Sequences of cognitive decline in typical Alzheimer's disease and posterior cortical atrophy estimated using a novel event-based model of disease progression

Abstract

Introduction: This work aims to characterize the sequence in which cognitive deficits appear in two dementia syndromes.

Methods: Event-based modeling estimated fine-grained sequences of cognitive decline in clinically-diagnosed posterior cortical atrophy (PCA) ( $n=94$ ) and typical Alzheimer's disease (tAD) ( $n=61$ ) at the UCL Dementia Research Centre. Our neuropsychological battery assessed memory, vision, arithmetic, and general cognition. We adapted the event-based model to handle highly non-Gaussian data such as cognitive test scores where ceiling/floor effects are common.

Results: Experiments revealed differences and similarities in the fine-grained ordering of cognitive decline in PCA (vision first) and tAD (memory first). Simulation experiments reveal that our new model equals or exceeds performance of the classic event-based model, especially for highly non-Gaussian data.

Discussion: Our model recovered realistic, phenotypical progression signatures that may be applied in dementia clinical trials for enrichment, and as a data-driven composite cognitive end-point.

Keywords: Alzheimer's disease; ceiling; cognitive decline; dementia; disease progression model; effect; floor; kernel density estimate; non-Gaussian; nonparametric mixture model; posterior cortical atrophy.