Assessing the Clinical Consequences of HIV Drug Resistance

新的抗逆转录病毒药物极大地增加了实现和保持抑制艾滋病毒复制的可能性，即使对于经验丰富的抗逆转录病毒治疗的患者也是如此。对于所有患者，目标是保持HIV RNA&lt；50拷贝/毫升。然而，并不是所有的患者都能在抗逆转录病毒(ARV)治疗中保持这种病毒抑制水平；如果病毒反弹发生，艾滋病毒耐药性就会出现。由于耐药性至少在短期内会损害病毒的适合性(与野生型病毒相比)，即使是非抑制性治疗也是有益的。然而，随着艾滋病毒在非抑制性治疗期间的持续演变，从长远来看，病毒复制增加(适应性改善)，耐药性和临床结果之间的平衡可能会改变。该项目的临床目标是在考虑到其他促成因素，如序贯疗法和对这些疗法的部分反应后，评估耐药性(由定义疾病或死亡的新艾滋病定义)的临床后果。这项提议将利用来自CNICs(CFAR综合临床系统网络)队列的数据，这是第一个基于电子病历的数据库存储库。由于CNICs是一个以临床为基础的研究网络，它直接反映了美国七家大型艾滋病毒诊所对艾滋病毒感染者的日常护理中做出的临床决策和管理选择的结果。CNICs通过在护理点收集数据，获取与快速变化的艾滋病毒疾病管理过程相关的更广泛的信息。以最基本的形式(密码子序列)收集的艾滋病毒耐药性数据通过检测实验室的直接数据传输被并入CNICs。利用CNICs的数据，该项目的具体目标是：“确定美国七个临床地点抗逆转录病毒疗法失败的发生率，并确定流行率是稳定的还是随着时间的变化而变化。”确定美国七个临床地点艾滋病毒耐药性的流行率，并确定流行率是稳定的还是随时间变化的。为了评估抗逆转录病毒药物失效、耐药性和临床疾病进展之间的关系。我们提出了有针对性的分析策略，包括新技术，以探讨方案序列的多维方面以及基因和表型艾滋病毒耐药性数据。分析方案数据的具体方法包括非参数贝叶斯模型、马尔科夫切换模型和基于核的方法。艾滋病毒耐药性数据将使用核树和基于分数的度量以及动态贝叶斯网络(DBN)进行汇总。临床结果将使用四种方法(COX比例风险回归、结构、核和DBN)进行建模。 公共卫生相关性：该项目将使用来自美国七家大型艾滋病毒专科诊所的数据来确定有多少患者未能通过抗逆转录病毒治疗，并确定正在接受艾滋病毒治疗的患者中存在多少艾滋病毒耐药性。我们将使用专门的统计技术来定义HIV耐药性与HIV临床疾病进展之间的关系，HIV临床疾病被定义为新的艾滋病感染或癌症或死亡。

DESCRIPTION (provided by applicant) New antiretroviral agents have greatly increased the likelihood of achieving and maintaining suppression of HIV replication, even for patients highly experienced with antiretroviral therapy. For all patients, the goal is to maintain HIV RNA < 50 copies/mL. However, not all patients are able to maintain this level of viral suppression on antiretroviral (ARV) therapy; if viral rebound occurs, HIV resistance emerges. Since resistance impairs viral fitness (compared to wild-type virus) at least in the short term, even non-suppressive therapy is beneficial. However, with continued evolution of HIV during non-suppressive therapy, in the longer term, viral replication increases (fitness improves) and the balance between resistance and clinical outcome may change. The clinical objective of this project is to evaluate the clinical consequences of drug resistance (defined by a new AIDS defining illness or death) after accounting for other contributing factors such as sequential therapies and partial responses to those treatments. This proposal will utilize data from the CNICS (CFAR Network of Integrated Clinical Systems) cohort, the first electronic medical record-based database repository. As CNICS is a clinic-based research network, it directly reflects the outcomes of clinical decisions and management options made daily in the care of HIV- infected individuals at seven large HIV clinics across the U.S. CNICS captures a broader range of information associated with the rapidly changing course of HIV disease management through collection of data at the point-of-care. HIV resistance data, collected in the most elemental form (codon sequences) are incorporated into CNICS by direct data transmission from the testing laboratories. With data from the CNICS, the specific aims of this project are: " To determine the prevalence of antiretroviral regimen failure at seven clinical sites in the U.S. and define if the prevalence is stable or changing with time. " To determine the prevalence of HIV drug resistance at seven clinical sites in the U.S. and define if the prevalence is stable or changing with time. " To evaluate the relationships between antiretroviral drug failure, resistance, and clinical disease progression. We propose targeted analytical strategies, including novel techniques, to approach the multidimensional aspect of regimen sequence and genotypic and phenotypic HIV resistance data. Specific methods to analyze regimen data include nonparametric Bayesian models, Markov switching models and kernel-based methods. HIV resistance data will be summarized using kernel-tree and score-based metrics, as well as with Dynamic Bayesian Networks (DBN). Clinical outcome will be modeled with four approaches (Cox proportional hazards regression, structural, kernel, and DBN). PUBLIC HEALTH RELEVANCE: This project will use data from seven large HIV specialty clinics in the U.S. to determine how many patients have failed antiretroviral regimens and to determine how much HIV drug resistance is present in the patients being treated for HIV. We will use specialized statistical techniques to define the relationship between HIV drug resistance and progression of HIV clinical disease, defined as a new AIDS infection or cancer or death.