
==== Front
J Neurol
J Neurol
Journal of Neurology
0340-5354
1432-1459
Springer Berlin Heidelberg Berlin/Heidelberg

38935148
12518
10.1007/s00415-024-12518-7
Original Communication
A multi-centre longitudinal study analysing multiple sclerosis disease-modifying therapy prescribing patterns during the COVID-19 pandemic
Lal Anoushka P. 12
Foong Yi Chao 1254
Sanfilippo Paul G. 1
Spelman Tim 1
Rath Louise 1
Levitz David 1
Fabis-Pedrini Marzena 34
Foschi Matteo 56
Habek Mario 78
Kalincik Tomas 910
Roos Izanne 9
Lechner-Scott Jeannette 11
John Nevin 1213
Soysal Aysun 14
D’Amico Emanuele 15
Gouider Riadh 1617
Mrabet Saloua 1617
Gross-Paju Katrin 18
Cárdenas-Robledo Simón 1920
Moghadasi Abdorreza Naser 21
Sa Maria Jose 22
Gray Orla 23
Oh Jiwon 24
Reddel Stephen 25
Ramanathan Sudarshini 26
Al-Harbi Talal 27
Altintas Ayse 28
Hardy Todd A. 25
Ozakbas Serkan 2930
Alroughani Raed 31
Kermode Allan G. 34
Surcinelli Andrea 5
Laureys Guy 32
Eichau Sara 33
Prat Alexandre 34
Girard Marc 34
Duquette Pierre 34
Hodgkinson Suzanne 35
Ramo-Tello Cristina 36
Maimone Davide 37
McCombe Pamela 3839
Spitaleri Daniele 40
Sanchez-Menoyo Jose Luis 41
Yetkin Mehmet Fatih 42
Baghbanian Seyed Mohammad 4344
Karabudak Rana 4546
Al-Asmi Abdullah 47
Jakob Gregor Brecl 4849
Khoury Samia J. 50
Etemadifar Masoud 51
van Pesch Vincent 52
Buzzard Katherine 53
Taylor Bruce 54
Butzkueven Helmut 12
http://orcid.org/0000-0002-4278-7003
Van der Walt Anneke anneke.vanderwalt@monash.edu

