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Updated: Jan 6, 2026

Quantitative Measurement of Intrathecally Synthesized Proteins in Mice
Published on: November 29, 2019
Optimized Kappa-Index Test Protocol to Detect Intrathecal Immunoglobulin Synthesis in Multiple Sclerosis
Joel Björklund1, Outi Itkonen1, Pasi Nokelainen1
1Department of Clinical Chemistry, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
Background:
Kappa free light chain (KFLC)-based Kappa-index (K-index) can substitute oligoclonal banding (OCB) to detect intrathecal immunoglobulin synthesis. Cutoffs for positive results vary; therefore, further comparison of different approaches is necessary to optimize K-index for diagnostic utilization.
Methods:
We analyzed 432 paired CSF/serum samples and selected 77 OCB-positive patients with multiple sclerosis (MS), clinically isolated syndrome (CIS) that did not progress to MS in > 10 years, and other neuroinflammatory diseases (non-MS). K-index subtests were measured on the Optilite platform (The Binding Site) and OCB with isoelectric focusing on the Hydrasys platform (Sebia).
Results:
OCB positive cases had a higher K-index than OCB negative. The MS group had a higher K-index than CIS (p = 0.0066) and non-MS (p < 0.0001). A K-index over 80.9 suggests MS over CIS, and 61.4 suggests MS over non-MS. Different values to mimic undetectable CSF KFLC levels resulted in different cutoffs against positive OCB. Using the limit of detection (LOD) of the assay and fixing sensitivity and specificity to 95% to establish the gray area, the cutoffs were < 4.45 (negative) and > 12.92 (positive). When undetectable CSF KFLC was also considered negative, specificity against OCB was 99.7% and sensitivity 92.7%, leaving 6% for gray area OCB verification testing.
Conclusions:
Published K-index cutoffs vary due to different settings of CSF KFLC results below LOD. Using a reflex approach, where samples within a certain K-index gray area are subjected to OCB verification testing, and where samples with CSF KFLC below LOD are considered negative, was the most efficient laboratory algorithm. K-index may also have prognostic value in MS.
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