Scoring treatment response in patients with relapsing multiple sclerosis

Author:

Sormani MP1,Rio J2,Tintorè M2,Signori A1,Li D3,Cornelisse P4,Stubinski B4,Stromillo ML5,Montalban X2,De Stefano N5

Affiliation:

1. Department of Health Sciences, University of Genoa, Italy

2. Unitat de Neuroimmunologia Clinica, Hospital Universitario Vall d’Hebron, Barcelona, Spain

3. University of British Columbia, Vancouver, Canada

4. Merck Serono, Geneva, Switzerland

5. Department of Neurological and Behavioural Sciences, University of Siena, Italy

Abstract

Background: We employed clinical and magnetic resonance imaging (MRI) measures in combination, to assess patient responses to interferon in multiple sclerosis. Objective: To optimize and validate a scoring system able to discriminate responses to interferon treatment in patients with relapsing–remitting multiple sclerosis (RRMS). Methods: Our analysis included two large, independent datasets of RRMS patients who were treated with interferons that included 4-year follow-up data. The first dataset (“training set”) comprised of 373 RRMS patients from a randomized clinical trial of subcutaneous interferon beta-1a. The second (“validation set”) included an observational cohort of 222 RRMS patients treated with different interferons. The new scoring system, a modified version of that previously proposed by Rio et al., was first tested on the training set, then validated using the validation set. The association between disability progression and risk group, as defined by the score, was evaluated by Kaplan Meier survival curves and Cox regression, and quantified by hazard ratios (HRs). Results: The score (0–3) was based on the number of new T2 lesions (>5) and clinical relapses (0,1 or 2) during the first year of therapy. The risk of disability progression increased with higher scores. In the validation set, patients with score of 0 showed a 3-year progression probability of 24%, while those with a score of 1 increased to 33% (HR = 1.56; p = 0.13), and those with score greater than or equal to 2 increased to 65% (HR = 4.60; p < 0.001). Conclusions: We report development of a simple, quantitative and complementary tool for predicting responses in interferon-treated patients that could help clinicians make treatment decisions.

Publisher

SAGE Publications

Subject

Clinical Neurology,Neurology

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