12
1 Department of Neuroscience, Central Clinical School, The Alfred, Melbourne, VIC Australia
2 https://ror.org/01wddqe20 grid.1623.6 0000 0004 0432 511X Department of Neurology, The Alfred Hospital, 55 Commercial Road, Melbourne, 3004 Australia
3 grid.1012.2 0000 0004 1936 7910 Perron Institute for Neurological and Translational Science, The University of Western Australia, Perth, Australia
4 https://ror.org/00r4sry34 grid.1025.6 0000 0004 0436 6763 Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, Perth, Australia
5 grid.415207.5 0000 0004 1760 3756 Department of Neuroscience, MS Center, Neurology Unit, S. Maria Delle Croci Hospital, AUSL Romagna, Ravenna, Italy
6 https://ror.org/01j9p1r26 grid.158820.6 0000 0004 1757 2611 Department of Biotechnological and Applied Clinical Sciences (DISCAB), University of L’Aquila, L’Aquila, Italy
7 https://ror.org/00r9vb833 grid.412688.1 0000 0004 0397 9648 Department of Neurology, University Hospital Center Zagreb, Zagreb, Croatia
8 https://ror.org/00mv6sv71 grid.4808.4 0000 0001 0657 4636 School of Medicine, University of Zagreb, Zagreb, Croatia
9 https://ror.org/005bvs909 grid.416153.4 0000 0004 0624 1200 Department of Neurology, Neuroimmunology Centre, Royal Melbourne Hospital, Melbourne, Australia
10 https://ror.org/01ej9dk98 grid.1008.9 0000 0001 2179 088X CORe, Department of Medicine, University of Melbourne, Melbourne, Australia
11 grid.266842.c 0000 0000 8831 109X Hunter Medical Research Institute, University Newcastle, Newcastle, Australia
12 https://ror.org/02bfwt286 grid.1002.3 0000 0004 1936 7857 Department of Medicine, School of Clinical Sciences, Monash University, Clayton, Australia
13 https://ror.org/02t1bej08 grid.419789.a 0000 0000 9295 3933 Department of Neurology, Monash Health, Clayton, Australia
14 Bakirkoy Education and Research Hospital for Psychiatric and Neurological Diseases, Istanbul, Turkey
15 https://ror.org/01xtv3204 grid.10796.39 0000 0001 2104 9995 Medical and Surgical Sciences, Universita Di Foggia, Foggia, Italy
16 Department of Neurology, LR 18SP03, Clinical Investigation Centre Neurosciences and Mental Health, Razi University Hospital, Tunis, Tunisia
17 grid.12574.35 0000000122959819 Faculty of Medicine of Tunis, University of Tunis El Manar, Tunis, Tunisia
18 grid.518553.f Multiple Sclerosis Centre, West-Tallinn Central Hospital, Tallinn, Estonia
19 https://ror.org/0544yj280 grid.511227.2 0000 0005 0181 2577 Department of Neurology, Centro de Esclerosis Múltiple (CEMHUN), Hospital Universitario Nacional de Colombia Bogota, Bogota, Colombia
20 https://ror.org/059yx9a68 grid.10689.36 0000 0004 9129 0751 Departamento de Medicina InternaFacultad de Medicina, Universidad Nacional de Colombia, Bogota, Colombia
21 grid.411705.6 0000 0001 0166 0922 Multiple Research Centre, Neuroscience Institute, Tehran University of Medical Science, Tehran, Iran
22 grid.414556.7 0000 0000 9375 4688 Department of Neurology, Centro Hospitalar Universitario de Sao Joao, Porto, Portugal
23 South Eastern HSC Trust, Belfast, UK
24 https://ror.org/04skqfp25 grid.415502.7 St. Michael’s Hospital, Toronto, Canada
25 https://ror.org/04b0n4406 grid.414685.a 0000 0004 0392 3935 Department of Neurology, Concord Repatriation General Hospital, Sydney, Australia
26 https://ror.org/04b0n4406 grid.414685.a 0000 0004 0392 3935 Translational Neuroimmunology Group, Kids Neuroscience Centre and Brain and Mind Centre, Concord Hospital, Sydney, Australia
27 https://ror.org/01m1gv240 grid.415280.a 0000 0004 0402 3867 Neurology Department, King Fahad Specialist Hospital-Dammam, Dammam, Saudi Arabia
28 grid.15876.3d 0000000106887552 Department of Neurology, School of Medicine and Koc University Research Center for Translational Medicine (KUTTAM), İstanbul, Turkey
29 https://ror.org/04hjr4202 grid.411796.c 0000 0001 0213 6380 Izmir University of Economics, Medical Point Hospital, Izmir, Turkey
30 Multiple Sclerosis Research Association, Izmir, Turkey
31 https://ror.org/04y2hdd14 grid.413513.1 Division of Neurology, Department of Medicine, Amiri Hospital, Sharq, Kuwait
32 grid.410566.0 0000 0004 0626 3303 Department of Neurology, University Hospital Ghent, Ghent, Belgium
33 https://ror.org/016p83279 grid.411375.5 0000 0004 1768 164X Department of Neurology, Hospital Universitario Virgen Macarena, Seville, Spain
34 grid.14848.31 0000 0001 2292 3357 CHUM and Universite de Montreal, Montreal, Canada
35 grid.1005.4 0000 0004 4902 0432 Immune Tolerance Laboratory Ingham Institute and Department of Medicine, UNSW, Sydney, Australia
36 grid.411438.b 0000 0004 1767 6330 Department of Neuroscience, Hospital Germans Trias I Pujol, Badalona, Spain
37 Centro Sclerosi Multipla, UOC Neurologia, Azienda Ospedaliera Per L’Emergenza Cannizzaro, Catania, Italy
38 https://ror.org/00rqy9422 grid.1003.2 0000 0000 9320 7537 University of Queensland, Brisbane, Australia
39 https://ror.org/05p52kj31 grid.416100.2 0000 0001 0688 4634 Royal Brisbane and Women’s Hospital, Brisbane, Australia
40 Azienda Ospedaliera Di Rilievo Nazionale San Giuseppe Moscati Avellino, Avellino, Italy
41 https://ror.org/02g7qcb42 grid.426049.d 0000 0004 1793 9479 Department of Neurology, Galdakao-Usansolo University Hospital, Osakidetza-Basque Health Service, Galdakao, Spain
42 https://ror.org/047g8vk19 grid.411739.9 0000 0001 2331 2603 Department of Neurology, Erciyes University, Kayseri, Turkey
43 https://ror.org/02wkcrp04 grid.411623.3 0000 0001 2227 0923 Neurology Department, Booalisina Hospital, Mazandaran University of Medical Sciences, Sari, Iran
44 https://ror.org/02wkcrp04 grid.411623.3 0000 0001 2227 0923 Faculty of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
45 https://ror.org/025mx2575 grid.32140.34 0000 0001 0744 4075 Department of Neurological Sciences, Faculty of Medicine, Yeditepe University, Istanbul, Turkey
46 Neuroimmunology Unit, Koşuyolu Hospitals, Istanbul, Turkey
47 grid.412846.d 0000 0001 0726 9430 College of Medicine & Health Sciences and Sultan Qaboos University Hospital, Sultan Qaboos University, Al-Khodh, Oman
48 https://ror.org/01nr6fy72 grid.29524.38 0000 0004 0571 7705 Department of Neurology, University Medical Centre Ljubljana, Ljubljana, Slovenia
49 https://ror.org/05njb9z20 grid.8954.0 0000 0001 0721 6013 Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
50 https://ror.org/00wmm6v75 grid.411654.3 0000 0004 0581 3406 Nehme and Therese Tohme Multiple Sclerosis Center, American University of Beirut Medical Center, Beirut, Lebanon
51 https://ror.org/04waqzz56 grid.411036.1 0000 0001 1498 685X Neurology, Dr. Etemadifar MS Institute, Isfahan University of Medical Sciences, Isfahan, Iran
52 https://ror.org/03s4khd80 grid.48769.34 0000 0004 0461 6320 Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
53 https://ror.org/0484pjq71 grid.414580.c 0000 0001 0459 2144 Department of Neurosciences, Box Hill Hospital, Box Hill, Australia
54 https://ror.org/031382m70 grid.416131.0 0000 0000 9575 7348 Royal Hobart Hospital, Hobart, Australia
27 6 2024
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© The Author(s) 2024
2024
https://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Background

The COVID-19 pandemic raised concern amongst clinicians that disease-modifying therapies (DMT), particularly anti-CD20 monoclonal antibodies (mAb) and fingolimod, could worsen COVID-19 in people with multiple sclerosis (pwMS). This study aimed to examine DMT prescribing trends pre- and post-pandemic onset.

Methods

A multi-centre longitudinal study with 8,771 participants from MSBase was conducted. Two time periods were defined: pre-pandemic (March 11 2018–March 10 2020) and post-pandemic onset (March 11 2020–11 March 2022). The association between time and prescribing trends was analysed using multivariable mixed-effects logistic regression. DMT initiation refers to first initiation of any DMT, whilst DMT switches indicate changing regimen within 6 months of last use.

Results

Post-pandemic onset, there was a significant increase in DMT initiation/switching to natalizumab and cladribine [(Natalizumab-initiation: OR 1.72, 95% CI 1.39–2.13; switching: OR 1.66, 95% CI 1.40–1.98), (Cladribine-initiation: OR 1.43, 95% CI 1.09–1.87; switching: OR 1.67, 95% CI 1.41–1.98)]. Anti-CD20mAb initiation/switching decreased in the year of the pandemic, but recovered in the second year, such that overall odds increased slightly post-pandemic (initiation: OR 1.26, 95% CI 1.06–1.49; Switching: OR 1.15, 95% CI 1.02–1.29. Initiation/switching of fingolimod, interferon-beta, and alemtuzumab significantly decreased [(Fingolimod-initiation: OR 0.55, 95% CI 0.41–0.73; switching: OR 0.49, 95% CI 0.41–0.58), (Interferon-gamma-initiation: OR 0.48, 95% CI 0.41–0.57; switching: OR 0.78, 95% CI 0.62–0.99), (Alemtuzumab-initiation: OR 0.27, 95% CI 0.15–0.48; switching: OR 0.27, 95% CI 0.17–0.44)].

