Group-sequential logrank methods for trial designs using bivariate non-competing event-time outcomes.
Bivariate dependence
Error-spending method
Independent censoring
Logrank statistic
Non-fatal events
Normal approximation
Journal
Lifetime data analysis
ISSN: 1572-9249
Titre abrégé: Lifetime Data Anal
Pays: United States
ID NLM: 9516348
Informations de publication
Date de publication:
04 2020
04 2020
Historique:
received:
18
04
2018
accepted:
03
04
2019
pubmed:
14
4
2019
medline:
23
7
2021
entrez:
14
4
2019
Statut:
ppublish
Résumé
We discuss the multivariate (2L-variate) correlation structure and the asymptotic distribution for the group-sequential weighted logrank statistics formulated when monitoring two correlated event-time outcomes in clinical trials. The asymptotic distribution and the variance-covariance for the 2L-variate weighted logrank statistic are derived as available in various group-sequential trial designs. These methods are used to determine a group-sequential testing procedure based on calendar times or information fractions. We apply the theoretical results to a group-sequential method for monitoring a clinical trial with early stopping for efficacy when the trial is designed to evaluate the joint effect on two correlated event-time outcomes. We illustrate the method with application to a clinical trial and describe how to calculate the required sample sizes and numbers of events.
Identifiants
pubmed: 30980317
doi: 10.1007/s10985-019-09470-4
pii: 10.1007/s10985-019-09470-4
pmc: PMC7517875
mid: NIHMS1629114
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
266-291Subventions
Organisme : NIAID NIH HHS
ID : UM1 AI068634
Pays : United States
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