首页> 外文期刊>European journal of neurology: the official journal of the European Federation of Neurological Societies >The combination of apolipoprotein E4, age and Alzheimer's Disease Assessment Scale - Cognitive Subscale improves the prediction of amyloid positron emission tomography status in clinically diagnosed mild cognitive impairment
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The combination of apolipoprotein E4, age and Alzheimer's Disease Assessment Scale - Cognitive Subscale improves the prediction of amyloid positron emission tomography status in clinically diagnosed mild cognitive impairment

机译:载脂蛋白E4,年龄和阿尔茨海默病评估规模的组合 - 认知亚级改善了临床诊断的温和认知障碍中淀粉样蛋白正电子发射断层扫描状态的预测

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Background and purpose Randomized clinical trials involving anti-amyloid interventions focus on the early stages of Alzheimer's disease (AD) with proven amyloid pathology, using amyloid positron emission tomography (amyloid-PET) imaging or cerebrospinal fluid analysis. However, these investigations are either expensive or invasive and are not readily available in resource-limited centres. Hence, the identification of cost-effective clinical alternatives to amyloid-PET is highly desirable. This study aimed to investigate the accuracy of combined clinical markers in predicting amyloid-PET status in mild cognitive impairment (MCI) individuals. Methods In all, 406 MCI participants from the Alzheimer's Disease Neuroimaging Initiative database were dichotomized into amyloid-PET(+) and amyloid-PET(-) using a cut-off of >1.11. The accuracies of single clinical markers [apolipoprotein E4 (ApoE4) genotype, demographics, cognitive measures and cerebrospinal fluid analysis] in predicting amyloid-PET status were evaluated using receiver operating characteristic curve analysis. A logistic regression model was then used to determine the optimal model with combined clinical markers to predict amyloid-PET status. Results Cerebrospinal fluid amyloid-beta (A beta) showed the best predictive accuracy of amyloid-PET status [area under the curve (AUC) = 0.927]. Whilst ApoE4 genotype (AUC = 0.737) and Alzheimer's Disease Assessment Scale - Cognitive Subscale (ADAS-Cog) 13 (AUC = 0.724) independently discriminated amyloid-PET(+) and amyloid-PET(-) MCI individuals, the combination of clinical markers (ApoE4 carrier, age >60 years and ADAS-Cog 13 > 13.5) improved the predictive accuracy of amyloid-PET status (AUC = 0.827, P < 0.001). Conclusions Cerebrospinal fluid A beta, which is an invasive procedure, is most accurate in predicting amyloid-PET status in MCI individuals. The combination of ApoE4, age and ADAS-Cog 13 also accurately predicts amyloid-PET status. As this combination of clinical markers is cheap, non-invasive and readily available, it offers an attractive surrogate assessment for amyloid status amongst MCI individuals in resource-limited settings.
机译:背景和目的随机化临床试验,涉及抗淀粉样蛋白干预的临床试验,重点是阿尔茨海默病(AD)的早期阶段,使用淀粉样蛋白正电子发射断层扫描(淀粉样蛋白-PET)成像或脑脊髓液分析。然而,这些调查是昂贵的或侵入性的,资源有限的中心不容易获得。因此,非常希望鉴定对淀粉样蛋白宠物的经济有效的临床替代品。本研究旨在探讨合并临床标志物在预测轻度认知障碍(MCI)个体中淀粉样蛋白宠物地位的准确性。在Alzheimer疾病的所有方法中,来自阿尔茨海默病的406个MCI参与者使用截止值> 1.11的截止值将来自阿尔茨海默氏病神经影像序列序列序列的序列序列序列组成。使用接收器操作特性曲线分析评估在预测淀粉样蛋白-PET状态方面的单一临床标记物[载脂蛋白E4(APOE4)基因型,人口统计,认知措施和脑脊液分析]。然后使用逻辑回归模型来确定组合临床标志物的最佳模型,以预测淀粉样蛋白 - 宠物状态。结果脑脊液淀粉样蛋白-β(β)显示出淀粉样蛋白 - 宠物状态[曲线下面积(AUC)= 0.927]的最佳预测精度。虽然Apoe4基因型(AUC = 0.737)和阿尔茨海默病评估规模 - 认知亚型(ACAS-COG)13(AUC = 0.724)独立区别地区淀粉样肽(+)和淀粉样肽( - )MCI个体,临床标志物的组合(APOE4载体,年龄> 60岁及ADAS-COG 13> 13.5)改善了淀粉样蛋白 - PET状态的预测精度(AUC = 0.827,P <0.001)。结论脑脊液Aβ,即侵入性手术,最准确地预测MCI个体中的淀粉样蛋白宠物状态。 APOE4,年龄和ADAS-COG 13的组合也准确地预测淀粉样蛋白宠物状态。由于这种临床标记的组合是廉价的,无侵入性和容易获得的,因此在资源有限的环境中为MCI个体中的淀粉样器状况提供有吸引力的替代评估。

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