Dynamic lifetime risk prediction of Alzheimer's disease with longitudinal cognitive assessment measurements.

ABSTRACT:

Introduction

The progressive nature of Alzheimer's disease (AD) highlights the importance of predicting lifetime risk and updating assessments as new data emerge. This study aimed to develop a dynamic model using longitudinal cognitive assessments for updated risk predictions.

Methods

This study used data from the Religious Orders Study and the Rush Memory and Aging Project (ROSMAP) to develop a dynamic risk prediction model based on five cognitive domains, updated annually over 10 years.

Results

The lifetime prediction models based on 2384 participants showed improved area under the curve (AUC) over time, rising from 0.578 at baseline to 0.765 with 10 years of data. The models predicting AD onset before ages 85 and 90 showed superior performance, with AUCs increasing

SUBMITTER: Ding H 

PROVIDER: S-EPMC11881628 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature