Early prediction of sustained virological response at day 3 of treatment with albinterferon‐α‐2b in patients with genotype 2/3 chronic hepatitis C
Bibliographic record
Abstract
BACKGROUND: Albinterferon-alpha-2b (albIFN) is a long-acting fusion polypeptide composed of albumin and IFN-alpha-2b. In a phase 2 study of albIFN 1500 mug q2wk or q4wk in patients with genotype 2/3 chronic hepatitis C, albIFN demonstrated sustained virological response (SVR) rates of 62-77% (intent-to-treat population). AIMS: To assess the association of initial viral kinetics during albIFN therapy with baseline factors and SVR prediction. METHODS: In all, 43 patients were treated with albIFN 1500 mug (q2wk/q4wk) plus ribavirin (RBV) 800 mg/day for 24 weeks. Hepatitis C virus (HCV)-RNA levels were measured by real-time polymerase chain reaction, insulin resistance by homeostasis model assessment of insulin resistance (HOMA-IR) and serum albIFN levels by enyzme-linked immunosorbent assay. Prediction analysis was performed in a per protocol 28-patient subset who were > or =80% adherent to albIFN/RBV and had HCV-RNA levels measured at treatment day 3. RESULTS: Day-3 HCV-RNA level and first-phase viral decline as well as second-phase slope of viral decline were significantly associated with SVR. In adherent patients, 82.1% had a day-3 viral load <4.2 log(10) IU/ml or first-phase decline >1.25 log(10) IU/ml, which was predictive of SVR, both positively (95.7%; sensitivity: 100%) and negatively (100%; specificity: 83.3%). As low first-phase decline was associated with a high pretreatment HOMA-IR index (P=0.004) and a low day-3 serum albIFN level (P=0.01). CONCLUSIONS: First-phase viral decline with albIFN/RBV was predictive of SVR in this study and may be modulated in part by IR.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".