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Modelling how ribavirin improves interferon response rates in hepatitis C virus infection

Abstract

Nearly 200 million individuals worldwide are currently infected with hepatitis C virus (HCV)1. Combination therapy with pegylated interferon and ribavirin, the latest treatment for HCV infection, elicits long-term responses in only about 50% of patients treated2,3,4. No effective alternative treatments exist for non-responders5. Consequently, significant efforts are continuing to maximize response to combination therapy6,7. However, rational therapy optimization is precluded by the poor understanding of the mechanism(s) of ribavirin action against HCV8. Ribavirin alone induces either a transient early decline or no decrease in HCV viral load9,10,11,12, but in combination with interferon it significantly improves long-term response rates2,3,4,13,14,15. Here we present a model of HCV dynamics in which, on the basis of growing evidence16,17,18,19,20,21, we assume that ribavirin decreases HCV infectivity in an infected individual in a dose-dependent manner. The model quantitatively predicts long-term response rates to interferon monotherapy and combination therapy, fits observed patterns of HCV RNA decline in patients undergoing therapy, reconciles conflicting observations of the influence of ribavirin on HCV RNA decline, provides key insights into the mechanism of ribavirin action against HCV, and establishes a framework for rational therapy optimization.

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Figure 1: Theoretical viral load decay profiles.
Figure 2: Comparison of theoretical viral load decay profiles with patient data.
Figure 3: Model predictions of ETR and SVR.

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Acknowledgements

We thank R. M. Ribeiro, J.-M. Pawlotsky, S. Zeuzem, X. Tong and B. Malcolm for helpful comments. Portions of this work were performed under the auspices of the US Department of Energy and supported by grants from the NIH, the University of Illinois and the Chicago VA.

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Correspondence to Alan S. Perelson.

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The authors declare that they have no competing financial interests.

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Supplementary Notes

Contains Supplementary Notes S1–S5, additional comments on the text. (DOC 25 kb)

Supplementary Tables S1–S3

Supplementary Table 1: Best-fit parameter estimates obtained from comparisons of model predictions with experimental viral load data from 17 patients who were given high dose daily interferon along with 1000 or 1200 mg ribavirin daily for the first 28 days of therapy; Supplementary Table 2: Model calculations of end-of-treatment (ETR) and sustained virological responses (SVR) for different initial viral loads, V0, interferon effectiveness, ε, and durations of treatment (24 or 48 weeks), with and without ribavirin; Supplementary Table 3: Estimates of ETR and SVR values as percentages of patients who completed therapy in various studies. (DOC 154 kb)

Supplementary Figure S1

Contains Supplementary Figure S1 and legends. (DOC 1041 kb)

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Dixit, N., Layden-Almer, J., Layden, T. et al. Modelling how ribavirin improves interferon response rates in hepatitis C virus infection. Nature 432, 922–924 (2004). https://doi.org/10.1038/nature03153

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