Modeling based response guided therapy in subjects with recent hepatitis C infection.


Journal

Antiviral research
ISSN: 1872-9096
Titre abrégé: Antiviral Res
Pays: Netherlands
ID NLM: 8109699

Informations de publication

Date de publication:
08 2020
Historique:
received: 05 02 2020
revised: 15 06 2020
accepted: 16 06 2020
pubmed: 28 6 2020
medline: 17 7 2021
entrez: 28 6 2020
Statut: ppublish

Résumé

Mathematical modeling of viral kinetics has been shown to identify patients with chronic hepatitis C virus (HCV) infection who could be cured with a shorter duration of direct-acting antiviral (DAA) treatment. However, modeling therapy duration has yet to be evaluated in recently infected individuals. The aim of this study was to retrospectively examine whether modeling can predict outcomes of six-week sofosbuvir (SOF) and weight-based ribavirin (R) therapy in individuals with recent HCV infection. Modeling was used to estimate viral host parameters and to predict time to cure for 12 adults with recent HCV infection (<12 months of infection) who received six weeks of treatment with SOF + R. Modeling results yielded a 100% negative predictive value for SOF + R treatment response in nine participants and suggested that a median of 13 [interquartile range: 8-16] weeks of therapy would be required for these patients to achieve cure. Modeling predicted cure after 5 weeks of therapy in the only modeled participant who achieved a sustained virological response. However, cure was also predicted for two participants who relapsed following treatment. The modeling results confirm that longer than 6 weeks of SOF + R is needed to reach cure in individuals with recent HCV infection. Prospective real-time modeling under current potent DAA regimens is needed to validate the potential of response-guided therapy in the management of recent HCV infection.

Sections du résumé

BACKGROUND & AIMS
Mathematical modeling of viral kinetics has been shown to identify patients with chronic hepatitis C virus (HCV) infection who could be cured with a shorter duration of direct-acting antiviral (DAA) treatment. However, modeling therapy duration has yet to be evaluated in recently infected individuals. The aim of this study was to retrospectively examine whether modeling can predict outcomes of six-week sofosbuvir (SOF) and weight-based ribavirin (R) therapy in individuals with recent HCV infection.
METHODS
Modeling was used to estimate viral host parameters and to predict time to cure for 12 adults with recent HCV infection (<12 months of infection) who received six weeks of treatment with SOF + R.
RESULTS
Modeling results yielded a 100% negative predictive value for SOF + R treatment response in nine participants and suggested that a median of 13 [interquartile range: 8-16] weeks of therapy would be required for these patients to achieve cure. Modeling predicted cure after 5 weeks of therapy in the only modeled participant who achieved a sustained virological response. However, cure was also predicted for two participants who relapsed following treatment.
CONCLUSIONS
The modeling results confirm that longer than 6 weeks of SOF + R is needed to reach cure in individuals with recent HCV infection. Prospective real-time modeling under current potent DAA regimens is needed to validate the potential of response-guided therapy in the management of recent HCV infection.

Identifiants

pubmed: 32592829
pii: S0166-3542(20)30276-X
doi: 10.1016/j.antiviral.2020.104862
pmc: PMC7387218
mid: NIHMS1607293
pii:
doi:

Substances chimiques

Antiviral Agents 0
RNA, Viral 0
Ribavirin 49717AWG6K
Sofosbuvir WJ6CA3ZU8B

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

104862

Subventions

Organisme : NIAID NIH HHS
ID : R01 AI078881
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM121600
Pays : United States

Informations de copyright

Copyright © 2020 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest GVM advises, is on the speakers' bureau, and received grants from Gilead. She is on the speakers’ bureau and received grants from AbbVie and Bristol-Myers Squibb. She received grants from Janssen. HD has consulted for CoCrystal Inc. None of the other authors has any financial interest or conflict of interest related to this research.

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Auteurs

Evan Gorstein (E)

The Program for Experimental and Theoretical Modeling, Division of Hepatology, Department of Medicine, Stritch School of Medicine, Loyola University Medical Center, Maywood, IL, 60053, USA.

Marianne Martinello (M)

Kirby Institute, University of New South Wales, Sydney, NSW, Australia.

Alexander Churkin (A)

Department of Software Engineering, Sami Shamoon College of Engineering, Beer-Sheva, Israel.

Swikriti Dasgupta (S)

The Program for Experimental and Theoretical Modeling, Division of Hepatology, Department of Medicine, Stritch School of Medicine, Loyola University Medical Center, Maywood, IL, 60053, USA.

Kevin Walsh (K)

The Program for Experimental and Theoretical Modeling, Division of Hepatology, Department of Medicine, Stritch School of Medicine, Loyola University Medical Center, Maywood, IL, 60053, USA.

Tanya L Applegate (TL)

Kirby Institute, University of New South Wales, Sydney, NSW, Australia.

David Yardeni (D)

Soroka University Medical Center, Beer Sheva, Israel.

Ohad Etzion (O)

Soroka University Medical Center, Beer Sheva, Israel.

Susan L Uprichard (SL)

The Program for Experimental and Theoretical Modeling, Division of Hepatology, Department of Medicine, Stritch School of Medicine, Loyola University Medical Center, Maywood, IL, 60053, USA.

Danny Barash (D)

Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, Israel.

Scott J Cotler (SJ)

The Program for Experimental and Theoretical Modeling, Division of Hepatology, Department of Medicine, Stritch School of Medicine, Loyola University Medical Center, Maywood, IL, 60053, USA.

Gail V Matthews (GV)

Kirby Institute, University of New South Wales, Sydney, NSW, Australia.

Harel Dahari (H)

The Program for Experimental and Theoretical Modeling, Division of Hepatology, Department of Medicine, Stritch School of Medicine, Loyola University Medical Center, Maywood, IL, 60053, USA. Electronic address: hdahari@luc.edu.

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Classifications MeSH