Prognostic value of cerebrospinal fluid biomarkers in multiple sclerosis: The key role of kappa free light chains and a multivariate predictor for disease progression

Abstract

ObjectiveMultiple sclerosis (MS) is a chronic, inflammatory, demyelinating disease of the central nervous system with varying progression rates among individuals. The ability to predict disease progression is crucial for treatment decisions with disease-modifying therapies (DMTs). A few cerebrospinal fluid (CSF) biomarkers have been investigated in relation to disease progression, but few have been effectively translated into clinical practice. The aim of this study was to evaluate the diagnostic and prognostic value of known CSF markers, to compare their sensitivity and specificity, and to develop a prognostic model using a combination of markers to predict disease progression. MethodsThis retrospective cohort study included 82 patients with a first episode of inflammatory demyelinating symptoms suggestive of MS between January 2018 and January 2021. Patients underwent diagnostic lumbar puncture and other investigations according to the multiple sclerosis (MS) protocol. They were divided into three groups according to MRI findings, relapse rate and EDSS score. CSF marker concentrations were determined by laser nephelometry and electrochemiluminescence immunoassay. ResultsThe results showed that the number of oligoclonal bands could discriminate the progression-free group from the other groups, but had a lower discriminatory power compared to CSF marker concentrations. Among CSF markers, FLC kappa showed the best discriminatory performance. By combining FLC kappa with gender and lesion localization information, a simple predictor of progression-free group membership was proposed. This predictor showed good sensitivity (91 %) and specificity (65 %). ConclusionIn conclusion, CSF FLC kappa concentration, together with gender and lesion localization, may be a valuable predictor of disease progression in MS patients. This study highlights the potential of using CSF biomarkers for prognostic purposes and offers a simple approach to predicting disease progression.