基于里程碑模型的认知筛查从轻度认知障碍到阿尔茨海默病转化的个体动态预测

IF 1.8 4区 医学 Q3 CLINICAL NEUROLOGY
Jing Cui, Durong Chen, Jiajia Zhang, Yao Qin, Wenlin Bai, Yifei Ma, Rong Zhang, Hongmei Yu
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引用次数: 0

摘要

背景:在认知筛查中识别阿尔茨海默病(AD)风险增加的轻度认知障碍(MCI)个体对AD的早期诊断和预防具有重要意义。目的:本研究旨在提出一种基于里程碑模型的筛查策略,根据纵向神经认知测试提供mci到ad转换的动态预测概率。方法:参与者是312名基线时患有轻度认知障碍的个体。纵向神经认知测试包括简易精神状态测试、阿尔茨海默病评估量表-认知13项、Rey听觉语言学习测试即时、学习和遗忘以及功能评估问卷。我们构建了三种类型的地标模型,并选择了最优的地标模型来动态预测2年的转换概率。数据集按7:3的比例随机分为训练集和验证集。结果:在所有三个里程碑模型中,FAQ、RAVLT-immediate和ravlt -forget是显著的mci - ad转换纵向神经认知测试。我们将模型3作为最终的里程碑模型(C-index = 0.894, Brier评分= 0.040),选择模型3c (FAQ和RAVLT-forgetting作为神经认知测试)作为最优的里程碑模型(C-index = 0.898, Brier评分= 0.027)。结论:我们的研究表明,结合FAQ和RAVLTforgetting的最优地标模型可用于识别mci - ad转换风险,可用于认知筛查。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Landmark Model-based Individual Dynamic Prediction of Conversion from Mild Cognitive Impairment to Alzheimer's Disease using Cognitive Screening.

Background: Identifying individuals with mild cognitive impairment (MCI) who are at increased risk of Alzheimer's Disease (AD) in cognitive screening is important for early diagnosis and prevention of AD.

Objective: This study aimed at proposing a screening strategy based on landmark models to provide dynamic predictive probabilities of MCI-to-AD conversion according to longitudinal neurocognitive tests.

Methods: Participants were 312 individuals who had MCI at baseline. The longitudinal neurocognitive tests were the Mini-Mental State Examination, Alzheimer Disease Assessment Scale-Cognitive 13 items, Rey Auditory Verbal Learning Test immediate, learning, and forgetting, and Functional Assessment Questionnaire. We constructed three types of landmark models and selected the optimal landmark model to dynamically predict 2-year probabilities of conversion. The dataset was randomly divided into training set and validation set at a ratio of 7:3.

Results: The FAQ, RAVLT-immediate, and RAVLT-forgetting were significant longitudinal neurocognitive tests for MCI-to-AD conversion in all three landmark models. We considered Model 3 as the final landmark model (C-index = 0.894, Brier score = 0.040) and selected Model 3c (FAQ and RAVLT-forgetting as neurocognitive tests) as the optimal landmark model (C-index = 0.898, Brier score = 0.027).

Conclusion: Our study shows that the optimal landmark model with a combination FAQ and RAVLTforgetting is feasible to identify the risk of MCI-to-AD conversion, which can be implemented in cognitive screening.

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来源期刊
Current Alzheimer research
Current Alzheimer research 医学-神经科学
CiteScore
4.00
自引率
4.80%
发文量
64
审稿时长
4-8 weeks
期刊介绍: Current Alzheimer Research publishes peer-reviewed frontier review, research, drug clinical trial studies and letter articles on all areas of Alzheimer’s disease. This multidisciplinary journal will help in understanding the neurobiology, genetics, pathogenesis, and treatment strategies of Alzheimer’s disease. The journal publishes objective reviews written by experts and leaders actively engaged in research using cellular, molecular, and animal models. The journal also covers original articles on recent research in fast emerging areas of molecular diagnostics, brain imaging, drug development and discovery, and clinical aspects of Alzheimer’s disease. Manuscripts are encouraged that relate to the synergistic mechanism of Alzheimer''s disease with other dementia and neurodegenerative disorders. Book reviews, meeting reports and letters-to-the-editor are also published. The journal is essential reading for researchers, educators and physicians with interest in age-related dementia and Alzheimer’s disease. Current Alzheimer Research provides a comprehensive ''bird''s-eye view'' of the current state of Alzheimer''s research for neuroscientists, clinicians, health science planners, granting, caregivers and families of this devastating disease.
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