Multi-state Models for the Analysis of Survival Studies in Biomedical Research: An Alternative to Composite Endpoints

Alicia Quirós, Armando Pérez de Prado, Natalia Montoya, José Hernández

Abstract

Primary endpoints of survival studies in biomedical research are usually composite endpoints, which indicate whether any of a list of events is observed. They are practical to empower studies and in the presence of competing risks, although constrained. In this work, we propose a more sophisticated modelization of the evolution of the disease for a patient with multi-state models, which allow to define relationships between adverse events by a state structure. Each transition between states may depend on different covariates, which provides a personalized prediction for patients, considering their characteristics, treatment and observed disease evolution. In order to illustrate their performance, we analyze a study in interventional cardiology including 1008 patients with acute coronary syndrome who underwent percutaneous revascularization between 2013 and 2019. The results show the great potential of multi-states models for analyzing survival studies in biomedical research.

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Paper Citation


in Harvard Style

Quirós A., Pérez de Prado A., Montoya N. and Hernández J. (2020). Multi-state Models for the Analysis of Survival Studies in Biomedical Research: An Alternative to Composite Endpoints.In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, ISBN 978-989-758-398-8, pages 194-199. DOI: 10.5220/0009105701940199


in Bibtex Style

@conference{bioinformatics20,
author={Alicia Quirós and Armando Pérez de Prado and Natalia Montoya and José Hernández},
title={Multi-state Models for the Analysis of Survival Studies in Biomedical Research: An Alternative to Composite Endpoints},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS,},
year={2020},
pages={194-199},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009105701940199},
isbn={978-989-758-398-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS,
TI - Multi-state Models for the Analysis of Survival Studies in Biomedical Research: An Alternative to Composite Endpoints
SN - 978-989-758-398-8
AU - Quirós A.
AU - Pérez de Prado A.
AU - Montoya N.
AU - Hernández J.
PY - 2020
SP - 194
EP - 199
DO - 10.5220/0009105701940199