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. 2021 Nov 1;11(1):21382.
doi: 10.1038/s41598-021-00362-y.

Assessing cost-effectiveness of hepatitis C testing pathways in Georgia using the Hep C Testing Calculator

Madeline Adee #  1 , Yueran Zhuo #  1   2   3 , Huaiyang Zhong  1   2 , Tiannan Zhan  1 , Rakesh Aggarwal  4 , Sonjelle Shilton  5 , Jagpreet Chhatwal  6   7
Affiliations

Assessing cost-effectiveness of hepatitis C testing pathways in Georgia using the Hep C Testing Calculator

Madeline Adee et al. Sci Rep. .

Erratum in

Abstract

The cost of testing can be a substantial contributor to hepatitis C virus (HCV) elimination program costs in many low- and middle-income countries such as Georgia, resulting in the need for innovative and cost-effective strategies for testing. Our objective was to investigate the most cost-effective testing pathways for scaling-up HCV testing in Georgia. We developed a Markov-based model with a lifetime horizon that simulates the natural history of HCV, and the cost of detection and treatment of HCV. We then created an interactive online tool that uses results from the Markov-based model to evaluate the cost-effectiveness of different HCV testing pathways. We compared the current standard-of-care (SoC) testing pathway and four innovative testing pathways for Georgia. The SoC testing was cost-saving compared to no testing, but all four new HCV testing pathways further increased QALYs and decreased costs. The pathway with the highest patient follow-up, due to on-site testing, resulted in the highest discounted QALYs (123 QALY more than the SoC) and lowest costs ($127,052 less than the SoC) per 10,000 persons screened. The current testing algorithm in Georgia can be replaced with a new pathway that is more effective while being cost-saving.

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Conflict of interest statement

S. Shilton is an employee of The Foundation for Innovative New Diagnostics. Dr. Chhatwal reported receiving grants from the National Science Foundation and Unitaid during the conduct of the study, grants and personal fees from Gilead and Merck & Co outside the submitted work, and served as a partner with Value Analytics Labs outside the submitted work. All other authors have no competing/conflict of interest.

Figures

Figure 1
Figure 1
Patient flow under the current standard-of-care testing pathway and innovative hepatitis C testing pathways in Georgia. Abbreviations: RDT, rapid diagnostic test; RNA, ribonucleic acid test; cAg, core antigen test; APRI/FIB4, aspartate aminotransferase (AST)-to-platelet ratio index (APRI)/fibrosis-4 index; F4, METAVIR fibrosis score of 4.
Figure 2
Figure 2
Model schematic of the natural history of hepatitis C virus in MATCH-Georgia model. Abbreviations: SVR, sustained virologic response; F0–F4, METAVIR fibrosis score; DC, decompensated cirrhosis; HCC, hepatocellular carcinoma; F4-SVR, sustained virologic response achieved at fibrosis stage 4.
Figure 3
Figure 3
Tornado diagram for one-way sensitivity analysis of incremental cost-effectiveness ratio of Pathway 1 versus no screening strategy. Horizontal bars show the variation in incremental cost-effectiveness ratio (ICER; in USD/QALY) with variation in the value of the parameter. In the parameter names, the prefix ‘C’ represents cost of a health-state, ‘Q’ the quality-of-life weight and ‘P’ the transition probability from one state to the other. Values of ICER below 0 indicate that the treatment is cost-saving. Abbreviations: SVR, sustained virologic response; F0–F4, METAVIR fibrosis score; DC, decompensated cirrhosis; HCC, hepatocellular carcinoma; F4-SVR, LRD, liver related death.
Figure 4
Figure 4
Cost-effectiveness Acceptability Curve of all pathways and no screening strategy.
See this image and copyright information in PMC

References

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