TY - JOUR
T1 - Modeling the effect of HIV coinfection on clearance and sustained virologic response during treatment for hepatitis C virus
AU - Birger, Ruthie
AU - Kouyos, Roger
AU - Dushoff, Jonathan
AU - Grenfell, Bryan
N1 - Funding Information:
We thank Professors Andrea Graham and Simon Levin, Department of Ecology and Evolutionary Biology, Princeton University for their helpful comments and insights. R.B. was supported by the Princeton University, Department of Ecology and Evolutionary Biology . R.D.K. was supported by the Swiss National Science Foundation # PZ00P3-142411 . B.G. was supported by the Bill and Melinda Gates Foundation and the RAPIDD program of the Science and Technology Directorate, U.S. Department of Homeland Security , and the Fogarty International Center, NIH .
Publisher Copyright:
© 2015 The Authors.
PY - 2015/9/1
Y1 - 2015/9/1
N2 - Background: HIV/hepatitis C (HCV) coinfection is a major concern in global health today. Each pathogen can exacerbate the effects of the other and affect treatment outcomes. Understanding the within-host dynamics of these coinfecting pathogens is crucial, particularly in light of new, direct-acting antiviral agents (DAAs) for HCV treatment that are becoming available. Methods and findings: In this study, we construct a within-host mathematical model of HCV/HIV coinfection by adapting a previously published model of HCV monoinfection to include an immune system component in infection clearance. We explore the effect of HIV-coinfection on spontaneous HCV clearance and sustained virologic response (SVR) by building in decreased immune function with increased HIV viral load. Treatment is modeled by modifying HCV burst-size, and we use clinically-relevant parameter estimates. Our model replicates real-world patient outcomes; it outputs infected and uninfected target cell counts, and HCV viral load for varying treatment and coinfection scenarios. Increased HIV viral load and reduced CD4+ count correlate with decreased spontaneous clearance and SVR chances. Treatment efficacy/duration combinations resulting in SVR are calculated for HIV-positive and negative patients, and crucially, we replicate the new findings that highly efficacious DAAs reduce treatment differences between HIV-positive and negative patients. However, we also find that if drug efficacy decays sufficiently over treatment course, SVR differences between HIV-positive and negative patients reappear. Conclusions: Our model shows theoretical evidence of the differing outcomes of HCV infection in cases where the immune system is compromised by HIV. Understanding what controls these outcomes is especially important with the advent of efficacious but often prohibitively expensive DAAs. Using a model to predict patient response can lend insight into optimal treatment design, both in helping to identify patients who might respond well to treatment and in helping to identify treatment pathways and pitfalls.
AB - Background: HIV/hepatitis C (HCV) coinfection is a major concern in global health today. Each pathogen can exacerbate the effects of the other and affect treatment outcomes. Understanding the within-host dynamics of these coinfecting pathogens is crucial, particularly in light of new, direct-acting antiviral agents (DAAs) for HCV treatment that are becoming available. Methods and findings: In this study, we construct a within-host mathematical model of HCV/HIV coinfection by adapting a previously published model of HCV monoinfection to include an immune system component in infection clearance. We explore the effect of HIV-coinfection on spontaneous HCV clearance and sustained virologic response (SVR) by building in decreased immune function with increased HIV viral load. Treatment is modeled by modifying HCV burst-size, and we use clinically-relevant parameter estimates. Our model replicates real-world patient outcomes; it outputs infected and uninfected target cell counts, and HCV viral load for varying treatment and coinfection scenarios. Increased HIV viral load and reduced CD4+ count correlate with decreased spontaneous clearance and SVR chances. Treatment efficacy/duration combinations resulting in SVR are calculated for HIV-positive and negative patients, and crucially, we replicate the new findings that highly efficacious DAAs reduce treatment differences between HIV-positive and negative patients. However, we also find that if drug efficacy decays sufficiently over treatment course, SVR differences between HIV-positive and negative patients reappear. Conclusions: Our model shows theoretical evidence of the differing outcomes of HCV infection in cases where the immune system is compromised by HIV. Understanding what controls these outcomes is especially important with the advent of efficacious but often prohibitively expensive DAAs. Using a model to predict patient response can lend insight into optimal treatment design, both in helping to identify patients who might respond well to treatment and in helping to identify treatment pathways and pitfalls.
KW - Antiviral therapy
KW - Coinfection
KW - HCV-HIV
KW - Immune response
KW - Mathematical model
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U2 - 10.1016/j.epidem.2015.04.001
DO - 10.1016/j.epidem.2015.04.001
M3 - Article
C2 - 26342237
AN - SCOPUS:84940793487
SN - 1755-4365
VL - 12
SP - 1
EP - 10
JO - Epidemics
JF - Epidemics
ER -