Conclusions

Post-pandemic onset, clinicians preferentially prescribed natalizumab and cladribine over anti-CD20 mAbs and fingolimod, likely to preserve efficacy but reduce perceived immunosuppressive risks. This could have implications for disease progression in pwMS. Our findings highlight the significance of equitable DMT access globally, and the importance of evidence-based decision-making in global health challenges.

Keywords

Multiple sclerosis
COVID-19
Disease-modifying therapy
Anti-CD20 monoclonal antibodies
Cladribine
Natalizumab
Monash UniversityOpen Access funding enabled and organized by CAUL and its Member Institutions

issue-copyright-statement© Springer-Verlag GmbH Germany, part of Springer Nature 2024
==== Body
pmcBackground

The COVID-19 pandemic caused a multitude of unprecedented challenges in healthcare systems across the globe. Amongst the vulnerable populations affected by the COVID-19 pandemic were people with multiple sclerosis (pwMS). The overall COVID-19 mortality rate amongst patients with either suspected or confirmed MS was estimated to be around 3.0% [1].

In general, pwMS, especially those on disease-modifying therapies (DMT), are more susceptible to infectious diseases and are at a higher risk of infection-related hospitalisations compared to the general population [2]. Specifically for COVID-19, older age, African American ethnicity, and a higher level of disability all significantly increase the risk of experiencing severe infections amongst pwMS [1, 3, 4]. A crucial additional risk factor identified for severe COVID-19 infections in pwMS was the use of certain immunosuppressive DMTs. This posed a significant challenge in MS care for clinicians and led to various consensus agreements and recommendations being published [5–7]. General consensus suggested that lower efficacy DMTs such as interferons and glatiramer acetate were unlikely to increase the risk of severe COVID-19 infection and, potentially, that interferon DMTs may even be protective [8]. However, higher efficacy medications, particularly anti-CD20 monoclonal antibodies (such as ocrelizumab and rituximab) and S1P inhibitors (such as fingolimod), were considered to potentially increase the susceptibility to as well as the severity of COVID-19 for pwMS [9–12].

Current literature suggests that there was a shift in DMT prescribing patterns in pwMS during the COVID-19 pandemic. There was a significant reduction in the initiation of high-efficacy immunosuppressive DMTs, such as anti-CD20 monoclonal antibodies and S1P inhibitors [13–15]. Instead, there was an increased preference for lower efficacy, self-injectable DMTs such as interferon-beta and glatiramer acetate, which were perceived as safer options during the pandemic [13, 16]. Despite the overall reduction in high-efficacy DMT prescriptions, some clinicians continued or initiated these therapies with modifications, such as extended interval dosing, to reduce the risk of severe infections whilst maintaining disease control [17, 18].

These studies, however, were limited by sample size and country-based variation in practice, and the implications of these changes on disease activity in pwMS are yet to be fully elucidated [15]. In this study, we performed a longitudinal multi-centre study across over 25 countries using the MSBase Registry to evaluate prescription patterns of DMTs and to analyse the impact of the COVID-19 pandemic on the care of pwMS.

Methods

Participant selection and patient consent

We conducted a multi-centre, retrospective study using 8,771 participants from the MSBase Registry. All participants provided written informed consent to be a part of the study. Ethics approval for the MSBase registry was granted by the Alfred Health Human Research and Ethics Committee and the local ethics committees of all the participating centres that comprise the MSBase. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.

Study participants

The inclusion criteria for this study were: (1) 18 years of age or over; (2) definite diagnosis of MS according to the McDonald Criteria [21]; and (3) at least one visit recorded in the pre-pandemic or post-pandemic period AND at least one visit after 11 March 2022. Patients with incomplete demographic (sex, age) or clinic (disease duration, the date of starting and/or stopping DMTs, Expanded Disability Status Scale, EDSS, assessments and dates of relapses for the duration of the study) were excluded.

Two time periods were defined as: (1) pre-pandemic (March 11 2018 to March 10 2020) and (2) post-pandemic (March 11 2020, when the COVID-19 pandemic was announced by World Health Organisation, to 11 March 2022) [18].

Outcomes and definitions

The primary outcome was to analyse the prescribing patterns of high- and low-efficacy DMTs pre- and post-pandemic onset. We classified initiation and switching to DMT as follows: DMT initiation referred to the first prescription of any DMT. DMT switching referred to change in DMT regimen within 6 months of last DMT use.

High-medium efficacy DMTs (called high-efficacy from here on) were defined as ocrelizumab, rituximab, ofatumumab, cladribine, alemtuzumab, natalizumab, and fingolimod. Low-efficacy DMTs were defined as interferon-beta/alpha, glatiramer acetate, teriflunomide and dimethyl fumarate (DMF). To reduce groups for comparison, interferon-beta/alpha and glatiramer acetate were grouped together as “BRACE”, and rituximab, ocrelizumab and ofatumumab were grouped as “Anti-CD20 mAbs”.

Statistical analysis

The demographic information and the baseline characteristics were reported as number and percentage for discrete variables and as mean (standard deviation [SD]) or median (interquartile range [IQR]) for continuous variables, as appropriate and according to the data distribution.

Using a pre-post design, we applied generalised linear mixed models with a binomial link function and a random effect for each country to assess associations between DMT initiation or switching (outcomes) as a function of DMT class across pandemic periods (exposures). In the models, the random effect was country of residence, whilst fixed covariates were age, gender, MS phenotype, disease duration, EDSS, and relapse count in the previous 24 months. All statistical tests were two-sided with a statistical significance defined as p ≤ 0.05. Analyses were performed in R version.4.3.0. (R Foundation for Statistical Computing).

