Stacked probability plots of the extended illness-death model using constant transition hazards – an easy to use shiny app

Bibliographic Details
Title: Stacked probability plots of the extended illness-death model using constant transition hazards – an easy to use shiny app
Authors: Marlon Grodd, Susanne Weber, Martin Wolkewitz
Source: BMC Medical Research Methodology, Vol 24, Iss 1, Pp 1-8 (2024)
Publisher Information: BMC, 2024.
Publication Year: 2024
Collection: LCC:Medicine (General)
Subject Terms: Markov process, Transition probability, Hazard rates, Extended illness-death model, Stacked probability plot, Medicine (General), R5-920
More Details: Abstract Background Extended illness-death models (a specific class of multistate models) are a useful tool to analyse situations like hospital-acquired infections, ventilation-associated pneumonia, and transfers between hospitals. The main components of these models are hazard rates and transition probabilities. Calculation of different measures and their interpretation can be challenging due to their complexity. Methods By assuming time-constant hazards, the complexity of these models becomes manageable and closed mathematical forms for transition probabilities can be derived. Using these forms, we created a tool in R to visualize transition probabilities via stacked probability plots. Results In this article, we present this tool and give some insights into its theoretical background. Using published examples, we give guidelines on how this tool can be used. Our goal is to provide an instrument that helps obtain a deeper understanding of a complex multistate setting. Conclusion While multistate models (in particular extended illness-death models), can be highly complex, this tool can be used in studies to both understand assumptions, which have been made during planning and as a first step in analysing complex data structures. An online version of this tool can be found at https://eidm.imbi.uni-freiburg.de/ .
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1471-2288
Relation: https://doaj.org/toc/1471-2288
DOI: 10.1186/s12874-024-02240-3
Access URL: https://doaj.org/article/e48fd2dbcd624b249333a6f3f435530c
Accession Number: edsdoj.48fd2dbcd624b249333a6f3f435530c
Database: Directory of Open Access Journals
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More Details
ISSN:14712288
DOI:10.1186/s12874-024-02240-3
Published in:BMC Medical Research Methodology
Language:English