Authors:
Alicia Quirós
1
;
Armando Pérez de Prado
2
;
Natalia Montoya
1
and
José M. De la Torre Hernández
3
Affiliations:
1
Departmento de Matemáticas, Universidad de León, Campus de Vegazana, León, Spain
;
2
Unidad de Cardiología Intervencionista, Complejo Asistencial Universitario de León, León, Spain
;
3
Unidad de Cardiología Intervencionista, Hospital Universitario Marqués de Valdecilla, Santander, Spain
Keyword(s):
Adverse Events, Competing Risks, Composite Endpoints, Disability Model, Interventional Cardiology, Multi-state Model, Survival Studies.
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.