BACKGROUND: Treatment switching is a common challenge and opportunity in real-world clinical practice. Increasing diversity in disease-modifying treatments (DMTs) has generated interest in the identification of reliable and robust predictors of treatment switching across different countries, DMTs, and time periods. OBJECTIVE: The objective of this retrospective, observational study was to identify independent predictors of treatment switching in a population of relapsing-remitting MS (RRMS) patients in the Big Multiple Sclerosis Data Network of national clinical registries, including the Italian MS registry, the OFSEP of France, the Danish MS registry, the Swedish national MS registry, and the international MSBase Registry. METHODS: In this cohort study, we merged information on 269,822 treatment episodes in 110,326 patients from 1997 to 2018 from five clinical registries. Patients were included in the final pooled analysis set if they had initiated at least one DMT during the relapsing-remitting MS (RRMS) stage. Patients not diagnosed with RRMS or RRMS patients not initiating DMT therapy during the RRMS phase were excluded from the analysis. The primary study outcome was treatment switching. A multilevel mixed-effects shared frailty time-to-event model was used to identify independent predictors of treatment switching. The contributing MS registry was included in the pooled analysis as a random effect. RESULTS: Every one-point increase in the Expanded Disability Status Scale (EDSS) score at treatment start was associated with 1.08 times the rate of subsequent switching, adjusting for age, sex, and calendar year (adjusted hazard ratio [aHR] 1.08; 95% CI 1.07-1.08). Women were associated with 1.11 times the rate of switching relative to men (95% CI 1.08-1.14), whilst older age was also associated with an increased rate of treatment switching. DMTs started between 2007 and 2012 were associated with 2.48 times the rate of switching relative to DMTs that began between 1996 and 2006 (aHR 2.48; 95% CI 2.48-2.56). DMTs started from 2013 onwards were more likely to switch relative to the earlier treatment epoch (aHR 8.09; 95% CI 7.79-8.41; reference = 1996-2006). CONCLUSION: Switching between DMTs is associated with female sex, age, and disability at baseline and has increased in frequency considerably in recent years as more treatment options have become available. Consideration of a patient's individual risk and tolerance profile needs to be taken into account when selecting the most appropriate switch therapy from an expanding array of treatment choices.

Academic MS Center Zuyderland Department of Neurology Zuyderland Medical Center Sittard Geleen Netherlands

Bakirkoy Education and Research Hospital for Psychiatric and Neurological Diseases Istanbul Türkiye

Biogen Digital Health Biogen Spain Madrid Spain

Biogen International GmbH Zug Switzerland

Center of Neuroimmunology Service of Neurology Hospital Clinic de Barcelona Barcelona Spain

Centre des Neurosciences de Lyon L'Institut national de la santé et de la recherche médicale 1028 et Centre national de la recherche scientifique joint research units5292 Lyon France

Clinical Outcomes Research Unit Department of Medicine University of Melbourne Melbourne VIC Australia

CSSS Saint Jérôme Saint Jerome QC Canada

Danish Multiple Sclerosis Center Department of Neurology Copenhagen University Hospital Rigshospitalet Glostrup Copenhagen Denmark

Department of Basic Medical Sciences Neurosciences and Sense Organs University of Bari Aldo Moro Bari Italy

Department of Clinical Neuroscience Karolinska Institute Stockholm Sweden

Department of Neurology Aarhus University Hospital Aarhus Denmark

Department of Neurology and Center of Clinical Neuroscience 1st Faculty of Medicine Charles University and General University Hospital Prague Czechia

Department of Neurology Copenhagen University Hospital Herlev and Gentofte København Denmark

Department of Neurology Faculty of Health Sciences University Fernando Pessoa Porto Portugal

Department of Neurology Hospital Clinico San Carlos Madrid Spain

Department of Neurology Hospital of Southern Jutland University of Southern Denmark Aabenraa Denmark

Department of Neurology Hospital Universitario Virgen Macarena Sevilla Spain

Department of Neurology Neuroscience Research Center Golestan University of Medical Sciences Gogan Iran

Department of Neurology Nordsjællands Hospital Hillerød Denmark

Department of Neurology Physiotherapy and Occupational Therapy Gødstrup Hospital Herning Denmark

Department of Neurology School of Medicine and Koc University Research Center for Translational Medicine Koc University Istanbul Türkiye

Department of Neurology Southwest Jutland Hospital University Hospital of Southern Denmark Esbjerg Denmark

