Claudia Balducci (Italy)

San Gerardo Hospital Neurology Department

Author Of 1 Presentation

Free Communication

IMMUNOGLOBULIN FREE LIGHT CHAINS AS A DIAGNOSTIC AND PROGNOSTIC BIOMARKER IN MULTIPLE SCLEROSIS: A REAL LIFE STUDY.

Session Type
Free Communication
Date
05.10.2021, Tuesday
Session Time
11:30 - 13:00
Room
Free Communication C
Lecture Time
12:10 - 12:20
Presenter
  • Claudia Cutelle' (Italy)

Abstract

Background and Aims:

Cerebrospinal fluid (CSF) immunoglobulin free light chains (FLCs) have been proposed as a quantitative and automatable alternative to oligoclonal bands (OCBs) with a potential role as predictor of Multiple Sclerosis (MS) severity. The aim of the study is to evaluate the utility of FLC determination in the initial assessment of patients with suspected MS as a diagnostic and prognostic biomarker.

Methods:

We included 59 consecutive patients diagnosed as Clinical Isolated Syndrome (CIS) or MS and 31 consecutive patients with not-inflammatory disease who underwent to CSF and blood sampling. We performed OCBs and FLCs on matched CSF/serum samples and calculated κ-index (κFLCs-ratio/albumin-ratio). We collected radiological and clinical data at baseline and clinical data over time (median follow-up: 7 years) for CIS and MS patients.

Results:

Κ-index showed higher sensitivity and specificity for MS diagnosis versus to the gold standard, OCBs (AUC 0,99 versus AUC 0,92) and distinguished patients with higher lesion load on baseline brain and spinal cord MRI (p <0,05). Κ-index directly correlated with Multiple Sclerosis Severity Score (MSSS) at the end of follow-up (rho=0,33; p=0,041) in our population with a low medium disability (median MSSS 1,41 range 0,21-8,53). Patients with κ-index >70° percentile showed a four times greater risk of relapse over time (HR=0,24; p=0,003) and a three times greater risk of disease modifying treatment (DMT) introduction (HR=0,39; p=0,023).graph1.jpg

Conclusions:

Our study suggests that κ-index determined during diagnostic work-up of MS could predict disease severity over time, leading to more individualized and early treatment.

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