Results

Participant demographics

8,771 participants were selected for this study. There were 4,533 initiations and 5899 switches recorded in 5165 unique individuals. Note that this discrepancy in sample numbers arises from instances where some participants may have had an initiation of DMT followed by a subsequent switch, thus contributing to both counts. Table 1 outlines the participant demographics for total participants and participants where initiations and switches were recorded.Table 1 Participant demographics

Characteristic	Total n = 8771 (%)	Initiation n = 4533 (%)	Switching n = 5165 (%)	
Gender	
 F	6,222 (71%)	3,150 (69%)	3,747 (73%)	
 M	2,549 (29%)	1,383 (31%)	1,418 (27%)	
Age category (years)	
 0–20	326 (3.7%)	257 (5.7%)	147 (2.8%)	
 21–30	1,682 (19%)	1,130 (25%)	841 (16%)	
 31–40	2,556 (29%)	1,386 (31%)	1,455 (28%)	
 41–50	2,318 (26%)	1,011 (22%)	1,490 (29%)	
 51–60	1,392 (16%)	520 (11%)	944 (18%)	
 > 60	497 (5.7%)	229 (5.1%)	288 (5.6%)	
Country	
 Australia	2,512 (29%)	1,293 (29%)	1,414 (27%)	
 Turkey	1,991 (23%)	927 (20%)	1,346 (26%)	
 Italy	706 (8.0%)	442 (9.8%)	352 (6.8%)	
 Spain	590 (6.7%)	288 (6.4%)	364 (7.0%)	
 Kuwait	559 (6.4%)	353 (7.8%)	244 (4.7%)	
 Iran	429 (4.9%)	163 (3.6%)	294 (5.7%)	
 Croatia	309 (3.5%)	234 (5.2%)	121 (2.3%)	
 Belgium	267 (3.0%)	150 (3.3%)	161 (3.1%)	
 Tunisia	103 (1.2%)	74 (1.6%)	47 (0.9%)	
 Japan	94 (1.1%)	70 (1.5%)	43 (0.8%)	
 Netherlands	87 (1.0%)	37 (0.8%)	59 (1.1%)	
 Other*	497 (5.7%)	274 (6.0%)	273 (5.3%)	
MS course		1,293 (29%)		
 Relapsing remitting	7,610 (87%)	3,906 (86%)	4,570 (88%)	
 Secondary progressive	537 (6.1%)	113 (2.5%)	443 (8.6%)	
 Primary progressive	303 (3.5%)	253 (5.6%)	66 (1.3%)	
 Progressive relapsing	95 (1.1%)	60 (1.3%)	42 (0.8%)	
  Radiologically isolated syndrome	4 (< 0.1%)	3 (< 0.1%)	2 (< 0.1%)	
  Clinically isolated syndrome	222 (2.5%)	198 (4.4%)	42 (0.8%)	
EDSS	2.4 (1.9%)	2.0 (1.7%)	2.6 (2.0%)	
Relapse count (in previous 24 months)	
 0	4,708 (54%)	2,016 (44%)	3,005 (58%)	
 1	2,847 (32%)	1,790 (39%)	1,478 (29%)	
 2	918 (10%)	570 (13%)	498 (9.6%)	
 3	228 (2.6%)	126 (2.8%)	137 (2.7%)	
 4	46 (0.5%)	23 (0.5%)	28 (0.5%)	
 5	16 (0.2%)	7 (0.2%)	12 (0.2%)	
 6	3 (< 0.1%)	1 (< 0.1%)	2 (< 0.1%)	
 7	4 (< 0.1%)	-	4 (< 0.1%)	
 10	1 (< 0.1%)	-	1 (< 0.1%)	
Disease duration (years)	8.2 (8.3%)	4.4 (6.7%)	10.6 (8.3%)	
*See appendix for full list of countries

Comparison of high- and low-efficacy DMT prescription pre- and post-pandemic onset

There was an overall decrease in initiating and switching DMTs post-pandemic compared to pre-pandemic (Table 2). There was a significant increase in initiation of low-efficacy DMTs post-pandemic compared to pre-pandemic (54.1 to 59.6%) and a decrease in initiation of high-efficacy DMTs (45.9 to 40.4%). There was a significant increase in switching to low-efficacy DMTs post-pandemic (27.4 to 29%) and a decrease in switching to high-efficacy DMTs post-pandemic (72.6 to 71%).Table 2 Comparison of initiation and switches pre- and post-pandemic with low-efficacy and high-efficacy DMTs

	Initiation	Switching	
Overall
N = 4,533	Pre-pandemic
N = 2,443	Post-pandemic
N = 2,090	Overall
N = 5,899	Pre-pandemic
N = 3,306	Post-pandemic
N = 2,593	
Low-efficacy DMT	2,568 (56.6%)	1,322 (54.1%)	1,246 (59.6%)	1,657 (28.1%)	906 (27.4%)	751 (29%)	
High-efficacy DMT	1,965 (43.4%)	1,121 (45.9%)	844 (40.4%)	4,242 (71.9%)	2,400 (72.6%)	1,842 (71.0%)	

Analysis of DMT prescribing patterns pre- and post-pandemic onset

Post-pandemic onset, there was an increase in DMT initiation and switching to natalizumab (OR 1.72, 95% CI 1.39–2.13; OR 1.66, 95% CI 1.40–1.98) and cladribine (OR 1.43, 95% CI 1.09–1.87; OR 1.67, 95% CI 1.41–1.98) (Table 3). The initiation and switching to anti-CD20 monoclonal antibodies (mABs) decreased immediately following the onset of the COVID-19 pandemic in 2020; however, there was a steady increase towards the end of the pandemic, resulting in an overall rise in initiation and switching to anti-CD20 mABs (OR 1.26, 95% CI 1.06–1.49; OR 1.15, 95% CI 1.02–1.29) (Fig. 1). This increase was statistically significant but relatively smaller increase compared to natalizumab or cladribine.Table 3 Comparison of DMT initiation and switching from pre- to post-pandemic

