Sustained Responders Have Better Quality of Life and Productivity Compared With Treatment Failures Long After Antiviral Therapy for Hepatitis C
Bibliographic record
Abstract
OBJECTIVES: We sought to compare the health status of patients with a sustained response to antiviral therapy for hepatitis C virus (HCV) infection with that of treatment failures, using health-related quality of life and preference (utility) measures. METHODS: Sustained responders had undetectable HCV viral levels 6 months after antiviral therapy. After antiviral therapy, participants completed, by mail or interview, the hepatitis-specific Medical Outcomes Study Short-Form 36-Item Health Survey (SF-36), the Health Utilities Index Mark 2/3 (HUI2/3), and time trade-off (TTO) for current health. The respondents provided information on demographics, history of substance abuse, comorbidities, and health history. Detailed clinical information was obtained by chart review. The respondents also indicated whether they missed work, volunteer opportunities, or household activities during the previous 3 months because of hepatitis C infection or its treatment. RESULTS: A total of 235 patients (133 responders and 102 treatment failures) completed questionnaires at an average of 3.7 years after the end of treatment. Treatment failures had significantly lower scores on the eight SF-36 domains (P<0.01), lower scores on the hepatitis-specific domains (P<0.0001), and lower physical (42.5 vs. 49.2) and mental (40.5 vs. 46.1) component summary scores (P<0.01). HUI3 (0.57 vs. 0.70), HUI2 (0.74 vs. 0.80), SF-6D (0.65 vs. 0.71), and TTO (0.84 vs. 0.89) were lower for treatment failures (P<0.05). The regression-adjusted difference in HUI3, SF-6D, physical summary score, and mental summary score was 0.08 (P=0.04), 0.05 (P=0.004), 5.22 (P=0.001), and 5.73 (P<0.0001), respectively. Differences in the HUI2 and TTO scores were not significant after adjustment for demographic and clinical variables. Treatment failures were more likely to have missed work, volunteer opportunities, or household activities in the previous 3 months because of hepatitis C infection or its treatment (44 vs. 9%, P<0.001). CONCLUSIONS: Patients with a sustained response to antiviral therapy for chronic HCV infection have better quality of life than treatment failures do. Our study validates the benefits associated with the sustained response to antiviral therapy in a real-world clinic population and shows that these benefits are maintained over the long term.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".