 2017 and 2020, 209 patients (126 hospital-based, 83 community-based; average age 53 years; 65% male) were recruited, and 143 completed the 1-year post-treatment assessment. Pre-treatment, utilities were (mean ± standard deviation) 0.77 ± 0.21 (EQ-5D-5L), 0.69 ± 0.24 (HUI2) and 0.58 ± 0.34 (HUI3). The mean changes at 1-year post-treatment were 0.035, 0.038 and 0.071, respectively. While utilities for hospital-based patients steadily improved, utilities for the community-based cohort improved between baseline and 12-weeks post-treatment, but decreased thereafter. DISCUSSION: This study suggests that utilities improve after DAA treatment in patients with CHC in a variety of settings. However, community-based patients may face challenges related to comorbid health and social conditions that are not meaningfully addressed by treatment. Our study is essential for valuing health outcomes in CHC-related CEA.
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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 | 0.000 |
| 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 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".