Explained variation and degrees of necessity and of sufficiency for competing risks survival data.
Fine and Gray model
competing risks
explained variation
necessary condition
sufficient condition
Journal
Biometrical journal. Biometrische Zeitschrift
ISSN: 1521-4036
Titre abrégé: Biom J
Pays: Germany
ID NLM: 7708048
Informations de publication
Date de publication:
Mar 2024
Mar 2024
Historique:
revised:
15
11
2023
received:
24
05
2023
accepted:
08
12
2023
medline:
27
2
2024
pubmed:
27
2
2024
entrez:
27
2
2024
Statut:
ppublish
Résumé
In this contribution, the Schemper-Henderson measure of explained variation for survival outcomes is extended to accommodate competing events (CEs) in addition to events of interest. The extension is achieved by moving from the unconditional and conditional survival functions of the original measure to unconditional and conditional cumulative incidence functions, the latter obtained, for example, from Fine and Gray models. In the absence of CEs, the original measure is obtained as a special case. We define explained variation on the population level and provide two different types of estimates. Recently, the authors have achieved a multiplicative decomposition of explained variation into degrees of necessity and degrees of sufficiency. These measures are also extended to the case of competing risks survival data. A SAS macro and an R function are provided to facilitate application. Interesting empirical properties of the measures are explored on the population level and by an extensive simulation study. Advantages of the approach are exemplified by an Austrian study of breast cancer with a high proportion of CEs.
Identifiants
pubmed: 38409618
doi: 10.1002/bimj.202300140
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e2300140Informations de copyright
© 2024 The Authors. Biometrical Journal published by Wiley-VCH GmbH.
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