Why follow-up matters in survival analysis: comparing cox proportional hazard regression and random survival forest for predicting heart failure outcomes

Improving PTFR enhances the validity and robustness of survival models. RSF outperformed Cox regression across both datasets, particularly under higher PTFR. Strategies such as extending follow-up duration and integrating data sources can help increase PTFR. These findings underscore the importance of adequate follow-up in predictive modeling and support the use of machine learning in clinical survival analysis.