Tools & techniques - Statistics: Dealing with time-varying covariates in survival analysis - joint models versus Cox models

摘要

Nowadays, there is great interest in interventional cardiology and in the medical scientific community in general in the development of prognostic models in the context of survival analysis. In particular, physicians have a variety of tests and biomarkers at their disposal to aid them in optimising medical care, and in many cases these tests are performed regularly in time to provide a better picture of the disease progression of a patient.When it comes to the statistical analysis of this type of data we need to pay particular attention to the fact that we have two types of covariates/predictors to consider, i.e., covariates whose values are fixed from baseline to the end of the study, and covariates whose values change during follow-up.