Analysis of HIV virologic response-rebound data: prognostic indicators of post-HAART viral control

HIV病毒学反应反弹数据分析：HAART后病毒控制的预后指标

• 批准号: nhmrc : 334606
• 负责人: Dr Elizabeth Mckinnon
• 金额: $ 9.6万
• 依托单位: Murdoch University
• 依托单位国家: 澳大利亚
• 项目类别: NHMRC Project Grants
• 财政年份: 2005
• 资助国家: 澳大利亚
• 起止时间: 2005-01-01 至 2006-12-31
• 项目状态: 已结题
• 来源: https://researchdata.edu.au/analysis-hiv-virologic-viral-control/99893
• 关键词: Analysis; HIV; virologic; response; rebound

The introduction of potent anti-retroviral therapy into standard clinical management of HIV infected individuals has been associated with high rates of reduction in plasma viral loads over short periods of time. However, there remains considerable variation in the degree of longer-term viral control as a result of viral resistance, toxicity, timing of treatment initiation and choice of drug regimen. In particular, the most appropriate time to initiate treatment remains clouded, with the need to initiate treatment sufficiently early in order to avoid irreversible damage balanced by the problems of potential viral resistance or toxicity if started too soon. Determination of factors which will assist practitioners to optimise the timing of treatment initiation remains a high priority. Our aim in this project is to develop and study the use of novel statistical mixed-effects models designed to analyse factors associated with visit-time viral load data following commencement of therapy, taking account of the entire follow-up profiles of responses over time. The project involves both theoretical and empirical analyses of the estimation and inferential properties of the mixed-model method in conjunction with comprehensive analyses of prognostic factors associated with post-treatment virologic control in patients from the Western Australian HIV Cohort Study. These include demographic, virologic, immunologic, adherence and host genetic factors. The statistical methods developed will have wide applicability and add significantly to the suite of procedures available for the analysis of longitudinal response data.

在HIV感染者的标准临床管理中引入有效的抗逆转录病毒疗法与短时间内血浆病毒载量的高降低率相关。然而，由于病毒耐药性、毒性、治疗开始时间和药物方案的选择，长期病毒控制程度仍存在相当大的差异。特别是，开始治疗的最适当时间仍然是模糊的，需要足够早地开始治疗，以避免不可逆的损害，如果开始得太快，潜在的病毒抗性或毒性的问题平衡。确定有助于医生优化治疗开始时间的因素仍然是一个高度优先事项。我们在这个项目中的目的是开发和研究新的统计混合效应模型的使用，该模型旨在分析治疗开始后与访视时间病毒载量数据相关的因素，同时考虑到随时间推移的整个随访反应。该项目包括理论和实证分析的估计和推理性质的混合模型方法结合综合分析的预后因素与治疗后的病毒学控制的患者从西澳大利亚艾滋病毒队列研究。这些因素包括人口统计学、病毒学、免疫学、粘附性和宿主遗传因素。所开发的统计方法将具有广泛的适用性，并大大增加了一套程序，可用于纵向响应数据的分析。