Cox proportional hazards regression models are used to evaluate associations between exposures of interest and time-to-event outcomes in observational data. When exposures are measured on only a sample of participants, as they are in a case-cohort design, the sampling weights must be incorporated into the regression model to obtain unbiased estimating equations. Robust Cox methods have been developed to better estimate associations when there are influential outliers in the exposure of interest, but these robust methods do not incorporate sampling weights. In this paper, we extend these robust methods, which already incorporate influence weights, so that they also accommodate sampling weights. Simulations illustrate that in the presence of influential outliers, the association estimate from the weighted robust method is closer to the true value than the estimate from traditional weighted Cox regression. As expected, in the absence of outliers, the use of robust methods yields a small loss of efficiency. Using data from a case-cohort study that is nested within the Multi-Ethnic Study of Atherosclerosis (MESA) longitudinal cohort study, we illustrate differences between traditional and robust weighted Cox association estimates for the relationships between immune cell traits and risk of stroke. Robust weighted Cox regression methods are a new tool to analyze time-to-event data with sampling, e.g. case-cohort data, when exposures of interest contain outliers.

中文翻译：

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将抽样权重纳入 Cox 比例风险回归模型的稳健估计，并在动脉粥样硬化的多种族研究中进行了说明。

Cox 比例风险回归模型用于评估观察数据中感兴趣的暴露与事件发生时间结果之间的关联。当仅对一部分参与者样本测量暴露时，因为他们在案例队列设计中，必须将抽样权重纳入回归模型以获得无偏估计方程。已经开发出稳健的 Cox 方法以在感兴趣的暴露中有影响力的异常值时更好地估计关联，但这些稳健的方法不包含采样权重。在本文中，我们扩展了这些已经包含影响权重的稳健方法，以便它们也适应采样权重。模拟表明，在有影响力的异常值存在的情况下，加权稳健方法的关联估计比传统加权 Cox 回归的估计更接近真实值。正如预期的那样，在没有异常值的情况下，使用稳健的方法会产生少量的效率损失。使用来自动脉粥样硬化多种族研究 (MESA) 纵向队列研究中嵌套的病例队列研究的数据，我们说明了免疫细胞特征与中风风险之间关系的传统和稳健加权 Cox 关联估计之间的差异。稳健加权 Cox 回归方法是一种新工具，可在感兴趣的暴露包含异常值时通过采样分析事件发生时间数据，例如病例组数据。使用稳健的方法会产生少量的效率损失。使用来自动脉粥样硬化多种族研究 (MESA) 纵向队列研究中嵌套的病例队列研究的数据，我们说明了免疫细胞特征与中风风险之间关系的传统和稳健加权 Cox 关联估计之间的差异。稳健加权 Cox 回归方法是一种新工具，可在感兴趣的暴露包含异常值时通过采样分析事件发生时间数据，例如病例组数据。使用稳健的方法会产生少量的效率损失。使用来自动脉粥样硬化多种族研究 (MESA) 纵向队列研究中嵌套的病例队列研究的数据，我们说明了免疫细胞特征与中风风险之间关系的传统和稳健加权 Cox 关联估计之间的差异。稳健加权 Cox 回归方法是一种新工具，可在感兴趣的暴露包含异常值时通过采样分析事件发生时间数据，例如病例组数据。