Extension and refinement of the predictive value of different classes of markers in ADNI: four-year follow-up data.
Extension and refinement of the predictive value of different classes of markers in ADNI: four-year follow-up data.
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DOI：
10.1016/j.jalz.2013.11.009
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发表时间：
2014-11
期刊：
影响因子：
--
通讯作者：
Alzheimer's Disease Neuroimaging Initiative
中科院分区：
文献类型：
--
作者：
Gomar JJ;Conejero-Goldberg C;Davies P;Goldberg TE;Alzheimer's Disease Neuroimaging Initiative
本研究在 ADNI 长达 4 年的随访中检验了不同类别标记物对从轻度认知障碍 (MCI) 发展为阿尔茨海默病 (AD) 的预测价值。 MCI 患者在基线时对临床、认知、MRI、PET-FDG 和 CSF 标志物进行评估，并在四年内每年进行随访，以确定 AD 的进展情况。对包括人口统计、APOE 基因型、认知标记和生物标记（形态测量、PET-FDG、CSF Abeta 和 tau）在内的聚类进行 Logistic 回归模型拟合。四岁时的预测模型显示，两种认知测量（情景记忆测量和钟图筛选测试）是转化的最佳预测因子（AUC = 0.78）。该预测模型与之前两年的模型一致，从而强调了认知测量在从 MCI 到 AD 进展过程中的重要性。认知标记是比生物标记更强大的预测因子。
This study examined the predictive value of different classes of markers in the progression from Mild Cognitive Impairment (MCI) to Alzheimer’s disease (AD) over an extended 4 year follow-up in ADNI. MCI patients assessed on clinical, cognitive, MRI, PET-FDG, and CSF markers at baseline, and followed on a yearly basis for four years to ascertain progression to AD. Logistic regression models were fitted in clusters including demographics, APOE genotype, cognitive markers, and biomarkers (morphometric, PET-FDG, CSF Abeta and tau). The predictive model at four years revealed that two cognitive measures, an episodic memory measure and a clock drawing screening test, were the best predictors of conversion (AUC= 0.78). This model of prediction is consistent to the previous model at two years, thus highlighting the importance of cognitive measures in progression from MCI to AD. Cognitive markers were more robust predictors than biomarkers.
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影响因子：
4.2
作者：
Ewers M;Walsh C;Trojanowski JQ;Shaw LM;Petersen RC;Jack CR Jr;Feldman HH;Bokde AL;Alexander GE;Scheltens P;Vellas B;Dubois B;Weiner M;Hampel H;North American Alzheimer's Disease Neuroimaging Initiative (ADNI)
通讯作者：
North American Alzheimer's Disease Neuroimaging Initiative (ADNI)
影响因子：
--
作者：
Gomar, Jesus J.;Bobes-Bascaran, Maria T.;Goldberg, Terry E.
通讯作者：
Goldberg, Terry E.
影响因子：
11.2
作者：
Desikan, Rahul S.;McEvoy, Linda K.;Thompson, Wesley K.;Holland, Dominic;Roddey, J. Cooper;Blennow, Kaj;Aisen, Paul S.;Brewer, James B.;Hyman, Bradley T.;Dale, Anders M.
通讯作者：
Dale, Anders M.
影响因子：
48
作者：
Petersen, Ronald C.
通讯作者：
Petersen, Ronald C.
影响因子：
168.9
作者：
Ferri, CP;Prince, M;Scazufca, M
通讯作者：
Scazufca, M