Zhang Min, Schaubel Douglas E
Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109-2029, USA.
Biometrics. 2012 Dec;68(4):999-1009. doi: 10.1111/j.1541-0420.2012.01759.x. Epub 2012 Apr 4.
Restricted mean lifetime is often of direct interest in epidemiologic studies involving censored survival times. Differences in this quantity can be used as a basis for comparing several groups. For example, transplant surgeons, nephrologists, and of course patients are interested in comparing posttransplant lifetimes among various types of kidney transplants to assist in clinical decision making. As the factor of interest is not randomized, covariate adjustment is needed to account for imbalances in confounding factors. In this report, we use semiparametric theory to develop an estimator for differences in restricted mean lifetimes although accounting for confounding factors. The proposed method involves building working models for the time-to-event and coarsening mechanism (i.e., group assignment and censoring). We show that the proposed estimator possesses the double robust property; i.e., when either the time-to-event or coarsening process is modeled correctly, the estimator is consistent and asymptotically normal. Simulation studies are conducted to assess its finite-sample performance and the method is applied to national kidney transplant data.
受限平均寿命在涉及删失生存时间的流行病学研究中常常是直接关注的对象。这个量的差异可作为比较多个组别的基础。例如，移植外科医生、肾病学家以及患者当然都有兴趣比较不同类型肾移植后的生存时间，以辅助临床决策。由于感兴趣的因素并非随机分配，所以需要进行协变量调整以考虑混杂因素的不平衡。在本报告中，我们运用半参数理论来开发一种用于估计受限平均寿命差异的方法，同时考虑混杂因素。所提出的方法涉及为事件发生时间和删失机制（即分组分配和删失）构建工作模型。我们表明，所提出的估计量具有双重稳健性；也就是说，当事件发生时间或删失过程被正确建模时，估计量是一致的且渐近正态。我们进行了模拟研究以评估其有限样本性能，并将该方法应用于全国肾移植数据。
