Predicting conversion to multiple sclerosis in patients with radiologically isolated syndrome: a retrospective study

Aims: To retrospectively analyse the Bernese radiologically isolated syndrome (RIS) cohort with the goal of developing a prediction score for conversion to multiple sclerosis (MS). Methods: A total of 31 patients with RIS were identified by screening medical records of neurological patients seen at the University Hospital of Bern between 2004 and 2017 for the diagnoses 'radiologically isolated syndrome' and 'RIS' adhering to 2009 Okuda recommendations. We analysed clinical, paraclinical and magnetic resonance imaging data during a maximum follow-up period of 3 years and identified significant predictors of conversion to MS. Results: Data were available for 31 patients meeting 2009 Okuda RIS criteria. During the 3 years of follow up, 5/31 RIS patients converted to relapsing-remitting (RR) MS. In our univariate analysis, gadolinium (Gd) enhancement, brainstem and cerebellar hemisphere lesions, immune cell count and albumin concentration in cerebrospinal fluid (CSF), and anti-nuclear antibody (ANA) positivity in serum were identified as significant predictors of conversion to MS. Integrating these factors into our 'RIS-MS prediction score' enabled us to calculate a cut-off for prediction of conversion to MS within 3 years with high specificity [1.0, 95% confidence interval (CI) 0.84-1.00) and acceptable sensitivity (0.6, 95% CI 0.17-0.93)]. Conclusion: Our RIS-MS prediction score, if validated in an independent cohort, integrating radiological (Gd enhancement, brainstem and cerebellar hemisphere lesions) and paraclinical factors (ANA in serum, cell count and albumin in CSF) could be a useful prognostic tool for early recognition of RIS patients with a high risk of clinical progression to MS.

Automated summary

This retrospective study analysed the Bernese radiologically isolated syndrome (RIS) cohort to develop a prediction score for multiple sclerosis (MS) conversion. Results show that gadolinium enhancement, brainstem and cerebellar hemisphere lesions, immune cell count and albumin concentration in CSF, and ANA positivity in serum were significant predictors of MS conversion. The RIS-MS prediction score could be a useful tool for early recognition of RIS patients at high risk of progressing to MS.