50: Statistical Methods for Composite Endpoints Accounting for Severity of Events

Music City Center 

Composite endpoints (CE), combining death and non-fatal events, are often used in randomized clinical trials when the incidence of individual events is low. CEs typically involve different event types, implying considerable differences in event severity and cost to the patient and healthcare system. Time-to-first-event analysis treats all components of the CE equally and is heavily influenced by short-term events, potentially misrepresenting clinical significance. Novel statistical methods have been introduced to overcome these limitations, including competing risk regression (CR), negative binomial (NB), and win ratio (WR). Joint frailty models (JFM) can account for the unobserved heterogeneity in the survival and informative censoring distributions associated with different event types and patient death. A simulation approach will be used to compare the performance of four methods – CR, NB, WR, and JFM. Performance will be assessed based on type I error, power, and ease of clinical interpretation. Best-performing approaches will then be applied to analyze the Comparative Effectiveness of an Individualized Hemodialysis model vs Conventional Hemodialysis (TwoPlus) trial.

composite endpoints

competing risk

negtative binomial

win ratio

joint frailty models

simulation 

Biopharmaceutical Section