Modèles de maladies complets et coût-analyses d'efficacité pour l'infection par le virus de l'hépatite C

Existing mathematical progression models of hepatitis C virus (HCV) infection tend to have some limitations and often only study the effects of a few key factors on the progression. In this PhD research project, I developed a comprehensive mathematical disease progression model for HCV disease that considers the effect of control measures such as screening and treatment and that compares the effectiveness and costs of different testing strategies in relation to the presently used PCR testing for HCV screening in different settings. Such models allow us to conduct cost-effectiveness studies that can provide policymakers with more accurate information in order to make efficient resource allocation decisions. For instance, based on our model comparing screening strategies in Switzerland, we provided a recommendation on screening different population groups for HCV in Switzerland for the Federal Office of Public Health (FOPH) and found that only large-scale screening of the general population could substantially accelerate the rate of HCV diagnosis and treatment in Switzerland and other countries with similar epidemics. The details of this recommendation can be found on the official website of the FOPH. Moreover, our models suggested that screening strategies using an antigen test to diagnose HCV infection performed reasonably well in countries such as Georgia compared with the traditional antibody- and PCR-based approach. Les modèles mathématiques de progression existants de l'infection par le virus de l'hépatite C (VHC) ont tendance à avoir certaines limites et n'étudient souvent que les effets de quelques facteurs clés sur la progression. Dans ce projet de recherche doctorale, j'ai développé des modèles mathématiques de progression de la maladie pour le VHC qui tiennent compte des effets des mesures de contrôle telles que le dépistage et le traitement et comparent l'efficacité et les coûts de différentes stratégies de test par rapport au test PCR actuellement utilisé pour le dépistage du VHC dans des endroits différents. Des tels modèles nous permettent de mener des études de rentabilité qui peuvent fournir aux décideurs des informations plus précises afin de prendre des décisions efficaces en matière d'allocation des ressources. Par exemple, sur la base de notre modèle de comparaison des stratégies de dépistage en Suisse, nous avons fourni une recommandation sur le dépistage du VHC dans différents groupes de population en Suisse pour l'Office fédéral de la santé publique (OFSP) et nous avons constaté que seul un dépistage à grande échelle de la population générale pouvait accélérer considérablement le taux de diagnostic et de traitement du VHC en Suisse et dans d'autres pays avec des épidémies similaires. Le détail de cette recommandation se trouve sur le site officiel de l'OFSP. De plus, nos modèles ont suggéré que les stratégies de dépistage utilisant un test antigénique pour diagnostiquer l'infection par le VHC fonctionnaient raisonnablement bien dans des pays comme la Géorgie par rapport à l'approche traditionnelle basée sur les anticorps et la PCR

Impact of Screening and Treatment for Hepatitis C Virus (HCV) Infection in Switzerland. A Comprehensive Mathematical Model of the Swiss HCV Epidemic

Background and objective: An estimated 40,000 people were chronically infected with Hepatitis C virus (HCV) in Switzerland in 2016. HCV is one of the leading causes of liver disease, but a considerable proportion of the infected people may remain unaware of their infections until the onset of severe symptoms. A few years ago, the new effective therapy with direct acting antivirals (DAA) became available, and since October 2017, all HCV infected patients in Switzerland are eligible to be treated. The aim of our project was to estimate the effect of various screening strategies on identifying the currently undiagnosed patients, and to project the number of annual new diagnoses, treated patients achieving sustained virological response (SVR), liver related deaths among HCV infected people, and the size of the HCV viremic population, between 2018 and 2029. We compared the following screening interventions with the current practice of screening (baseline scenario): intensified testing of current injection drug users (IDU); screening of former IDU; screening of people originating in high prevalence regions (South Europe, Asia, Africa); screening of people born 1951-1985; and universal screening of the entire population. Methods: We developed a mathematical model of HCV disease progression that simulates individual patients from HCV infection until death. The progression of the disease is represented using health states that account for the current stage of liver disease (F0-F4, decompensated cirrhosis, hepatocellular carcinoma, transplanted liver) and stage of the infection and care (acute, chronic undiagnosed, diagnosed, on treatment, SVR/cured). Patients are assigned demographic and behavioral baseline characteristics. Transition times between health states are sampled from hazard functions, which were parameterized based on a comprehensive literature search and consulting experts. Because of uncertainty in input parameters, we conducted four alternative analyses, combining two assumptions about the rate of fibrosis progression (dynamic age- and stage-dependent vs. constant) and past diagnosis rate among IDU (low increasing vs. constant high). The outputs of the model were converted into the assumed HCV infected population of Switzerland by giving each simulated patient a weight based on his/her baseline characteristics, corresponding to the representativeness of this simulated patient among the true infected population. We used the notification database of the Federal Office of Public Health and the data collected by the Swiss Hepatitis C Cohort Study to estimate the distribution of the characteristics among the individuals diagnosed by 2016. We estimated the size of the undiagnosed population in 2016 by assuming a total infected population of 40,000 individuals. We assumed that the distribution of the characteristics was the same among the individuals infected in a particular year regardless of being diagnosed or not by 2016, and that the number of annual new cases of HCV would continue in the future on the same level as in the recent years. We also conducted sensitivity analyses where we either increased or decreased the total size of the infected population, or the proportion of individuals with high-risk behavior among the undiagnosed, or increased the liver related mortality rate. Results: In this summary, we present the results comparing the future strategies from the main analysis assuming dynamic fibrosis progression and low diagnosis rate among IDU in the past (see Section 6 and Appendix E of the full report for the other analyses). The expected number of new diagnoses in 2018 was about 700 in the baseline scenario, which represents a substantial drop from 2017 due to the decreasing number of undiagnosed patients in the easy-to-identify population groups (Figure i). Afterwards, the annual new diagnoses continued to slightly decrease. More intensive screening of current IDU did not considerably change the number of new diagnoses. With origin based screening, the new diagnoses were slightly above the baseline scenario, with similar pattern across the years. The number of diagnoses in 2018 was considerably higher with birth cohort screening (3,000) and universal screening (3,900). After the first years, the diagnoses decreased rapidly. The model predicted in the baseline scenario that over 7,000 patients would achieve SVR in 2018. Afterwards, the number decreased fast, with only about 200 patients achieving SVR in 2029. The differences in annual number of SVR across the scenarios followed those of the new diagnoses. In particular universal and birth cohort screening scenarios will be able to cure over 1,000 patients more than the baseline scenario in the first years

