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Early prediction of unfavorable evolution after a first clinical episode suggestive of multiple sclerosis: the EUMUS score

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Abstract

Background

Predicting disease progression in patients with the first clinical episode suggestive of multiple sclerosis (MS) is crucial for personalized therapeutic approaches. This study aimed to develop the EUMUS score for accurately estimating the risk of early evidence of disease activity and progression (EDA).

Methods

Retrospective analysis was conducted on data from 221 patients with a first clinical MS episode collected from four Italian MS centers. Various variables including socio-demographics, clinical features, cerebrospinal fluid analysis, evoked potentials, and brain MRI were considered. A prognostic multivariate regression model was identified to develop the EUMUS score. The optimal cutoff for predicting the transition from no evidence of disease activity (NEDA3) to EDA was determined. The accuracy of the prognostic model and score were tested in a separate UK MS cohort.

Results

After 12 months, 61.54% of patients experienced relapses and/or new MRI lesions. Younger age (OR 0.96, CI 0.93–0.99; p = 0.005), MRI infratentorial lesion(s) at baseline (OR 2.21, CI 1.27–3.87; p = 0.005), positive oligoclonal bands (OR 2.89, CI 1.47–5.69; p = 0.002), and abnormal lower limb somatosensory-evoked potentials (OR 2.77, CI 1.41–5.42; p = 0.003) were significantly associated with increased risk of EDA. The EUMUS score demonstrated good specificity (72%) and correctly classified 80% of patients with EDA in the independent UK cohort.

Conclusions

The EUMUS score is a simple and useful tool for predicting MS evolution within 12 months of the first clinical episode. It has the potential to guide personalized therapeutic approaches and aid in clinical decision-making.

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Data availability

The data supporting the findings of this study are available upon request from the corresponding author.

References

  1. Giovannoni G, Turner B, Gnanapavan S, Offiah C, Schmierer K, Marta M (2015) Is it time to target no evident disease activity (NEDA) in multiple sclerosis? Mult Scler Relat Disord 4(4):329–333

    Article  PubMed  Google Scholar 

  2. Bergamaschi R, Montomoli C (2016) Modeling the course and outcomes of MS is statistical twaddle—no. Mult Scler 22(2):142–144

    Article  PubMed  Google Scholar 

  3. Trojano M, Bergamaschi R, Amato MP, Comi G, Ghezzi A, Lepore V et al (2019) The Italian multiple sclerosis register. Neurol Sci 40(1):155–165

    Article  PubMed  Google Scholar 

  4. Thompson AJ, Banwell BL, Barkhof F, Carroll WM, Coetzee T, Comi G et al (2018) Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol 17(2):162–173

    Article  PubMed  Google Scholar 

  5. Sullivan LM, Massaro JM, D’Agostino RB Sr (2004) Presentation of multivariate data for clinical use: the Framingham Study risk score functions. Stat Med 23(10):1631–1660

    Article  PubMed  Google Scholar 

  6. Jacobs LD, Beck RW, Simon JH, Kinkel RP, Brownscheidle CM, Murray TJ et al (2000) Intramuscular interferon beta-1a therapy initiated during a first demyelinating event in multiple sclerosis. CHAMPS Study Group. N Engl J Med 343(13):898–904

    Article  CAS  PubMed  Google Scholar 

  7. Kappos L, Polman CH, Freedman MS, Edan G, Hartung HP, Miller DH et al (2006) Treatment with interferon beta-1b delays conversion to clinically definite and McDonald MS in patients with clinically isolated syndromes. Neurology 67(7):1242–1249

    Article  CAS  PubMed  Google Scholar 

  8. Leist TP, Comi G, Cree BA, Coyle PK, Freedman MS, Hartung HP et al (2014) Effect of oral cladribine on time to conversion to clinically definite multiple sclerosis in patients with a first demyelinating event (ORACLE MS): a phase 3 randomised trial. Lancet Neurol 13(3):257–267

    Article  CAS  PubMed  Google Scholar 

  9. Miller AE, Wolinsky JS, Kappos L, Comi G, Freedman MS, Olsson TP et al (2014) Oral teriflunomide for patients with a first clinical episode suggestive of multiple sclerosis (TOPIC): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Neurol 13(10):977–986

    Article  CAS  PubMed  Google Scholar 

  10. Metz LM, Li DKB, Traboulsee AL, Duquette P, Eliasziw M, Cerchiaro G et al (2017) Trial of minocycline in a clinically isolated syndrome of multiple sclerosis. N Engl J Med 376(22):2122–2133

