Improved Methods for Assessing Immune Correlates in HIV-1 Vaccine Trials

描述（由申请人提供）：艾滋病毒疫苗研究是抗击全球艾滋病毒/艾滋病流行病的重要组成部分。寻找预测疫苗诱导保护的免疫反应或“免疫相关物”对HIV疫苗研究有很大影响，因为它揭示了保护机制并有助于改进疫苗设计。该建议由两组统计方法组成，用于提高识别免疫相关物的统计能力。目的1开发的方法，将帮助研究人员选择最佳的免疫反应阳性标准。免疫应答的阳性标准是将受试者的应答分类为阴性或阳性的一组规则。一个好的阳性标准可以用来帮助定义免疫反应变量，以评估它们与感染状态的相关性。该提案采用决策理论方法来选择平衡假阳性率和假阴性率的阳性标准。目的2为用于测量免疫应答的重要技术：多重微珠阵列（MBA）开发分析方法。处理MBA数据的一个关键步骤是使用含有已知量待测分析物的标准样品的数据拟合浓度-响应曲线。较差的曲线拟合导致较大的测量误差，这将抑制感染状态与观察到的免疫应答之间的统计关联。该提案审查了曲线拟合中的两个问题。首先，两种方法来处理所观察到的荧光强度的均值-方差关系进行了比较：加权最小二乘法和非加权最小二乘法对对数转换的荧光强度。其次，比较了三种模型的浓度-响应曲线的形状：四参数logistic模型，五参数logistic模型和半参数模型。

DESCRIPTION (provided by applicant): HIV vaccine research is an essential part of the fight against the global HIV/AIDS pandemic. Finding immune responses that predict vaccine-induced protection, or "immune correlates", has a great impact on the HIV vaccine research, as it sheds light on the mechanism of the protection and helps improve vaccine design. This proposal is composed of two sets of statistical methods for improving the statistical power of identifying immune correlates. Aim 1 develops methods that will help investigators choose the best immune response positivity criteria. A positivity criterion for an immune response is a set of rules that classifies a subject's response as either negative or positive. A good positivity criteron can be used to help define immune response variables to assess their correlation with infection status. The proposal takes a decision theoretic approach to choosing positivity criteria that balance the false positive rates and the false negative rates. Aim 2 develops analytical methods for an important technology used to measure immune responses: the multiplex bead array (MBA). A key step in processing MBA data is to fit a concentration-response curve using data from standard samples which contain known amounts of analytes to be measured. Poor curve fits lead to large measurement error, which will dampen the statistical association between the infection status and the observed immune responses. The proposal examines two issues in curve fitting. First, two approaches for handling the mean-variance relationship of the observed fluorescence intensity are compared: weighted least squares and un-weighted least squares on log-transformed fluorescence intensity. Second, three models for the shape of the concentration-response curves are compared: four-parameter logistic model, five-parameter logistic model, and a semi-parametric model.