Surveillance for Antiviral Resistant Variants in Chronic Hepatitis C Patients (SEARCH-C)
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|ClinicalTrials.gov Identifier: NCT02065999|
Recruitment Status : Recruiting
First Posted : February 19, 2014
Last Update Posted : August 8, 2018
|Condition or disease|
|Chronic Hepatitis C Infection|
- To analyse for resistance-associated HCV variants in DAA-naïve HCV patients using population and ultra-deep pyrosequencing (UDPS). Resistance associated variants will be analysed by qualitative and quantitative methods both pre-treatment and on-treatment.
- To determine whether in the absence of drug pressure there is variation in the prevalence of naturally occurring resistance associated variants.
- To correlate the presence and frequency of baseline resistance-associated variants with the response to therapy with DAA-based triple therapy regimens for HCV.
- To identify predictors of emergent DAA resistance and treatment failure during therapy with DAA-based combination strategies, including virological, clinical and immunological factors.
- To characterize the natural history of HCV resistance associated variants that are selected during antiviral therapy after the withdrawal of treatment.
- To establish a cohort of DAA-treatment failure patients suitable for re-treatment studies.
- To establish a tissue repository of serum and PBMCs from well-characterized patients treated with DAA-based triple therapy to allow future examination of the role of other variables that may potentially impact on the outcomes of DAA based therapy and development of RAVs.
|Study Type :||Observational|
|Estimated Enrollment :||100 participants|
|Official Title:||Surveillance for Antiviral Resistant Variants in Chronic Hepatitis C Patients|
|Study Start Date :||November 2012|
|Estimated Primary Completion Date :||April 2022|
|Estimated Study Completion Date :||April 2022|
- Prevalence of HCV resistance associated variants (RAVs) and the incidence of RAVs arising during therapy. [ Time Frame: Baseline ]Descriptive statistics will be used to describe RAVs using standard international nomenclature and presented in table form. Baseline clinical and demographic data on subjects will be presented, as will rates of treatment failure and reasons for failure.
- Factors associated with treatment failure due to virological breakthrough / relapse. [ Time Frame: Baseline ]Multivariable logistic regression modelling with backwards elimination will be used to identify factors associated with this.
Biospecimen Retention: Samples With DNA
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT02065999
|Contact: Amanda Erratt||+61 2 9385 email@example.com|
|Contact: Pip Marks, BSc MPH (Hons)||+61 2 9385 firstname.lastname@example.org|
|Australia, New South Wales|
|St Vincent's Hospital||Recruiting|
|Sydney, New South Wales, Australia, 2010|
|Contact: Dianne How Chow +612 8382 3607 email@example.com|
|Principal Investigator: Gail Dr Matthews, MBChB, MRCP (UK), FRACP, PhD|
|St Vincent's Hospital||Recruiting|
|Melbourne, Victoria, Australia, 3065|
|Contact: Alex Dr Thompson, MBBS, FRACP, PhD +61 3 9288 3580 Alexander.THOMPSON@svhm.org.au|
|Principal Investigator: Alex Dr Thompson, MBBS, FRACP, PhD|
|Principal Investigator:||Gail Dr Matthews, MBChB, MRCP (UK), FRACP, PhD||The University of New South Wales|