Time-varying cox model for heart failure prediction in phospholamban p.(Arg14del)-positive individuals

Abstract Background Phospholamban (PLN) p.(Arg14del)-positive individuals are at risk for developing severe heart failure (HF), yet a comprehensive risk model for this outcome is missing. Our PLN registry contains longitudinal data which enables us to capture dynamic changes in covariables over time, while prior prediction models rely on baseline clinical information which may change over time. Using this longitudinal clinical information will enhance the accuracy of HF prediction and may aid patients selection for future (gene)therapy. Purpose The aim of this study is to develop a dynamic HF risk prediction model for PLN p.(Arg14del)-positive individuals. Method Data were collected of 594 PLN p.(Arg14del)-positive individuals who had no documented history of HF or myocardial infarction at time of the first echocardiography. We incorporated two time-dependent covariates in our time-varying Cox regression model: longitudinal individual predicted left ventricular ejection fraction (LVEF) and longitudinal individual predicted relative risk for major ventricular arrhythmia (VA). Predicted LVEF values were derived using observed LVEF values in a linear mixed-effect model, while the relative risk for major VA was predicted using a Cox regression model with major VA as the outcome. These time-dependent covariates were included in the time-varying Cox regression along with baseline covariables age at inclusion and previous major VA. The results were validated using 5-fold cross-validation. Results Over a median follow-up period of 3.6 years (interquartile range 1.4-6.8), 77 (13%) individuals developed HF, defined as a composite endpoint of HF hospitalisation, implantation of left ventricular assist device, heart transplantation and HF-related mortality. Our time-varying Cox regression model demonstrated a robust 5-year mean C-statistic of 0.904 (95% CI 0.901-0.908). The hazard ratio for time-dependent LVEF predictions was 0.89 per % LVEF increase (95% CI 0.87-0.91, p <0.001) and for time-dependent relative major VA risk predictions 3.59 (95% CI 1.49-8.69, p = 0.005). Regarding baseline covariates, age at inclusion had a hazard ratio of 1.01 (95% CI 0.99-1.03, p = 0.47) and previous major VA 0.48 (95% CI 0.21-1.1, p = 0.08). Combining the hazard ratios of time-dependent predicted relative risk for major VA and major VA in history results in a hazard ratio of 1.73. Conclusion Our study introduces a novel time-varying Cox regression model for the individual prediction of heart failure events in PLN p.(Arg14del)-positive individuals which may aid patient selection for future (gene)therapy. Results demonstrate robust predictive performance (C-statistic of 0.904, 95% CI 0.901-0.908), highlighting the significance of incorporating longitudinal data for enhanced prediction accuracy.