Cost‐effectiveness analysis of sofosbuvir and velpatasvir in chronic hepatitis C patients with decompensated cirrhosis
Bibliographic record
Abstract
BACKGROUND: Current literature indicates that direct-acting antivirals (DAAs) are cost-effective to treat compensated cirrhotic patients with hepatitis C. Although already funded by public payers, it is unknown whether it is economical to reimburse DAAs within the more advanced decompensated cirrhosis population. METHODS: A state-transition model was developed to conduct a cost-utility analysis of sofosbuvir-velpatasvir (SOF/VEL) plus ribavirin regimen for 12 weeks. The evaluated cohort had a mean age of 58 years and Child-Turcotte-Pugh (CTP) class B cirrhosis with decompensated symptoms. A scenario analysis was performed on CTP C patients. We used a payer perspective, a lifetime time horizon and a 1.5% annual discount rate. RESULTS: While SOF/VEL plus ribavirin treatment for 12 weeks increased costs by $156 676, it provided an extra 4.00 quality-adjusted life years (QALYs) compared to best supportive care (no DAA therapy). With an incremental cost-effectiveness ratio of $39 169 per QALY, SOF/VEL plus ribavirin was determined to be cost-effective at a willingness to pay of $50 000 per QALY. SOF/VEL reduced liver-related deaths and reduced progression to CTP C cirrhosis by 20.4% and 21.9%, respectively. On the contrary, SOF/VEL regimen resulted in increases in liver transplants and hepatocellular carcinoma (HCC) by 54.0% and 42.5%, respectively. Similar results were found for CTP C patients. CONCLUSION: This analysis informs payers that SOF/VEL should continue to be reimbursed in decompensated hepatitis C patients. It also supports the recommendations by the American Association for the Study of Liver Diseases to continue screening for HCC in decompensated cirrhotic patients who have achieved sustained virologic response.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".