<i><scp>HCV E1E</scp>2‐<scp>MF</scp>59</i> vaccine in chronic hepatitis <scp>C</scp> patients treated with <scp>PEG</scp>‐<scp>IFN</scp>α2a and <scp>R</scp>ibavirin: a randomized controlled trial
Bibliographic record
Abstract
Hepatitis C virus (HCV) vaccines may be able to increase viral clearance in combination with antiviral therapy. We analysed viral dynamics and HCV-specific immune response during retreatment for experienced patients in a phase Ib study with E1E2MF59 vaccine. Seventy-eight genotype 1a/1b patients [relapsers (30), partial responders (16) and nonresponders (32) to interferon-(IFN)/ribavirin-(RBV)] were randomly assigned to vaccine (V:23), Peg-IFNα2a-180-ug/qw and ribavirin 1000-1200-mg/qd for 48 weeks (P/R:25), or their combination (P/R + V:30). Vaccine (100 μg/0.5 mL) was administered intramuscularly at week 0-4-8-12-24-28-32-36. Neutralizing of binding (NOB) antibodies and lymphocyte proliferation assay (LPA) for E1E2-specific-CD4 + T cells were performed at week 0-12-16-48. Viral kinetics were analysed up to week 16. The vaccine was safe, and a sustained virological response (SVR) was achieved in 4 P/R + V and 2 P/R patients. Higher SVR rates were observed in prior relapsers (P/R + V = 27.3%; P/R = 12.5%). Higher NOB titres and LPA indexes were found at week 12 and 16 in P/R + V as compared to P/R patients (P = 0.023 and 0.025, P = 0.019 and <0.001, respectively). Among the 22 patients with the strongest direct antiviral effects of IFN (ε ≥ 0.800), those treated with P/R + V (10) reached lower HCV-RNA levels (P = 0.026) at week 16. HCV E1E2MF59 vaccine in combination with Peg-IFNα2a + RBV was safe and elicited E1E2 neutralizing antibodies and specific CD4 + T cell proliferation. Upon early response to IFN, vaccinations were associated with an enhanced second phase viral load decline. These results prompt phase II trials in combination with new antiviral therapies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".