Optimizing HIV Treatment Monitoring under Resource Constraints

在资源限制下优化艾滋病毒治疗监测

• 批准号: 8847003
• 负责人: JOSEPH W HOGAN
• 金额: $ 76.67万
• 依托单位: BROWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-11-15 至 2019-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8847003
• 关键词: Algorithms; Anti-Retroviral Agents; Archives; Biological Assay; Calibration; Canada; Caring; Cations; Characteristics; Cities; Clinical; Clinical Markers; Computer software; Cost Savings; Data; Diagnosis; Diagnostic; Diagnostic tests; Drug resistance; Early Diagnosis; Effectiveness; Europe; Failure; Funding; Goals; Gold; Guidelines; HIV; HIV therapy; Health Services Accessibility; Individual; Kenya; Laboratories; Machine Learning; Methods; Modality; Modeling; Monitor; Morbidity - disease rate; Motivation; Outcome; Patient Care; Patients; Plasma; Population; Prevention therapy; Primary Health Care; Property; Protocols documentation; Provider; Regimen; Research Infrastructure; Resources; Risk; Sampling; Schedule; Side; Statistical Methods; Techniques; Technology; Testing; Time; Treatment Failure; Viral; Viral Load result; World Health Organization; accurate diagnosis; antiretroviral therapy; base; clinically relevant; cohort; cost; design; effective therapy; improved; mortality; novel diagnostics; patient population; prevent; programs; public health relevance; resistant strain; response; simulation; software development; standard care; theories; treatment program

 DESCRIPTION (provided by applicant): With escalating global access to HIV antiretroviral (ARV) therapy, treatment failure is inevitable and must be anticipated. Correct and early diagnosis of treatment failure is essential for cost savings, durable response to therapy and prevention of morbidity and mortality. Most HIV treatment programs in the developing world either do not have access to viral load (VL) testing, the gold-standard treatment monitoring modality, or can apply it only on a limited basis. Other monitoring technologies such as drug resistance testing are even less common for financial and infrastructure constraints. In this proposal we will develop, evaluate and implement methods to optimize monitoring of ARV therapy in resource limited settings (RLS) that have diverse VL availability. Though several recent studies have proposed and evaluated lower-cost markers as VL surrogates and strategies for selective VL use, they generally are not based on a formal, decision theoretic framework that allows discovery of strategies with optimality properties that can be expressed in terms of misclassification rate, cost, and other clinically relevant parameters. We propose to develop the statistical framework, theory and methods required to discover optimal diagnostic algorithms for monitoring treatment failure with limited or no VL availability; to use cohort data from both the US and Kenya to derive, calibrate and cross-validate the algorithms; to use extant plasma samples from patients in a PEPFAR-funded HIV care program to design and cross-validate a new diagnostic algorithm that includes implementation of pooled assays; and to develop usable software that will enable programs to design their own protocols based on the characteristics of their patient population and local capacity for viral load testing.

 描述（由申请人提供）：随着全球越来越多地获得艾滋病毒抗逆转录病毒（ARV）治疗，治疗失败是不可避免的，必须预期。治疗失败的正确和早期诊断对于节省费用、对治疗的持久反应以及预防发病率和死亡率至关重要。发展中国家的大多数艾滋病毒治疗方案要么无法获得病毒载量（VL）检测，这是金标准治疗监测模式，要么只能在有限的基础上应用。由于资金和基础设施的限制，其他监测技术，如抗药性测试，甚至更不常见。在这项提案中，我们将开发，评估和实施方法，以优化资源有限的设置（RLS），具有不同的VL可用性的ARV治疗的监测。虽然最近的几项研究已经提出并评估了低成本的标记物作为VL替代品和选择性VL使用的策略，但它们通常不是基于正式的决策理论框架，该框架允许发现具有最优性属性的策略，这些策略可以用误分类率，成本和其他临床相关参数来表示。我们建议开发所需的统计框架，理论和方法，以发现最佳的诊断算法，用于监测有限或没有VL可用性的治疗失败;使用来自美国和肯尼亚的队列数据来推导，校准和交叉验证算法;利用PEPFAR资助的艾滋病护理项目中患者的现有血浆样本，验证一种新的诊断算法，包括合并检测的实施;并开发可用的软件，使项目能够根据其患者人群的特征和当地的病毒载量检测能力设计自己的方案。