Bridging Hepatitis C Care Gaps: A Modeling Approach for Achieving the WHO’s Targets in Ontario, Canada
Abstract
:1. Introduction
2. Methods
2.1. Population
2.2. Strategies
- (i)
- A “status quo” strategy, which refers to the existing two-step diagnostic process with current diagnosis and treatment coverage. The annual probability of receiving an HCV antibody test was estimated using the back-calculation model and ranges from 0.040 to 0.127 depending on a birth cohort (Table S1) [10]. Of those who tested positive on the antibody test, 88% received the confirmatory RNA test, and of those who tested RNA positive, 53% received an antiviral treatment, mirroring the current care cascade [9]. Individuals not receiving RNA tests (12%) and not initiating treatment (47%) were assumed to be lost to care.
- (ii)
- An “improving linkage to care” strategy. This strategy considers reflex testing that increases the proportion of RNA testing to 98% and treatment uptake to 98% for individuals who tested RNA positive. The near-optimal rates for RNA testing and treatment uptake were chosen considering feasibility and constraints in real-world healthcare settings.
- (iii)
- “Reaching the undiagnosed population” by scaling up antibody testing in addition to the measures described under the second strategy to achieve a 65% reduction in liver mortality in 2030 as per the WHO’s mortality target. We assumed one-time screening. Considering that screening rates in the US surged by 50% following recommendations for birth cohort screening [13], we allowed for a potential 100% increase in the current antibody testing rates as the maximum limit, since exceeding this might not be feasible.
2.3. Model Structure and Assumptions
2.4. Health and Economic Outcomes
2.5. Data
2.6. Analysis
3. Results
3.1. Meeting WHO Targets
3.2. Cost-Effectiveness
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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>1965 | 1965–1945 | >1945 | Source | |
---|---|---|---|---|
Uninfected individuals (%) | 99.26 | 97.62 | 99.08 | [10,11] † |
Acute hepatitis C (%) | 0.11 | 0.64 | 0.16 | [10,11] †† |
Chronic hepatitis C (CHC) (%) | 0.63 | 1.74 | 0.76 | [11] |
Proportion of undiagnosed CHC (%) | 42.39 | 15.72 | 19.71 | [11] |
No cirrhosis (%) | 80.9 | 50.2 | 50.2 | [10] |
Cirrhosis (%) | 19.1 | 49.8 | 49.8 | [10] |
Proportion diagnosed CHC (%) | 57.61 | 84.28 | 80.29 | [10] |
Age | 39 | 58 | 78 | [9,10] |
Male (%) | 57.0 | 65.0 | 46.0 | [9] |
No cirrhosis (%) | 93.8 | 77.5 | 76.0 | [9] |
Cirrhosis (%) | 4.2 | 12.8 | 12.0 | [9] |
DC (%) | 1.8 | 6.6 | 7.2 | [9] |
HCC (%) | 0.2 | 3.1 | 4.8 | [9] |
Proportion with RNA positive test (%) | 48.1 | 61.5 | 50.4 | [9] |
Proportion with viral genotype on record (%) | 44.1 | 58.9 | 47.6 | [9] |
Proportion initiated antiviral therapy (%) | 21.7 | 36.6 | 25.8 | [9] |
Proportion achieved SVR (%) | 15.4 | 28.8 | 19.4 | [9] |
Predicted Cases as of 31 December 2030 1 per 100,000 People | Predicted Cases as of 31 December 2035 1 per 100,000 People | ||||||
---|---|---|---|---|---|---|---|
Estimated Cases as of January 2019 2 | Status Quo | RNA Rate = 98% and Tx Rate = 98% | RNA Rate = 98% and Tx Rate = 98% AB Testing Rate x2 | Status Quo | RNA Rate = 98% and Tx Rate = 98% | RNA Rate = 98% and Tx Rate = 98% and AB Testing Rate x2 | |
Care cascade outcomes | |||||||
Total CHC cases 3 | 986 | 1313 (100%) | 1313 (100%) | 1313 (100%) | 1448 (100%) | 1448 (100%) | 1448 (100%) |
Diagnosed at F0–F4 stages 4 | 383 | 946 (72%) | 1012 (77%) | 1124 (85%) | 1060 (73%) | 1140 (78%) | 1258 (86%) |
Initiated antiviral therapy 5 | 203 | 567 (43%) | 982 (75%) | 1190 (83%) | 623 (43%) | 1106 (76%) | 1221 (84%) |
Achieved SVR 5 | 153 | 546 (42%) | 940 (71%) | 1044 (79%) | 600 (41%) | 1060 (73%) | 1144 (80%) |
ESLD 6 | 47 | 130 (10%) | 93 (7%) | 86 (6%) | 169 (12%) | 107 (8%) | 97 (7%) |
Health and economic outcomes | |||||||
Liver-related mortality, cumulative | NA | 81 | 60 | 56 | 116 | 75 | 69 |
Liver-related mortality in 2030, 2035 | NA | 6.73 | 3.43 | 2.95 | 7.07 | 2.86 | 2.41 |
Life years per person | NA | 11.583 | 11.584 | 11.584 | 16.076 | 16.078 | 16.079 |
QALYs per person | NA | 9.155 | 9.157 | 9.157 | 12.239 | 12.242 | 12.243 |
Costs per person 7 | NA | CAD 56,791 | CAD 56,793 | CAD 56,812 | CAD 79,635 | CAD 79,517 | CAD 79,509 |
ΔQALY 8 per person | NA | - | 0.0018 | 0.0004 | - | 0.0035 | 0.0007 |
ΔCost 8 per person | NA | - | CAD 2 | CAD 19 | - | CAD −118 | CAD −7 |
ICUR 8 (sequential) | NA | - | CAD 1018 | CAD 52,505 | - | Cost saving | Cost saving |
Program implementation’s maximum cost per 100,000 people for the strategy to remain cost-effective at 50,000 CAD/QALY gained threshold | |||||||
Compared to the “Status quo” | NA | ref. | CAD 852,273 | - | ref. | CAD 2,049,381 | CAD 2,329,160 |
Compared to the previous strategy | NA | - | - | - | - | ref. | CAD 279,779 |
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Sahakyan, Y.; Erman, A.; Wong, W.W.L.; Greenaway, C.; Janjua, N.; Kwong, J.C.; Sander, B. Bridging Hepatitis C Care Gaps: A Modeling Approach for Achieving the WHO’s Targets in Ontario, Canada. Viruses 2024, 16, 1224. https://doi.org/10.3390/v16081224
Sahakyan Y, Erman A, Wong WWL, Greenaway C, Janjua N, Kwong JC, Sander B. Bridging Hepatitis C Care Gaps: A Modeling Approach for Achieving the WHO’s Targets in Ontario, Canada. Viruses. 2024; 16(8):1224. https://doi.org/10.3390/v16081224
Chicago/Turabian StyleSahakyan, Yeva, Aysegul Erman, William W. L. Wong, Christina Greenaway, Naveed Janjua, Jeffrey C. Kwong, and Beate Sander. 2024. "Bridging Hepatitis C Care Gaps: A Modeling Approach for Achieving the WHO’s Targets in Ontario, Canada" Viruses 16, no. 8: 1224. https://doi.org/10.3390/v16081224
APA StyleSahakyan, Y., Erman, A., Wong, W. W. L., Greenaway, C., Janjua, N., Kwong, J. C., & Sander, B. (2024). Bridging Hepatitis C Care Gaps: A Modeling Approach for Achieving the WHO’s Targets in Ontario, Canada. Viruses, 16(8), 1224. https://doi.org/10.3390/v16081224