	Initiation—OR (95% CI)	Switching—OR (95% CI)	
Anti-CD20 mAb	
 Ocrelizumab, ofatumumab and rituximab	1.26 (1.06–1.49)	1.15 (1.02–1.29)	
Oral immunomodulators	
 Dimethyl fumarate	1.76 (1.49–2.09)	0.85 (0.69–1.05)	
 Teriflunomide	0.77 (0.62–0.96)	0.80 (0.64–0.99)	
 Fingolimod	0.55 (0.41–0.73)	0.49 (0.41–0.58)	
Injectable immunomodulators	
 BRACE	0.78 (0.62–0.99)	0.78 (0.62–0.99)	
Integrin antagonist	
 Natalizumab	1.72 (1.39–2.13)	1.66 (1.40–1.98)	
Purine analogue	
 Cladribine	1.43 (1.09–1.87)	1.67 (1.41–1.98)	
Other	
 Alemtuzumab	0.27 (0.15–0.48)	0.27 (0.17–0.44)	
BRACE includes interferon-beta and glatiramer acetate, and anti-CD20 mAbs includes rituximab, ocrelizumab and ofatumumab. Data are displayed with Odds ratios and 95% CI

Fig. 1 Patterns of frequency of DMT initiation (a) and DMT switching (b) divided by year. Year 1 represents March 2018 to March 2019, Year 2 represents March 2019 to March 2020, Year 3 represents March 2021 to March 2022, and Year 4 represents March 2021 to March 2022

There was a decrease in initiating and switching patients to fingolimod (OR 0.55, 95% CI 0.41–0.73; OR 0.49, 95% CI 0.41–0.58), interferon-beta (OR 0.48, 95% CI 0.41–0.57; OR 0.78, 95% CI 0.62–0.99) and alemtuzumab (OR 0.27, 95% CI 0.15–0.48; OR 0.27, 95% CI 0.17–0.44) post-pandemic onset (Table 3). There was an increase in initiating (OR 1.76, 95% CI 1.49–2.09), but a decrease in switching (OR 0.85, 95% CI 0.69–1.05) patients to DMF.

Discussion

We performed a retrospective multi-site analysis of the prescribing patterns of DMTs in pwMS after the onset of the COVID-19 pandemic. We hypothesised there would be a significant decrease in DMT prescription, particularly anti-CD20 mAbs and fingolimod, given concerns regarding immunosuppression during the COVID-19 pandemic. Our results demonstrate a significant decrease in initiation and switching to fingolimod, alemtuzumab and interferon-beta post-pandemic onset, and a significant increase in initiation and switching patients to natalizumab and cladribine There was also a slight increase to anti-CD20 mAbs (though notably less than other higher-efficacy DMTs). This supports our hypothesis that concerns around more severe COVID-19 outcomes for pwMS on fingolimod and anti-CD20 mAbs influenced prescribing patterns during the pandemic. The increased usage of natalizumab and cladribine post-pandemic onset was likely driven by clinicians attempting to maintain prescribing high-efficacy treatments for patients but avoiding the usage of anti-CD20 mAb therapies due to perceived immunosuppression risks.

Our results show an overall decrease in the initiation and switching of DMTs during the COVID-19 pandemic. We specifically observed an approximate 5% decrease in initiation and 1% decrease in switching patients to high-efficacy DMTs post-pandemic onset, which was likely driven by clinicians choosing to reduce the prescribing of high-efficacy treatments based on concerns of worsening COVID-19 susceptibility and severity in patients. This is consistent with retrospective cohort studies, which have noted an overall decrease in DMT prescription or a change in dosing regimen, specifically in high-efficacy DMTs [13, 16]. This significant shift in underutilisation of higher efficacy DMTs and increased initiation and switching to lower efficacy DMTs has significant implications for relapse probability in pwMS at a population scale and could have a negative impact on overall health outcomes for pwMS [22].

Our results reveal that clinicians increased the prescription of cladribine and natalizumab during the COVID-19 pandemic, likely as they were considered safer, high-efficacy treatments for pwMS. Current evidence indicates that cladribine does not increase susceptibility to COVID-19 infections or exacerbate infection severity. Case studies have shown that pwMS treated with cladribine mount an appropriate immunological response and typically experience mild symptoms following COVID-19 infection [23–25]. This may be due to the immune reconstitution properties of cladribine, wherein it causes selectively transient reductions in CD19+ B and T cells, followed by reconstitution and restoration of the body’s adaptive immunity [26]. Natalizumab is not associated with worse COVID-19 clinical outcomes [27, 28]. Indeed, there is some postulation that natalizumab may be protective against COVID-19 infection by limiting viral entry into cells through the integrin blockade [29, 30].

Anti-CD20 mAb initiation and switching decreased in 2020. Still, it returned to pre-pandemic levels in 2021, such that overall, there was a slight increase in anti-CD20 mAb prescription (though less than other high-efficacy DMTs). These results are consistent with other studies that also observed a decrease in prescribing anti-CD20 mAbs during the COVID-19 pandemic [14]. Multiple cohort studies have indicated a significant relationship between anti-CD20 mAbs and increased severity of COVID-19 infection, thereby indicating the rapid response from clinicians to avoid prescribing, initiating or switching patients to these therapies was appropriate from a COVID-19 disease severity perspective [17, 18, 31, 32].

Concerns with its lymphopenic effects may have driven the decrease in initiating and switching to fingolimod as it is specifically associated with higher rates of Herpes Zoster virus infections compared to other DMTs [33, 34]. Whilst individual case studies have suggested a potential increase in the severity of COVID-19 infections with fingolimod use, larger cohort studies and current evidence indicate that fingolimod is not associated with worse COVID-19 outcomes or increased hospitalisation rates [32, 35–37]. The continued decrease in usage of fingolimod in 2021 implies that clinicians might be progressively opting for other high-efficacy DMTs over fingolimod.

