TY  - JOUR
AU  - Edelmann, Dominic
AU  - Saadati, Maral
AU  - Putter, Hein
AU  - Goeman, Jelle
TI  - A global test for competing risks survival analysis.
JO  - Statistical methods in medical research
VL  - 29
IS  - 12
SN  - 1477-0334
CY  - London [u.a.]
PB  - Sage
M1  - DKFZ-2020-01224
SP  - 3666-3683
PY  - 2020
N1  - 2020 Dec;29(12):3666-3683#EA:C060#
AB  - Standard tests for the Cox model, such as the likelihood ratio test or the Wald test, do not perform well in situations, where the number of covariates is substantially higher than the number of observed events. This issue is perpetuated in competing risks settings, where the number of observed occurrences for each event type is usually rather small. Yet, appropriate testing methodology for competing risks survival analysis with few events per variable is missing. In this article, we show how to extend the global test for survival by Goeman et al. to competing risks and multistate models[Per journal style, abstracts should not have reference citations. Therefore, can you kindly delete this reference citation.]. Conducting detailed simulation studies, we show that both for type I error control and for power, the novel test outperforms the likelihood ratio test and the Wald test based on the cause-specific hazards model in settings where the number of events is small compared to the number of covariates. The benefit of the global tests for competing risks survival analysis and multistate models is further demonstrated in real data examples of cancer patients from the European Society for Blood and Marrow Transplantation.
LB  - PUB:(DE-HGF)16
C6  - pmid:32631137
DO  - DOI:10.1177/0962280220938402
UR  - https://inrepo02.dkfz.de/record/156917
ER  -