Literature DB >> 36038263

Updated Results of the COVID-19 in MS Global Data Sharing Initiative: Anti-CD20 and Other Risk Factors Associated With COVID-19 Severity.

Steve Simpson-Yap1, Ashkan Pirmani2, Tomas Kalincik2, Edward De Brouwer2, Lotte Geys2, Tina Parciak2, Anne Helme2, Nick Rijke2, Jan A Hillert2, Yves Moreau2, Gilles Edan2, Sifat Sharmin2, Tim Spelman2, Robert McBurney2, Hollie Schmidt2, Arnfin B Bergmann2, Stefan Braune2, Alexander Stahmann2, Rod M Middleton2, Amber Salter2, Bruce Bebo2, Anneke Van der Walt2, Helmut Butzkueven2, Serkan Ozakbas2, Cavit Boz2, Rana Karabudak2, Raed Alroughani2, Juan I Rojas2, Ingrid A van der Mei2, Guilherme Sciascia do Olival2, Melinda Magyari2, Ricardo N Alonso2, Richard S Nicholas2, Anibal S Chertcoff2, Ana Zabalza de Torres2, Georgina Arrambide2, Nupur Nag2, Annabel Descamps2, Lars Costers2, Ruth Dobson2, Aleisha Miller2, Paulo Rodrigues2, Vesna Prčkovska2, Giancarlo Comi2, Liesbet M Peeters2.   

Abstract

BACKGROUND AND OBJECTIVES: Certain demographic and clinical characteristics, including the use of some disease-modifying therapies (DMTs), are associated with severe acute respiratory syndrome coronavirus 2 infection severity in people with multiple sclerosis (MS). Comprehensive exploration of these relationships in large international samples is needed.
METHODS: Clinician-reported demographic/clinical data from 27 countries were aggregated into a data set of 5,648 patients with suspected/confirmed coronavirus disease 2019 (COVID-19). COVID-19 severity outcomes (hospitalization, admission to intensive care unit [ICU], requiring artificial ventilation, and death) were assessed using multilevel mixed-effects ordered probit and logistic regression, adjusted for age, sex, disability, and MS phenotype. DMTs were individually compared with glatiramer acetate, and anti-CD20 DMTs with pooled other DMTs and with natalizumab.
RESULTS: Of 5,648 patients, 922 (16.6%) with suspected and 4,646 (83.4%) with confirmed COVID-19 were included. Male sex, older age, progressive MS, and higher disability were associated with more severe COVID-19. Compared with glatiramer acetate, ocrelizumab and rituximab were associated with higher probabilities of hospitalization (4% [95% CI 1-7] and 7% [95% CI 4-11]), ICU/artificial ventilation (2% [95% CI 0-4] and 4% [95% CI 2-6]), and death (1% [95% CI 0-2] and 2% [95% CI 1-4]) (predicted marginal effects). Untreated patients had 5% (95% CI 2-8), 3% (95% CI 1-5), and 1% (95% CI 0-3) higher probabilities of the 3 respective levels of COVID-19 severity than glatiramer acetate. Compared with pooled other DMTs and with natalizumab, the associations of ocrelizumab and rituximab with COVID-19 severity were also more pronounced. All associations persisted/enhanced on restriction to confirmed COVID-19. DISCUSSION: Analyzing the largest international real-world data set of people with MS with suspected/confirmed COVID-19 confirms that the use of anti-CD20 medication (both ocrelizumab and rituximab), as well as male sex, older age, progressive MS, and higher disability are associated with more severe course of COVID-19.
Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.

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Year:  2022        PMID: 36038263      PMCID: PMC9423711          DOI: 10.1212/NXI.0000000000200021

Source DB:  PubMed          Journal:  Neurol Neuroimmunol Neuroinflamm        ISSN: 2332-7812


