Kandel Benjamin M, Avants Brian B, Gee James C, Arnold Steven E, Wolk David A
Penn Image Computing and Science Laboratory and Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
Penn Image Computing and Science Laboratory and Department of Radiology, Perelman School of Medicine of the University of Pennsylvania, Philadelphia, PA, USA.
J Alzheimers Dis. 2015;46(4):901-12. doi: 10.3233/JAD-142943.
Psychometric tests predict conversion of mild cognitive impairment (MCI) to probable Alzheimer's disease (AD). Because the definition of clinical AD relies on those same psychometric tests, the ability of these tests to identify underlying AD pathology remains unclear.
To determine the degree to which psychometric testing predicts molecular evidence of AD amyloid pathology, as indicated by cerebrospinal fluid (CSF) amyloid-β (Aβ)1 - 42, in patients with MCI, as compared to neuroimaging biomarkers.
We identified 408 MCI subjects with CSF Aβ levels, psychometric test data, FDG-PET scans, and acceptable volumetric MR scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We used psychometric tests and imaging biomarkers in univariate and multivariate models to predict Aβ status.
The 30-min delayed recall score of the Rey Auditory Verbal Learning Test was the best predictor of Aβ status among the psychometric tests, achieving an AUC of 0.67 ± 0.02 and odds ratio of 2.5 ± 0.4. FDG-PET was the best imaging-based biomarker (AUC 0.67 ± 0.03, OR 3.2 ± 1.2), followed by hippocampal volume (AUC 0.64 ± 0.02, OR 2.4 ± 0.3). A multivariate analysis based on the psychometric tests improved on the univariate predictors, achieving an AUC of 0.68 ± 0.03 (OR 3.38 ± 1.2). Adding imaging biomarkers to the multivariate analysis did not improve the AUC.
Psychometric tests perform as well as imaging biomarkers to predict presence of molecular markers of AD pathology in MCI patients and should be considered in the determination of the likelihood that MCI is due to AD.
心理测量测试可预测轻度认知障碍（MCI）向可能的阿尔茨海默病（AD）的转化。由于临床AD的定义依赖于这些相同的心理测量测试，这些测试识别潜在AD病理的能力仍不清楚。
与神经影像学生物标志物相比，确定心理测量测试在预测MCI患者脑脊液（CSF）淀粉样蛋白-β（Aβ）1 - 42所示的AD淀粉样病理分子证据方面的程度。
我们从阿尔茨海默病神经影像学倡议（ADNI）中确定了408名具有CSF Aβ水平、心理测量测试数据、氟代脱氧葡萄糖正电子发射断层扫描（FDG-PET）和可接受的容积磁共振成像（MR）扫描的MCI受试者。我们在单变量和多变量模型中使用心理测量测试和成像生物标志物来预测Aβ状态。
在心理测量测试中，雷伊听觉词语学习测试的30分钟延迟回忆分数是Aβ状态的最佳预测指标，曲线下面积（AUC）为0.67±0.02，比值比为2.5±0.4。FDG-PET是最佳的基于成像的生物标志物（AUC 0.67±0.03，OR 3.2±1.2），其次是海马体积（AUC 0.64±0.02，OR 2.4±0.3）。基于心理测量测试的多变量分析在单变量预测指标的基础上有所改善，AUC为0.68±0.03（OR 3.38±1.2）。将成像生物标志物添加到多变量分析中并未提高AUC。
心理测量测试在预测MCI患者AD病理分子标志物的存在方面与成像生物标志物表现相当，在确定MCI由AD引起的可能性时应予以考虑。
