A sex-dependent algorithm including kappa free light chain for multiple sclerosis diagnosis.

Area of Science:

• Neurology
• Clinical Chemistry
• Immunology

Background:

• Multiple sclerosis (MS) diagnosis traditionally relies on cerebrospinal fluid (CSF) oligoclonal bands (OCB), a method with limitations including subjectivity and dichotomous results.
• Kappa free light chains (KFLC) present a quantitative, objective alternative, but established cut-off values and potential sex-based differences require investigation.

Purpose of the Study:

• To evaluate CSF kappa free light chains (KFLC) and derived indexes as diagnostic tools for MS.
• To compare the diagnostic accuracy of KFLC with traditional OCB testing.
• To determine if sex influences KFLC cut-off values and diagnostic performance.

Main Methods:

• Paired CSF and serum samples from 193 patients were analyzed for albumin, total protein, immunoglobulins, and OCB.
• KFLC levels and KFLC-derived indexes (K-index, Q KFLC) were measured using a BN II analyzer.
• Diagnostic accuracy was assessed using Area Under the Curve (AUC), Youden's index, and odds ratio, with analysis stratified by sex.

Main Results:

• KFLC-derived indexes (K-index, Q KFLC) demonstrated good diagnostic accuracy for MS, comparable to OCB.
• Significant differences in K-index and Q KFLC cut-off values were observed between sexes.
• A sex-dependent algorithm combining K-index, Q KFLC, and OCB achieved the highest diagnostic accuracy.

Conclusions:

• CSF KFLC measurement is a rapid, quantitative, and easily standardized method for MS diagnosis.
• Implementing a sex-dependent algorithm utilizing KFLC and OCB can enhance diagnostic accuracy.
• This approach may reduce the reliance on manual OCB testing in MS diagnostics.