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

HIV 感染者的长期随访方法

• 批准号: 6450475
• 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/6450475
• 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）我们旨在开发方法来帮助理解抗逆转录病毒治疗的长期后果 用于控制病毒的药物，用于发展抗病毒药的药物 临床结果。抗逆转录病毒治疗选择的长期后果持续远远超出治疗期。 在药物压力下发展病毒的抗性菌株，并且 累积毒性。了解治疗之间的关系 病史，抗性突变的发作以及对随后治疗的反应 帮助确定治疗的长期后果和进行治疗 选择。诸如翻滚研究和观察性的信息来源 数据库退出。但是，这样的调查需要开发新的 统计方法由于遗传的高维度 信息;当遗传序列是 随着时间的流逝而获得的，因为辍学和选择性产生的问题 愿意参加长期研究/顺序随机化的意愿 被解决。我们的具体目的是：开发新的调查方法 抗病毒抗性，包括：1）基于模型的方法来帮助药物 通过表征不同抗病毒的相对性能来选择 基因型的药物； 2）用于预测HIV药物的非参数方法 敏感性表型或患者对基因型治疗的反应。我们 还旨在开发处理的新方法 内容丰富的辍学，重点是与分析的特殊相关性问题 来自长期艾滋病临床研究和翻转研究的数据。具体 区域是：3）分析滚动序列的序列 研究可能会辍学，自选治疗中止，缺乏 同意滚动和选择性应计； 4）协变量调整后的K样本 审查重复措施和事件数据的时间的测试，内容丰富 辍学。