Department of Neurology, Pavol Jozef Šafárik University in Košice, Košice, Slovak Republic/Department of Neurology, L. Pasteur University Hospital, Košice, Slovak Republic.
Department of Social and Behavioural Medicine, Pavol Jozef Šafárik University in Košice, Košice, Slovak Republic.
Mult Scler. 2021 Nov;27(13):2023-2030. doi: 10.1177/1352458521998039. Epub 2021 Feb 26.
The research is focused on sensitive biomarkers in multiple sclerosis (MS).
The aim of the study was to assess the relationship between plasma neurofilament light chain (pNfL) and disease activity as defined by the concept NEDA (no evident disease activity), including brain volumetry, in a cohort of MS patients treated with disease-modifying treatment (DMT).
Levels of pNfL (Single Molecule Array (SIMOA) technology) were examined in 95 RRMS (relapsing-remitting multiple sclerosis) patients and analyzed in relationship to NEDA-3 status and NEDA-BVL (brain volume loss; NEDA-3 extended by brain volumetry) during the last 12 months. The statistical model was developed using logistic regression analysis, including the independent variables: demographic, clinical, and magnetic resonance imaging (MRI) data. Dependent variables were NEDA-3 and NEDA-BVL status.
The mean age of the study participants ( = 95, 62% females) was 37.85 years (standard deviation (SD) = 9.62) and the median disability score was 3.5 (2.5-4.1). Receiver operating characteristics (ROC) analysis showed that pNfL predicts NEDA-3 (the sensitivity and specificity of the model were 92% and 78%, respectively, < 0.001) and NEDA-BVL status (the sensitivity and specificity were 80% and 65%, respectively, < 0.001).
The results show that pNfL levels are a useful biomarker of disease activity determined by NEDA-BVL status, including brain MRI-volumetry in patients with RRMS.
本研究专注于多发性硬化症(MS)中的敏感生物标志物。
本研究旨在评估接受疾病修正治疗(DMT)的 MS 患者队列中,血浆神经丝轻链(pNfL)与无明显疾病活动(NEDA)概念定义的疾病活动之间的关系,包括脑容积。
检查了 95 例 RRMS(复发缓解型多发性硬化症)患者的 pNfL 水平(单分子阵列(SIMOA)技术),并分析了其与过去 12 个月中 NEDA-3 状态和 NEDA-BVL(脑容积损失;NEDA-3 通过脑容积扩展)的关系。使用逻辑回归分析建立了统计模型,其中包括独立变量:人口统计学、临床和磁共振成像(MRI)数据。依赖变量为 NEDA-3 和 NEDA-BVL 状态。
研究参与者的平均年龄( = 95,62%为女性)为 37.85 岁(标准差(SD)= 9.62),中位数残疾评分 3.5(2.5-4.1)。受试者工作特征(ROC)分析表明,pNfL 可预测 NEDA-3(模型的敏感性和特异性分别为 92%和 78%, < 0.001)和 NEDA-BVL 状态(敏感性和特异性分别为 80%和 65%, < 0.001)。
结果表明,pNfL 水平是 RRMS 患者通过 NEDA-BVL 状态(包括脑 MRI 容积)确定的疾病活动的有用生物标志物。