The ongoing coronavirus disease 2019 (COVID-19) pandemic has had significant effects on health and wellbeing worldwide. Beyond its general effects, however, there is interest in the effects on patient populations, including people with multiple sclerosis (MS). Several clinic-based and other studies have been undertaken to assess the epidemiology of COVID-19 severity among people with MS.[1-4] The Covisep clinical registry study in France studied 347 people with MS with suspected or confirmed COVID-19[1]; finding disease-modifying therapies (DMTs) with a higher infection risk were associated with more than 4 times greater risk of more severe COVID-19. Sormani and colleagues described the results of the national Musc-19 Italian registry study, including 593 suspected and 191 confirmed COVID-19[2]; finding anti-CD20 DMTs, ocrelizumab and rituximab, were associated with 2.4 and 2.7 times greater risk of more severe COVID-19, respectively, compared with the untreated and with dimethyl fumarate. These results were replicated in a pooled analysis comprising 1,066 Italian and 721 French patients with confirmed COVID-19, finding anti-CD20 DMT use was associated with 2.1 times greater risk of more severe COVID-19 than the untreated, although evaluating each DMT individually, the association of rituximab was twice as strong as ocrelizumab (OR 3.78 vs 1.79).[4] In the United States/Canada, Salter and colleagues conducted the large multicenter CoviMS study, comprising 281 suspected and 1,345 confirmed COVID-19,[3] evaluating DMTs compared with the untreated, and the authors found rituximab and ocrelizumab were associated with greater risk of hospitalization; however, only rituximab showed positive trends for intensive care unit (ICU) admission/artificial ventilation and death. Langer-Gould and colleagues used data from the Kaiser Permanente patient population to evaluate COVID-19 severity between 1,895 people with MS treated with rituximab and 4.8 million non-MS patients; finding rituximab-treated patients with MS was more likely to be hospitalized because of COVID-19, although none died.[5] Although there has been some variability in the comparators used, including DMTs with less infection risk,[1] dimethyl fumarate,[2] and no treatment,[2-4] broadly, these studies show a detrimental association of the anti-CD20 DMTs, ocrelizumab and rituximab. We have previously examined COVID-19 severity among 2,340 people with MS and suspected or confirmed COVID-19 up to October 2020; finding older age, progressive MS phenotype, and greater disability were each associated with more severe COVID-19, including hospitalization, admission to ICU, artificial ventilation, and death.[6] We also showed ocrelizumab and rituximab were associated with higher frequencies of hospitalization, admission to ICU, and need for artificial ventilation. In this full and final analysis data set, we applied an ordered probit regression methodology to an expanded cohort of people with MS followed until September 2021 to describe the associations of severity of COVID-19 with clinical and treatment-related factors, with a goal to confirm our previous findings[6] and to unify the analytical approach.

Methods

Study Design

This was a multicenter cross-sectional study; patients with suspected or confirmed COVID-19 were assessed for the characteristics of COVID-19 severity outcomes. Data were acquired through an international online central data-entry platform and 11 independent registries and cohorts from 27 countries, including Argentina (n = 173), Australia (n = 11), Azerbaijan (n = 2), Bahamas (n = 1), Belgium (n = 36), Brazil (n = 225), Bulgaria (n = 3), Chile (n = 15), Colombia (n = 14), Czech Republic (n = 14), Denmark (n = 157), Ecuador (n = 26), France (n = 2), Germany (n = 168), Honduras (n = 3), Italy (n = 30), Kuwait (n = 102), Mexico (n = 5), the Netherlands (n = 65), New Zealand (n = 1), Paraguay (n = 1), Romania (n = 3), Saudi Arabia (n = 6), Serbia (n = 3), Spain (n = 273), Sweden (n = 880), Turkey (n = 412), the United Kingdom (n = 26), and Canada/the United States (n = 2,911). Some of the constituent registries and cohorts included multiple countries, but the enumeration of these data sources is platform (n = 114), source 1 (n = 880), source 2 (n = 664), source 3 (n = 214), source 4 (n = 3), source 5 (n = 90), source 6 (n = 25), source 7 (n = 157), source 8 (n = 214), source 9 (n = 79), source 10 (n = 2,910), and source 11 (n = 218). Data were entered in 3 fashions: (1) direct entry to the central platform, (2) patient-level data-sharing through participating registries/cohorts which uploaded their COVID-19 core data set into the central data platform at interval, and (3) aggregated data-sharing through participating registries/cohorts as described previously.[6] Multidimensional contingency tables from the constituent data sources were merged, and from this, a combined anonymized data set was reconstructed. Data were entered for each given participant once, but information for that participant could be reentered, this then replacing the original record. Clinicians entered demographic, lifestyle, and MS-specific and COVID-19–specific clinical characteristics, as described previously.[7] In this article, only age, sex, MS phenotype, disability, DMT use, glucocorticoid use, smoking status, body mass index (BMI), comorbidities, COVID-19 status, hospitalization, ICU admission, artificial ventilation, and death are described. Study participation was restricted to patients with MS aged 18 years or older with suspected or confirmed COVID-19. Confirmed COVID-19 was based on a positive PCR test, while suspected COVID-19 was based on clinician judgement of the clinical presentation and its alignment with COVID-19.

Standard Protocol Approvals, Registrations, and Patient Consents

This study was approved by the ethical committee of Hasselt University (CME2020/025). Other ethics information from data custodians, MSBase data were provided with the consent of individual participants and principal investigators at each MSBase participating center. The GMSR was first approved by the ethics committee of the Julius-Maximilians-University of Würzburg (vote number 142/12). After switching to the web-based documentation system, further positive votes, e.g., by the ethics committee of the Thuringia state chamber of physicians, followed by several ethics' committees of different universities, were given, and all patients signed an informed consent. Research subject protection was sought from the Washington University in the St. Louis Institutional Review Board for housing COViMS Registry data, who determined it to be “not human subjects” research and therefore exempt from active IRB oversight at WUSTL and did not require patient consent. The patient data sent to analyses resulting in the study “Associations of DMT therapies with COVID-19 severity in multiple sclerosis” originated from a study approved by the ethics Committee of the Faculdade de Medicina de Botucatu, Universidade Estadual Paulista under internal review board number CAAE 31021220.2.0000.5411. All participants signed a written informed consent form before enrollment. The Cemcat cohort study was approved by the ethics committee of the Vall d'Hebron University Hospital (XMG-INT-2014-01), and all patients signed an informed consent.

