Daclatasvir and asunaprevir treatment in patients infected by genotype 1b of hepatitis C virus with no or subtle resistant associated substitutions (RAS) in NS5A‐Y93
Bibliographic record
Abstract
In this study, we investigated the real-world data of the first approved interferon-free regimen in Japan, daclatasvir and asunaprevir (DCV+ASV), in chronic hepatitis C patients infected HCV genotype 1b with no or subtle amount of baseline resistant associated substitutions (RAS). Among 924 patients registered in our multicenter study, 750 patients who were proven not to be infected with NS5A-Y93H RAS by direct sequencing and to have no or subtle amount (less than 20%) of NS5A-Y93H RAS by probe assays (Cycleave or PCR invader assay) were included in this study. We investigated the anti-viral effect and factors associated with SVR12. In statistical analysis, P < 0.05 was considered as significant. The SVR12 rate in this population was 92.1% (562/618). Factors associated with SVR12 were male (odds ratio: 2.128; 95%CI: 1.134-4.000, P = 0.019); lower serum γGTP (odds ratio: 1.007; 95%CI: 1.002-1.012, P = 0.006); lower HCV-RNA (odds ratio: 1.848; 95%CI: 1.087-3.145, P = 0.023), and RVR (odds ratio: 6.250; 95%CI: 2.445-15.873, P < 0.001). No patients with γGTP ≧ 80 IU/L without RVR showed SVR12 (0/4, 0%) and one patients with γGTP ≧ 20-< 80 IU/L and HCV-RNA ≧ 6.5 logIU/mL without RVR (5/10, 50%) and two female patients with RVR but γGTP ≧ 80 IU/L and HCV-RNA ≧ 6.5 logIU/mL (7/13, 53.8%) showed a low SVR12 rate. In the present study, we showed a good viral response with DCV-ASV treatment and identified four predictive factors associated with SVR12. These four markers could be a good predictive markers for the viral effect of this treatment regimen in patients with no or subtle amount of RAS in NS5A-Y93.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".