O'Bryant Sid E, Petersen Melissa, Zhang Fan, Johnson Leigh, German Dwight, Hall James
Department of Neuroscience and Pharmacology, University of North Texas Health Science Center, Fort Worth, Texas, USA.
Department of Medicine, University of North Texas Health Science Center, Fort Worth, Texas, USA.
J Alzheimers Dis Parkinsonism. 2022;12(4). Epub 2022 Jul 22.
A blood-test that could serve as a potential first step in a multi-tiered neurodiagnostic process for ruling out Parkinson's disease (PD) in primary care settings would be of tremendous value. This study therefore sought to conduct a large-scale cross-validation of our Parkinson's disease Blood Test (PDBT) for use in primary care settings.
Serum samples were analyzed from 846 PD and 2291 volunteer controls. Proteomic assays were run on a multiplex biomarker assay platform using Electrochemiluminescence (ECL). Diagnostic accuracy statistics were generated using area under the receiver operating characteristic curve (AUC), Sensitivity (SN), Specificity (SP) and Negative Predictive Value (NPV).
In the training set, the PDBT reached an AUC of 0.98 when distinguishing PD cases from controls with a SN of 0.84 and SP of 0.98. When applied to the test set, the PDBT yielded an AUC of 0.96, SN of 0.79 and SP of 0.97. The PDBT obtained a negative predictive value of 99% for a 2% base rate.
The PDBT was highly successful in discriminating PD patients from control cases and has great potential for providing primary care providers with a rapid, scalable and cost-effective tool for screening out PD.
一种血液检测方法若能作为初级医疗环境中多层级神经诊断流程的潜在第一步，用于排除帕金森病（PD），将具有巨大价值。因此，本研究旨在对我们的帕金森病血液检测（PDBT）在初级医疗环境中的应用进行大规模交叉验证。
分析了846例帕金森病患者和2291例志愿者对照的血清样本。使用电化学发光（ECL）在多重生物标志物检测平台上进行蛋白质组学检测。使用受试者操作特征曲线下面积（AUC）、灵敏度（SN）、特异性（SP）和阴性预测值（NPV）生成诊断准确性统计数据。
在训练集中，PDBT区分帕金森病病例与对照时，AUC达到0.98，灵敏度为0.84，特异性为0.98。应用于测试集时，PDBT的AUC为0.96，灵敏度为0.79，特异性为0.97。对于2%的基础发病率，PDBT的阴性预测值为99%。
PDBT在区分帕金森病患者与对照病例方面非常成功，具有为初级医疗提供者提供一种快速、可扩展且经济高效的工具以筛查出帕金森病的巨大潜力。
