Learning the Treatment Impact on Time-to-Event Outcomes: The Transcarotid Artery Revascularization Simulated Cohort

Proportional hazard Cox regression models are overwhelmingly used for analyzing time-dependent outcomes. Despite their associated hazard ratio is a valuable index for the difference between populations, its strong dependency on the underlying assumptions makes it a source of misinterpretation. Recen...

Full description

Saved in:
Bibliographic Details
Published in:International journal of environmental research and public health 2022-09, Vol.19 (19), p.12476
Main Author: Martínez-Camblor, Pablo
Format: Article
Language:English
Subjects:
Arteries
Carotid arteries
Cohort Studies
Comorbidity
Humans
Proportional Hazards Models
Random variables
Regression analysis
Vascular Surgical Procedures
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Proportional hazard Cox regression models are overwhelmingly used for analyzing time-dependent outcomes. Despite their associated hazard ratio is a valuable index for the difference between populations, its strong dependency on the underlying assumptions makes it a source of misinterpretation. Recently, a number of works have dealt with the subtleties and limitations of this interpretation. Besides, a number of alternative indices and different Cox-type models have been proposed. In this work, we use synthetic data, motivated by a real-world problem, for showing the strengths and weaknesses of some of those methods in the analysis of time-dependent outcomes. We use the power of synthetic data for considering observable results but also utopian designs.
ISSN:1660-4601
1661-7827
1660-4601
DOI:10.3390/ijerph191912476