Prediction of early Alzheimer′s disease progression based on Lasso Cox regression model

HAN Hongjuan; QIN Yao; QIAO Guoguo; CHEN Durong; CUI Jing; MA Yifei; ZHANG Rong; YU Hongmei

doi:10.16462/j.cnki.zhjbkz.2023.08.007

Volume 27 Issue 8

Aug. 2023

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HAN Hongjuan, QIN Yao, QIAO Guoguo, CHEN Durong, CUI Jing, MA Yifei, ZHANG Rong, YU Hongmei. Prediction of early Alzheimer′s disease progression based on Lasso Cox regression model[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2023, 27(8): 907-915. doi: 10.16462/j.cnki.zhjbkz.2023.08.007

Citation:

HAN Hongjuan, QIN Yao, QIAO Guoguo, CHEN Durong, CUI Jing, MA Yifei, ZHANG Rong, YU Hongmei. Prediction of early Alzheimer′s disease progression based on Lasso Cox regression model[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2023, 27(8): 907-915. doi: 10.16462/j.cnki.zhjbkz.2023.08.007

Citation:

HAN Hongjuan, QIN Yao, QIAO Guoguo, CHEN Durong, CUI Jing, MA Yifei, ZHANG Rong, YU Hongmei. Prediction of early Alzheimer′s disease progression based on Lasso Cox regression model[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2023, 27(8): 907-915. doi: 10.16462/j.cnki.zhjbkz.2023.08.007

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Prediction of early Alzheimer′s disease progression based on Lasso Cox regression model

doi: 10.16462/j.cnki.zhjbkz.2023.08.007

1.
Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan 030001, China
2.
Department of Mathematics, School of Basic Medical Sciences, Shanxi Medical University, Taiyuan 030001, China
3.
Teaching Experiment Center, School of Public Health, Shanxi Medical University, Taiyuan 030001, China
4.
Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment, Taiyuan 030001, China

Funds:

National Natural Science Foundation of China 81973154

Natural Science Foundation for Young Scientists of Shanxi Province 201901D211330

Natural Science Foundation for Young Scientists of Shanxi Province 20210302123242

Postgraduate Innovation Project in Shanxi Province 2022Y367

More Information

Corresponding author: YU Hongmei, E-mail: yu@sxmu.edu.cn
Received Date: 2022-04-14
Rev Recd Date: 2022-12-15

Available Online: 2023-09-02

Publish Date: 2023-08-10

Abstract

Abstract

Objective The study aims to explore predictors related to the progression from normal cognition (NC) to mild cognitive impairment (MCI), the reversion from MCI to NC, and the progression from MCI to Alzheimer′s disease (AD), and to establish corresponding prediction models. Methods Based on the Alzheimer′s Disease Neuroimaging Initiative (ADNI) database, three Lasso Cox regression models were developed to predict the transition from NC to MCI, the reversion from MCI to NC, and the progression from MCI to AD. Results The study included 502 NC and 990 MCI patients, of which 104 NC progressed to MCI, 90 MCI reverted to NC, and 370 MCI progressed to AD. The covariate effects of the predictors showed that lower Rey′s auditory verbal learning test-learning (HR=0.884 0, 95% CI: 0.778 0-0.990 0), atrophy of the entorhinal cortex (HR=0.999 6, 95% CI: 0.999 2-0.999 9), higher functional activities questionary score (HR=1.552 0, 95% CI: 1.292 0-1.813 0) and Tau protein (HR=1.003 0, 95% CI: 1.001 0-1.006 0) were associated with the progression from NC to MCI. Lower scores of Alzheimer′s disease assessment scale-13 (HR=0.925 0, 95% CI: 0.857 0-0.993 0), functional activity scale scores (HR=0.826 0, 95% CI: 0.691 0-0.961 0) and lower concentrations of Tau protein (HR=0.997 0, 95% CI: 0.994 0-0.999 0) were all relevant factors for MCI reversal to NC. The apolipoprotein E4 (APOE4) gene (HR=1.304 0, 95% CI: 1.069 0-1.540 0), longer years of education (HR=1.055 0, 95% CI: 1.017 0-1.093 0), higher clinical dementia rating sum of boxes score (HR=1.192 0, 95% CI: 1.060 0-1.324 0), Alzheimer′s disease assessment scale-13 entries (HR=1.036 0, 95% CI: 1.011 0-1.061 0), Rey′s auditory verbal learning test-immediate (HR=0.973 0, 95% CI: 0.956 0-0.990 0), functional activities questionary score (HR=1.065 0, 95% CI: 1.039 0-1.091 0), and phosphorylation Tau (HR=1.018 0, 95% CI: 1.009 0-1.027 0), lower Rey′s auditory verbal learning test-immediate (HR=0.973 0, 95% CI: 0.956 0-0.990 0) and lower concentrations of Aβ amyloid (HR=0.999 2, 95% CI: 0.998 8-0.999 6) were associated with the progression from MCI to AD. Conclusions The transformation among different stages of AD are affected by multiple factors. Risk prediction of AD is beneficial to perform health management intervention and preventive care in key populations, thereby reducing the risk of future disease progression.
- Alzheimer′s disease,
- Mild cognitive impairment,
- Normal cognition,
- Lasso Cox regression model

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References(16)

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