基于 Cogstate One 卡片学习准确性表现，比较在临床前阿尔茨海默病中定义客观轻度认知衰退的横断面和纵向方法。
A Comparison of Cross-Sectional and Longitudinal Methods of Defining Objective Subtle Cognitive Decline in Preclinical Alzheimer's Disease Based on Cogstate One Card Learning Accuracy Performance.
机构信息
Division of Neurocognitive Disorders, Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA.
Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
出版信息
J Alzheimers Dis. 2021;83(2):861-877. doi: 10.3233/JAD-210251.
BACKGROUND
Longitudinal, but not cross-sectional, cognitive testing is one option proposed to define transitional cognitive decline for individuals on the Alzheimer's disease continuum.
OBJECTIVE
Compare diagnostic accuracy of cross-sectional subtle objective cognitive impairment (sOBJ) and longitudinal objective decline (ΔOBJ) over 30 months for identifying 1) cognitively unimpaired participants with preclinical Alzheimer's disease defined by elevated brain amyloid and tau (A+T+) and 2) incident mild cognitive impairment (MCI) based on Cogstate One Card Learning (OCL) accuracy performance.
METHODS
Mayo Clinic Study of Aging cognitively unimpaired participants aged 50 + with amyloid and tau PET scans (n = 311) comprised the biomarker-defined sample. A case-control sample of participants aged 65 + remaining cognitively unimpaired for at least 30 months included 64 who subsequently developed MCI (incident MCI cases) and 184 controls, risk-set matched by age, sex, education, and visit number. sOBJ was assessed by OCL z-scores. ΔOBJ was assessed using within subjects' standard deviation and annualized change from linear regression or linear mixed effects (LME) models. Concordance measures Area Under the ROC Curve (AUC) or C-statistic and odds ratios (OR) from conditional logistic regression models were derived. sOBJ and ΔOBJ were modeled jointly to compare methods.
RESULTS
sOBJ and ΔOBJ-LME methods differentiated A+T+ from A-T- (AUC = 0.64, 0.69) and controls from incident MCI (C-statistic = 0.59, 0.69) better than chance; other ΔOBJ methods did not. ΔOBJ-LME improved prediction of future MCI over baseline sOBJ (p = 0.003) but not over 30-month sOBJ (p = 0.09).
CONCLUSION
Longitudinal decline did not offer substantial benefit over cross-sectional assessment in detecting preclinical Alzheimer's disease or incident MCI.
背景
纵向而非横断面认知测试是用于定义阿尔茨海默病连续体中个体过渡性认知下降的一种方法。
目的
比较横断面隐匿性客观认知障碍（sOBJ）和 30 个月纵向客观下降（ΔOBJ）的诊断准确性，以识别 1）认知未受损但脑淀粉样蛋白和 tau 升高（A+T+）的临床前阿尔茨海默病患者，以及 2）根据 Cogstate One Card Learning（OCL）准确性表现确定的新发轻度认知障碍（MCI）患者。
方法
梅奥诊所衰老研究中认知未受损的参与者年龄在 50 岁以上，进行了淀粉样蛋白和 tau PET 扫描（n=311），构成了生物标志物定义的样本。年龄在 65 岁以上且至少 30 个月认知未受损的参与者包括 64 名随后发展为 MCI（新发 MCI 病例）和 184 名对照者，按年龄、性别、教育程度和就诊次数进行风险集匹配。sOBJ 通过 OCL z 分数进行评估。ΔOBJ 通过使用受试者内标准偏差和线性回归或线性混合效应（LME）模型的年度变化进行评估。从条件逻辑回归模型得出一致性指标曲线下面积（AUC）或 C 统计量和优势比（OR）。联合评估 sOBJ 和 ΔOBJ 以比较方法。
结果
sOBJ 和 ΔOBJ-LME 方法能够区分 A+T+和 A-T-（AUC=0.64，0.69）以及对照组和新发 MCI（C 统计量=0.59，0.69），优于偶然情况；其他 ΔOBJ 方法则不然。与基线 sOBJ 相比，ΔOBJ-LME 改善了对未来 MCI 的预测（p=0.003），但与 30 个月 sOBJ 相比无显著差异（p=0.09）。
结论
与横断面评估相比，纵向下降在检测临床前阿尔茨海默病或新发 MCI 方面没有明显优势。
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