Lin D Y, Fleming T R, De Gruttola V
Department of Biostatistics, University of Washington, Seattle 98195, USA.
Stat Med. 1997 Jul 15;16(13):1515-27. doi: 10.1002/(sici)1097-0258(19970715)16:13<1515::aid-sim572>3.0.co;2-1.
In this paper, we measure the extent to which a biological marker is a surrogate endpoint for a clinical event by the proportional reduction in the regression coefficient for the treatment indicator due to the inclusion of the marker in the Cox regression model. We estimate this proportion by applying the partial likelihood function to two Cox models postulated on the same failure time variable. We show that the resultant estimator is asymptotically normal with a simple variance estimator. One can construct confidence intervals for the proportion by using the direct normal approximation to the point estimator or by using Fieller's theorem. Extensive simulation studies demonstrate that the proposed methods are appropriate for practical use. We provide applications to HIV/AIDS clinical trials.
在本文中，我们通过在Cox回归模型中纳入生物标志物后治疗指标回归系数的比例降低，来衡量该生物标志物作为临床事件替代终点的程度。我们通过将偏似然函数应用于基于相同失效时间变量假设的两个Cox模型来估计这个比例。我们表明，所得估计量渐近正态，且具有简单的方差估计量。可以通过对点估计量使用直接正态近似或使用菲勒定理来构建该比例的置信区间。大量的模拟研究表明，所提出的方法适用于实际应用。我们提供了在HIV/AIDS临床试验中的应用。
