Associations of Disease-Modifying Therapies with COVID-19 Severity in Multiple Sclerosis

S Simpson-Yap; E De Brouwer; T Kalincik; N Rijke; JA Hillert; C Walton; G Edan; Y Moreau; T Spelman; L Geys; T Parciak; C Gautrais; N Lazovski; A Pirmani; A Ardeshirdavanai; L Forsberg; A Glaser; R McBurney; H Schmidt; AB Bergmann; S Braune; A Stahmann; R Middleton; A Salter; RJ Fox; A Van Der Walt; H Butzkueven; R Alroughani; S Ozakbas; JI Rojas; I Van Der Mei; N Nag; R Ivanov; G Sciascia Do Olival; AE Dias; M Magyari; D Brum; MF Mendes; RN Alonso; RS Nicholas; J Bauer; AS Chertcoff; A Zabalza; G Arrambide; A Fidao; G Comi; L Peeters

Journal article

Associations of Disease-Modifying Therapies with COVID-19 Severity in Multiple Sclerosis

S Simpson-Yap, E De Brouwer, T Kalincik, N Rijke, JA Hillert, C Walton, G Edan, Y Moreau, T Spelman, L Geys, T Parciak, C Gautrais, N Lazovski, A Pirmani, A Ardeshirdavanai, L Forsberg, A Glaser, R McBurney, H Schmidt, AB Bergmann Show all

Neurology | Published : 2021

DOI: 10.1212/WNL.0000000000012753

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Abstract

Background and ObjectivesPeople with multiple sclerosis MS are a vulnerable group for severe coronavirus disease 2019 COVID-19, particularly those taking immunosuppressive disease-modifying therapies DMTs. We examined the characteristics of COVID-19 severity in an international sample of people with MS.MethodsData from 12 data sources in 28 countries were aggregated sources could include patients from 1-12 countries. Demographic age, sex, clinical MS phenotype, disability, and DMT untreated, alemtuzumab, cladribine, dimethyl fumarate, glatiramer acetate, interferon, natalizumab, ocrelizumab, rituximab, siponimod, other DMTs covariates were queried, along with COVID-19 severity outcomes, hosp..

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University of Melbourne Researchers

Steve Simpson-Yap Author

Tomas Kalincik Author

Timothy Spelman Author

Nupur Nag Author

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Awarded by National Multiple Sclerosis Society

Funding Acknowledgements

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article. The operational costs linked to this study are funded by theMultiple Sclerosis International Federation (MSIF) and the Multiple Sclerosis Data Alliance (MSDA), acting under the umbrella of the European Charcot Foundation. The MSDA receives income from a range of corporate sponsors, recently including Biogen, Bristol-Myers Squibb (formerly Celgene), Canopy Growth Corp, Genzyme, Icometrix, Merck, Mylan, Novartis, QMENTA, Quanterix, and Roche. MSIF receives income from a range of corporate sponsors, recently including Biogen, Bristol-Myers Squibb (formerly Celgene), Genzyme, Med-Day, Merck, Mylan, Novartis, and Roche. This work was supported by the Flemish government under the Onderzoeksprogramma Artificiele Intelligentie Vlaanderen programme and the Research Foundation Fladers (FWO) for ELIXIR Belgium-Flanders (FWO) for ELIXIR Belgium. The central platform was provided by QMENTA, and the computational resources used in this work were provided by Amazon. The statistical analysis was carried out at CORe, The University of Melbourne, with support from the National Health and Medical Research Council (NHMRC; 1129189 and 1140766).