Related Experiment Video
Updated: Jan 18, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Replication of the 2023 radiologically isolated syndrome criteria in a multi-centre cohort
Friederike Held1, Paula Uibel1, Cornelius Berberich2
1Technical University of Munich, School of Medicine and Health, Department of Neurology, TUM University Hospital, 81675 Munich, Germany.
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.
More Related Videos
Related Concept Videos
Rheumatic Heart Disease II: Clinical Manifestations and Diagnostic Studies
Acute Coronary Syndrome III: Diagnostic Studies
Bias in Epidemiological Studies