Department of Neuroscience Central Clinical School Monash University Melbourne VIC Australia

Department of Translational Biomedicine and Neuroscience DiBraiN University of Bari Aldo Moro Bari Italy

Division of Neurology Department of Medicine Amiri Hospital Sharq Kuwait

Dokuz Eylul University Konak Izmir Türkiye

Faculté de Médicine Lyon Est Université Claude Bernard Lyon 1 Villeurbanne Auvergne Rhône Alpes France

Faculty of Medicine Division of Neurology Geneva University Hospital Geneva Switzerland

Groene Hart Ziekenhuis Gouda Netherlands

Hacettepe University Ankara Türkiye

Hunter Medical Research Institute Hunter New England Health John Hunter Hospital New Lambton Heights NSW Australia

Isfahan University of Medical Sciences Isfahan Iran

Medical Faculty 19 Mayis University Samsun Türkiye

Monash Health Melbourne VIC Australia

MS and Neuroimmunology Research Central Clinical School Alfred and Box Hill Hospitals Monash University Melbourne VIC Australia

MSBase Foundation Melbourne VIC Australia

Nehme and Therese Tohme Multiple Sclerosis Center American University of Beirut Medical Center Beirut Lebanon

Nemocnice Jihlava Jihlava Czechia

Neuro Rive Sud Longueuil QC Canada

NIDO | Centre for Research and Education Gødstrup Hospital Herning Denmark

Rashid Hospital Dubai United Arab Emirates

Royal Victoria Hospital Belfast United Kingdom

Service de Neurologie Sclérose en Plaques Pathologies de la Myéline et Neuro Inflammation Hôpital Neurologique Pierre Wertheimer Hospices Civils de Lyon Lyon France

St Vincent's University Hospital Dublin Ireland

The Danish Multiple Sclerosis Registry Copenhagen University Hospital Rigshospitalet Glostrup Denmark

University Newcastle Callaghan NSW Australia

University of Montreal Hospital Research Centre and Universite de Montreal Montreal QC Canada

University of Queensland Brisbane QLD Australia

Zobrazit více v PubMed

Fymat AL. Multiple sclerosis: II. Diagnosis and symptoms management. J Neurol Psychol Res. (2023) 4:1–21.

Harding K, Williams O, Willis M, Hrastelj J, Rimmer A, Joseph F, et al. . Clinical outcomes of escalation vs early intensive disease-modifying therapy in patients with multiple sclerosis. JAMA Neurol. (2019) 76:536–41. 10.1001/jamaneurol.2018.4905 PubMed DOI PMC

Spelman T, Magyari M, Piehl F, Svenningsson A, Rasmussen PV, Kant M, et al. . Treatment escalation vs immediate initiation of highly effective treatment for patients with relapsing-remitting multiple sclerosis: Data from 2 different national strategies. JAMA Neurol. (2021) 78:1197–204. 10.1001/jamaneurol.2021.2738 PubMed DOI PMC

Lorscheider J, Benkert P, Lienert C, Hänni P, Derfuss T, Kuhle J, et al. . Comparative analysis of dimethyl fumarate and fingolimod in relapsing–remitting multiple sclerosis. J Neurol. (2021) 268:941–9. 10.1007/s00415-020-10226-6 PubMed DOI PMC

Papp V, Buron MD, Siersma V, Rasmussen PV, Illes Z, Kant M, et al. . Real-world outcomes for a complete nationwide cohort of more than 3200 teriflunomide-treated multiple sclerosis patients in The Danish Multiple Sclerosis Registry. PLoS ONE. (2021) 16:e0250820. 10.1371/journal.pone.0250820 PubMed DOI PMC

Setayeshgar S, Kingwell E, Zhu F, Zhang T, Carruthers R, Marrie RA, et al. . Persistence and adherence to the new oral disease-modifying therapies for multiple sclerosis: a population-based study. Mult Scler Relat Disord. (2019) 27:364–9. 10.1016/j.msard.2018.11.004 PubMed DOI

Evans C, Marrie RA, Zhu F, Leung S, Lu X, Melesse DY, et al. . Adherence and persistence to drug therapies for multiple sclerosis: a population-based study. Mult Scler Relat Disord. (2016) 8:78–85. 10.1016/j.msard.2016.05.006 PubMed DOI

Warrender-Sparkes M, Spelman T, Izquierdo G, Trojano M, Lugaresi A, Grand'Maison F, et al. . The effect of oral immunomodulatory therapy on treatment uptake and persistence in multiple sclerosis. Multiple Sclerosis J. (2016) 22:520–532. 10.1177/1352458515594041 PubMed DOI