    Article  CAS  PubMed  Google Scholar 

  11. Bergamaschi R, Quaglini S, Trojano M, Amato MP, Tavazzi E, Paolicelli D et al (2007) Early prediction of the long term evolution of multiple sclerosis: the Bayesian Risk Estimate for Multiple Sclerosis (BREMS) score. J Neurol Neurosurg Psychiatry 78(7):757–759

    Article  PubMed  PubMed Central  Google Scholar 

  12. Bergamaschi R, Montomoli C, Mallucci G, Lugaresi A, Izquierdo G, Grand’Maison F et al (2015) BREMSO: a simple score to predict early the natural course of multiple sclerosis. Eur J Neurol 22(6):981–989

    Article  CAS  PubMed  Google Scholar 

  13. Pelayo R, Montalban X, Minoves T, Moncho D, Rio J, Nos C et al (2010) Do multimodal evoked potentials add information to MRI in clinically isolated syndromes? Mult Scler 16(1):55–61

    Article  CAS  PubMed  Google Scholar 

  14. Gronseth GS, Ashman EJ (2000) Practice parameter: the usefulness of evoked potentials in identifying clinically silent lesions in patients with suspected multiple sclerosis (an evidence-based review): report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology 54(9):1720–1725

    Article  CAS  PubMed  Google Scholar 

  15. Dziadkowiak E, Wieczorek M, Zagrajek M, Chojdak-Lukasiewicz J, Gruszka E, Budrewicz S et al (2021) Multimodal evoked potentials as potential biomarkers of disease activity in patients with clinically isolated syndrome. Front Neurol 12:678035

    Article  PubMed  Google Scholar 

  16. Tintore M, Rovira A, Rio J, Otero-Romero S, Arrambide G, Tur C et al (2015) Defining high, medium and low impact prognostic factors for developing multiple sclerosis. Brain 138(Pt 7):1863–1874

    Article  PubMed  Google Scholar 

  17. Tintore M, Arrambide G, Otero-Romero S, Carbonell-Mirabent P, Rio J, Tur C et al (2020) The long-term outcomes of CIS patients in the Barcelona inception cohort: looking back to recognize aggressive MS. Mult Scler 26(13):1658–1669

    Article  CAS  PubMed  Google Scholar 

  18. Dalton CM, Bodini B, Samson RS, Battaglini M, Fisniku LK, Thompson AJ et al (2012) Brain lesion location and clinical status 20 years after a diagnosis of clinically isolated syndrome suggestive of multiple sclerosis. Mult Scler 18(3):322–328

    Article  CAS  PubMed  Google Scholar 

  19. Giorgio A, Battaglini M, Rocca MA, De Leucio A, Absinta M, van Schijndel R et al (2013) Location of brain lesions predicts conversion of clinically isolated syndromes to multiple sclerosis. Neurology 80(3):234–241

    Article  PubMed  Google Scholar 

  20. Eran A, Garcia M, Malouf R, Bosak N, Wagner R, Ganelin-Cohen E et al (2018) MRI in predicting conversion to multiple sclerosis within 1 year. Brain Behav 8(9):e01042

    Article  PubMed  PubMed Central  Google Scholar 

  21. Battaglini M, Vrenken H, Tappa Brocci R, Gentile G, Luchetti L, Versteeg A et al (2022) Evolution from a first clinical demyelinating event to multiple sclerosis in the REFLEX trial: Regional susceptibility in the conversion to multiple sclerosis at disease onset and its amenability to subcutaneous interferon beta-1a. Eur J Neurol 29(7):2024–2035

    Article  PubMed  PubMed Central  Google Scholar 

  22. Scalfari A (2019) MS progression is predominantly driven by age-related mechanisms—YES. Mult Scler 25(7):902–904

    Article  PubMed  Google Scholar 

  23. Kalincik T, Buzzard K, Jokubaitis V, Trojano M, Duquette P, Izquierdo G et al (2014) Risk of relapse phenotype recurrence in multiple sclerosis. Mult Scler 20(11):1511–1522

    Article  PubMed  Google Scholar 

  24. Scalfari A, Lederer C, Daumer M, Nicholas R, Ebers GC, Muraro PA (2016) The relationship of age with the clinical phenotype in multiple sclerosis. Mult Scler 22(13):1750–1758

    Article  CAS  PubMed  Google Scholar 

  25. Koch MW, Mostert J, Greenfield J, Liu WQ, Metz L (2020) Gadolinium enhancement on cranial MRI in multiple sclerosis is age dependent. J Neurol 267(9):2619–2624

