| Literature DB >> 23950920 |
Anouk T Urbanus1, Marjolijn van Keep, Amy A Matser, Mark H Rozenbaum, Christine J Weegink, Anneke van den Hoek, Maria Prins, Maarten J Postma.
Abstract
INTRODUCTION: Hepatitis C virus (HCV) infection can lead to severe liver disease. Pregnant women are already routinely screened for several infectious diseases, but not yet for HCV infection. Here we examine whether adding HCV screening to routine screening is cost-effective.Entities:
Mesh:
Year: 2013 PMID: 23950920 PMCID: PMC3741285 DOI: 10.1371/journal.pone.0070319
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Figure 1Schematic description of the Markov model.
Annually, women move between health stages according to defined transition rates given in Table 1. The natural history of HCV infection (hepatitis C virus) is modelled through the stages of chronic infection, cirrhosis, decompensated cirrhosis, hepatocellular carcinoma (HCC), liver transplantation, and the years after transplantation. The dotted arrows indicate competing mortality. In Figure 1A the model is presented for the women who are not routinely screened for HCV during their pregnancy and are diagnosed in a later stage of infection, in Figure 1b the model is presented for women who are routinely screened during their pregnancy.
Overview of annual transition probabilities and cost variables used in the Markov model.
| Variable | Value | Distribution/range | Reference |
| Probability of HCV infection, all women | 0.002 | Beta (9, 4555) |
|
| Probability of HCV infection, first generation non-Western migrants | 0.0043 | Beta (7, 1605) |
|
| Transition from asymptomatic to symptomatic HCV | 0.012 |
| |
| Percentage genotype 1 | 24% |
| |
| Percentage genotype 2 | 22% | ||
| Percentage genotype 3 | 30% | ||
| Percentage genotype 4 | 24% | ||
| Transition from chronic disease to treatment | 0.50 |
| |
| Probability of successful treatment outcome: | |||
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| Genotype 1 | 0.70 |
| |
| Genotype 2 and 3 | 0.78 |
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| Genotype 4 | 0.56 |
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| Genotype 1 | 0.40 | ||
| Genotype 2 and 3 | 0.78 | ||
| Genotype 4 | 0.56 | ||
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| Genotype 1 | 0.78 | ||
| Genotype 2 and 3 | 0.78 | ||
| Genotype 4 | 0.78 | ||
| Transition to cirrhosis per year | Range: |
| |
| 20–39 years | 0.000 | 0.00–0.001 | |
| 40–49 years | 0.001 | 0.00–0.002 | |
| 50–59 years | 0.004 | 0.003–0.005 | |
| 60–69 years | 0.005 | 0.003–0.007 | |
| >70 years | 0.019 | 0.015–0.02 | |
| Transition from cirrhosis to decompensated cirrhosis | 0.039 | Beta: (14.617, 260.1732) |
|
| Transition from cirrhosis to HCC | 0.015 |
| |
| Transition from decompensated cirrhosis to HCC | 0.015 |
| |
| Transition from decompensated cirrhosis to liver transplantation | 0.031 |
| |
| Transition from decompensated cirrhosis to HCV related death | 0.129 |
| |
| Transition from HCC to liver transplantation | 0.031 |
| |
| Transition from HCC to HCV-related death | 0.43 | Beta (117.1–155.23) |
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| Transition from post transplantation to HCV-related death | 0.21 | Beta (430, 1617). |
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| Transition after transplantation to HCV-related death | 0.057 | Beta (112, 2027) |
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| Competing mortality | Depending on age |
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| Cost, antibody HCV test | €12.69 | Based on PHSA Laboratory prices | |
| Cost, RNA-test | €122.11 | Based on PHSA Laboratory prices | |
| Cost, chronic infection, per year | €158.73 | Range: €79.37–€317.46 |
|
| Cost treatment | |||
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| |||
| Genotype 1 (24 w) | €34,900 | (Mean cost for Boceprevir and telaprevir) |
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| Genotype 2/3 | €9830 |
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| Genotype 4 | €16,178 |
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| Genotype 1 | €16,178 | ||
| Genotype 2/3 | €9,830 | ||
| Genotype 4 | €16,178 | ||
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| Genotype 1 | €34,900 | ||
| Genotype 2/3 | €34,900 | ||
| Genotype 4 | €34,900 | ||
| Annual cost cirrhosis | €821.73 | Range min - max: €410.87–€ 1,643.47 |
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| Cost decompensated cirrhosis, per year | €27,921.72 |
| |
| Cost HCC, per year | €21,054.92 | Range: €10,527.46–€42,109.85 |
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| Cost liver transplantation | €143,226.96 | Range: €71,613.48–€286,453.93 |
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| Cost after transplantation, per year | €20,714.27 | Range: €10,357.13–€41,428.53 |
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HCV: hepatitis C virus.
HCC: hepatocellular carcinoma.
In the prevalence a clearance rate of 42% [14] was included. The prevalence used in the model for all pregnant women is 0.2% (9/4563; 95% CI: 0.10–0.37) and for first generation non-Western women 0.43% (7/1612; 95% CI 0.21–0.89).
Transition rate is age-dependent.
same distribution was used for first-generation non-Western women.
new protease inhibitors are added to the standard of care regimen (peginterferon alfa and ribavirine).
Cost-effectiveness outcomes for all pregnant women and first-generation non-Western women (scenarios 1a and 1b), based on probabilistic uncertainty analysis (10000 simulations).
| Mean costs | Mean life years | Incremental costs | LYG | ICER (€/LYG) | ||
| All pregnant women | Screening | € 55,474 | 35492.8 | € 41,869 | 0,80 | € 52,473 |
| No routine screening | €13,605 | 35492.0 | ||||
| non-Western migrants | Screening | €106,307 | 36378.6 | € 77,582 | 1,65 | € 47,113 |
| No routine screening | € 28,725 | 36377.0 |
The incremental cost-effectiveness ratio (ICER) is calculated with reference to the “no routine screening” strategy.
LYG:life years gained.
ICER: incremental cost-effectiveness ratio.
Best-case scenarios for screening all pregnant women (scenario 1a) and first-generation non-Western women (scenario 1b).
| Mean costs | Mean life years | Incremental costs | LYG | ICER (€/LYG) | ||
| All pregnant women | Screening | € 41,809 | 35492.8 | € 30,228 | 1,55 | € 19,505 |
| No routine screening | € 11,581 | 35491.3 | ||||
| non-Western migrants | Screening | € 78,978 | 36378.6 | € 55.320 | 3,16 | € 17,533 |
| No routine screening | € 23,658 | 36375.4 |
With parameter optimization ±25% and incremental cost-effectiveness ratio calculated with reference to the “no routine screening” strategy.
LYG:life years gained.
ICER: incremental cost-effectiveness ratio.
Figure 2Cost-effectiveness acceptability curves (CEAC) for all pregnant women (indicated with the black line) and for first-generation non-Western women (indicated with the grey line) for scenarios 1a and 1b.
The graph shows the probability of screening being cost-effective when different cost-effectiveness thresholds are used, resulting from uncertainty analysis. In the Netherlands, the certain cost-effective threshold is €20,000 (indicated by the dotted line) and regimens that are calculated at €20,000 and €50,000 are potentially cost-effective. As shown in both scenarios, 10% of the simulations were below the cost-effectiveness threshold of €20 000.
Figure 3Tornado diagrams of the sensitivity analyses.
Diagram A) describes scenario 1a and diagram B) scenario describes scenario 1b. Both diagrams show the change in ICER when reducing or increasing each parameter with 25%.