Assessing the Clinical Consequences of HIV Drug Resistance

评估 HIV 耐药性的临床后果

• 批准号: 7690947
• 负责人: RICHARD H HAUBRICH
• 金额: $ 23.18万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-25 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7690947
• 关键词: Accounting; Acquired Immunodeficiency Syndrome; Amino Acids; Anti-Retroviral Agents; Antiretroviral drug resistance; Antiretroviral resistance; Caring; Cessation of life; Clinic; Clinical; Clinical Data; Codon Nucleotides; Cohort Analysis; Computerized Medical Record; Consequences of HIV; Data; Data Collection; Databases; Disease; Disease Management; Disease Progression; Drug resistance; Equilibrium; Evolution; Failure; Goals; HIV; HIV drug resistance; Individual; Infection; Laboratories; Malignant Neoplasms; Methods; Metric; Modeling; Outcome; Patients; Pharmaceutical Preparations; Phenotype; Prevalence; RNA; Research; Resistance; Site; Statistical Methods; System; Techniques; Testing; Time; Treatment Protocols; Trees; Viral; Virus; antiretroviral therapy; base; clinical research site; cohort; computer based statistical methods; data exchange; experience; fitness; hazard; improved; markov model; medical specialties; novel; partial response; point of care; public health relevance; repository

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.

新的抗逆转录病毒药物大大增加了实现和维持抑制HIV复制的可能性，即使对抗逆转录病毒治疗经验丰富的患者也是如此。对于所有患者，目标是维持HIV RNA < 50拷贝/mL。然而，并非所有患者都能在抗逆转录病毒（ARV）治疗中保持这种水平的病毒抑制；如果病毒反弹，就会出现HIV耐药性。由于耐药性至少在短期内会损害病毒的适应性（与野生型病毒相比），因此即使是非抑制性治疗也是有益的。然而，随着HIV在非抑制性治疗期间的持续进化，从长远来看，病毒复制增加（适应度提高），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诸如顺序治疗和对这些治疗的部分反应等其他因素后，评估耐药性（由一种新的艾滋病定义的疾病或死亡）的临床后果。该提案将利用来自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，它直接反映了在美国七个大型艾滋病毒诊所每天对艾滋病毒感染者进行护理的临床决策和管理选择的结果。CNICS通过在护理点收集数据，获取了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纳入CNICS。根据来自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治疗方案失败的发生率，并确定患病率是稳定的还是随时间变化的。”确定美国七个临床站点的HIV耐药性流行情况，并确定其流行情况是稳定的还是随时间变化的。”评估抗逆转录病毒药物失败、耐药性与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，以接近方案序列和基因型和表型HIV抗性数据的多维方面。具体分析方案数据的方法包括非参数贝叶斯模型、马尔可夫切换模型和基于核的方法。HIV耐药性数据将使用核树和基于分数的指标以及动态贝叶斯网络（DBN）进行总结。临床结果将采用四种方法建模（Cox比例风险回归、结构、内核和DBN）。