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）：本资助申请的目标是开发方法，以了解抗逆转录病毒治疗对抗病毒药物耐药性发展的影响。耐药性的产生源于随着时间的推移而获得的突变——这一过程既反映了病毒复制的数量，也可能有助于病毒的适应性。我们打算共同建立这些过程的模型，以研究病毒基因型的复杂共同进化，以及诸如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)在病毒遗传进展的隐马尔可夫模型中包含时变协变量，以检查病毒多样性，病毒载量和其他因素对抗病毒抗性途径的影响。2)在遗传状态已知但存在错误的情况下，对抗性遗传途径（使用隐马尔可夫模型）和病毒学失败时间进行联合建模。3)将病毒基因型与表型联系起来的半参数方法，以及在其他存在的情况下研究特定突变的影响。4)在任意测量次数的情况下，用于重复测量病毒载量的两组比较的u -统计方法。5)评估测量误差和缺失的高维纵向标记的替代性。目的1)调查诸如病毒载量、治疗、依从史或其他时变因素如何影响病毒采取的耐药途径。目的2)研究遗传途径对纵向测量时间过程的影响，如病毒载量或适应度。目标3)扩展上一个拨款期开发的方法，将基因型与任何反应变量联系起来。新方法是半参数的；它们应该对错误的非正态性更健壮，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，该概念表旨在调查原发性耐药突变对治疗的病毒学反应的影响。目的5)调查病毒载量的短期反应和获得耐药突变的信息在多大程度上可以作为长期临床结果的替代品。