Predicting the Risk of Alzheimer’s Disease and Related Dementia in Patients with Mild Cognitive Impairment Using a Semi-Competing Risk Approach

Author:

Chen Zhaoyi1,Yang Yuchen2ORCID,Zhang Dazheng2,Guo Jingchuan3,Guo Yi1ORCID,Hu Xia4,Chen Yong2,Bian Jiang1ORCID

Affiliation:

1. Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL 32611, USA

2. Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA

3. Department of Pharmaceutical Outcomes & Policy, University of Florida, Gainesville, FL 32611, USA

4. Department of Computer Science, Rice University, Houston, TX 77005, USA

Abstract

Alzheimer’s disease (AD) and AD-related dementias (AD/ADRD) are a group of progressive neurodegenerative diseases. The progression of AD can be conceptualized as a continuum in which patients progress from normal cognition to preclinical AD (i.e., no symptoms but biological changes in the brain) to mild cognitive impairment (MCI) due to AD (i.e., mild symptoms but not interfere with daily activities), followed by increasing severity of dementia due to AD. Early detection and prediction models for the transition of MCI to AD/ADRD are needed, and efforts have been made to build predictions of MCI conversion to AD/ADRD. However, most existing studies developing such prediction models did not consider the competing risks of death, which may result in biased risk estimates. In this study, we aim to develop a prediction model for AD/ADRD among patients with MCI considering the competing risks of death using a semi-competing risk approach.

Funder

National Institutes of Health

Patient-Centered Outcomes Research Institute

Publisher

MDPI AG

Subject

Computer Networks and Communications,Human-Computer Interaction,Communication

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