Making Sense of Hierarchical Composite End Points in Randomized Clinical Trials—A Primer for Infectious Diseases Clinicians and Researchers

Abstract

Hierarchical composite end points (HCEs), combining features of simple composite end points and conventional ordinal end points, are increasingly being used in infectious diseases (ID) research. However, many clinicians may be unfamiliar with these novel end points, including the variety of different target parameters that may be of interest and the methods that can be used to estimate them. In this review, we provide a conceptual overview of HCEs by defining them and providing examples from the ID literature. We explain different methods for analyzing HCEs, including (1) the Wilcoxon rank sum approach (often used in studies with a desirability of outcome ranking [DOOR] end point), (2) generalized pairwise comparisons (used to estimate a win ratio or win odds), (3) proportional odds model (and the relevance of the proportional odds assumption), and, (4) the probabilistic index model. This review will help ID clinicians and healthcare providers interpret current and future research using such end points.