Employing a latent variable framework to improve efficiency in composite endpoint analysis.

ABSTRACT: Composite endpoints that combine multiple outcomes on different scales are common in clinical trials, particularly in chronic conditions. In many of these cases, patients will have to cross a predefined responder threshold in each of the outcomes to be classed as a responder overall. One instance of this occurs in systemic lupus erythematosus, where the responder endpoint combines two continuous, one ordinal and one binary measure. The overall binary responder endpoint is typically analysed using logistic regression, resulting in a substantial loss of information. We propose a latent variable model for the systemic lupus erythematosus endpoint, which assumes that the discrete outcomes are manifestations of latent continuous measures and can proceed to jointly model the components of the co

SUBMITTER: McMenamin M 

PROVIDER: S-EPMC8172253 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature