Guo Ying, Manatunga Amita K
Department of Biostatistics, Rollins School of Public Health of Emory University, 1518 Clifton Road N.E., Atlanta, Georgia 30322, USA.
Biometrics. 2007 Mar;63(1):164-72. doi: 10.1111/j.1541-0420.2006.00664.x.
Assessing agreement is often of interest in clinical studies to evaluate the similarity of measurements produced by different raters or methods on the same subjects. Lin's (1989, Biometrics 45, 255-268) concordance correlation coefficient (CCC) has become a popular measure of agreement for correlated continuous outcomes. However, commonly used estimation methods for the CCC do not accommodate censored observations and are, therefore, not applicable for survival outcomes. In this article, we estimate the CCC nonparametrically through the bivariate survival function. The proposed estimator of the CCC is proven to be strongly consistent and asymptotically normal, with a consistent bootstrap variance estimator. Furthermore, we propose a time-dependent agreement coefficient as an extension of Lin's (1989) CCC for measuring the agreement between survival times among subjects who survive beyond a specified time point. A nonparametric estimator is developed for the time-dependent agreement coefficient as well. It has the same asymptotic properties as the estimator of the CCC. Simulation studies are conducted to evaluate the performance of the proposed estimators. A real data example from a prostate cancer study is used to illustrate the method.
在临床研究中，评估一致性通常很重要，目的是评估不同评分者或方法对同一受试者所产生测量结果的相似性。林（1989年，《生物统计学》45卷，255 - 268页）的一致性相关系数（CCC）已成为用于相关连续结局一致性的常用度量。然而，常用的CCC估计方法无法处理删失观测值，因此不适用于生存结局。在本文中，我们通过二元生存函数对CCC进行非参数估计。所提出的CCC估计量被证明是强一致且渐近正态的，同时具有一个一致的自助方差估计量。此外，我们提出了一个随时间变化的一致性系数，作为林（1989年）CCC的扩展，用于测量在特定时间点后存活的受试者之间生存时间的一致性。还为随时间变化的一致性系数开发了一个非参数估计量。它具有与CCC估计量相同的渐近性质。进行了模拟研究以评估所提出估计量的性能。使用来自一项前列腺癌研究的真实数据示例来说明该方法。
