Competing risks in survival data analysis

被引：35

作者：

Dutz, Almut ^{[1
,2
,3
]}

Loeck, Steffen ^{[1
,2
,4
,5
,6
,7
]}

机构：

[1] Tech Univ Dresden, Fac Med, OncoRay Natl Ctr Radiat Res Oncol, Helmholtz Zentrum Dresden Rossendorf, Dresden, Germany

[2] Tech Univ Dresden, Univ Hosp Carl Gustav Carus, Helmholtz Zentrum Dresden Rossendorf, Dresden, Germany

[3] Inst Radiooncol OncoRay, Helmholtz Zentrum Dresden Rossendorf, Dresden, Germany

[4] German Canc Consortium DKTK, Partner Site Dresden, Heidelberg, Germany

[5] German Canc Res Ctr, Heidelberg, Germany

[6] Tech Univ Dresden, Fac Med, Dept Radiotherapy & Radiat Oncol, Dresden, Germany

[7] Tech Univ Dresden, Univ Hosp Carl Gustav Carus, Dresden, Germany

来源：

RADIOTHERAPY AND ONCOLOGY | 2019年 / 130卷

关键词：

Competing risk; Survival data; Time-to-event data; Cox regression; CUMULATIVE INCIDENCE; RADIOCHEMOTHERAPY; HAZARDS; TESTS; GUIDE;

D O I：

10.1016/j.radonc.2018.09.007

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

Clinical trials and retrospective studies in the field of radiation oncology often consider time-to-event data as their primary endpoint. Such studies are susceptible to competing risks, i.e. competing events may preclude the occurrence of the event of interest or modify the chance that the primary endpoint occurs. Competing risks are frequently neglected and the event of interest is analysed with standard statistical methods. Here, we would like to create awareness of the problem and demonstrate different methods for survival data analysis in the presence of competing risks. (C) 2018 Elsevier B.V. All rights reserved.

引用

页码：185 / 189

页数：5

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