Recent Advances in Pegylated Interferon Antiviral Therapy of Chronic Hepatitis C
Bibliographic record
Abstract
Effective hepatitis C antiviral treatment is important given the significant global morbidity and mortality from liver-related complications. Therapy for hepatitis C has advanced remarkably in the past two decades starting with interferon- alpha (IFN) monotherapy, followed by genetically engineered recombinant interferons (consensus IFN alpha) and subsequently IFN alpha in combination with the nucleoside analog ribavirin. The current gold standard is a combination of long-acting pegylated interferon (PEG-IFN) with ribavirin achieving a sustained virological response (SVR) with acceptable safety profiles in 54-66% of patients. These therapies have significantly contributed to our armamentarium against hepatitis C virus infection. Despite this success some subgroups have lower response rates (i.e. previous IFN nonresponders, patients with genotype 1 or cirrhosis). Moreover, the question of a “true SVR ” has been raised. Recent studies confirming detection of residual HCV RNA using ultra-sensitive polymerase chain reaction (PCR) based assays in patients many years after complete clinical resolution of chronic hepatitis C raise concerns whether these patients have actually been cured. In this paper we review the natural history, epidemiology and basic virology of hepatitis C. Current treatments and long-term benefits of achieving a SVR, including the antiviral and anti-inflammatory effects of IFN are also explored. Finally, we review the current understanding of persistent occult viremia in patients apparently cleared of HCV after achieving SVR with antiviral treatment. Keywords: Peginterferon, ribavirin, sustained virological response, occult, persistence
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.002 |
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".