Power and sample size for multistate model analysis of longitudinal discrete outcomes in disease prevention trials.
clinical trial design
discrete outcomes
longitudinal data
multistate model
Journal
Statistics in medicine
ISSN: 1097-0258
Titre abrégé: Stat Med
Pays: England
ID NLM: 8215016
Informations de publication
Date de publication:
15 04 2021
15 04 2021
Historique:
received:
25
12
2019
revised:
18
12
2020
accepted:
19
12
2020
pubmed:
8
2
2021
medline:
30
6
2021
entrez:
7
2
2021
Statut:
ppublish
Résumé
For clinical trials where participants pass through a number of discrete health states resulting in longitudinal measures over time, there are several potential primary estimands for the treatment effect. Incidence or time to a particular health state are commonly used outcomes but the choice of health state may not be obvious and these estimands do not make full use of the longitudinal assessments. Multistate models have been developed for some diseases and conditions with the purpose of understanding their natural history and have been used for secondary analysis to understand mechanisms of action of treatments. There is little published on the use of multistate models as the primary analysis method and potential implications on design features, such as assessment schedules. We illustrate methods via analysis of data from a motivating example; a Phase III clinical trial of pressure ulcer prevention strategies. We clarify some of the possible estimands that might be considered and we show, via a simulation study, that under some circumstances the sample size could be reduced by half using a multistate model based analysis, without adversely affecting the power of the trial.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1960-1971Subventions
Organisme : Department of Health
ID : DRF-2016-09-085
Pays : United Kingdom
Informations de copyright
© 2021 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd.
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