Zhao Xiaobing, Zhou Xian
School of Mathematics and Statistics, Zhejiang University of Finance and Economics, Hangzhou, Zhejiang Province, China.
Lifetime Data Anal. 2010 Jul;16(3):316-32. doi: 10.1007/s10985-010-9159-8. Epub 2010 Mar 11.
Two-sample comparison of survival times with "cured patients" is of major interest and a challenging issue in many areas, particularly in cancer clinical research. Recently, several authors have proposed various procedures of comparison, including tests of no overall, no short-term and no long-term differences between two samples. In clinical practice, it is often of interest to detect the difference in treatment effects among noncured patients regardless of the difference between cure fractions. In this paper, we propose a statistical test to compare two samples with cured patients and possibly heterogeneous treatment effects based on a class of semi-parametric transformation models, and our main focus is on the survival times of noncured patients. The empirical and quantile processes are used to construct strong approximations for the empirical curves. The two-sample test is then constructed from general least squares estimators derived from these processes. Simulation results show that the proposed test perform well. As an example of application, a set of bladder cancer data is analyzed to illustrate the proposed methods.
对含“治愈患者”的生存时间进行两样本比较在许多领域都是主要关注点且是一个具有挑战性的问题，尤其是在癌症临床研究中。最近，几位作者提出了各种比较方法，包括检验两个样本之间无总体差异、无短期差异和无长期差异。在临床实践中，通常关注的是检测未治愈患者之间治疗效果的差异，而不考虑治愈比例之间的差异。在本文中，我们基于一类半参数变换模型提出了一种统计检验，用于比较两个含治愈患者且可能具有异质性治疗效果的样本，并且我们主要关注未治愈患者的生存时间。经验过程和分位数过程用于构建经验曲线的强近似。然后从由这些过程导出的一般最小二乘估计量构建两样本检验。模拟结果表明所提出的检验表现良好。作为应用示例，分析了一组膀胱癌数据以说明所提出的方法。
