Abstract Number:
3024
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Speed
Participants:
Xiao Yu (1), Michael Lu (1)
Institutions:
(1) Edwards Lifesciences, Irvine, CA, USA
Co-Author:
First Author:
Presenting Author:
Abstract Text:
The cox regression model is widely applied in survival analysis. Time dependent covariates can be analyzed with cox regression model to solve the situation that the covariate changes over time during the follow-up period. While lacking the application this method using cardiovascular clinical trial data, this presentation illustrates the statistical methodology and the application of cox regression model with time dependent covariate. The results shows that post-discharge atrial fibrillation or flutter was a significant predictor of the composite endpoint of death, stroke or rehospitalization at 2 years irrespective the treatment (transcatheter heart valve replacement or surgery) among the low-risk patients with severe aortic stenosis.
Keywords:
cox regression model|time dependent covariate|survival analysis| | |
Sponsors:
Biometrics Section
Tracks:
Survival Analysis
Can this be considered for alternate subtype?
Yes
Are you interested in volunteering to serve as a session chair?
No
I have read and understand that JSM participants must abide by the Participant Guidelines.
Yes
I understand that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is non-refundable.
I understand