    Article  CAS  PubMed  Google Scholar 

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Funding

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Author information

Authors and Affiliations

  1. Multiple Sclerosis Center, Neurocenter of Southern Switzerland, EOC, Lugano, Switzerland

    Giulia Mallucci

  2. Department of Public Health, Experimental and Forensic Medicine, Unit of Biostatistics and Clinical Epidemiology, University of Pavia, Pavia, Italy

    Ottavia Eleonora Ferraro & Cristina Montomoli

  3. Department of Translational Biomedicines and Neurosciences University of Bari, A. Moro, Bari, Italy

    Maria Trojano, Pietro Iaffaldano & Damiano Paolicelli

  4. Department NEUROFARBA, University of Florence, Florence, Italy

    Maria Pia Amato, Emilio Portaccio & Lorenzo Razzolini

  5. Centre of Neuroscience, Department of Medicine, Imperial College London, Charing Cross Hospital, London, UK

    Antonio Scalfari

  6. Neuroimmunology Unit and Multiple Sclerosis Center, ASST della Valle Olona, Hospital of Gallarate, Gallarate, VA, Italy

    Mauro Zaffaroni

  7. IRCCS Mondino Foundation, Pavia, Italy

    Elena Colombo, Eleonora Rigoni & Roberto Bergamaschi

  8. IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy

    Maria Pia Amato

  9. Department of Neurosciences, Neurology and Stroke Unit, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy

    Lorenzo Saraceno

Authors
  1. Giulia Mallucci
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  2. Ottavia Eleonora Ferraro
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  3. Maria Trojano
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  4. Maria Pia Amato
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  5. Antonio Scalfari
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  6. Mauro Zaffaroni
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  7. Elena Colombo
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  8. Eleonora Rigoni
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  9. Pietro Iaffaldano
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  10. Emilio Portaccio
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  11. Lorenzo Saraceno
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  12. Damiano Paolicelli
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  13. Lorenzo Razzolini
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  14. Cristina Montomoli
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  15. Roberto Bergamaschi
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Contributions

GM conceptualized the project, designed the survey, wrote the first draft, handled submission, and was responsible for the final approval of the manuscript. RB conceptualized the project, co-wrote the first draft, and was responsible for the final approval of the manuscript. OF analyzed data, revised the manuscript for intellectual content, and co-wrote the final draft. CM co-analyzed data, conceptualized the project, co-wrote the first draft, and was responsible for the final approval of the manuscript. MPA, MT, MZ, and AS revised and co-wrote the first draft, revised the final manuscript for intellectual content, and were responsible for the final approval of the manuscript. EC, co-designed the survey, inputted data, revised the manuscript for intellectual content, and co-wrote the final draft. ER, EP, LR, PI, DP, and LS inputted data, revised the manuscript for intellectual content, and co-wrote the final draft.

Corresponding author

Correspondence to Giulia Mallucci.

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Conflicts of interest

GM, OF, and LS no competing interests are disclaimed. RB has served on scientific advisory boards and received funding for travel, speaker honoraria, research support from Almirall, Bayer, Biogen, Bristol Myers Squibb/Celgene, Janssen, Merck-Serono, Novartis, Roche, Sanofi-Genzyme, and Teva. MPA has served on Scientific Advisory Boards for Biogen, Novartis, Roche, Merck, Sanofi Genzyme and Teva; has received speaker honoraria from Biogen, Merck, Sanofi Genzyme, Roche, Novartis, and Teva; has received research grants for her Institution from Biogen, Merck, Sanofi Genzyme, Novartis and Roche, Italian MS Foundation, Canadian MS Foundation, Italian Health Ministry, Regione Toscana. She is co-Editor of the Multiple Sclerosis Journal. MT has served on Scientific Advisory Boards for Biogen, Novartis, Roche, Merck, BMS Celgene, and Janssen; has received speaker honoraria from Biogen, Sanofi, Merck, Roche, and Novartis; and has received research grants for her Department from Biogen, Merck, Roche, and Novartis. MZ has received travel support, speaking honoraria or served on advisory boards for Alexion, Biogen, BMS-Celgene, Janssen-Cilag, Novartis, Merck, Roche, and Sanofi. CM, AS, EC, ER, EP, LR, PI, and DP report no disclosures relevant to this manuscript.

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Mallucci, G., Ferraro, O.E., Trojano, M. et al. Early prediction of unfavorable evolution after a first clinical episode suggestive of multiple sclerosis: the EUMUS score. J Neurol 271, 3496–3505 (2024). https://doi.org/10.1007/s00415-024-12304-5

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