Joint modeling of multistate survival processes with informative examination scheme: application to progressions in diabetes

Our joint model offers a framework for analyzing multistate survival processes while accounting for the dependence between disease progression and examination frequency. Unlike traditional MSMs that estimate only transition intensities, our model captures variations in healthcare visit frequencies across different disease states, providing a more comprehensive understanding of disease dynamics and healthcare access patterns.

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Publication Details

Journal
BMC Medical Research Methodology
Published
2025-04-16
DOI
https://doi.org/10.1186/s12874-025-02543-z
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

Joint modeling of multistate survival processes with informative examination scheme: application to progressions in diabetes

Guy Brock, Neena Thomas, Joshua J. Joseph, Yuxi Zhu et al.
BMC Medical Research Methodology
Machine Learning in Healthcare
article

Joint modeling of multistate survival processes with informative examination scheme: application to progressions in diabetes

Guy Brock, Neena Thomas, Joshua J. Joseph, Yuxi Zhu, Lang Li
article en

Abstract

Our joint model offers a framework for analyzing multistate survival processes while accounting for the dependence between disease progression and examination frequency. Unlike traditional MSMs that estimate only transition intensities, our model captures variations in healthcare visit frequencies across different disease states, providing a more comprehensive understanding of disease dynamics and healthcare access patterns.

BMC Medical Research MethodologyVol. 25(1)
The Ohio State University (US)
Openalex Percentile: Top 97%
Machine Learning in Healthcare
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Joint modeling of multistate survival processes with informative examination scheme: application to progressions in diabetes — Guy Brock, Neena Thomas, et al. · BMC Medical Research Methodology (2025) | TGRS Research Map | TGRS