The Cost-effectiveness of Screening for Chronic Hepatitis B Infection in the United States
Bibliographic record
Abstract
BACKGROUND: Hepatitis B virus (HBV) continues to cause significant morbidity and mortality in the United States. Current guidelines suggest screening populations with a prevalence of ≥2%. Our objective was to determine whether this screening threshold is cost-effective and whether screening lower-prevalence populations might also be cost-effective. METHODS: We developed a Markov state transition model to examine screening of asymptomatic outpatients in the United States. The base case was a 35-year-old man living in a region with an HBV infection prevalence of 2%. Interventions (versus no screening) included screening for Hepatitis B surface antigen followed by treatment of appropriate patients with (1) pegylated interferon-α2a for 48 weeks, (2) a low-cost nucleoside or nucleotide agent with a high rate of developing viral resistance for 48 weeks, (3) prolonged treatment with low-cost, high-resistance nucleoside or nucleotide, or (4) prolonged treatment with a high-cost nucleoside or nucleotide with a low rate of developing viral resistance. Effectiveness was measured in quality-adjusted life years (QALYs) and costs in 2008 US dollars. RESULTS: Screening followed by treatment with a low-cost, high-resistance nucleoside or nucleotide was cost-effective ($29,230 per QALY). Sensitivity analyses revealed that screening costs <$50,000 per QALY in extremely low-risk populations unless the prevalence of chronic HBV infection is <.3%. CONCLUSIONS: The 2% threshold for prevalence of chronic HBV infection in current Centers for Disease Control and Prevention/US Public Health Service screening guidelines is cost-effective. Furthermore, screening of adults in the United States in lower-prevalence populations (eg, as low as .3%) also is likely to be cost-effective, suggesting that current health policy should be reconsidered.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| 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".