KMstability: R tools to report the stability and precision of Kaplan-Meier estimates as well as measures of follow-up in time-to-event studies

In order to appropriately report time-to-event analyses by means of Kaplan-Meier estimates, its precision and stability should be described. The precision is often reported by confidence intervals. For reporting the stability, various measures of the follow-up time distribution are used. However, th...

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Hauptverfasser: Erdmann, Stella (VerfasserIn) , Betensky, Rebecca (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: May 2024
In: SoftwareX
Year: 2024, Jahrgang: 26, Pages: 1-6
ISSN:2352-7110
DOI:10.1016/j.softx.2024.101650
Online-Zugang:Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.softx.2024.101650
Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S2352711024000219
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Verfasserangaben:Stella Erdmann, Rebecca Betensky

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520 |a In order to appropriately report time-to-event analyses by means of Kaplan-Meier estimates, its precision and stability should be described. The precision is often reported by confidence intervals. For reporting the stability, various measures of the follow-up time distribution are used. However, these do not provide the intended insight. Recently, a new stability measure was presented. We have developed the software KMstability for calculation and display of this stability measure, including a user-friendly R shiny application and an open-source R package. The software enables informative reporting of time-to-event analysis. This is essential for reporting time-to-event analyses at interim-analyses of clinical trials and for observational (real-world-data) studies. 
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