Validation and Demonstration of a New Comprehensive Model of Alzheimer's Disease Progression

Overview

Journal Alzheimers Dement

Specialties Neurology
Psychiatry

Date 2021 May 15

PMID 33991041

Citations 6

Authors

Yaakov Stern

Eric Stallard

Bruce Kinosian

Carolyn Zhu

Stephanie Cosentino

Zhezhen Jin

Yian Gu

Affiliations

Soon will be listed here.

Abstract

Introduction: Identifying the course of Alzheimer's disease (AD) for individual patients is important for numerous clinical applications. Ideally, prognostic models should provide information about a range of clinical features across the entire disease process. Previously, we published a new comprehensive longitudinal model of AD progression with inputs/outputs covering 11 interconnected clinical measurement domains.

Methods: Here, we (1) validate the model on an independent cohort; and (2) demonstrate the model's utility in clinical applications by projecting changes in 6 of the 11 domains.

Results: Survival and prevalence curves for two representative outcomes-mortality and dependency-generated by the model accurately reproduced the observed curves both overall and for patients subdivided according to risk levels using an independent Cox model.

Discussion: The new model, validated here, effectively reproduces the observed course of AD from an initial visit assessment, allowing users to project coordinated developments for individual patients of multiple disease features.

Citing Articles

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Disentangling the genetic underpinnings of neuropsychiatric symptoms in Alzheimer's disease in the Alzheimer's Disease Sequencing Project: Study design and methodology.

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Stallard E, Kociolek A, Jin Z, Ryu H, Lee S, Cosentino S J Alzheimers Dis. 2023; 95(1):93-117.

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Berry D, Nguyen D, Cosentino S, Louis E J Neurol Sci. 2023; 450:120675.

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