Modeling the underlying biological processes in Alzheimer's disease using a multivariate competing risk joint model.

ABSTRACT: Many clinical trials repeatedly measure several longitudinal outcomes on patients. Patient follow-up can discontinue due to an outcome-dependent event, such as clinical diagnosis, death, or dropout. Joint modeling is a popular choice for the analysis of this type of data. Using example data from a prodromal Alzheimer's disease trial, we propose a new type of multivariate joint model in which longitudinal brain imaging outcomes and memory impairment ratings are allowed to be associated both with time to open-label medication and dropout, and where the brain imaging outcomes may also directly affect the memory impairment ratings. Existing joint models for multivariate longitudinal outcomes account for the correlation between the longitudinal outcomes through the random effects, often by assu

SUBMITTER: van Oudenhoven FM 

PROVIDER: S-EPMC9545329 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature