A Formula to Estimate the Optimal Dosage of Ribavirin for the Treatment of Chronic Hepatitis C: Influence of Itpa Polymorphisms

Krishnan, Sheeja M.; Dixit, Narendra M.

doi:10.3851/imp2251

Cited by 6 publications

(7 citation statements)

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“…The model presented in the current work accounts for ribavirin's systemic PK, in contrast to previously reported models, allowing different dosing regimens to be simulated. Furthermore, covariate effects of sex and ITPA and IL28B genetics were incorporated into the anemia model, in addition to the previously reported effects of weight, creatinine clearance, sex, telaprevir use, and ITPA phenotype on the plasma PK, and the effects of ITPA phenotype on RBC phosphorylation .…”

Section: Discussionmentioning

confidence: 99%

“…Mathematical models of ribavirin‐induced anemia have been reported previously by Tod et al . and Krishnan and Dixit . The Tod model uses a maximum effect model of ribavirin dosage administration rate stimulating the elimination of hemoglobin, and a static proportional term describing the feedback that increases hemoglobin production under ribavirin treatment.…”

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confidence: 99%

“…The first version of the Krishnan and Dixit model uses partial differential equations, whereas the second version (ref. ) simplifies the model to ordinary differential equations with very similar parameter estimates. Rather than using the dosage administration rate or empirical accumulation equation, our approach links the previously published model of plasma and intracellular ribavirin phosphorylation kinetics to the effect of RTP accumulation on RBC homeostasis.…”

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confidence: 99%

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Modeling Ribavirin‐Induced Anemia in Patients with Chronic Hepatitis C Virus

Jimmerson

MacBrayne

et al. 2016

CPT Pharmacometrics Syst. Pharmacol.

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Ribavirin remains an important component of hepatitis C treatment in certain clinical scenarios, but it causes hemolytic anemia. A quantitative understanding of the ribavirin exposure‐anemia relationship is important in dose individualization/optimization. We developed a model relating ribavirin triphosphate (RTP) exposure in red blood cells (RBCs), RBC lifespan, feedback regulation of RBC production when anemia occurs, and the resulting hemoglobin decline. Inosine triphosphatase (ITPA) and interleukin 28B (IL28B) genetics were found to be significant covariates. Clinical trial simulations predicted that anemia is least severe in IL28B non‐CC (rs12979860, CT or TT), ITPA variant subjects, followed by IL28B non‐CC, ITPA wild‐type, IL28B CC, ITPA variant, and IL28B CC, ITPA wild‐type subjects (most severe). Reducing the ribavirin dose from 1,200/1,000 mg to 800/600 mg could reduce the proportions of grade 2 anemia by about half. The resulting model framework will aid the development of dosing strategies that minimize the incidence of anemia in treatment regimens that include ribavirin.

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Section: Discussionmentioning

confidence: 99%

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Modeling Ribavirin‐Induced Anemia in Patients with Chronic Hepatitis C Virus

Jimmerson

MacBrayne

et al. 2016

CPT Pharmacometrics Syst. Pharmacol.

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“…The role of ribavirin in improving SVR in combination with interferon was described assuming that ribavirin rendered virions noninfectious . Models that suggested optimal ribavirin usage, which kept its key side effect, hemolytic anemia, tolerable, were also constructed . Homeostatic proliferation of hepatocytes was incorporated to explain the triphasic decline of viremia observed in some patients .…”

Section: Interferon At the Infected Individual Levelmentioning

confidence: 99%

Interferon at the cellular, individual, and population level in hepatitis C virus infection: Its role in the interferon‐free treatment era

