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Marginal additive hazards model for case-cohort studies with multiple disease outcomes: an application to the Atherosclerosis Risk in Communities (ARIC) study

机译:具有多种疾病结局的病例队列研究的边际附加危害模型:在社区动脉粥样硬化风险(ARIC)研究中的应用

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摘要

In the case-cohort studies conducted within the Atherosclerosis Risk in Communities (ARIC) study, it is of interest to assess and compare the effect of high-sensitivity C-reactive protein (hs-CRP) on the increased risks of incident coronary heart disease and incident ischemic stroke. Empirical cumulative hazards functions for different levels of hs-CRP reveal an additive structure for the risks for each disease outcome. Additionally, we are interested in estimating the difference in the risk for the different hs-CRP groups. Motivated by this, we consider fitting marginal additive hazards regression models for case-cohort studies with multiple disease outcomes. We consider a weighted estimating equations approach for the estimation of model parameters. The asymptotic properties of the proposed estimators are derived and their finite-sample properties are assessed via simulation studies. The proposed method is applied to analyze the ARIC Study.
机译:在社区动脉粥样硬化风险研究(ARIC)中进行的病例队列研究中,评估和比较高敏C反应蛋白(hs-CRP)对增加冠心病风险的作用是有意义的和缺血性中风。不同水平的hs-CRP的经验累积危害函数揭示了每种疾病结局风险的累加结构。此外,我们有兴趣估算不同hs-CRP组的风险差异。因此,我们考虑对具有多种疾病结局的病例队列研究拟合边际加性危害回归模型。我们考虑使用加权估计方程法估计模型参数。推导了拟议估计量的渐近性质,并通过模拟研究评估了它们的有限样本性质。该方法被用于分析ARIC研究。

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