Sample Size Calculation Under Nonproportional Hazards Using Average Hazard Ratios.
effect measure
hazard ratio
log‐rank test
sample size
simulation study
survival analysis
time‐to‐event data
Journal
Biometrical journal. Biometrische Zeitschrift
ISSN: 1521-4036
Titre abrégé: Biom J
Pays: Germany
ID NLM: 7708048
Informations de publication
Date de publication:
Sep 2024
Sep 2024
Historique:
revised:
18
03
2024
received:
05
10
2023
accepted:
28
04
2024
medline:
12
8
2024
pubmed:
12
8
2024
entrez:
12
8
2024
Statut:
ppublish
Résumé
Many clinical trials assess time-to-event endpoints. To describe the difference between groups in terms of time to event, we often employ hazard ratios. However, the hazard ratio is only informative in the case of proportional hazards (PHs) over time. There exist many other effect measures that do not require PHs. One of them is the average hazard ratio (AHR). Its core idea is to utilize a time-dependent weighting function that accounts for time variation. Though propagated in methodological research papers, the AHR is rarely used in practice. To facilitate its application, we unfold approaches for sample size calculation of an AHR test. We assess the reliability of the sample size calculation by extensive simulation studies covering various survival and censoring distributions with proportional as well as nonproportional hazards (N-PHs). The findings suggest that a simulation-based sample size calculation approach can be useful for designing clinical trials with N-PHs. Using the AHR can result in increased statistical power to detect differences between groups with more efficient sample sizes.
Identifiants
pubmed: 39132909
doi: 10.1002/bimj.202300271
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e202300271Subventions
Organisme : Research Center Trustworthy Data Science and Security
Organisme : DFG
Informations de copyright
© 2024 The Author(s). Biometrical Journal published by Wiley‐VCH GmbH.
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