Similarity of competing risks models with constant intensities in an application to clinical healthcare pathways involving prostate cancer surgery.
bootstrap
competing risks
multi-state models
similarity
small data
Journal
Statistics in medicine
ISSN: 1097-0258
Titre abrégé: Stat Med
Pays: England
ID NLM: 8215016
Informations de publication
Date de publication:
30 08 2022
30 08 2022
Historique:
revised:
28
02
2022
received:
06
10
2021
accepted:
16
05
2022
pubmed:
14
6
2022
medline:
22
7
2022
entrez:
13
6
2022
Statut:
ppublish
Résumé
The recent availability of routine medical data, especially in a university-clinical context, may enable the discovery of typical healthcare pathways, that is, typical temporal sequences of clinical interventions or hospital readmissions. However, such pathways are heterogeneous in a large provider such as a university hospital, and it is important to identify similar care pathways that can still be considered typical pathways. We understand the pathway as a temporal process with possible transitions from a single initial treatment state to hospital readmission of different types, which constitutes a competing risks setting. In this article, we propose a multi-state model-based approach to uncover pathway similarity between two groups of individuals. We describe a new bootstrap procedure for testing the similarity of constant transition intensities from two competing risk models. In a large simulation study, we investigate the performance of our similarity approach with respect to different sample sizes and different similarity thresholds. The studies are motivated by an application from urological clinical routine and we show how the results can be transferred to the application example.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
3804-3819Informations de copyright
© 2022 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
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