The decrease in initiation and switching patients to alemtuzumab was likely due to published recommendations at the start of the pandemic, which suggested delaying lymphodepleting treatments such as alemtuzumab until the COVID-19 pandemic was more controlled [7]. In addition, prescription may have been influenced by limited access to inpatient healthcare services as various countries navigated the pandemic with various lockdown restrictions.

The increase in DMF initiation may have been based on recommendations from early guidelines that were published at the start of the pandemic, which encouraged the prescription of first-line DMTs such as teriflunomide and dimethyl fumarate [7]. The observed decrease in initiation and switching to interferon treatments post-pandemic onset may have been driven by concerns over immune system modulation and a preference for oral medications during the pandemic due to decreased access to healthcare facilities.

The limitations of our study include the fact that we did not record the reasons for clinicians’ choices of DMT initiation or switching. Patients’ co-morbidities and COVID-19 vaccine status were not recorded, which could have influenced DMT choice. Furthermore, concerns regarding DMTs affecting vaccine efficacy may also have influenced DMT therapy initiation choices [38, 39]. The temporal dynamics of the pandemic which varied substantially between countries, characterised by various waves and changing public health responses, alongside the evolution in the availability and types of COVID-19 vaccines, may have also influenced clinicians’ choices for DMT initiation and switching. In addiiton, individual access to DMTs, which varied greatly between countries and supply chain issues, may have influenced prescribing preferences.

Considered collectively, it is evident that during the COVID-19 pandemic, there was a nuanced balance between mitigating severe COVID-19 infections and ensuring continued use of high-efficacy DMTs to minimise MS disease activity. The approach to prescribing DMTs for pwMS demonstrated a significant evolution from initial, recommendation-driven practices to more robust, data-driven strategies. The initial hesitancy to prescribe certain high-efficacy DMTs, such as anti-CD20 monoclonal antibodies and fingolimod, was influenced by concerns regarding their impact on COVID-19 severity and vaccine efficacy. Over time, however, prescribing patterns adapted in response to accumulating clinical evidence, highlighting the resilience and adaptability of clinicians in managing treatment of pwMS under global health challenges.

Moreover, this shift highlights a crucial need for international equity in access to DMTs. Our findings suggest that the ability to select the most appropriate therapy based on up-to-date evidence was at times limited by availability and accessibility, affecting treatment choices globally. As such, ensuring equitable access to a range of DMTs is essential, not only for managing MS more effectively but also for preparing healthcare systems to respond more effectively to future global health emergencies. Our research highlights the necessity of evidence-based decision-making and collaborative efforts amongst researchers, clinicians, and healthcare systems to optimise care and protect the health outcomes of pwMS amid ongoing global health challenges.

Appendix 1

See Table Table 4 Participant demographics

Characteristic	Total n = 8771 (%)	Initiation n = 4533 (%)	Switching n = 5165 (%)	
Gender	
 F	6,222 (71%)	3,150 (69%)	3,747 (73%)	
 M	2,549 (29%)	1,383 (31%)	1,418 (27%)	
Age category (years)				
 0–20	326 (3.7%)	257 (5.7%)	147 (2.8%)	
 21–30	1,682 (19%)	1,130 (25%)	841 (16%)	
 31–40	2,556 (29%)	1,386 (31%)	1,455 (28%)	
 41–50	2,318 (26%)	1,011 (22%)	1,490 (29%)	
 51–60	1,392 (16%)	520 (11%)	944 (18%)	
 > 60	497 (5.7%)	229 (5.1%)	288 (5.6%)	
Country				
 AU	2,512 (29%)	1,293 (29%)	1,414 (27%)	
 AE	30 (0.3%)	15 (0.3%)	18 (0.3%)	
 BE	267 (3.0%)	150 (3.3%)	161 (3.1%)	
 CA	627 (7.1%)	228 (5.0%)	447 (8.7%)	
 CO	68 (0.8%)	63 (1.4%)	16 (0.3%)	
 EE	70 (0.8%)	34 (0.8%)	45 (0.9%)	
 ES	590 (6.7%)	288 (6.4%)	364 (7.0%)	
 GB	38 (0.4%)	13 (0.3%)	29 (0.6%)	
 GR	4 (< 0.1%)	1 (< 0.1%)	3 (< 0.1%)	
 HR	309 (3.5%)	234 (5.2%)	121 (2.3%)	
 HU	2 (< 0.1%)	2 (< 0.1%)	1 (< 0.1%)	
 IR	429 (4.9%)	163 (3.6%)	294 (5.7%)	
 IT	706 (8.0%)	442 (9.8%)	352 (6.8%)	
 JP	94 (1.1%)	70 (1.5%)	43 (0.8%)	
 KW	559 (6.4%)	353 (7.8%)	244 (4.7%)	
 LB	45 (0.5%)	20 (0.4%)	31 (0.6%)	
 NL	87 (1.0%)	37 (0.8%)	59 (1.1%)	
 NZ	28 (0.3%)	17 (0.4%)	14 (0.3%)	
 OM	53 (0.6%)	23 (0.5%)	37 (0.7%)	
 Other	107 (1.2%)	72 (1.6%)	40 (0.8%)	
 PL	1 (< 0.1%)	1 (< 0.1%)	0 (0%)	
 PT	50 (0.6%)	12 (0.3%)	39 (0.8%)	
 TN	103 (1.2%)	74 (1.6%)	47 (0.9%)	
 TR	1,991 (23%)	927 (20%)	1,346 (26%)	
 US	1 (< 0.1%)	1 (< 0.1%)	0 (0%)	
MS course		1,293 (29%)		
Relapsing remitting	7,610 (87%)	3,906 (86%)	4,570 (88%)	
Secondary progressive	537 (6.1%)	113 (2.5%)	443 (8.6%)	
Primary progressive	303 (3.5%)	253 (5.6%)	66 (1.3%)	
Progressive relapsing	95 (1.1%)	60 (1.3%)	42 (0.8%)	
 Radiologically isolated syndrome	4 (< 0.1%)	3 (< 0.1%)	2 (< 0.1%)	
 Clinically isolated syndrome	222 (2.5%)	198 (4.4%)	42 (0.8%)	
EDSS	2.37 (1.88)	1.99 (1.67)	2.64 (1.96)	
Relapse count (in previous 24 months)				
 0	4,708 (54%)	2,016 (44%)	3,005 (58%)	
 1	2,847 (32%)	1,790 (39%)	1,478 (29%)	
 2	918 (10%)	570 (13%)	498 (9.6%)	
 3	228 (2.6%)	126 (2.8%)	137 (2.7%)	
 4	46 (0.5%)	23 (0.5%)	28 (0.5%)	
 5	16 (0.2%)	7 (0.2%)	12 (0.2%)	
 6	3 (< 0.1%)	1 (< 0.1%)	2 (< 0.1%)	
 7	4 (< 0.1%)	–	4 (< 0.1%)	
 10	1 (< 0.1%)	–	1 (< 0.1%)	
Disease duration (years)	8.20 (8.31)	4.44 (6.69)	10.56 (8.34)	

