Genetic predictors of the response to the treatment of hepatitis C virus infection
Bibliographic record
Abstract
The genome-wide association studies have identified a strong association between interleukin 28B (IL28B) gene polymorphisms and the response to treatment in patients with hepatitis C virus (HCV) infection. The aim of the study was to evaluate the association between three most widely studied IL28B gene polymorphisms and the response to antiviral treatment of chronic hepatitis C. We performed the genotyping of the three IL28B gene polymorphisms: rs12979860, rs8099917, and rs12980275 in 72 Caucasian patients with chronic hepatitis C, previously treated with the combination therapy of pegylated interferon alpha (PEGIFN α) and ribavirin (RBV). The patients included in the study had finished the treatment regimen at least 6 months before enrolling in the study. We used the sustained viral response (SVR) for the evaluation of the effectiveness of the antiviral treatment, and it was tested with an assay with a sensitivity of 20 IU/mL. An SVR was achieved in 59.7% (43/72) of the treated patients. The three IL28B gene polymorphisms (CC genotype of rs12979860, TT genotype of rs8099917, and AA genotype of rs12980275) were associated with the SVR (p=0.029, p=0.016, and p=0.028, respectively) in the study patients with chronic hepatitis C treated with the combination therapy of PEGIFN α and RBV. The association of IL28B gene polymorphisms with the treatment response points to the possibility of personalized medicine for the treatment of HCV infection.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".