The Kappa Free Light Chains Index in Multiple Sclerosis: From Emerging Evidence to Clinical Application

The kappa free light chain (KFLC) index is a promising biomarker for detecting intrathecal immunoglobulin synthesis in multiple sclerosis (MS), offering a quantitative and automated alternative to oligoclonal bands (OCBs). However, its use in clinical practice is limited by heterogeneous thresholds and a lack of standardized diagnostic algorithms. Objective to develop and validate a biological diagnostic algorithm for MS that fully integrates the KFLC-index alongside current recommended CSF biomarkers, particularly CSF-restricted OCBs. We conducted a prospective, monocentric study including 198 patients undergoing lumbar puncture for suspected neurological disease. Patients were classified as having MS (including CIS/RIS) or non-inflammatory neurological disorders. Paired cerebrospinal fluid and serum KFLC and LFLC were quantified using a turbidimetric assay (Optilite, The Binding Site). Diagnostic performance was assessed by ROC analysis. A diagnostic algorithm was developed and validated in an independent cohort. In the derivation cohort (n = 80), the KFLC-index showed excellent accuracy (AUC = 0.93). An optimal threshold of 20.27 provided 80.6% sensitivity and 100% specificity. A lower threshold of 3 increased sensitivity (96.8%) but reduced specificity (26.5%). Application of the diagnostic algorithm to the replication cohort (n = 70) confirmed the absence of false positive and false negative results for threshold values. Systematic OCBs testing enhanced interpretation in intermediate KFLC-index ranges (3-20). The algorithm's performance was consistent with previously published thresholds. The KFLC-index is a robust biomarker for MS diagnosis. Integration into a tiered algorithm offers excellent diagnostic performance, though local validation remains essential before broad clinical adoption.