Evaluating prognostic accuracy of biomarkers in nested case-control studies
Evaluating prognostic accuracy of biomarkers in nested case-control studies
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DOI：
10.1093/biostatistics/kxr021
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发表时间：
2012-01-01
期刊：
影响因子：
2.1
通讯作者：
Zheng, Yingye
中科院分区：
文献类型：
--
作者：
Cai, Tianxi;Zheng, Yingye
巢式病例对照（NCC）设计是流行病学研究中经常使用的一种经济有效的亚队列抽样策略，用于进行生物标志物研究。另一方面，由于生物标志物测量结果依赖性缺失，采样策略为数据分析带来了挑战。在本文中，我们提出了逆概率加权（IPW）的方法进行推断的一种新的生物标志物预测未来事件的数据从NCC研究的预后准确性。利用经验过程理论和弱相依随机变量序列的收敛定理，得到了这些估计的相合性和渐近正态性。使用Frachial Offspring Study数据的仿真和分析表明，所提出的方法在有限样本中表现良好。
Nested case-control (NCC) design is used frequently in epidemiological studies as a cost-effective subcohort sampling strategy to conduct biomarker research. Sampling strategy, on the other hoand, creates challenges for data analysis because of outcome-dependent missingness in biomarker measurements. In this paper, we propose inverse probability weighted (IPW) methods for making inference about the prognostic accuracy of a novel biomarker for predicting future events with data from NCC studies. The consistency and asymptotic normality of these estimators are derived using the empirical process theory and convergence theorems for sequences of weakly dependent random variables. Simulation and analysis using Framingham Offspring Study data suggest that the proposed methods perform well in finite samples.