Katsahian Sandrine, Porcher Raphaël, Mary Jean-Yves, Chevret Sylvie
Département de Biostatistique et Informatique Médicale, Hôpital Saint-Louis, Paris, France.
Stat Med. 2004 Dec 30;23(24):3851-63. doi: 10.1002/sim.1999.
In failure time studies involving a chronic disease such as cancer, data often focus on one or more non-fatal events, in addition to survival, to describe the course of the disease. In the example of allogeneic bone marrow transplantation in leukaemic patients, acute graft-versus host disease (aGvHD), relapse and death were taken as the reported events, and we focused on testing the existence of graft-versus-leukaemia (GvL) effect, i.e. that the occurrence of aGvHD modifies the probability of relapse. One of the weaknesses of the standard competing risks models is their inability to model secondary relapses. We thus derived, from two competing risks models, two estimators of cumulative incidence functions of primary and secondary relapses, as well as statistics to test the GvL effect. The approach is illustrated by application to a data set from a cohort of 442 children with acute leukaemia who received an unrelated transplant.
在涉及癌症等慢性疾病的生存时间研究中，除了生存情况外，数据通常还聚焦于一个或多个非致命事件，以描述疾病的进程。以白血病患者的异基因骨髓移植为例，急性移植物抗宿主病（aGvHD）、复发和死亡被视为报告事件，并且我们着重于检验移植物抗白血病（GvL）效应的存在，即aGvHD的发生是否会改变复发的概率。标准竞争风险模型的一个缺点是它们无法对二次复发进行建模。因此，我们从两个竞争风险模型中推导出了原发性和继发性复发累积发病率函数的两个估计量，以及用于检验GvL效应的统计量。通过应用于一个由442名接受非亲缘移植的急性白血病儿童组成的队列的数据集，对该方法进行了说明。
