Highlights
- •There have already been several cost-utility analyses of direct-acting antiviral (DAA) regimens conducted, but very few have either evaluated DAA regimens on hepatitis C virus (HCV) genotype 6 patients or undertaken a societal perspective. Our study has addressed this gap in knowledge by being among the first cost-utility analyses of DAA regimens on HCV genotype 6 patients using a societal perspective.
- •In this study, sofosbuvir/velpatasvir (SOF/VEL), sofosbuvir/ledipasvir (SOF/LDV), and sofosbuvir plus daclatasvir (SOF+DCV) are found to be cost-saving compared with pegylated-interferon plus ribavirin (PR) in HCV patients with genotypes 1 and 6 in Vietnam, from both societal and payer perspectives. Among 3 DAAs, SOF/VEL is the most cost-effective, followed by SOF/LDV as the second, and SOF+DCV as the third. These results remain robust across all government’s copayment rates for DAAs. Our result would be particularly useful for countries with a high prevalence of HCV genotype 6 such as Laos, Cambodia, Myanmar, or Thailand.
Abstract
Objective
Methods
Results
Conclusions
Keywords
Introduction
Methods
Target Population
Vietnam Ministry of Health. The Treatment Guideline in Diagnosis and Treatment of Hepatitis C. Decision No 4817/QD-BYT. https://thuvienphapluat.vn/van-ban/the-thao-y-te/quyet-dinh-4817-qd-byt-nam-2013-tai-lieu-huong-dan-chan-doan-dieu-tri-viem-gan-vi-rut-c-215782.aspx. Accessed 10 July 2020.
Vietnam Ministry of Health. The Treatment Guideline in Diagnosis and Treatment of Hepatitis C. Decision No 5012/QD-BYT. https://thuvienphapluat.vn/van-ban/the-thao-y-te/Quyet-dinh-5012-QD-BYT-chan-doan-dieu-tri-benh-viem-gan-vi-rut-c-2016-322718.aspx. Accessed 10 July 2020.
Model Structure
- Yoshida H.
- Shiratori Y.
- Moriyama M.
- et al.

Vietnam Ministry of Health. The Treatment Guideline in Diagnosis and Treatment of Hepatitis C. Decision No 5012/QD-BYT. https://thuvienphapluat.vn/van-ban/the-thao-y-te/Quyet-dinh-5012-QD-BYT-chan-doan-dieu-tri-benh-viem-gan-vi-rut-c-2016-322718.aspx. Accessed 10 July 2020.
Announcement of monthly exchange rate.
Interventions and Comparator
Vietnam Ministry of Health. The Treatment Guideline in Diagnosis and Treatment of Hepatitis C. Decision No 4817/QD-BYT. https://thuvienphapluat.vn/van-ban/the-thao-y-te/quyet-dinh-4817-qd-byt-nam-2013-tai-lieu-huong-dan-chan-doan-dieu-tri-viem-gan-vi-rut-c-215782.aspx. Accessed 10 July 2020.
Vietnam Ministry of Health. The Treatment Guideline in Diagnosis and Treatment of Hepatitis C. Decision No 5012/QD-BYT. https://thuvienphapluat.vn/van-ban/the-thao-y-te/Quyet-dinh-5012-QD-BYT-chan-doan-dieu-tri-benh-viem-gan-vi-rut-c-2016-322718.aspx. Accessed 10 July 2020.