4.

Abbreviations

MS Multiple sclerosis

pwMS People with multiple sclerosis

DMT Disease-modifying therapy

mAb Monoclonal antibodies

DMF Dimethyl fumarate

RAT Rapid-antigen testing

PCR Polymerase chain reaction

EDSS Expanded Disability Status Scale

Funding

Open Access funding enabled and organized by CAUL and its Member Institutions.

Declarations

Conflicts of interest

Yi Chao Foong: reports a relationship with Biogen that includes: travel reimbursement. Tim Spelman: received compensation for serving on scientific advisory board for Biogen and speaker honoraria from Novartis. Marzena Fabis-Pedrini: received travel compensation from Merck. Matteo Foschi: received travel and meeting attendance support from Novartis, Biogen, Roche, Sanofi-Genzyme, and Merck. Mario Habek: participated as a clinical investigator and/or received consultation and/or speaker fees from Biogen, Sanofi-Genzyme, Merck, Novartis, Pliva/Teva, Roche, Zentiva, Astra-Zeneca, TG Pharmaceuticals, and CNSystems. Tomas Kalincik: served on scientific advisory boards for the MS International Federation and the World Health Organization, BMS, Roche, Janssen, Sanofi-Genzyme, Novartis, Merck, and Biogen. He served on the steering committee for the Brain Atrophy Initiative by Sanofi-Genzyme, received conference travel support and/or speaker honoraria from WebMD Global, Eisai, Novartis, Biogen, Roche, Sanofi-Genzyme, Teva, BioCSL, and Merck, and received research or educational event support from Biogen, Novartis, Genzyme, Roche, Celgene, and Merck. Izanne Roos: has served on scientific advisory boards and received conference travel support and/or speaker honoraria from Roche, Novartis, Merck, and Biogen. Izanne Roos is supported by MS Australia and the Trish Multiple Sclerosis Research Foundation. Anneke van der Walt: served on advisory boards and receives unrestricted research grants from Novartis, Biogen, Merck, and Roche. She has received speaker’s honoraria and travel support from Novartis, Roche, and Merck. She receives grant support from the National Health and Medical Research Council of Australia and MS Research Australia. Helmut Butzkueven: received institutional (Monash University) funding from Biogen, F. Hoffmann-La Roche Ltd, Merck, Alexion, CSL, and Novartis; has carried out contracted research for Novartis, Merck, F. Hoffmann-La Roche Ltd, and Biogen; has taken part in speakers’ bureaus for Biogen, Genzyme, UCB, Novartis, F. Hoffmann-La Roche Ltd, and Merck; has received personal compensation from the Oxford Health Policy Forum for the Brain Health Steering Committee. Jeannette Lechner-Scott: received travel compensation from Novartis, Biogen, Roche, and Merck. Her institution receives honoraria for talks and advisory board commitments as well as research grants from Biogen, Merck, Roche, TEVA, and Novartis. Nevin John: is a PI on commercial MS studies sponsored by Novartis, Roche, Biogen, and Sanofi. He has received speaker’s honoraria from Merck and conference travel and registration reimbursement from Novartis. “Emanuele D'amico”: has received speaker honoraria and consultant fees from Biogen-Idec, Novartis, Merck, Janssen, Bristol-Myers, Bayer, Sanofi-Genzyme, and Roche. Riadh Gouider: has received research grant and/or advisory board honoraria from Biogen, Hikma, Merck, Roche, and Sanofi. He has no conflict of interest related to this study. Saloua Mrabet: has received a MENACTRIMS clinical fellowship grant (2020). Katrin Gross-Paju: received honoraria as a consultant on scientific advisory boards for Biogen, Roche, and Novartis; has received travel grants from Biogen, Roche, and Novartis; and has participated in clinical trials by Biogen, Merck, Sanofi, Roche, and Novartis. Simón Cárdenas-Robledo: has received travel expenses for scientific meetings from Biopas, Roche, Merck, and Genzyme; compensation for consulting services or participation on advisory boards from Merck, Biogen-Idec, Sanofi, and Novartis; lecture fees from Biopas, Novartis, Merck, Sanofi, Janssen, and Biogen-Idec; and research support from Biogen-Idec and Novartis. He is a subject editor on Multiple Sclerosis for Acta Neurológica Colombiana and a member of the editorial board of Frontiers of Neurology. Abdorreza Naser Moghadasi: has served on scientific advisory boards and received conference travel support and/or speaker honoraria from Roche, Novartis, Genzyme, Merck, and Biogen. Maria Jose Sa: received consulting fees, speaker honoraria, and/or travel expenses for scientific meetings from Alexion, Bayer Healthcare, Biogen, Bristol Myers Squibb, Celgene, Janssen, Merck-Serono, Novartis, Roche, Sanofi, and Teva. Orla Gray: received honoraria as a consultant on scientific advisory boards for Genzyme, Biogen, Merck, Roche, and Novartis; has received travel grants from Biogen, Merck, Roche, and Novartis; has participated in clinical trials by Biogen and Merck. Her institution has received research grant support from Biogen. Jiwon Oh: has received research funding from the MS Society of Canada, National MS Society, Brain Canada, Biogen, Roche, and EMD Serono (an affiliate of Merck KGaA); and personal compensation for consulting or speaking from Alexion, Biogen, Celgene (BMS), EMD Serono (an affiliate of Merck KGaA), Novartis, Roche, and Sanofi-Genzyme. Sudarshini Ramanathan: has received research funding from the National Health and Medical Research Council (NHMRC, Australia), the Petre Foundation, the Brain Foundation, the Royal Australasian College