Murray S, Tsiatis A A
Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109-2029, USA.
Lifetime Data Anal. 2001 Jun;7(2):125-41. doi: 10.1023/a:1011392622173.
Murray and Tsiatis (1996) described a weighted survival estimate that incorporates prognostic time-dependent covariate information to increase the efficiency of estimation. We propose a test statistic based on the statistic of Pepe and Fleming (1989, 1991) that incorporates these weighted survival estimates. As in Pepe and Fleming, the test is an integrated weighted difference of two estimated survival curves. This test has been shown to be effective at detecting survival differences in crossing hazards settings where the logrank test performs poorly. This method uses stratified longitudinal covariate information to get more precise estimates of the underlying survival curves when there is censored information and this leads to more powerful tests. Another important feature of the test is that it remains valid when informative censoring is captured by the incorporated covariate. In this case, the Pepe-Fleming statistic is known to be biased and should not be used. These methods could be useful in clinical trials with heavy censoring that include collection over time of covariates, such as laboratory measurements, that are prognostic of subsequent survival or capture information related to censoring.
默里和齐亚蒂斯（1996年）描述了一种加权生存估计方法，该方法纳入了与预后相关的随时间变化的协变量信息，以提高估计效率。我们基于佩佩和弗莱明（1989年、1991年）的统计量提出了一种检验统计量，该统计量纳入了这些加权生存估计值。与佩佩和弗莱明的方法一样，该检验是两条估计生存曲线的综合加权差值。在对数秩检验表现不佳的交叉风险环境中，已证明该检验在检测生存差异方面是有效的。当存在删失信息时，该方法使用分层纵向协变量信息来更精确地估计潜在的生存曲线，这会带来更强大的检验。该检验的另一个重要特征是，当纳入的协变量捕捉到信息性删失时，它仍然有效。在这种情况下，已知佩佩 - 弗莱明统计量存在偏差，不应使用。这些方法在具有大量删失的临床试验中可能有用，这些试验包括随着时间收集协变量，如实验室测量值，这些协变量对后续生存具有预后作用或捕捉与删失相关的信息。
