Methods for Long-Term Follow-Up of HIV-Infected Patients

HIV 感染者的长期随访方法

• 批准号: 7197314
• 负责人: VICTOR GERARD DEGRUTTOLA
• 金额: $ 31.1万
• 依托单位: HARVARD SCHOOL OF PUBLIC HEALTH
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-03-01 至 2008-12-09
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7197314
• 关键词: Address; Adherence; Anti-Retroviral Agents; Antiviral resistance; Applications Grants; Biological Markers; CD4 Lymphocyte Count; Clinical; Communities; Complex; Development; Dimensions; Evolution; Failure; Genetic; Genetic Models; Genotype; Goals; Grant; HIV; HIV-1; Immune response; Investigation; Joints; Long-Term Effects; Measurement; Measures; Medical; Methodology; Methods; Modeling; Mutation; Outcome; Pathway interactions; Patients; Pattern; Phenotype; Process; Recording of previous events; Resistance; Resistance development; Standards of Weights and Measures; Surrogate Endpoint; Time; Viral; Viral Drug Resistance; Viral Load result; Virus; base; comparison group; concept; fitness; follow-up; interest; markov model; method development; response; statistics; surrogacy; therapy development; treatment effect; virus genetics

DESCRIPTION (provided by applicant): The goal of this grant application is development of methods for understanding the consequences of antiretroviral treatment for the development of antiviral resistance. The development of resistance results from the acquisition of mutations over time-a process that both reflects and contributes to amount of replicating virus and perhaps also the fitness of virus. We intend to model these process jointly to study the complex co-evolution of viral genotype and such longitudinal measures as viral load or fitness, and CD4 count. Specifically our aims are: 1) Inclusion of time-varying covariates in hidden Markov models of viral genetic progression to examine the impact of viral diversity, viral load, and other factors on pathways to antiviral resistance. 2) Joint modeling of genetic pathways to resistance (using hidden Markov models) and time to virological failure, in settings where the genetic state is know with error. 3) Semiparametric methods for relating viral genotype to phenotype and to investigate the impact of specific mutations in the presence of others. 4) U-statistic approaches for two group comparisons of repeated measures of viral load, when times of measurement are arbitrary. 5) Assessing surrogacy of high-dimensional longitudinal markers subject to measurement error and missingness. Aim 1) investigates how factors like viral load, treatment, adherence history or other time-varying factors influence the pathways to resistance taken by the virus. Aim 2) investigates the influence of genetic pathway on the time course of longitudinal measures, like viral load or fitness. Aim 3) extends the methods developed in the last grant period to relate genotype to any response variable. The new methods are semi parametric; they should be more robust to nonnormality of errors and more powerful than the previous methods. Aim 4) arose from consideration of the problems raised in an AIEDRP concept sheet to investigate the impact of primary resistance mutations on the virological response to treatment. Aim 5) investigates the degree to which information on short-term response of viral load and on acquisition of resistance mutations can serve as surrogates for longer term clinical outcomes.

描述（由申请人提供）：本拨款申请的目标是开发方法来了解抗逆转录病毒治疗对抗病毒耐药性产生的影响。耐药性的发展是随着时间的推移而获得突变的结果，这一过程既反映并有助于病毒复制的数量，也可能反映病毒的适应性。我们打算联合模拟这些过程，以研究病毒基因型的复杂共同进化以及病毒载量或适应度以及 CD4 计数等纵向测量。具体来说，我们的目标是：1）将时变协变量纳入病毒遗传进展的隐马尔可夫模型中，以检查病毒多样性、病毒载量和其他因素对抗病毒耐药途径的影响。 2）在遗传状态已知有误的情况下，对耐药性的遗传途径（使用隐马尔可夫模型）和病毒学失败的时间进行联合建模。 3）半参数方法，用于将病毒基因型与表型联系起来，并研究特定突变在其他突变存在下的影响。 4）当测量次数任意时，U统计方法用于重复测量病毒载量的两组比较。 5）评估受测量误差和缺失影响的高维纵向标记的替代性。 目标 1) 研究病毒载量、治疗、依从史或其他随时间变化的因素如何影响病毒的耐药途径。目标 2) 研究遗传途径对纵向测量（如病毒载量或适应性）的时间进程的影响。目标 3) 扩展了上一个资助期开发的方法，将基因型与任何响应变量相关联。新方法是半参数的；它们应该对非正态误差更加鲁棒，并且比以前的方法更强大。目标 4) 源于对 AIEDRP 概念表中提出的问题的考虑，以调查主要耐药突变对治疗病毒学反应的影响。目标 5) 研究病毒载量短期反应和耐药突变获得信息在多大程度上可以作为长期临床结果的替代指标。