Effectiveness and cost-effectiveness of initial combination therapy with interferon/peginterferon plus ribavirin in patients with chronic hepatitis C in Germany: A health technology assessment commissioned by the German Federal Ministry of Health and Social Security

Siebert, Uwe; Sroczynski, Gaby

doi:10.1017/s0266462305050075

Cited by 39 publications

(22 citation statements)

References 46 publications

(89 reference statements)

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“…Our studies are in accordance with those carried by Zeuzem; who did find heterogeneous virological response rates to interferon-based therapy in patients with chronic hepatitis C based on genotypes and subtypes of HCV [37,41]. Hence then virus clearance rates are variable different depending on viral genotypes and that could be used to monitor HCV therapy.…”

Section: Discussionsupporting

confidence: 90%

The role of hepatitis C virus genotyping in evaluating the efficacy of INF-based therapy used in treating hepatitis C infected patients in Libya

Daw¹,

Elasifer²,

Dau³

et al. 2013

Virol Discov

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Background: Hepatitis C virus (HCV) therapy has been evolved over years and many parameters were used to evaluate such therapy particularly genotyping. In North Africa and Eastern Mediterranean the genotypes vary from most of world and rarely studies were conducted to assess the influence of such genotypes on the HCV therapy. Aims: This study was designed to determine; the role of HCV genotyping in assessing the efficacy of interferon therapy and to analyze the rates of sustained virological response (SVR) in INF and PegIFN-based regimens according on HCV genotype infecting Libyan patients with chronic hepatitis C infection. Methods: A total of 479 patients with chronic HCV registered at Tripoli Medical Centre were treated with 'INF alfa or PEG-INF-Pegylated INF alfa 2a in combination with ribavirin' for a five year period. These patients were registered and followed up from January 2007 to October 2012. The information were reviewed and data were collected from each patient regarding age, gender, ALT level, and viral load, viral genotype using qualitative PCR. The statistical analysis were carried using SPSS version 11.5. Results: Of the patients studied 86 patients were treated with INF based regimen, only 54% of them had end treatment response (ETR) and 28% had SVR. Off 143 patients treated with peg-INF alfa 2a based therapy; 69% had ETR and 36% had SVR. The SVR of Peg-INF based regimen was higher than INF based regimen in all genotypes except for genotype 4. The relationship between SVR and gender was significant in patients who were given INF based therapy comparable to PEG INF based regimen, though the relationship between SVR and age, basal viral load and basal ALT were also reported in both regimens. Conclusions: HCV genotyping has been found to play an important valuable role in determining the efficacy of Hepatitis C therapy. SVR vary according to the HCV genotype involved. HCV genotype 1 and 4 were found to be the prevalent resistant genotypes infecting Libyan patients. Such findings are particularly important in guiding the clinical therapy of patients infected with hepatitis C virus.

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Section: Discussionsupporting

confidence: 90%

The role of hepatitis C virus genotyping in evaluating the efficacy of INF-based therapy used in treating hepatitis C infected patients in Libya

Daw¹,

Elasifer²,

Dau³

et al. 2013

Virol Discov

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“…An STM disease process should reflect the disease's natural history, expected prognostic pathways in the absence of intervention, and treatment effects [31][32][33].…”

Section: Treatmentmentioning

confidence: 99%

“…An efficient and transparent way to model such events is as a decision tree preceding the STM, unless there are justified reasons for representing them within the states. When events are modeled preceding an STM, the time spent before entering the STM should be captured appropriately by giving credit to the starting cohorts for the time elapsed (e.g., an up-front decision tree could be used to represent results and subsequent outcomes from diagnostic test strategies [29], or treatments with limited duration [33], or initial coronary interventions [31] ; Fig. 3).…”

