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Scenarios to manage the hepatitis C disease burden and associated economic impact of treatment in Turkey

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Abstract

Background

Hepatitis C virus (HCV) infection is a significant health problem. The aim of this study is to evaluate the cost-effectiveness of HCV treatment and estimate its economic burden in Turkey.

Methods

An Excel-based disease progression model was used to estimate the HCV-infected population for 2015–2030. Direct costs in US dollars (USD) including diagnostic, laboratory, and healthcare costs were provided by experts in the country. Indirect costs were estimated as lost productivity using the World Health Organization (WHO) disability-adjusted life years (DALYs) metric from the Global Burden of Disease study. Three scenarios were developed to estimate the cost-effectiveness of HCV treatment through 2030: Base 2016, Increase Treatment and SVR (where SVR is sustained virological response), and WHO Targets. Additionally, the WHO Targets scenario was assessed at three different treatment price points: 10,900 USD, 16,730 USD (base cost), and 27,285 USD.

Results

Cumulative total direct and indirect costs (2015–2030) for the WHO Targets scenario were estimated to be 10.8 billion USD, or a 1.5 % increase compared with Base 2016. However, by the following decade, due to a marked decline in DALYs, cumulative direct and indirect costs were estimated to be 45 % less when compared with Base 2016. At a threshold of 9125 USD, all scenarios were cost-effective.

Conclusions

By implementing the WHO Targets scenario, Turkey would be able to lower HCV prevalence by 80 % and reduce the total number of liver-related deaths by >65 % by 2030. Treating HCV infection in the country is cost-effective if healthcare and indirect costs are taken into consideration.

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Abbreviations

HCV:

Hepatitis C virus

HCC:

Hepatocellular carcinoma

Peg-IFN:

Pegylated interferon

RBV:

Ribavirin

SVR:

Sustained virological response

DAAs:

Direct-acting antivirals

WHO:

World Health Organization

UN:

United Nations

IRODaT:

The International Registry on Organ Donation and Transplantation

USD:

US dollars

DALYs:

Disability-adjusted life years

GBD:

Global Burden of Disease

GDP:

2015 gross domestic product

TIS:

Turkish Insurance System

WPAI-SHP:

Work Productivity and Activity Impairment–Specific Health Problem

QALY:

Quality-adjusted life year

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Author information

Authors and Affiliations

  1. Department of Gastroenterology, Ankara University Medical School, Sihhiye, 06100, Ankara, Turkey

    Necati Örmeci

  2. Department of Health Care Management, Başkent University Ankara, Ankara, Turkey

    Simten Malhan

  3. Department of Infectious Diseases, Ankara University Medical School, Ankara, Turkey

    İsmail Balık

  4. Public Health and Epidemiology, Dokuz Eylül University, İzmir, Turkey

    Gül Ergör

  5. Center for Disease Analysis, Lafayette, CO, USA

    Homie Razavi & Sarah Robbins

Authors
  1. Necati Örmeci
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  2. Simten Malhan
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  3. İsmail Balık
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  4. Gül Ergör
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  5. Homie Razavi
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  6. Sarah Robbins
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Corresponding author

Correspondence to Necati Örmeci.

Ethics declarations

Funding

This study was funded by the Polaris Observatory.

Conflict of interest

Necati Örmeci, Simten Malhan, İsmail Balık, and Gül Ergör have nothing to disclose. Homie Razavi and Sarah Robbins are employees of the Center for Disease Analysis.

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.

Appendix: Expert panel and Delphi process

Appendix: Expert panel and Delphi process

The Center for Disease Analysis convened an expert panel to gain consensus surrounding the inputs of the hepatitis C disease burden model and economic analysis. The expert panel was identified through HCV-related and HCV econometric scientific contributions and consisted of gastroenterologists, health economists, infectious disease specialists, and epidemiologists with keen insight into the current hepatitis C disease and economic burden across Turkey. Authors Örmeci, Malhan, Balık, and Ergör were included in this panel. Örmeci, Malhan, Balık, and Ergör provided feedback regarding the disease burden inputs, while Örmeci, Malhan, and Balık provided insights into the economic inputs.

 

Activities

Phase 1: data gathering

 

 1a

Identify experts who are willing to collaborate

 Experts were identified through HCV-related scientific contributions, or through referrals and recommendations from leading researchers. Panels consisted of hepatologists, gastroenterologists, virologists, infectious disease specialists, epidemiologists, health economists, health scientists, and Ministry of Health representatives

 1b

Literature search

 Review the internal database for previously identified sources

 Review online sources (MOH, WHO, etc.) to capture nonindexed sources

 Run a literature search from 2013 forward to identify recent publications

 Summarize input data available through the literature

 Gather empirical data for new HCC cases, liver transplants (LT), percent of HCC and LT due to HCV, annual newly diagnosed, annual treated, percent of infection due to transfusion, and percent of infections that are among active people who inject drugs (PWID)

 Build draft model based on published data or extrapolate inputs from countries with data when data are missing (as a placeholder)

Schedule meeting with experts

Phase 2: country meetings and modeling

 

 2a

Expert meeting 1 (2–3 h)

 Provide a background on the project, model, and methodology

 Review data identified in phase 1b and highlight gaps in data

 Request data in local nonindexed journals, unpublished data, and any other available data (e.g., hospital-level data) that can be used to fill the gaps

 Gain agreement on countries that can used for extrapolation when no local data are available

 2b

Follow up with experts post meeting 1

 Send minutes of the meeting and list of remaining action items to experts

 Follow up with experts to collect missing data and get copies of publications in local journals, unpublished data, relevant Ph.D. theses, government reports, and raw hospital or registry-level data

 Analyze raw data and send to experts for approval

 2c

Disease burden modeling

 Populate disease burden model with inputs and calibrate model to empirical data

 Develop two to three scenarios to prepare for meeting 2, including a WHO target scenario (elimination by 2030)

 Schedule second meeting

 Develop a slide deck summarizing all inputs and associated data sources

 Perform a final check of the model and slide deck and approve internally

 2d

Expert meeting 2 (2–3 h)

 Review all inputs as well as data provided by experts since meeting 1 and results of analyses of any raw data provided

 Gain agreement on all inputs to be used in the model

 Update the model using any updated inputs

 Run scenarios requested by experts (e.g., slow increase in the number of treated patients, disease control, WHO target) and review results and insights

 Agree on final strategies that would be considered as part of a national strategy

Phase 3: follow-up analyses

 

 3a

Follow-up analyses

 Update model as necessary and send results to experts

 Provide support to address follow-up questions

 Lock down inputs and outputs as approved

 Run additional scenarios to support the development of a national strategy (e.g., economic impact, birth cohort screening, and sources of transmission)

 Report results to Polaris Observatory

 Update analysis as new information becomes available (e.g., new national studies, updated treatment data)

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Örmeci, N., Malhan, S., Balık, İ. et al. Scenarios to manage the hepatitis C disease burden and associated economic impact of treatment in Turkey. Hepatol Int 11, 509–516 (2017). https://doi.org/10.1007/s12072-017-9820-3

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  • DOI: https://doi.org/10.1007/s12072-017-9820-3

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