Skip to main content
padlock icon - secure page this page is secure

Open Access STOP-HCV - Stratified Medicine to Optimise Treatment for Hepatitis C Virus Infection

Download Article:
(PDF 148.6 kb)
With funding from the Medical Research Council we have established a consortium - STOP-HCV - to explore the use of personalised medicine as a tool to improve clinical outcomes and patient management for patients with HCV infection. STOP-HCV brings together experts in the fields of Hepatitis C, genomics and big data from all across the UK. It is a national collaboration between researchers, clinicians, patient groups and industrial representatives.

Approximately 300,000 people in the UK are infected with HCV, only half of whom have been diagnosed as carrying the virus. The virus has a high tendency to persist, as the body's immune system is usually unable to clear infection. HCV exists in different genetic forms called genotypes. In the UK, most infections are caused by either genotype 1 (gt1) or 3 (gt3), which occur at about equal frequency. HCV infects the liver, causing liver cirrhosis (scarring), liver failure and liver cancer.

In the past, treatment for HCV consisted of two drugs: interferon and ribavirin. This was typically a long-course treatment (24 weeks), with unpleasant side-effects, and only a ∼60% chance of cure. The development and launch of direct-acting antiviral (DAA) drugs in 2012 revolutionised treatment for Hepatitis C. These DAAs (now in their third generation) are an all-oral treatment regime, which can be taken for shorter durations of time and have cure rates of over 95%. Third generation DAAs are effective against all genotypes of HCV. However, HCV gt3 infection remains notoriously more difficult to treat, especially in patients that have severe liver disease. A small, but significant, proportion of patients (especially those with severe liver disease) continue to fail DAA treatment.

STOP-HCV's objectives are 4 fold: 1) Through the use of stratified medicine, understand how factors such as viral genetics, viral load, immune parameters, host genetics and other biomarkers affect treatment of hepatitis C and the management of liver disease; 2) Develop clinical studies and prognostic models to predict treatment response and utilise patient information to establish the most effective and cost-effective hepatitis C treatment regimes; 3) Optimise treatment regimes to patients - individual characteristics in a bid to ultimately eradicate the hepatitis C virus and 4) To use stratified medicine technologies to predict the progression or regression of liver disease and the development of liver cancer after viral clearance.
No References for this article.
No Supplementary Data.
No Article Media
No Metrics


Document Type: Research Article

Publication date: August 1, 2017

More about this publication?
  • Impact is a series of high-quality, open access and free to access science reports designed to enable the dissemination of research impact to key stakeholders. Communicating the impact and relevance of research projects across a large number of subjects in a content format that is easily accessible by an academic and stakeholder audience. The publication features content from the world's leading research councils, policy groups, universities and research projects. Impact is published under a CC-BY Creative Commons licence.

  • Subscribe to this Title
  • Terms & Conditions
  • Disseminating research in Impact
  • Information about Impact
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more