Health Utilities in People with Hepatitis C Virus Infection: A Study Using Real-World Population-Level Data
Bibliographic record
Abstract
BackgroundHepatitis C virus (HCV) infection is associated with reduced quality of life and health utility. It is unclear whether this is primarily due to HCV infection itself or commonly co-occurring patient characteristics such as low income and mental health issues. This study aims to estimate and separate the effects of HCV infection on health utility from the effects of clinical and sociodemographic factors using real-world population-level data.MethodsWe conducted a cross-sectional retrospective cohort study to estimate health utilities in people with and without HCV infection in Ontario, Canada, from 2000 to 2014 using linked survey data from the Canadian Community Health Survey and health administrative data. Utilities were derived from the Health Utilities Index Mark 3 instrument. We used propensity score matching and multivariable linear regression to examine the impact of HCV infection on utility scores while adjusting for clinical and sociodemographic factors.ResultsThere were 7,102 individuals with hepatitis C status and health utility data available (506 HCV-positive, 6,596 HCV-negative). Factors associated with marginalization were more prevalent in the HCV-positive cohort (e.g., household income <$20,000: 36% versus 15%). Propensity score matching resulted in 454 matched pairs of HCV-positive and HCV-negative individuals. HCV-positive individuals had substantially lower unadjusted utilities than HCV-negative individuals did (mean ± standard error: 0.662 ± 0.016 versus 0.734 ± 0.015). The regression model showed that HCV positivity (coefficient: -0.066), age, comorbidity, mental health history, and household income had large impacts on health utility.ConclusionsHCV infection is associated with low health utility even after controlling for clinical and sociodemographic variables. Individuals with HCV infection may benefit from additional social services and supports alongside antiviral therapy to improve their quality of life.HighlightsHepatitis C virus (HCV) infection is associated with reduced quality of life and health utility. There is debate in the literature on whether this is primarily due to HCV infection itself or commonly co-occurring patient characteristics such as low income and mental health issues.We showed that individuals with HCV infection have substantially lower health utilities than uninfected individuals do even after controlling for clinical and sociodemographic variables, based on a large, real-world population-level dataset. Socioeconomically marginalized individuals with HCV infection had particularly low health utilities.In addition to improving access to HCV testing and treatment, it may be beneficial to provide social services such as mental health and financial supports to improve the quality of life and health utility of people living with HCV.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".