Raja

Baral

Dixit

2018

Immunological Reviews

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The advent of powerful direct-acting antiviral agents (DAAs) has revolutionized the treatment of hepatitis C. DAAs cure nearly all patients with short duration, oral treatments. Significant efforts are now underway to optimize DAA-based treatments. We discuss the potential role of interferon in this optimization. Clinical studies present compelling evidence that DAAs perform better in treatment-naive individuals than in individuals who previously failed treatment with interferon, a surprising correlation because interferon and DAAs are thought to act independently. Recent mathematical models explore a mechanistic hypothesis underlying this correlation. The hypothesis invokes the action of interferon at the cellular, individual, and population levels. Strong interferon responses prevent the productive infection of cells, reduce viral replication, and impede the development of resistance to DAAs in infected individuals and improve cure rates elicited by DAAs in treated populations. The models develop descriptions of these processes, integrate them into a comprehensive framework, and capture clinical data quantitatively, providing a successful test of the hypothesis. Individuals with strong endogenous interferon responses thus present a promising subpopulation for reducing DAA treatment durations. This review discusses the conceptual advances made by the models, highlights the new insights they unravel, and examines their applicability to optimize DAA-based treatments.

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“…Identifying patients at high risk of anemia is crucial for improving patient compliance and SOC outcomes for CHC patients ( 12 ). Novel treatment strategies or algorithms based on a combination of relevant pharmacogenetics and host factors may facilitate patient counseling prior to anemia events ( 13 ). However, limited studies included predictive modeling of severe anemia (hemoglobin, Hb < 10 g/dL) based on an index incorporating the strong predictor, ITPA SNP status ( 14 , 15 ).…”

Section: Introductionmentioning

confidence: 99%

An Index to Predict Ribavirin-Induced Anemia in Asian Patients With Chronic Genotype 1 Hepatitis C

Chen¹,

Peng²,

Lai³

et al. 2015

Hepat Mon

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Background:Single-nucleotide polymorphisms (SNP) in the inosine triphosphate pyrophosphatase (ITPA) gene correlate with ribavirin (RBV)-induced anemia in patients with chronic hepatitis C (CHC) receiving combination therapy. Managing anemia is an early priority in the treatment process.Objectives:The aim was to develop a predictive index based on ITPA SNP status to identify CHC patients at risk of anemia.Patients and Methods:A total of 418 eligible East Asian patients diagnosed with CHC genotype 1 (G1) received combination therapy in this study. Participant DNA was genotyped for a functional ITPA SNP (C/C, A/A or C/A) on chromosome 20 at rs1127354. A predictive index was constructed by incorporating independent factors identified for severe anemia events (hemoglobin < 10 g/dL). Areas under the receiver-operating characteristic curves (AUCs) represented the diagnostic accuracies of the predictive index in randomly assigned development and validation cohorts.Results:Multiple logistic regressions identified age (≥ 50 y: OR = 9.7, 95% CI = 5.0 - 18.6), ITPA rs1127354 (C/C: OR = 3.3, 95% CI = 1.8 - 5.8) and baseline hemoglobin (< 14.0 g/dL: OR 6.4, 95% CI = 3.3 - 12.1; 14.0 - 14.9: OR = 2.4, 95% CI = 1.2 - 4.6) as predictors of severe anemia throughout the treatment. For severe anemia, the predictive index incorporating age, ITPA SNP status and baseline hemoglobin yielded diagnostic accuracies (AUCs) of 0.830 (95% CI = 0.783 - 0.871) in the development (n = 324) and 0.902 (0.826 - 0.925) in the validation (n = 81) cohorts.Conclusions:In patients with CHC G1 and receiving combination therapy, ITPA SNP-based index was an accurate and practical solution for prediction of severe anemia.

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A Formula to Estimate the Optimal Dosage of Ribavirin for the Treatment of Chronic Hepatitis C: Influence of Itpa Polymorphisms

Cited by 6 publications

References 47 publications

Modeling Ribavirin‐Induced Anemia in Patients with Chronic Hepatitis C Virus

Modeling Ribavirin‐Induced Anemia in Patients with Chronic Hepatitis C Virus

Interferon at the cellular, individual, and population level in hepatitis C virus infection: Its role in the interferon‐free treatment era

An Index to Predict Ribavirin-Induced Anemia in Asian Patients With Chronic Genotype 1 Hepatitis C

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