Vecchio Domizia, Puricelli C, Virgilio E, Passarelli F, Guida S, Naldi P, Crespi I, Dianzani U, Comi C
Neurology Unit, Department of Translational Medicine, Maggiore Della Carità University Hospital, University of Piemonte Orientale, Corso Mazzini 18, 28100, Novara, Italy.
Clinical Biochemistry Laboratory, Department of Health Sciences, Maggiore Della Carità University Hospital, University of Piemonte Orientale, Novara, Italy.
J Neurol. 2024 Dec 12;272(1):30. doi: 10.1007/s00415-024-12826-y.
Cerebrospinal fluid (CSF) kappa-free light chains (KFLC) are becoming a diagnostic biomarker for multiple sclerosis (MS).
We aimed to compare the diagnostic performance of intrathecal synthesis biomarkers to that of oligoclonal bands (OB) in diagnosing MS, radiological and clinical isolated syndromes (RIS-CIS) on a large cohort of patients collected over 10 years.
We collected 1124 patients (58% females) in 10 years who underwent CSF analysis for intrathecal synthesis in the diagnostic work-up, and they were classified according to their diagnosis as 417 MS, 287 with other neurological inflammatory disorders (including 76 RIS-CIS), and 420 non-inflammatory diseases (excluding lymphoproliferative and infective diagnosis).
MS patients significantly differ from all other groups (including if considering the RIS-CIS cohort) for CSF KFLC, KFLC intrathecal fraction (IF), Kappa index, and OB. Evaluating the diagnostic performance, the Kappa index cut-off was 6.4 for diagnosing MS and 5.7 for predicting OB. A diagnostic algorithm could avoid IEF if the Kappa index is higher than 20.
The KFLC index confirmed its accuracy for MS diagnosis in this large Italian cohort, adding information also in the RIS-CIS population.
脑脊液(CSF)κ自由轻链(KFLC)正成为多发性硬化症(MS)的一种诊断生物标志物。
我们旨在比较鞘内合成生物标志物与寡克隆带(OB)在诊断MS、放射性和临床孤立综合征(RIS-CIS)方面的诊断性能,研究对象为10年间收集的大量患者。
我们在10年间收集了1124例患者(58%为女性),这些患者在诊断检查中接受了脑脊液分析以检测鞘内合成情况,并根据诊断结果分为417例MS患者、287例患有其他神经炎性疾病(包括76例RIS-CIS)以及420例非炎性疾病(不包括淋巴增殖性和感染性诊断)。
MS患者在脑脊液KFLC、KFLC鞘内分数(IF)、κ指数和OB方面与所有其他组(包括考虑RIS-CIS队列时)存在显著差异。评估诊断性能时,诊断MS的κ指数临界值为6.4,预测OB的临界值为5.7。如果κ指数高于20,诊断算法可避免进行等电聚焦(IEF)。
在这个大型意大利队列中,KFLC指数证实了其在MS诊断中的准确性,在RIS-CIS人群中也增加了相关信息。