TY - JOUR JO - EuroIntervention TI - The “A, B, C” of multiple statistical methods for composite endpoints AB - Composite endpoints are commonly used in clinical trials, and time-to-first-event analysis has been the usual standard. Time-to-first-event analysis treats all components of the composite endpoint as having equal severity and is heavily influenced by short-term components. Over the last decade, novel statistical approaches have been introduced to overcome these limitations. We reviewed win ratio analysis, competing risk regression, negative binomial regression, Andersen-Gill regression, and weighted composite endpoint (WCE) analysis. Each method has both advantages and limitations.The advantage of win ratio and WCE analyses is that they take event severity into account by assigning weights to each component of the composite endpoint. These weights should be pre-specified, because they strongly influence treatment effect estimates. Negative binomial regression and Andersen-Gill analyses consider all events for each patient – rather than only the first event – and tend to have more statistical power than time-to-first-event analysis.Pre-specified novel statistical methods may enhance our understanding of novel therapy when components vary substantially in severity and timing. These methods consider the specific type of patients, drugs, devices, events, and follow-up duration. AU - Hara Hironori AU - van Klaveren David AU - Kogame Norihiro AU - Chichareon Ply AU - Modolo Rodrigo AU - Tomaniak Mariusz AU - Ono Masafumi AU - Kawashima Hideyuki AU - Takahashi Kuniaki AU - Capodanno Davide AU - Onuma Yoshinobu AU - Serruys Patrick W. VL - IS - Y1 - 28/04/2020 Y1 - 2020 DOI - 10.4244/EIJ-D-19-00953 SP - KW - clinical research KW - clinical trials KW - training and education PB - Europa Digital & Publishing UR - https://eurointervention.pcronline.com/article/the-a-b-c-of-multiple-statistical-methods-for-composite-endpoints SN - 1774-024X ER -