Evaluation of Sustained Virologic Response as a Relevant Surrogate Endpoint for Long-term Outcomes of Hepatitis C Virus Infection
Bibliographic record
Abstract
BACKGROUND: The causal link of sustained virologic response (SVR) with outcome has been challenged. With improved SVR rates with direct-acting antivirals (DAAs), the benefit of SVR would be expected to diminish if the association with outcome is not causal. METHODS: Data were collected for patients starting treatment with interferon (IFN) or DAAs between June 2006 and December 2016. To control for disease severity, criteria for the IDEAL (Individualized Dosing Efficacy vs. Flat Dosing to Assess Optimal Pegylated Interferon Therapy) trial determined IFN-eligibility. Clinical events were decompensation, hepatocellular carcinoma, liver transplantation, and all-cause mortality. RESULTS: In 1078 IDEAL-eligible patients, 1306 treatments occurred (52% IFN, 49% DAAs). Cirrhosis was present in 30% DAAs vs 21% IFN (P < .001). SVR was 97% with DAAs vs 52% with IFN (P < .0001). The 24-month cumulative event-free survival was 99% for IFN and 97% for DAAs with SVR (P = .08) and 96% and 75%, respectively, for non-SVR (P = .01). SVR was associated with improved event-free survival with an adjusted hazard ratio of 0.21 (95% confidence interval, .06-.71; P = .01). Using inverse probability of treatment weighting to match IFN nonresponders with DAA-treated patients, the 24-month event-rate was 1.1% with DAAs compared to 3.4% in IFN nonresponders (P = .005), highlighting the clinical benefit of maximizing SVR. CONCLUSIONS: In IFN-eligible patients, SVR is more commonly achieved with DAAs and confers a similar clinical benefit as in those treated with IFN. The reduced event-rate with DAAs compared to IFN, despite similar disease severity, confirm that SVR alters prognosis leading to improved clinical outcomes.
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 | 0.051 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".