Sun Wenguang, Joffe Marshall M, Chen Jinbo, Brunelli Steven M
Department of Statistics, North Carolina State University, Raleigh, North Carolina 27695, USA.
Biometrics. 2010 Dec;66(4):1220-9. doi: 10.1111/j.1541-0420.2009.01369.x.
In case-control research where there are multiple case groups, standard analyses fail to make use of all available information. Multiple events case-control (MECC) studies provide a new approach to sampling from a cohort and are useful when it is desired to study multiple types of events in the cohort. In this design, subjects in the cohort who develop any event of interest are sampled, as well as a fraction of the remaining subjects. We show that a simple case-control analysis of data arising from MECC studies is biased and develop three general estimating-equation-based approaches to analyzing data from these studies. We conduct simulation studies to compare the efficiency of the various MECC analyses with each other and with the corresponding conventional analyses. It is shown that the gain in efficiency by using the new design is substantial in many situations. We demonstrate the application of our approach to a nested case-control study of the effect of oral sodium phosphate use on chronic kidney injury with multiple case definitions.
在存在多个病例组的病例对照研究中，标准分析未能利用所有可用信息。多事件病例对照（MECC）研究提供了一种从队列中抽样的新方法，当希望研究队列中的多种事件类型时非常有用。在这种设计中，对队列中发生任何感兴趣事件的受试者以及其余部分受试者的一部分进行抽样。我们表明，对MECC研究产生的数据进行简单的病例对照分析存在偏差，并开发了三种基于一般估计方程的方法来分析这些研究的数据。我们进行模拟研究，以比较各种MECC分析彼此之间以及与相应传统分析的效率。结果表明，在许多情况下，使用新设计可大幅提高效率。我们展示了我们的方法在一项嵌套病例对照研究中的应用，该研究探讨了使用口服磷酸钠对慢性肾损伤的影响，采用了多种病例定义。
