基于血液的阿尔茨海默病检测算法。
A blood-based algorithm for the detection of Alzheimer's disease.
机构信息
Department of Neurology, F. Marie Hall Institute for Rural and Community Health, Texas Tech University Health Sciences Center, Lubbock, Tex., USA. sid.obryant @ ttuhsc.edu
出版信息
Dement Geriatr Cogn Disord. 2011;32(1):55-62. doi: 10.1159/000330750. Epub 2011 Aug 24.
BACKGROUND
We previously created a serum-based algorithm that yielded excellent diagnostic accuracy in Alzheimer's disease. The current project was designed to refine that algorithm by reducing the number of serum proteins and by including clinical labs. The link between the biomarker risk score and neuropsychological performance was also examined.
METHODS
Serum-protein multiplex biomarker data from 197 patients diagnosed with Alzheimer's disease and 203 cognitively normal controls from the Texas Alzheimer's Research Consortium were analyzed. The 30 markers identified as the most important from our initial analyses and clinical labs were utilized to create the algorithm.
RESULTS
The 30-protein risk score yielded a sensitivity, specificity, and AUC of 0.88, 0.82, and 0.91, respectively. When combined with demographic data and clinical labs, the algorithm yielded a sensitivity, specificity, and AUC of 0.89, 0.85, and 0.94, respectively. In linear regression models, the biomarker risk score was most strongly related to neuropsychological tests of language and memory.
CONCLUSIONS
Our previously published diagnostic algorithm can be restricted to only 30 serum proteins and still retain excellent diagnostic accuracy. Additionally, the revised biomarker risk score is significantly related to neuropsychological test performance.
背景
我们之前创建了一个基于血清的算法，该算法在阿尔茨海默病的诊断中具有出色的准确性。本项目旨在通过减少血清蛋白的数量并纳入临床实验室来改进该算法。还检查了生物标志物风险评分与神经心理学表现之间的联系。
方法
分析了来自德克萨斯州阿尔茨海默病研究联合会的 197 名被诊断为阿尔茨海默病的患者和 203 名认知正常对照者的血清蛋白多重生物标志物数据。利用我们最初分析和临床实验室确定的 30 个最重要的标志物来创建算法。
结果
30 种蛋白风险评分的敏感性、特异性和 AUC 分别为 0.88、0.82 和 0.91。当与人口统计学数据和临床实验室相结合时，该算法的敏感性、特异性和 AUC 分别为 0.89、0.85 和 0.94。在线性回归模型中，生物标志物风险评分与语言和记忆的神经心理学测试最密切相关。
结论
我们之前发表的诊断算法可以限制在仅 30 种血清蛋白，仍然保持出色的诊断准确性。此外，修订后的生物标志物风险评分与神经心理学测试表现显著相关。
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