Model Parameters
Input parameters | Mean | Standard error | Distribution | Source | |
---|---|---|---|---|---|
Transition probabilities | |||||
From | To | ||||
CHC | CC | 0.019 | 0.005 | Beta | 38 |
CC | DC | 0.056 | 0.014 | Beta | 37
Development of the fundamental model for HCV: research on health-economics of various initiatives related to viral liver diseases. Ministry of Health, Labour and Welfare, Japan. 2014; : 76-95 https://mhlw-grants.niph.go.jp/niph/search/NIDD00.do?resrchNum=201333004A Date accessed: July 10, 2020 |
HCC | 0.056 | 0.014 | Beta | 37
Development of the fundamental model for HCV: research on health-economics of various initiatives related to viral liver diseases. Ministry of Health, Labour and Welfare, Japan. 2014; : 76-95 https://mhlw-grants.niph.go.jp/niph/search/NIDD00.do?resrchNum=201333004A Date accessed: July 10, 2020 | |
DC | HCC | 0.056 | 0.014 | Beta | 37
Development of the fundamental model for HCV: research on health-economics of various initiatives related to viral liver diseases. Ministry of Health, Labour and Welfare, Japan. 2014; : 76-95 https://mhlw-grants.niph.go.jp/niph/search/NIDD00.do?resrchNum=201333004A Date accessed: July 10, 2020 |
LRD | 0.151 | 0.038 | Beta | 37
Development of the fundamental model for HCV: research on health-economics of various initiatives related to viral liver diseases. Ministry of Health, Labour and Welfare, Japan. 2014; : 76-95 https://mhlw-grants.niph.go.jp/niph/search/NIDD00.do?resrchNum=201333004A Date accessed: July 10, 2020 | |
HCC | LRD (year 1) | 0.118 | 0.030 | Beta | 38 |
LRD (from year 2) | 0.222 | 0.056 | Beta | 38 | |
SVR (CC) | HCC | 0.018 | 0.005 | Beta | 27 |
Treatment efficacy (SVR12) | |||||
Genotype 1 | |||||
SOF/LDV | 0.980 | 0.008 | Beta | Meta-analysis | |
SOF/VEL | 0.980 | 0.005 | Beta | Meta-analysis | |
SOF+DCV | 0.990 | 0.020 | Beta | Meta-analysis | |
PegIFN+RBV | 0.625 | 0.096 | Beta | 47 | |
Genotype 6 | |||||
SOF/LDV | 0.992 | 0.008 | Beta | 46 | |
SOF/VEL | 1.000 | - | Beta | 46 | |
SOF+DCV | 0.990 | 0.020 | Beta | 46 | |
PegIFN+RBV | 0.802 | 0.027 | Beta | 47 | |
Costs (US dollars, 2019) | |||||
Direct medical cost | |||||
Drug cost | |||||
SOF/LDV (12-week) | 1,384.4 | 276.9 | gamma | Primary data | |
SOF/VEL (12-week) | 1,739.7 | 347.9 | gamma | Primary data | |
SOF+DCV (12-week) | 1,733.0 | 346.6 | gamma | Primary data | |
PegIFN (per week) | 114.5 | 22.9 | gamma | Primary data | |
RBV (per day) | 1.2 | 0.2 | gamma | Primary data | |
Monitoring cost | |||||
DAAs (12-week) | 355.6 | 71.1 | gamma | Primary data | |
DAAs (24-week) | 360.4 | 72.1 | gamma | Primary data | |
PegIFN+RBV (48-week) | 525.3 | 105.1 | gamma | Primary data | |
Cost of palliative care (per year) | |||||
CHC | 108.5 | 21.7 | gamma | Primary data | |
CC | 598.7 | 119.7 | gamma | Primary data | |
DC | 964.1 | 192.8 | gamma | Primary data | |
HCC | 3,676.0 | 735.2 | gamma | Primary data | |
Direct non-medical cost (per year) | |||||
For antiviral treatment | |||||
CHC treated with DAAs | 87.6 | 17.5 | gamma | Primary data | |
CC treated with DAAs | 268.1 | 53.6 | gamma | Primary data | |
CHC/CC treated with PegIFN+RBV | 235.7 | 47.1 | gamma | Primary data | |
For palliative care | |||||
CHC | 174.1 | 34.8 | gamma | Primary data | |
CC | 212.2 | 42.4 | gamma | Primary data | |
DC | 364.5 | 72.9 | gamma | Primary data | |
HCC | 334.2 | 66.8 | gamma | Primary data | |
Time cost (per year) | |||||
For antiviral treatment | |||||
CHC treated with DAAs | 129.2 | 25.8 | gamma | Primary data | |
CC treated with DAAs | 165.1 | 33.0 | gamma | Primary data | |
CHC treated with PegIFN+RBV | 129.2 | 25.8 | gamma | Assumed | |
CC treated with PegIFN+RBV | 165.1 | 33.0 | gamma | Assumed | |
For palliative care | |||||
CHC | 189.8 | 38.0 | gamma | Primary data | |
CC | 201.6 | 40.3 | gamma | Primary data | |
DC | 369.9 | 74.0 | gamma | Primary data | |
HCC | 361.5 | 72.3 | gamma | Primary data | |
Utilities | |||||
CHC | 0.878 | 0.026 | triangular | Primary data | |
CC | 0.695 | 0.077 | triangular | Primary data | |
DC | 0.491 | 0.155 | triangular | Primary data | |
HCC | 0.358 | 0.160 | triangular | Primary data | |
Epidemiology | |||||
Genotype distribution in CHC-CC population (target population) | |||||
Genotype 1 | 0.358 | 0.072 | Beta | 8 | |
Genotype 6 | 0.642 | 0.128 | Beta | 8 | |
CHC-CC distribution in genotype 1 | |||||
CHC | 0.550 | 0.110 | Beta | 9 | |
CC | 0.450 | 0.090 | Beta | 9 | |
CHC-CC distribution in genotype 6 | |||||
CHC | 0.620 | 0.124 | Beta | 9 | |
CC | 0.380 | 0.076 | Beta | 9 |
Transition probabilities
- Suga M.
