Treatment of Hepatitis C in HIV Patients in the New Era of Direct-Acting Antivirals

The impact of HCV therapy in a high HIV-HCV prevalence population: A modeling study on people who inject drugs in Ho Chi Minh City, Vietnam

BACKGROUND

Human Immunodeficiency Virus (HIV) and Hepatitis C Virus (HCV) coinfection is a major global health problem especially among people who inject drugs (PWID), with significant clinical implications. Mathematical models have been used to great effect to shape HIV care, but few have been proposed for HIV/HCV.

METHODS

We constructed a deterministic compartmental ODE model that incorporated layers for HIV disease progression, HCV disease progression and PWID demography. Antiretroviral therapy (ART) and Methadone Maintenance Therapy (MMT) scale-ups were modeled as from 2016 and projected forward 10 years. HCV treatment roll-out was modeled beginning in 2026, after a variety of MMT scale-up scenarios, and projected forward 10 years.

RESULTS

Our results indicate that scale-up of ART has a major impact on HIV though not on HCV burden. MMT scale-up has an impact on incidence of both infections. HCV treatment roll-out has a measurable impact on reductions of deaths, increasing multifold the mortality reductions afforded by just ART/MMT scale-ups.

CONCLUSION

HCV treatment roll-out can have major and long-lasting effects on averting PWID deaths on top of those averted by ART/MMT scale-up. Efficient intervention scale-up of HCV alongside HIV interventions is critical in Vietnam.

Modeling the effect of HIV coinfection on clearance and sustained virologic response during treatment for hepatitis C virus

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.