A comparative study to alternatives to the log-rank test.
Crossing hazards
Log-rank
Non-proportional hazards
Simulation study
Survival analysis
Journal
Contemporary clinical trials
ISSN: 1559-2030
Titre abrégé: Contemp Clin Trials
Pays: United States
ID NLM: 101242342
Informations de publication
Date de publication:
05 2023
05 2023
Historique:
received:
09
11
2022
revised:
17
03
2023
accepted:
20
03
2023
medline:
8
5
2023
pubmed:
28
3
2023
entrez:
27
3
2023
Statut:
ppublish
Résumé
Studies to compare the survival of two or more groups using time-to-event data are of high importance in medical research. The gold standard is the log-rank test, which is optimal under proportional hazards. As the latter is no simple regularity assumption, we are interested in evaluating the power of various statistical tests under different settings including proportional and non-proportional hazards with a special emphasis on crossing hazards. This challenge has been going on for many years now and multiple methods have already been investigated in extensive simulation studies. However, in recent years new omnibus tests and methods based on the restricted mean survival time appeared that have been strongly recommended in biometric literature. Thus, to give updated recommendations, we perform a vast simulation study to compare tests that showed high power in previous studies with these more recent approaches. We thereby analyze various simulation settings with varying survival and censoring distributions, unequal censoring between groups, small sample sizes and unbalanced group sizes. Overall, omnibus tests are more robust in terms of power against deviations from the proportional hazards assumption. We recommend considering the more robust omnibus approaches for group comparison in case of uncertainty about the underlying survival time distributions.
Sections du résumé
BACKGROUND
Studies to compare the survival of two or more groups using time-to-event data are of high importance in medical research. The gold standard is the log-rank test, which is optimal under proportional hazards. As the latter is no simple regularity assumption, we are interested in evaluating the power of various statistical tests under different settings including proportional and non-proportional hazards with a special emphasis on crossing hazards. This challenge has been going on for many years now and multiple methods have already been investigated in extensive simulation studies. However, in recent years new omnibus tests and methods based on the restricted mean survival time appeared that have been strongly recommended in biometric literature.
METHODS
Thus, to give updated recommendations, we perform a vast simulation study to compare tests that showed high power in previous studies with these more recent approaches. We thereby analyze various simulation settings with varying survival and censoring distributions, unequal censoring between groups, small sample sizes and unbalanced group sizes.
RESULTS
Overall, omnibus tests are more robust in terms of power against deviations from the proportional hazards assumption.
CONCLUSION
We recommend considering the more robust omnibus approaches for group comparison in case of uncertainty about the underlying survival time distributions.
Identifiants
pubmed: 36972865
pii: S1551-7144(23)00088-5
doi: 10.1016/j.cct.2023.107165
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
107165Informations de copyright
Copyright © 2023. Published by Elsevier Inc.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.