- et al.
Treatment efficacy
Costs
Utilities
Result Presentation
Uncertainty Analysis
Parameter uncertainty
Scenario analysis
Value of Information Analysis
Vietnam Ministry of Health. The Treatment Guideline in Diagnosis and Treatment of Hepatitis C. Decision No 5012/QD-BYT. https://thuvienphapluat.vn/van-ban/the-thao-y-te/Quyet-dinh-5012-QD-BYT-chan-doan-dieu-tri-benh-viem-gan-vi-rut-c-2016-322718.aspx. Accessed 10 July 2020.
Results
Model Validation
Base-Case Analysis
Societal perspective | PR | SOF/LDV | SOF/VEL | SOF+DCV |
---|---|---|---|---|
Discounted cost | 11 301 | 4430 | 4055 | 4782 |
Discounted LYs | 14.69 | 15.34 | 15.36 | 15.35 |
Discounted QALYs | 13.74 | 15.06 | 15.09 | 15.08 |
Incremental cost | –6870 | –7246 | –6519 | |
Incremental LYs | 0.65 | 0.66 | 0.66 | |
Incremental QALYs | 1.33 | 1.35 | 1.34 | |
ICER per LY | Dominant | Dominant | Dominant | |
ICER per QALY | Dominant | Dominant | Dominant | |
NMB | 21 519 | 31 555 | 31 993 | 31 234 |
Payer perspective | PR | SOF/LDV | SOF/VEL | SOF+DCV |
Discounted cost | 4611 | 2317 | 2101 | 2461 |
Discounted LYs | 14.69 | 15.34 | 15.36 | 15.35 |
Discounted QALYs | 13.74 | 15.06 | 15.09 | 15.08 |
Incremental cost | –2294 | –2509 | –2149 | |
Incremental LYs | 0.65 | 0.66 | 0.66 | |
Incremental QALYs | 1.33 | 1.35 | 1.34 | |
ICER per LY | Dominant | Dominant | Dominant | |
ICER per QALY | Dominant | Dominant | Dominant | |
NMB | 28 209 | 33 669 | 33 947 | 33 555 |
Parameter Uncertainty


Value of Information Analysis

Discussion
Limitations
Conclusions
Supplemental Materials



- Supplemental Materials
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Article info
Publication history
Footnotes
Author Contributions: Concept and design: Ong The, Thakkinstian, Thavorncharoensap, Sobhonslidsuk, Wu, Nguyen Khanh, Chaikledkaew
Acquisition of data: Ong The
Analysis and interpretation of data: Ong The
Drafting of the manuscript: Ong The, Thavorncharoensap, Chaikledkaew
Critical revision of the paper for important intellectual content: Ong The, Thakkinstian, Thavorncharoensap, Sobhonslidsuk, Wu, Nguyen Khanh, Chaikledkaew
Statistical analysis: Ong The
Provision of study materials or patients: Ong The
Administrative, technical, or logistic support: Ong The
Supervision: Thakkinstian, Thavorncharoensap, Sobhonslidsuk, Wu, Nguyen Khanh, Chaikledkaew
Conflict of Interest Disclosures: The authors reported no disclosures.
Funding/Support: This work is a part of training in Health Technology Assessment PhD degree, scholarship provided by Mahidol University and the International Decision Support Initiative (iDSI). This work was produced as part of the International Decision Support Initiative (www.idsihealth.org) which supports countries to get the best value for money from health spending. iDSI receives funding support from the Bill & Melinda Gates Foundation under the iDSI2 grant name and number OPP1087363, the UK Department for International Development, and the Rockefeller Foundation.
Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
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