Kappa Free Light Chain Index as a Diagnostic Biomarker in Multiple Sclerosis: Validation in an Argentinian Cohort and Cut off Proposal

Background: Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system (CNS). Cerebrospinal fluid (CSF) analysis, including oligoclonal bands (OCB) and the IgG index, is central to MS diagnosis but presents technical and interpretative limitations. The kappa free light chain (κFLC) index has emerged as a promising biomarker of intrathecal immunoglobulin synthesis. Objective: To evaluate the diagnostic performance of the κFLC index in MS, determine an optimal cutoff value, and compare its accuracy with OCB detection and the IgG index. Methods: We conducted a retrospective study including 176 patients evaluated at the Neuroimmunology Laboratory of Buenos Aires, Argentina. Patients were classified into four groups: MS (n = 106), neuromyelitis optica spectrum disorders (NMOSD, n = 15), other inflammatory CNS disorders of autoimmune or infectious origin (ICNSDAI, n = 41), and paraneoplastic neurological syndromes (PNS, n = 14). κFLC, IgG, and albumin concentrations were measured in paired CSF and serum samples. The κFLC index was calculated and compared with OCB and IgG index results. Diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis. Results: The κFLC index was significantly higher in MS patients (median: 85; IQR: 30–305) compared with NMOSD (3.37), ICNSDAI (1.62), and PNS (1.96) groups (p < 0.0001). A κFLC index cutoff of 15 demonstrated 92% sensitivity and 83% specificity, with an area under the ROC curve of 0.952. The κFLC index correlated with the IgG index (ρ = 0.587, p < 0.0001) and OCB positivity (ρ = 0.586, p < 0.0001). κFLC index values ≥100 were observed almost exclusively in MS, with one exception in a patient with acute HSV-1 encephalitis. Conclusion: The κFLC index is a sensitive and reliable biomarker for intrathecal immunoglobulin synthesis in MS, offering advantages of automation, rapid processing, and objective quantification. External validation in independent cohorts is required before routine clinical implementation.