Bigaut K, Cohen M, Durand-Dubief F, Maillard E, Planque E, Zephir H, et al. . How to switch disease-modifying treatments in multiple sclerosis: guidelines from the French Multiple Sclerosis Society (SFSEP). Mult Scler Relat Disord. (2021) 103076. 10.1016/j.msard.2021.103076 PubMed DOI

Patti F, Chisari CG, D'Amico E, Annovazzi P, Banfi P, Bergamaschi R, et al. . Clinical and patient determinants of changing therapy in relapsing-remitting multiple sclerosis (SWITCH study). Mult Scler Relat Disord. (2020) 42:102124. 10.1016/j.msard.2020.102124 PubMed DOI

Trojano M, Tintore M, Montalban X, Hillert J, Kalincik T, Iaffaldano P, et al. . Treatment decisions in multiple sclerosis—insights from real-world observational studies. Nat Rev Neurol. (2017) 13:105–18. 10.1038/nrneurol.2016.188 PubMed DOI

Hillert J, Magyari M, Soelberg Sørensen P, Butzkueven H, Van Der Welt A, Vukusic S, et al. . Treatment switching and discontinuation over 20 years in the big multiple sclerosis data network. Front Neurol. (2021) 12:295. 10.3389/fneur.2021.647811 PubMed DOI PMC

Stühler E, Braune S, Lionetto F, Heer Y, Jules E, Westermann C, et al. . Framework for personalized prediction of treatment response in relapsing remitting multiple sclerosis. BMC Med Res Methodol. (2020) 20:1–15. 10.1186/s12874-020-0906-6 PubMed DOI PMC

Rotstein D, Montalban X. Reaching an evidence-based prognosis for personalized treatment of multiple sclerosis. Nat Rev Neurol. (2019) 15:287–300. 10.1038/s41582-019-0170-8 PubMed DOI

Chitnis T, Prat A. A roadmap to precision medicine for multiple sclerosis. Multiple Scler J. (2020) 26:522–32. 10.1177/1352458519881558 PubMed DOI

Havas J, Leray E, Rollot F, Casey R, Michel L, Lejeune F, et al. . Predictive medicine in multiple sclerosis: a systematic review. Mult Scler Relat Disord. (2020) 40:101928. 10.1016/j.msard.2020.101928 PubMed DOI

Iaffaldano P, Lucisano G, Butzkueven H, Hillert J, Hyde R, Koch-Henriksen N, et al. . Early treatment delays long-term disability accrual in RRMS: results from the BMSD network. Multiple Sclerosis J. (2021) 27:13524585211010128. 10.1177/13524585211010128 PubMed DOI

Kalincik T, Butzkueven H. The MSBase registry: informing clinical practice. Multiple Scler J. (2019) 25:1828–34. 10.1177/1352458519848965 PubMed DOI

Hillert J, Stawiarz L. The Swedish MS registry–clinical support tool and scientific resource. Acta Neurol Scand. (2015) 132:11–9. 10.1111/ane.12425 PubMed DOI PMC

Magyari M, Joensen H, Laursen B, Koch-Henriksen N. The Danish multiple sclerosis registry. Brain Behav. (2021) 11:e01921. 10.1002/brb3.1921 PubMed DOI PMC

Trojano M, Bergamaschi R, Amato MP, Comi G, Ghezzi A, Lepore V, et al. . The Italian multiple sclerosis register. Neurol Sci. (2019) 40:155–65. 10.1007/s10072-018-3610-0 PubMed DOI PMC

Vukusic S, Casey R, Rollot F, Brochet B, Pelletier J, Laplaud DA, et al. . Observatoire Français de la Sclérose en Plaques (OFSEP): a unique multimodal nationwide MS registry in France. Multiple Scler J. (2020) 26:118–22. 10.1177/1352458518815602 PubMed DOI

Spelman T, Horakova D, Ozakbas S, Alroughani R, Onofrj M, Kalincik T, et al. . Switching to natalizumab or fingolimod in multiple sclerosis: comparative effectiveness and effect of pre-switch disease activity. Multiple Scler Relat Disor. (2023) 70:104477. 10.1016/j.msard.2022.104477 PubMed DOI

Gutierrez RG. Parametric frailty and shared frailty survival models. Stata J. (2002) 2:22–44. 10.1177/1536867X0200200102 DOI

