Cost effectiveness of screening immigrants for hepatitis B
Bibliographic record
Abstract
BACKGROUND: The prevalence of chronic hepatitis B (CHB) infection among the immigrants of North America ranges from 2 to 15%, among whom 40% develop advanced liver disease. Screening for hepatitis B surface antigen is not recommended for immigrants. AIMS: The objective of this study is to estimate the health and economic effects of screening strategies for CHB among immigrants. METHODS: We used the Markov model to examine the cost-effectiveness of three screening strategies: (i) 'No screening'; (ii) 'Screen and Treat' and (iii) 'Screen, Treat and Vaccinate' for 20-65 years old individuals who were born abroad but are currently living in Canada. Model data were obtained from the published literature. We measured predicted hepatitis B virus (HBV)-related deaths, costs (2008 Canadian Dollars), quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratio (ICER). RESULTS: Our results show that screening all immigrants will prevent 59 HBV-related deaths per 10, 000 persons screened over the lifetime of the cohort. Screening was associated with an increase in quality-adjusted life expectancy (0.024 QALYs) and cost ($1665) per person with an ICER of $69, 209/QALY gained compared with 'No screening'. The 'Screen, Treat and Vaccinate' costs an additional $81, generates an additional 0.000022 QALYs per person, with an ICER of $3, 648,123/QALY compared with the 'Screen and Treat'. Sensitivity analyses suggested that the 'Screen and Treat' is likely to be moderately cost-effective. CONCLUSION: We show that a selective hepatitis B screening programme targeted at all immigrants in Canada is likely to be moderately cost-effective. Identification of silent CHB infection with the offer of treatment when appropriate can extend the lives of immigrants at reasonable cost.
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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".