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

HIV 感染者的长期随访方法

• 批准号: 6622564
• 负责人: VICTOR GERARD DEGRUTTOLA
• 金额: $ 28.32万
• 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 2005-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6622564
• 关键词: HIV infections; antiAIDS agent; antiviral agents; clinical research; data collection methodology /evaluation; drug classification; drug interactions; drug resistance; drug tolerance; genotype; human data; indinavir; longitudinal human study; method development; nelfinavir; statistics /biometry

DESCRIPTION: (provided by applicant) We aim to develop methods to help in understanding the long-term consequences of treatment with antiretroviral drugs, for control of virus, for development of antiviral resistance, and for clinical outcome. Antiretroviral treatment choices have longer-term consequences lasting well beyond the period of treatment because of the development of resistant strains of virus under drug pressure and because of cumulative toxicities. Understanding the relationship between treatment history, onset of resistant mutations, and response to subsequent therapy can help in determining longer-term consequences of therapy and in making treatment choices. Sources of information such as rollover studies and observational databases exit. However such investigations require development of new statistical methods because of the high dimensionality of the genetic information; this dimensionality is increased when genetic sequences are obtained over time and because problems arising from dropout and selective willingness to participate in long-term studies/sequential randomizations must be addressed. Our specific aims are: to develop new methods for investigation of antiviral resistance, including: 1) Model-based methods to aid in drug selection by characterizing the relative performance of different antiviral drugs by genotype; and 2) Nonparametric methods for predicting HIV drug susceptibility phenotype or patient response to treatment from genotype. We also aim to develop new methods of estimation and testing that handle informative dropout, with focus on issues of special relevance to analyses of data from longer-term AIDS clinical studies and rollover studies. The specific areas are: 3) Analyzing the effects of sequences of treatments from rollover studies subject to dropout, self-selected treatment discontinuation, lack of consent to rollover, and selective accrual; and 4) Covariate-adjusted K-sample tests for censored repeated measures and time to event data with informative dropout.

描述：（由申请人提供）我们的目标是开发方法，以帮助 了解抗逆转录病毒治疗的长期后果 药物，用于控制病毒，用于产生抗病毒抗性，以及用于 临床结果。抗逆转录病毒治疗的选择具有更长期的 治疗期后的后果，因为 在药物压力下以及由于病毒耐药株的发展 累积毒性了解治疗与 病史、耐药突变的发生和对后续治疗的反应可 帮助确定治疗的长期结果， 选择.信息来源，如滚动研究和观察 数据库退出。然而，这种调查需要开发新的 由于遗传的高维性， 信息;当基因序列被 随着时间的推移，由于辍学和选择性学习所产生的问题， 参与长期研究/序贯随机化的意愿必须 被解决。我们的具体目标是：开发新的调查方法 抗病毒耐药性的研究，包括：1）基于模型的方法，以帮助药物治疗 通过表征不同抗病毒药物的相对性能进行选择 按基因型分类的药物; 2）预测HIV药物的非参数方法 易感性表型或患者对来自基因型的治疗的反应。我们 还旨在开发新的评估和测试方法， 信息性辍学问题，重点是与分析辍学问题特别相关的问题， 来自长期艾滋病临床研究和滚动研究的数据。具体 3）分析从滚动开始的治疗顺序的影响 受脱落、自行选择的治疗中止、缺乏 同意展期和选择性应计;以及4）协变量调整的K样本 删失重复测量和事件发生时间数据的检验， 辍学生