Modelling the impact of different testing strategies for HCV infection in Switzerland.

Objective Hepatitis C virus (HCV) infection is a major cause of liver disease. Since symptoms of chronic liver disease usually appear only late in the course of the disease, infected individuals may remain undiagnosed until advanced disease has developed. We aimed to investigate which screening strategies would be most effective to detect individuals unaware of their infection. Methods We developed a mathematical model for HCV disease progression and compared the current practice of HCV testing in Switzerland with the following screening strategies: intensive screening of active injection drug users (IDU), screening of former IDU, screening of individuals originating from countries with high HCV prevalence, screening of individuals born 1951-1985 (birth-cohort) and universal screening. All screening interventions were considered in addition to a baseline scenario that reflected the current practice of HCV testing. Results Within the first 4 years (2018-2021), every year, on average 650 cases were diagnosed in the baseline scenario, 660 with intensified IDU screening, 760 with former IDU screening, 830 with origin-based screening, 1420 with birth-cohort screening and 1940 with universal screening. No difference in liver-related mortality and incidence of end-stage liver disease between the screening scenarios was observed. Conclusion Our results suggest that only large-scale screening of the general population could substantially accelerate the rate of HCV diagnosis and treatment in Switzerland and other countries with similar epidemics. However, this implies screening of a large population with low prevalence, and may trigger considerable numbers of false-positive and borderline test results

Hepatitis C core antigen test as an alternative for diagnosing HCV infection: mathematical model and cost-effectiveness analysis

Background: The cost and complexity of the polymerase chain reaction (PCR) test are barriers to diagnosis and treatment of hepatitis C virus (HCV) infection. We investigated the cost-effectiveness of testing strategies using antigen instead of PCR testing. Methods: We developed a mathematical model for HCV to estimate the number of diagnoses and cases of liver disease. We compared the following testing strategies: antibody test followed by PCR in case of positive antibody (baseline strategy); antibody test followed by HCV-antigen test (antibody-antigen); antigen test alone; PCR test alone. We conducted cost-effectiveness analyses considering either the costs of HCV testing of infected and uninfected individuals alone (A1), HCV testing and liver-related complications (A2), or all costs including HCV treatment (A3). The model was parameterized for the country of Georgia. We conducted several sensitivity analyses. Results: The baseline scenario could detect 89% of infected individuals. Antibody-antigen detected 86% and antigen alone 88% of infected individuals. PCR testing alone detected 91% of the infected individuals: the remaining 9% either died or spontaneously recovered before testing. In analysis A1, the baseline strategy was not essentially more expensive than antibody-antigen. In analysis A2, strategies using PCR became cheaper than antigen-based strategies. In analysis A3, antibody-antigen was again the cheapest strategy, followed by the baseline strategy, and PCR testing alone. Conclusions: Antigen testing, either following a positive antibody test or alone, performed almost as well as the current practice of HCV testing. The cost-effectiveness of these strategies depends on the inclusion of treatment costs.</p