of Physicians, and the University of Sydney. She is supported by an NHMRC Investigator Grant (GNT2008339). She serves as a consultant on the International Steering Committee for a clinical trial led by UCB (NCT05063162). She is on the advisory board for educational activities led by Limbic Neurology. She has been an invited speaker for educational/research sessions coordinated by Biogen, Alexion, Novartis, Excemed, and Limbic Neurology. She is on the medical advisory board (non-remunerated positions) of The MOG Project and the Sumaira Foundation. Ayse Altintas: received speaker honoraria from Novartis and Alexion. Todd A. Hardy: received speaker honoraria/conference travel support or served on advisory boards for Bayer Schering, Biogen, Merck, Novartis, Roche, Sanofi-Genzyme, Bristol Myers Squibb, and Teva. Raed Alroughani: received honoraria as a speaker and for serving on scientific advisory boards from Bayer, Biogen, GSK, Merck, Novartis, Roche, and Sanofi-Genzyme. Allan G Kermode: received speaker honoraria and scientific advisory board fees from Bayer, BioCSL, Biogen, Genzyme, Innate Immunotherapeutics, Merck, Novartis, Sanofi, Sanofi-Aventis, and Teva. Andrea Surcinelli: received travel and meeting attendance support from Novartis, Biogen, Roche, Merck, Bristol, Sanofi-Genzyme, Almirall, and Piam. Guy Laureys: received travel and/or consultancy compensation from Sanofi-Genzyme, Roche, Teva, Merck, Novartis, Celgene, and Biogen. Sara Eichau: has received speaker honoraria and consultant fees from Biogen-Idec, Novartis, Merck, Janssen, Bristol-Myers, Bayer, Sanofi-Genzyme, Roche, and Teva. Pierre Duquette: served on editorial boards and has been supported to attend meetings by EMD, Biogen, Novartis, Genzyme, and TEVA Neuroscience. He holds grants from the CIHR and the MS Society of Canada and has received funding for investigator-initiated trials from Biogen, Novartis, and Genzyme. Suzanne Hodgkinson: has received consulting fees and speaker honoraria from Biogen, Novartis, Roche, and Merck, and has received grants for her institution from Biogen, Merck, Novartis, and Roche. Cristina Ramo-Tello: has received consulting fees, speaker honoraria, support for attending meetings and/or travel, participation on advisory boards, and research grants for her institution from Biogen, Novartis, Sanofi, Bristol, Roche, Almirall, Janssen, Sandoz, and Merck. Davide Maimone: received speaker honoraria for the advisory board and travel grants from Alexion, Almirall, Bayer, Biogen, Bristol Myers Squibb, Merck, Novartis, Roche, Sanofi-Genzyme, and Teva. Pamela McCombe: received speakers fees and travel grants from Novartis, Biogen, T’évalua, and Sanofi. Daniele Spitaleri: received honoraria as a consultant on scientific advisory boards by Bayer-Schering, Novartis, and Sanofi-Aventis, and compensation for travel from Novartis, Biogen, Sanofi-Aventis, Teva, and Merck. Jose Luis Sanchez-Menoyo: accepted travel compensation from Novartis, Merck, and Biogen; speaking honoraria from Biogen, Novartis, Sanofi, Merck, Almirall, Bayer, and Teva; and has participated in clinical trials by Biogen, Merck, and Roche. Seyed Mohammad Baghbanian: has served on scientific advisory boards and has received conference travel support and/or speaker honoraria from several pharmaceutical companies, including Roche, Novartis, Merck, Cinnagen, Nanoalvand, and Biogen. Rana Karabudak: received consulting fees, payment, or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events; support for attending meetings and/or travel; and participation on a data safety monitoring board or advisory board from Gen Turkey. Abdullah Al-Asmi: received personal compensation for serving as a scientific advisor or speaker/moderator for Novartis, Biogen, Roche, Sanofi-Genzyme, and Merck. Gregor Brecl Jakob: participated as a clinical investigator and/or received consultation and/or speaker fees from Amgen, Astra-Zeneca, Biogen, Janssen, Lek, Merck, Novartis, Pliva/Teva, Roche, Sanofi-Genzyme, and Swixx. Samia J. Khoury: received compensation for scientific advisory board activity from Merck and Roche, and received compensation for serving on the IDMC for Biogen. Vincent van Pesch: received travel grants from Merck Healthcare KGaA (Darmstadt, Germany), Biogen, Sanofi, Bristol Meyer Squibb, Almirall, and Roche. His institution has received research grants and consultancy fees from Roche, Biogen, Sanofi, Merck Healthcare KGaA (Darmstadt, Germany), Bristol Meyer Squibb, Janssen, Almirall, Novartis Pharma, and Alexion. Helmut Butzkueven: received institutional (Monash University) funding from Biogen, F. Hoffmann-La Roche Ltd, Merck, Alexion, CSL, and Novartis; has carried out contracted research for Novartis, Merck, F. Hoffmann-La Roche Ltd and Biogen; has taken part in speakers’ bureaus for Biogen, Genzyme, UCB, Novartis, F. Hoffmann-La Roche Ltd and Merck; has received personal compensation from Oxford Health Policy Forum for the Brain Health Steering Committee. Anneke van der Walt: served on advisory boards and receives unrestricted research grants from Novartis, Biogen, Merck and Roche She has received speaker’s honoraria and travel support from Novartis, Roche, and Merck. She receives grant support from the National Health and Medical Research Council of Australia and MS Research Australia. The remaining authors have nothing to declare.

Anoushka P. Lal and Yi Chao Foong contributed equally to this work.
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