HCV-related liver disease is a leading cause of mortality among HIV-infected individuals in the U.S. Current therapy for HCV infection has limited efficacy, but the first HCV protease inhibitors were recently approved by the FDA and have substantially improved treatment outcomes. Many HCV-infected individuals, however, are not aware that they are infected. Further, as a result of limited treatment uptake and high rates of loss to follow- up, few HIV/HCV co-infected patients ever initiate HCV therapy. Recognizing the public health challenge represented by HCV, the Institute of Medicine and American Association for the Study of Liver Diseases have called for studies to identify the best strategies for HCV screening and care delivery. We propose to build a mathematical model of HIV/HCV co-infection to generate urgently-needed evidence that will inform screening and treatment guidelines and improve patient outcomes. The three specific aims are: 1. To develop and validate a Monte Carlo simulation model of HIV/HCV co-infection that includes HCV and HIV screening, linkage to and retention in care, and treatment. 2. To use the model to conduct and disseminate a series of analyses that will develop the evidence needed to inform clinical guidelines for identifying and managing HIV/HCV co-infection in the era of directly acting antiviral therapies against HCV. 3. To conduct policy analyses that will develop priorities for improving access to HCV treatment and project the budgetary impact of widely-available directly acting therapies against HCV. The proposed specific aims will answer critical questions about the best strategies for identifying and treating HCV and HIV/HCV co-infection. The project will develop a durable platform poised to be the premier tool for rapidly conducting rigorous analyses of the comparative-effectiveness and cost-effectiveness of strategies for improving HCV and HIV/HCV care in the new era of effective HCV therapy.
Hepatitis C Virus-related (HCV) liver disease is a leading cause of mortality in HIV-infected people in the U.S. and a particular health threat for vulnerable populations, such as current and former drug users. The Institute of Medicine recently recommended expanding screening for HCV and improving the availability of HCV treatment in vulnerable populations. This project uses simulation modeling methods to generate the evidence needed to establish best practices for identifying HCV infection and managing HIV/HCV co-infection.
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|Barocas, Joshua A; Linas, Benjamin P (2017) Editorial Commentary: Decision Science at Work: The Case of Hepatitis C Virus Postexposure Prophylaxis. Clin Infect Dis 64:100-101|
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