SMILE: a predictive model for Scoring the severity of relapses in M ult I ple sc LE rosis
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SMILE: a predictive model for Scoring the severity of relapses in MultIple scLErosis F. Lejeune1,2 · A. Chatton3 · D.‑A. Laplaud1,2 · E. Le Page4 · S. Wiertlewski1,2 · G. Edan4 · A. Kerbrat4 · D. Veillard5 · S. Hamonic5 · N. Jousset6 · F. Le Frère6 · J.‑C. Ouallet7 · B. Brochet7 · A. Ruet7 · Y. Foucher3,8 · Laure Michel4,9,10 Received: 22 April 2020 / Revised: 21 July 2020 / Accepted: 10 August 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Background In relapsing–remitting multiple sclerosis (RRMS), relapse severity and residual disability are difficult to predict. Nevertheless, this information is crucial both for guiding relapse treatment strategies and for informing patients. Objective We, therefore, developed and validated a clinical-based model for predicting the risk of residual disability at 6 months post-relapse in MS. Methods We used the data of 186 patients with RRMS collected during the COPOUSEP multicentre trial. The outcome was an increase of ≥ 1 EDSS point 6 months post-relapse treatment. We used logistic regression with LASSO penalization to construct the model, and bootstrap cross-validation to internally validate it. The model was externally validated with an independent retrospective French single-centre cohort of 175 patients. Results The predictive factors contained in the model were age > 40 years, shorter disease duration, EDSS increase ≥ 1.5 points at time of relapse, EDSS = 0 before relapse, proprioceptive ataxia, and absence of subjective sensory disorders. Discriminative accuracy was acceptable in both the internal (AUC 0.82, 95% CI [0.73, 0.91]) and external (AUC 0.71, 95% CI [0.62, 0.80]) validations. Conclusion The predictive model we developed should prove useful for adapting therapeutic strategy of relapse and followup to individual patients. Keywords Multiple sclerosis · Relapse phenotype · Predictive model · Relapse recovery · EDSS
Introduction Relapse severity and residual disability are highly variable in patients with relapsing–remitting multiple sclerosis (RRMS), and recovery remains difficult to predict [1, 2]. * Laure Michel laure.michel@chu‑rennes.fr 1
Neurology Department and CIC 0004, Nantes University Hospital, Nantes, France
Centre de Recherche en Transplantation et Immunologie, INSERM U1064, Nantes, France
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MethodS in Patient‑Centred Outcomes and HEalth ResEarch (SPHERE) Unit, INSERM, Universities of Nantes and Tours, Nantes, France
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Clinical Neuroscience Centre, CIC_P1414 INSERM, Rennes University Hospital, Rennes University, Rennes, France
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Epidemiology and Public Health Department, Rennes University Hospital, Rennes, France
From experience, neurologists know that several clinical factors influence the risk of sequelae, and, thus, midterm disability. Previous studies have shown that older age, relapse severity, and relapse phenotype (particularly
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Nantes Clinical Investigation Centre, Nantes University Hospital, Nantes, France
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Neurology Department, Magendie Neurocentr
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