Observational analysis evaluated KFLC-index performance for diagnosing multiple sclerosis, indicating its effectiveness against MOGAD and NMOSD diseases.
Background The kappa free light chain (KFLC)-index has emerged as a diagnostic biomarker for multiple sclerosis (MS). This study aims to evaluate the diagnostic accuracy of the KFLC-index in Chinese patients with MS, and its capacity to discriminate MS from myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) and neuromyelitis optica spectrum disorders (NMOSD). Methods From December 2022 to October 2024, 414 patients were tested for KFLC-index, including 133 patients with MS, 43 with MOGAD, 25 with NMOSD, 108 with other inflammatory neurological disorders (OIND), and 105 with non-inflammatory neurological disorders (NIND). Their oligoclonal bands (OCB) results and clinical data were reviewed. Results KFLC-index was significantly higher in MS [19.6 (0.9-388.9)] compared to MOGAD [4.7 (0.7-56.1), p < 0.001], NMOSD [4.5 (1.5-46.4), p = 0.010], OIND [2.7 (0.6-27.5), p < 0.001], and NIND [1.8 (0.6-110.7), p < 0.001]. The optimal cut-off value for KFLC-index to identify MS from the nonselective controls was 8.3, with an accuracy comparable to that of OCB (AUC 0.85 vs 0.82, p = 0.174). The optimal cut-off values for differentiating MS from MOGAD and NMOSD was 16.8 and 12.1, with performance similar to OCB (p = 0.735, p = 0.061). Combination of KFLC-index and OCB outperformed OCB alone in differentiating MS from nonselective controls and MOGAD (p < 0.001 and p = 0.035). Female (p = 0.012) and higher cerebrospinal fluid leucocyte count (p < 0.001) were associated with higher KFLC-index in MS. Conclusion KFLC-index is a valuable diagnostic tool for differentiating MS from other antibody-mediated demyelinating diseases.
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Jiang et al. (2025) studied this question.
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