在正确的时间进行正确的治疗：建立认知能力衰退轨迹模型，确定阿尔茨海默病患者最早发生变化的年龄。

IF 4 Q1 CLINICAL NEUROLOGY Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring Pub Date : 2024-03-07 eCollection Date: 2024-01-01 DOI:10.1002/dad2.12563

R Asaad Baksh, André Strydom, Ben Carter, Isabelle Carriere, Karen Ritchie

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引用次数: 0

摘要

简介年龄是阿尔茨海默病（AD）的最大风险因素。阿兹海默病随机对照试验的一个局限性是，参加疾病改变疗法研究的参与者的年龄范围缺乏特异性。我们旨在应用Emax（即最大效应）建模作为确定理想治疗窗口的新方法：我们对101名AD患者和1392名健康对照者的纵向认知数据进行了Emax曲线拟合。方法：我们对101名AD患者和1392名健康对照者的纵向认知数据进行了Emax曲线拟合，其中包括迷你精神状态检查（MMSE）以及语言流畅性和执行功能测试：结果表明：在注意力缺失症患者中，67-71 岁年龄段的 MMSE 下降最早，而语言流畅性则从 41-45 岁年龄段开始下降。在健康对照组中，认知能力的下降轨迹较晚：讨论：Emax模型可用于设计更有效的试验，这对针对AD早期阶段的随机对照试验具有重要意义。

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Toward the right treatment at the right time: Modeling the trajectory of cognitive decline to identify the earliest age of change in people with Alzheimer's disease.

Introduction: Age is the greatest risk factor for Alzheimer's disease (AD). A limitation of randomized control trials in AD is a lack of specificity in the age ranges of participants who are enrolled in studies of disease-modifying therapies. We aimed to apply Emax (i.e., maximum effect) modeling as a novel approach to identity ideal treatment windows.

Methods: Emax curves were fitted to longitudinal cognitive data of 101 participants with AD and 1392 healthy controls. We included the Mini-Mental State Examination (MMSE) and tests of verbal fluency and executive functioning.

Results: In people with AD, the earliest decline in the MMSE could be detected in the 67-71 age band while verbal fluency declined from the 41-45 age band. In healthy controls, changes in cognition showed a later trajectory of decline.

Discussion: Emax modeling could be used to design more efficient trials which has implications for randomized control trials targeting the earlier stages of AD.

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来源期刊

Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring Medicine-Psychiatry and Mental Health

CiteScore

7.80

自引率

7.50%

发文量

101

审稿时长

8 weeks

期刊介绍： Alzheimer''s & Dementia: Diagnosis, Assessment & Disease Monitoring (DADM) is an open access, peer-reviewed, journal from the Alzheimer''s Association® that will publish new research that reports the discovery, development and validation of instruments, technologies, algorithms, and innovative processes. Papers will cover a range of topics interested in the early and accurate detection of individuals with memory complaints and/or among asymptomatic individuals at elevated risk for various forms of memory disorders. The expectation for published papers will be to translate fundamental knowledge about the neurobiology of the disease into practical reports that describe both the conceptual and methodological aspects of the submitted scientific inquiry. Published topics will explore the development of biomarkers, surrogate markers, and conceptual/methodological challenges. Publication priority will be given to papers that 1) describe putative surrogate markers that accurately track disease progression, 2) biomarkers that fulfill international regulatory requirements, 3) reports from large, well-characterized population-based cohorts that comprise the heterogeneity and diversity of asymptomatic individuals and 4) algorithmic development that considers multi-marker arrays (e.g., integrated-omics, genetics, biofluids, imaging, etc.) and advanced computational analytics and technologies.