Meyniel C, Spelman T, Jokubaitis VG, Trojano M, Izquierdo G, Grand'Maison F, et al. . Country, sex, EDSS change and therapy choice independently predict treatment discontinuation in multiple sclerosis and clinically isolated syndrome. PLoS ONE. (2012) 7:e38661. 10.1371/journal.pone.0038661 PubMed DOI PMC

Kalincik T, Manouchehrinia A, Sobisek L, Jokubaitis V, Spelman T, Horakova D, et al. . Towards personalized therapy for multiple sclerosis: prediction of individual treatment response. Brain. (2017) 140:2426–43. 10.1093/brain/awx185 PubMed DOI

Ayrignac X, Bigaut K, Pelletier J, de Seze J, Demortiere S, Collongues N, et al. . First line treatment failure: Predictive factors in a cohort of 863 relapsing remitting MS patients. Mult Scler Relat Disord. (2021) 48:102686. 10.1016/j.msard.2020.102686 PubMed DOI

Sorensen PS, Kopp TI, Joensen H, Olsson A, Sellebjerg F, Magyari M. Age and sex as determinants of treatment decisions in patients with relapsing-remitting MS. Mult Scler Relat Disord. (2021) 50:102813. 10.1016/j.msard.2021.102813 PubMed DOI

Patti F, Chisari CG, Arena S, Toscano S, Finocchiaro C, Fermo SL, et al. . Factors driving delayed time to multiple sclerosis diagnosis: results from a population-based study. Mult Scler Relat Disord. (2022) 57:103361. 10.1016/j.msard.2021.103361 PubMed DOI

Ghezzi A. European and American guidelines for multiple sclerosis treatment. Neurol Ther. (2018) 7:189–94. 10.1007/s40120-018-0112-1 PubMed DOI PMC

Ziemssen T, Derfuss T, de Stefano N, Giovannoni G, Palavra F, Tomic D, et al. . Optimizing treatment success in multiple sclerosis. J Neurol. (2016) 263:1053–65. 10.1007/s00415-015-7986-y PubMed DOI PMC

Gross RH, Corboy JR. Monitoring, switching, and stopping multiple sclerosis disease-modifying therapies. Continuum. (2019) 25:715–35. 10.1212/CON.0000000000000738 PubMed DOI

Hauser SL, Cree BA. Treatment of multiple sclerosis: a review. Am J Med. (2020) 133:1380–90. 10.1016/j.amjmed.2020.05.049 PubMed DOI PMC

Wattjes MP, Ciccarelli O, Reich DS, Banwell B, de Stefano N, Enzinger C, et al. . 2021 MAGNIMS–CMSC–NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis. Lancet Neurol. (2021) 20:653–70. 10.1016/S1474-4422(21)00095-8 PubMed DOI

Cross A, Riley C. Treatment of multiple sclerosis. Continuum. (2022) 28:1025–51. 10.1212/CON.0000000000001170 PubMed DOI

Stankiewicz JM, Weiner HL. An argument for broad use of high efficacy treatments in early multiple sclerosis. Neurol Neuroimmunol Neuroinflam. (2020) 7:636. 10.1212/NXI.0000000000000636 PubMed DOI PMC

Cree BA, Mares J, Hartung HP. Current therapeutic landscape in multiple sclerosis: an evolving treatment paradigm. Curr Opin Neurol. (2019) 32:365–77. 10.1097/WCO.0000000000000700 PubMed DOI

Sabathé C, Casey R, Vukusic S, Leray E, Mathey G, De Sèze J, et al. . Improving the decision to switch from first-to second-line therapy in multiple sclerosis: a dynamic scoring system. Multiple Scler J. (2023) 29:236–47. 10.1177/13524585221139156 PubMed DOI

Berger T, Adamczyk-Sowa M, Csépány T, Fazekas F, Fabjan TH, Horáková D, et al. . Factors influencing daily treatment choices in multiple sclerosis: practice guidelines, biomarkers and burden of disease. Ther Adv Neurol Disord. (2020) 13:1756286420975223. 10.1177/1756286420975223 PubMed DOI PMC

Toscano S, Chisari CG, Meli A, Finocchiaro C, Fermo SL, Zappia M, et al. . Pregnancy planning and management for women with multiple sclerosis: what has changed over the last 15 years? An Italian single-center experience. Multiple Scler Relat Disor. (2023) 104526. 10.1016/j.msard.2023.104526 PubMed DOI

Big Multiple Sclerosis Data network: an international registry research network