Concordance of sustained virological response 4, 12, and 24 weeks post‐treatment with sofosbuvir‐containing regimens for hepatitis C virus
Bibliographic record
Abstract
UNLABELLED: Historically, clinical trials of regimens to treat chronic infection with hepatitis C virus (HCV) have used, as their primary efficacy endpoint, a sustained virological response (SVR)—defined as HCV RNA levels below a designated threshold of quantification—24 weeks after the end of treatment (SVR24). More recently, regulatory authorities have begun to accept SVR at 12 weeks post-treatment (SVR12) as a valid efficacy endpoint because of its high rate of concordance with SVR24. However, the concordance between SVR12 and SVR24 has not been systematically assessed with new regimens of recently approved direct-acting antiviral agents. The aim of this study was to assess the concordance between SVR at various post-treatment time points in phase III clinical trials of sofosbuvir (SOF)-containing regimens. We conducted a retrospective analysis of five trials enrolling 863 patients infected with HCV genotypes 1-6. The concordance between SVR at 4 weeks post-treatment (SVR4) and SVR12, and between SVR12 and SVR24, were determined, as well as positive predictive values (PPVs) and negative predictive values (NPVs). Overall, 779 of 796 patients (98.0%) with an SVR4 also achieved an SVR12, making the PPV of SVR4 for SVR12 98% and the NPV 100%. Of the 779 patients with an SVR12, 777 (99.7%) also achieved an SVR24, making the PPV of SVR12 for SVR24 >99% and the NPV 100%. Of patients who relapsed post-therapy, 77.6% did so within 4 weeks of completing therapy. CONCLUSION: Data from phase III studies demonstrate that with SOF-based regimens, with or without interferon, SVR12 and SVR24 correlate closely. Thus, SVR12 can be used effectively to determine "cure" rates in trials and in clinical practice.
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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 | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".