Cox Regression Model with Time-varying Coefficients Applied to Survival Estimation of Heart Failure

Abstract

This study focuses on survival analysis of heart failure patients. All the patients, who are over 40 years old, have NYHA classes III or IV stages of heart failure. Cox regression model with time-varying coefficients is applied to deal with these data, which is updated in 2015. Kaplan Meier curves are plotted to screen out categorical variables that violates PH assumptions. As for continuous variables violating PH assumption, Schoenfeld residual plot is drawn to realize time stratification. Therefore, for each time period, cox proportional hazard model can be fit to estimate mortality and find out the key factors promoting or inhibiting death event of heart failure. As a result, age, blood pressure, serum creatinine, and ejection fraction are the significant features of hazard of death led by heart failure, which is validated by Wald test, Likelihood ratio test, and Log-rank test. Discrimination ability is also characterized by ROC curves and AUC finally.