D'Angelo Gina, Weissfeld Lisa
Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110-1093, USA.
Stat Med. 2008 Sep 30;27(22):4502-14. doi: 10.1002/sim.3285.
Medical studies frequently collect biological markers in which many subjects have values below the detectable limits of the assay, resulting in heavily censored data. We develop a modification of the Rigobon and Stoker index method for application to a Cox regression model with censored covariates. The index approach is compared with a complete case method and various fill-in methods. Our simulation results demonstrated that the index approach is an improvement over the other methods. We illustrated the usefulness of this approach with an example for the GenIMS study examining the relationship between two inflammatory markers and survival.
医学研究经常收集生物标志物,其中许多受试者的值低于检测方法的可检测限,从而产生大量删失数据。我们对里戈邦和斯托克指数方法进行了改进,以应用于具有删失协变量的Cox回归模型。将该指数方法与完全病例法和各种填补法进行了比较。我们的模拟结果表明,该指数方法比其他方法有所改进。我们通过一个关于GenIMS研究的例子说明了这种方法的实用性,该研究考察了两种炎症标志物与生存率之间的关系。