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SMILE: a predictive model for Scoring the severity of relapses in MultIple scLErosis

Journal of Neurology volume 268, pages 669–679 (2021)Cite this article

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 follow-up to individual patients.

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Author information

Authors and Affiliations

  1. Neurology Department and CIC 0004, Nantes University Hospital, Nantes, France

    F. Lejeune, D.-A. Laplaud & S. Wiertlewski

  2. Centre de Recherche en Transplantation et Immunologie, INSERM U1064, Nantes, France

    F. Lejeune, D.-A. Laplaud & S. Wiertlewski

  3. MethodS in Patient-Centred Outcomes and HEalth ResEarch (SPHERE) Unit, INSERM, Universities of Nantes and Tours, Nantes, France

    A. Chatton & Y. Foucher

  4. Clinical Neuroscience Centre, CIC_P1414 INSERM, Rennes University Hospital, Rennes University, Rennes, France

    E. Le Page, G. Edan, A. Kerbrat & Laure Michel

  5. Epidemiology and Public Health Department, Rennes University Hospital, Rennes, France

    D. Veillard & S. Hamonic

  6. Nantes Clinical Investigation Centre, Nantes University Hospital, Nantes, France

    N. Jousset & F. Le Frère

  7. Neurology Department, Magendie Neurocentre, Bordeaux University Hospital, INSERM U1215, Bordeaux, France

    J.-C. Ouallet, B. Brochet & A. Ruet

  8. Nantes University Hospital, Nantes, France

    Y. Foucher

  9. Microenvironment, Cell Differentiation, Immunology and Cancer Unit, INSERM, Rennes I University, French Blood Agency, Rennes, France

    Laure Michel

  10. Neurology Department, Rennes University Hospital, Rennes, France

    Laure Michel

Authors
  1. F. Lejeune
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  2. A. Chatton
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  3. D.-A. Laplaud
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  4. E. Le Page
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  8. D. Veillard
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  9. S. Hamonic
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  12. J.-C. Ouallet
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  13. B. Brochet
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  14. A. Ruet
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  16. Laure Michel
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Corresponding author

Correspondence to Laure Michel.

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Conflicts of interest

F. Lejeune reports no disclosures. A. Chatton reports no disclosures. D.-A. Laplaud reports personal fees and non-financial support from Biogen, Merck, Novartis, Genzyme, Teva, Roche and MedDay, all outside the submitted work. S. Wiertlewski received consultancy fees, speaker fees, honoraria and clinical research grants from Biogen-Idec, Merck, Novartis, Genzyme, Roche, Sanofi-Aventis and Teva, all outside the submitted work. G. Edan reports no disclosures. E. Le Page has received grants, personal fees and non-financial support from Biogen Idec, Genzyme, Merck-Serono, Novartis, Roche, Sanofi and Teva, all outside the submitted work. A. Kerbrat reports no disclosures. D. Veillard reports no disclosures. S. Hamonic reports no disclosures. N. Jousset reports no disclosures. F. Le Frère reports no disclosures. J.-C. Ouallet reports personal fees from Biogen, Roche and Genzyme, and grants, personal fees and non-financial support from Novartis and Merck, all outside the submitted work. B. Brochet reports grants from the French Ministry of Health, personal fees and non-financial support from Biogen-Idec, grants from Merck-Serono, personal fees and non-financial support from Novartis, personal fees and non-financial support from Genzyme, grants, personal fees and non-financial support from Teva, and grants and non-financial support from Bayer, all outside the submitted work. A. Ruet has received consultancy fees, speaker fees, research grants (non-personal) or honoraria from Medday, Novartis, Biogen Idec, Genzyme, Roche, Teva, and Merck, all outside the submitted work. Y. Foucher has received speaking honoraria from Biogen and Sanofi-Genzyme. L. Michel has received grants and fees from Biogen Idec, Merck Serono, Roche, Sanofi Genzyme, Teva and Novartis, all outside the submitted work.

Ethics approval

Data confidentiality and safety were ensured in accordance with the recommendations of the French National Ethics Committee (CNIL-Commission Nationale Informatique et Libertés), which provided approval for the EDMUS database. All data identifying patients were anonymised. All human studies were performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. Specific national laws were also observed.

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Lejeune, F., Chatton, A., Laplaud, DA. et al. SMILE: a predictive model for Scoring the severity of relapses in MultIple scLErosis. J Neurol 268, 669–679 (2021). https://doi.org/10.1007/s00415-020-10154-5

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  • DOI: https://doi.org/10.1007/s00415-020-10154-5

Keywords

  • Multiple sclerosis
  • Relapse phenotype
  • Predictive model
  • Relapse recovery
  • EDSS