ArticleHepatic medicine : evidence and research2010
Potential treatment options and future research to increase hepatitis C virus treatment response rate.
Article in Hepatic medicine : evidence and research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- A systematic review of treatment response rates in Pakistani hepatitis C virus patients; current prospects and future challenges.Medicine · 2016Pooled it
- A pharmacokinetic/viral kinetic model to evaluate the treatment effectiveness of danoprevir against chronic HCV.Antiviral therapy · 2015Trial
- Article
- A New Model for the Dynamics of Hepatitis C Infection: Derivation, Analysis and Implications.Viruses · 2018Review
- Oxidative stress modulation in hepatitis C virus infected cells.World journal of hepatology · 2015Review
- Emerging therapeutic options for the management of hepatitis C infection.World journal of gastroenterology · 2014Review
- Hepatitis C viral kinetics: the past, present, and future.Clinics in liver disease · 2013Review
- Identification of hepatitis C virus inhibitors targeting different aspects of infection using a cell-based assay.Antimicrobial agents and chemotherapy · 2012Article
- New hepatitis C virus drug discovery strategies and model systems.Expert opinion on drug discovery · 2012Review
- Permissiveness of human hepatoma cell lines for HCV infection.Virology journal · 2012Article
- Hepatitis C Viral Kinetics in the Era of Direct Acting Antiviral Agents and IL28B.Current hepatitis reports · 2011Article
- Hepatitis C virus experimental model systems and antiviral drug research.Virologica Sinica · 2010Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Hepatitis C virus (HCV) is a liver-tropic blood-borne pathogen that affects more than 170 million people worldwide. Although acute infections are usually asymptomatic, up to 90% of HCV infections persist with the possibility of long-term consequences such as liver fibrosis, cirrhosis, steatosis, insulin resistance, or hepatocellular carcinoma. As such, HCV-associated liver disease is a major public health concern. Although the currently available standard of care therapy of pegylated interferon α plus ribavirin successfully treats infection in a subset of patients, the development of more effective, less toxic HCV antivirals is a health care imperative. This review not only discusses the limitations of the current HCV standard of care but also evaluates upcoming HCV treatment options and how current research elucidating the viral life cycle is facilitating the development of HCV-specific therapeutics that promise to greatly improve treatment response rates both before and after liver transplantation.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.