Statistical methods for HIV-1 immune correlates studies

 描述(申请人提供)：寻找疫苗诱导的免疫反应生物标记物，预测对艾滋病毒-1和其他重要的fi病原体感染的疫苗保护作用，并了解它们作为保护机制的作用，是疫苗研究的重要组成部分。我们将免疫相关性研究分为三个阶段。fi第一阶段涉及免疫反应的测量，并可能涉及实验设计。第二阶段对fi第一阶段获得的免疫应答变量进行预处理，形成复合免疫应答变量。第三阶段研究临床结果和免疫反应变量之间的关系。我们将为每个阶段开发新的统计方法，以提高免疫反应测量的信噪比，创建具有最大信号多样性的免疫反应分数，并通过使用变点回归模型增加假设检验的能力。

 DESCRIPTION (provided by applicant): Finding vaccine-induced immune response biomarkers that predict vaccine-protection against HIV-1 and other significant pathogen infection, and understanding their role as mechanisms of protection, is an essential part of vaccine research. We distinguish three stages in immune correlates studies. The first stage deals with measurement of immune response and may involve experimental design. The second stage performs preprocessing of immune response variables obtained in the first stage to form composite immune response variables. The third stage examines the association between clinical outcome and immune response variables. We will develop novel statistical methods for each stage in order to increase the signal- to-noise ratio in immune response measurement, create immune response scores with maximum signal diversity, and increase the power of hypothesis testing by using change point regression model.