A great time to invest in baby Boomer's hepatitis C!
Bibliographic record
Abstract
BACKGROUND: In the United States, hepatitis C virus (HCV) infection is most prevalent among adults born from 1945 through 1965, and approximately 50% to 75% of infected adults are unaware of their infection. OBJECTIVE: To estimate the cost-effectiveness of birth-cohort screening. DESIGN: Cost-effectiveness simulation. DATA SOURCES: National Health and Nutrition Examination Survey, U.S. Census, Medicare reimbursement schedule, and published sources.TARGET POPULATION: Adults born from 1945 through 1965 with 1 or more visits to a primary care provider annually.TIME HORIZON: Lifetime.PERSPECTIVE: Societal, health care.INTERVENTION: One-time antibody test of 1945-1965 birth cohort.OUTCOME MEASURES: Numbers of cases that were identified and treated and that achieved a sustained viral response; liver disease and death from HCV; medical and productivity costs; quality-adjusted life-years (QALYs); incremental cost-effectiveness ratio (ICER). RESULTS OF BASE-CASE ANALYSIS: Compared with the status quo, birth-cohort screening identified 808,580 additional cases of chronic HCV infection at a screening cost of $2874 per case identified. Assuming that birth-cohort screening was followed by pegylated interferon and ribavirin (PEG-IFN+R) for treated patients, screening increased QALYs by 348,800 and costs by $5.5 billion, for an ICER of $15,700 per QALY gained. Assuming that birth-cohort screening was followed by direct-acting antiviral plus PEG-IFN+R treatment for treated patients, screening increased QALYs by 532,200 and costs by $19.0 billion, for an ICER of $35,700 per QALY saved. RESULTS OF SENSITIVITY ANALYSIS: The ICER of birth-cohort screening was most sensitive to sustained viral response of antiviral therapy, the cost of therapy, the discount rate, and the QALY losses assigned to disease states. LIMITATION: Empirical data on screening and direct-acting antiviral treatment in real-world clinical settings are scarce. CONCLUSION: Birth-cohort screening for HCV in primary care settings was cost-effective. PRIMARY FUNDING SOURCE: Division of Viral Hepatitis, Centers for Disease Control and Prevention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.036 | 0.006 |
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".