Section: Defining Statesmentioning

confidence: 99%

State-Transition Modeling: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-3

et al. 2012

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State-transition modeling is an intuitive, flexible, and transparent approach of computer-based decision-analytic modeling including both Markov model cohort simulation and individual-based (first-order Monte Carlo) microsimulation. Conceptualizing a decision problem in terms of a set of (health) states and transitions among these states, state-transition modeling is one of the most widespread modeling techniques in clinical decision analysis, health technology assessment, and health-economic evaluation. State-transition models have been used in many different populations and diseases, and their applications range from personalized health care strategies to public health programs. Most frequently, state-transition models are used in the evaluation of risk factor interventions, screening, diagnostic procedures, treatment strategies, and disease management programs. The goal of this article was to provide consensus-based guidelines for the application of state-transition models in the context of health care. We structured the best practice recommendations in the following sections: choice of model type (cohort vs. individual-level model), model structure, model parameters, analysis, reporting, and communication. In each of these sections, we give a brief description, address the issues that are of particular relevance to the application of state-transition models, give specific examples from the literature, and provide best practice recommendations for state-transition modeling. These recommendations are directed both to modelers and to users of modeling results such as clinicians, clinical guideline developers, manufacturers, or policymakers.

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“…QALYs are derived from utility loss estimates from five studies based on HCV states F0‐1, F2‐3, CC, DC, HCC, postliver transplant, and post‐SVR 17, 18, 19, 20, 21, 22. QALYs are calculated by multiplying annual stage utility losses by expected background utility based on age for each year of life 23…”

Section: Methodsmentioning

confidence: 99%

Potential epidemiologic, economic, and budgetary impacts of current rates of hepatitis C treatment in medicare and non‐medicare populations

Wittenborn

Brady

Dougherty

et al. 2017

Hepatology Communications

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We forecast the health and budgetary impact of hepatitis C (HCV) treatment on the Medicare program based on currently observed rates of treatment among Medicare and non‐Medicare patients and identify the impact of higher rates of treatment among non‐Medicare populations. We developed a computer microsimulation model to conduct an epidemiologic forecast, a budgetary impact analysis, and a cost‐effectiveness analysis of the treatment of HCV based on three scenarios: 1) no treatment, 2) continuation of current‐treatment rates, and 3) treatment rates among non‐Medicare patients increased to match that of Medicare patients. The simulated population is based on National Health and Nutrition Examination Survey data. HCV progression rates and costs were calculated in Surveillance, Epidemiology, and End Results Program Medicare 5% claims data from the Chronic Hepatitis Cohort Study and published literature. We estimate that 13.6% of patients with HCV in the United States are enrolled in Medicare, but 75% will enter Medicare in the next 20 years. Medicare patients were over 5 times as likely to be treated in 2014‐2015 as other patients. Medicare paid over $9 billion in treatment costs in both 2015 and 2016 and will total $28.4 billion from 2017‐2026. Increasing treatment rates among non‐Medicare patients would lead to 234,000 more patients being treated, reduce HCV mortality by 19%, and decrease Medicare costs by $18.6 billion from 2017‐2026. We find that treatment remains cost‐effective under most assumptions, costing $31,718 per quality adjusted life year gained. Conclusion: Medicare treats a disproportionately large share of HCV patients. Continued low rates of treatment among non‐Medicare HCV patients will result in both reduced and deferred treatment, shifting future treatment costs to Medicare while increasing overall medical management costs, morbidity, and mortality. (Hepatology Communications 2017;1:99‐109)

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Effectiveness and cost-effectiveness of initial combination therapy with interferon/peginterferon plus ribavirin in patients with chronic hepatitis C in Germany: A health technology assessment commissioned by the German Federal Ministry of Health and Social Security

Cited by 39 publications

References 46 publications

The role of hepatitis C virus genotyping in evaluating the efficacy of INF-based therapy used in treating hepatitis C infected patients in Libya

The role of hepatitis C virus genotyping in evaluating the efficacy of INF-based therapy used in treating hepatitis C infected patients in Libya

State-Transition Modeling: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-3

Potential epidemiologic, economic, and budgetary impacts of current rates of hepatitis C treatment in medicare and non‐medicare populations

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