Waltoft Berit Lindum
National Centre for Register-based Research, University of Aarhus, Taasingegade 1, 8000 Aarhus C, Denmark.
Comput Methods Programs Biomed. 2009 Feb;93(2):140-7. doi: 10.1016/j.cmpb.2008.08.004. Epub 2008 Oct 15.
In survival analyses, we often estimate the hazard rate of a specific cause. Sometimes the main focus is not the hazard rates but the cumulative incidences, i.e., the probability of having failed from a specific cause prior to a given time. The cumulative incidences may be calculated using the hazard rates, and the hazard rates are often estimated by the Cox regression. This procedure may not be suitable for large studies due to limited computer resources. Instead one uses Poisson regression, which approximates the Cox regression. Rosthøj et al. presented a SAS-macro for the estimation of the cumulative incidences based on the Cox regression. I present the functional form of the probabilities and variances when using piecewise constant hazard rates and a SAS-macro for the estimation using Poisson regression. The use of the macro is demonstrated through examples and compared to the macro presented by Rosthøj et al.
在生存分析中，我们常常估计特定病因的风险率。有时，主要关注点并非风险率，而是累积发病率，即给定时间之前因特定病因失败的概率。累积发病率可通过风险率计算得出，而风险率通常由Cox回归估计。由于计算机资源有限，此程序可能不适用于大型研究。取而代之的是使用泊松回归，它近似于Cox回归。罗斯托伊等人提出了一个基于Cox回归估计累积发病率的SAS宏程序。我给出了使用分段常数风险率时概率和方差的函数形式，以及一个使用泊松回归进行估计的SAS宏程序。通过示例展示了该宏程序的使用，并与罗斯托伊等人提出的宏程序进行了比较。
