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Simulation Modeling to Improve HIV/HCV Screening, Treatment and Care

Simulation Modeling to Improve HIV/HCV Screening, Treatment and Care
模拟建模改善 HIV/HCV 筛查、治疗和护理
批准号:
8486407
负责人:
Benjamin P. Linas
金额:
$45.0万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-06-15 至 2016-05-31

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项目成果

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中文摘要
翻译
描述(由申请人提供):HCV相关肝病是美国HIV感染者死亡的主要原因。目前治疗HCV感染的疗效有限,但第一种HCV蛋白酶抑制剂最近获得FDA批准,并大大改善了治疗效果。然而,许多HCV感染者并不知道自己被感染了。此外,由于有限的治疗吸收和高失访率,很少有HIV/HCV共感染患者开始HCV治疗。认识到HCV所代表的公共卫生挑战,医学研究所和美国肝病研究协会呼吁进行研究,以确定HCV筛查和护理提供的最佳策略。我们建议建立一个HIV/HCV合并感染的数学模型,以产生急需的证据,为筛查和治疗指南提供信息,并改善患者的预后。三个具体目标是:1。开发并验证HIV/HCV合并感染的Monte Carlo模拟模型,包括HCV和HIV筛查、护理联系和保留以及治疗。2.使用该模型进行和传播一系列分析,这些分析将为在直接作用于HCV的抗病毒治疗时代识别和管理HIV/HCV合并感染的临床指南提供所需的证据。3.开展政策分析,制定优先事项,以改善获得丙型肝炎病毒治疗,并预测广泛提供的直接作用于丙型肝炎病毒的治疗的预算影响。拟议的具体目标将回答有关识别和治疗HCV和HIV/HCV合并感染的最佳策略的关键问题。该项目将开发一个持久的平台,有望成为快速进行严格的比较有效性和成本效益分析的主要工具,在有效的HCV治疗的新时代,改善HCV和HIV/HCV护理的战略。
英文摘要
DESCRIPTION (provided by applicant): 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.
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HEAL Data2Action Modeling and Economic Resource Center
HEAL Data2Action Modeling and Economic Resource Center
Researching Effective Strategies to Prevent Opioid Death (RESPOND)
  • 批准号:
    10804924
  • 项目类别:
  • 资助金额:
    $89.58万
  • 财政年份:
    2018
  • 负责人:
    Benjamin P. Linas
  • 依托单位:
Researching Effective Strategies to Prevent Opioid Death (RESPOND)
  • 批准号:
    10369647
  • 项目类别:
  • 资助金额:
    $68.65万
  • 财政年份:
    2018
  • 负责人:
    Benjamin P. Linas
  • 依托单位:
海外基金