Replication of the 2023 radiologically isolated syndrome criteria in a multi-centre cohort

Held, Friederike ; Uibel, Paula; Berberich, Cornelius; Schaller-Nagengast, Jonas; Mitrevski, Vasil; Hutter, Leo; Tumani, Hayrettin ; Havla, Joachim ; Gasperi, Christiane ; Mühlau, Mark ; Berthele, Achim ; Kirschke, Jan S. und Hemmer, Bernhard (2025): Replication of the 2023 radiologically isolated syndrome criteria in a multi-centre cohort. In: Brain Communications, Bd. 7, Nr. 5, fcaf323

Abstract

Radiologically isolated syndrome (RIS) represents a pivotal stage for identifying individuals at high risk of transitioning into multiple sclerosis (MS). Early therapy initiation reduces the risk of conversion. The 2023-RIS criteria were proposed to identify presymptomatic individuals earlier. We aimed to replicate the diagnostic value of the 2023-RIS criteria in an independent cohort. In this retrospective cohort study, individuals diagnosed with RIS and longitudinally followed in three centres were stratified by the 2009- and 2023-RIS criteria. We conducted comparative analyses, including survival, hazard ratio and performance evaluations. Among n = 136 individuals, 27.2% converted to MS between 2009 and 2024 (observation time 55.4 months). We confirmed improved identification of individuals at risk using the 2023-RIS criteria (HR 4.30, P < 0.05; HR 4.71, P < 0.05) compared to 2009-RIS criteria (HR 1.32, P = 0.4; HR 1.43; P = 0.3) in 5- and 10-year intervals, respectively. 2023-RIS criteria demonstrated high sensitivity (94%) and negative predictive value (94%) but low specificity (29%). Adding CSF immunoglobulin G and M indices as an additional parameter following RIS diagnosis enhanced risk prediction specificity. We confirm the high sensitivity and predictive value of the 2023-RIS criteria for identifying individuals at risk of conversion to MS and suggest adding immunoglobulin indices to further improve specificity.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Medizin > Munich Cluster for Systems Neurology (SyNergy)
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• Sprache: Englisch
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 390857198