Variables

Definitions for all terms were provided to data partners and were available on the MS Data Alliance platform: msdataalliance.com/wp-content/uploads/2020/04/Data-Dictionary-for-COVID-19-in-people-with-MS.docx. As described previously,[6] hospitalization was queried as Admission in hospital because of COVID-19 (suspicious) infection? ICU admission was queried as Stay in ICU because of COVID-19 (suspicious) infection? Requiring artificial ventilation was queried as Ventilation needed during hospital stay? Death due to COVID-19 was queried as Did the patient die because of the (suspected) COVID-19 infection? Clinicians made all judgements regardless of how data were entered. As described previously,[6] patient age was categorized into 3 groups: 18–49, 50–69, and ≥70 years. MS phenotype was grouped into relapsing-remitting MS (RRMS) and progressive MS (secondary progressive MS and primary progressive MS). Disability was assessed by the Expanded Disability Status Scale (EDSS)[8,9] and dichotomized into 0–6.0 and >6.0. Comorbidities were queried, including cardiovascular disease, hypertension, diabetes, chronic liver disease, kidney disease, other neurologic/neuromuscular disorder, lung disease, or malignant neoplasia. BMI was categorized as nonobese (BMI ≤30) and obese (BMI >30). Current smoker status was queried as yes or no. Current DMT use was queried, including alemtuzumab, cladribine, dimethyl fumarate, fingolimod, glatiramer acetate, interferons, natalizumab, ocrelizumab, rituximab, siponimod, teriflunomide, or another DMT, this latter queried as On another drug not listed. In addition, the use of glucocorticoids was queried; although dose and frequency were queried, this was insufficiently completed and so only dichotomous glucocorticoid use was evaluated. Data on DMT dose and duration were not queried.

Statistical Analysis

Mixed-effects ordered logistic regression was assessed, but models failed the proportional odds assumption. Accordingly, mixed-effects ordered probit regression, random effects grouped by data source, was used to evaluate associations with ordered COVID-19 severity, categorized as none, hospitalization, ICU admission/requiring artificial ventilation, and death. All models were adjusted for age, sex, MS phenotype, and disability. From these, the marginal effects of each covariate level relative to its reference were estimated at means of model covariates. In addition, associations with dichotomous hospitalization, ICU admission, artificial ventilation, and death outcomes were assessed using multilevel mixed-effects logistic regression, random effects grouped by data source, as univariable and adjusted for age, sex, MS phenotype, and disability. Adjustment for multiple comparisons was undertaken using the family-wise Holm step-down method such that within each hypothesis and within models 1 and 2, statistical tests were ranked by lowest p value and significance threshold evaluated relative to the number of statistical tests within that family. Associations reaching significance after this adjustment are annotated as such in tables. Subgroup analyses were also undertaken where data on comorbidities, BMI, and smoking were available, allowing additional adjustment for these covariates. Due to the way data were aggregated, these covariates could not be assessed in the ordered probit regression analyses. All analyses were complete-case. Individual DMT associations with outcomes were assessed relative to glatiramer acetate because it has little immunosuppressive activity that might affect infection risk and, thus, represents an ideal comparator. Next, ocrelizumab and rituximab, as well as the untreated, were evaluated relative to all other pooled DMTs. Afterward, ocrelizumab and rituximab were evaluated relative to natalizumab to account for a possibility of ascertainment bias due to treatment with high-efficacy DMT. In addition, with a goal to assess whether DMT associations were just a function of underlying COVID-19 severity risk predisposing characteristics, stratified analyses by age (≥70 vs <70 years), MS phenotype (progressive vs RRMS), and EDSS (>6 vs ≤6) were undertaken. These were assessed by including a product term between the interaction covariate and the primary predictor, the significance of this term denoting the significance of the intergroup difference. Intergroup differences were accounted for by mixed-effects regression. Leave-one-out analyses serially excluding each data source were also undertaken (data not shown). All statistical analyses were undertaken in STATA/SE 16.0 (StataCorp, College Station, TX).

Data Availability

Data used in this study are in the custody of the participating registries and databases. For further enquiries, those interested in access to the data liaise with the MS Data Alliance.

Results

The cohort comprised 5,568 participants with suspected or confirmed COVID-19, of whom 83.4% were confirmed COVID-19. In evaluating COVID-19 severity outcomes between data sources, those patients in the platform, source C-3, and source C-11 had higher rates of hospitalization, but source C-4 and source C-5 had lower hospitalization. ICU admission was more frequent among patients in the platform and did not occur in source C-4 and source C-6, but otherwise did not differ. Requiring artificial ventilation was more common among patients in the platform, source C-3, and source C-5, and less common in source C-4 and source C-7. Death was more common among patients in source C-7 but did not occur in sources C-4, C-5, C-6, C-8, and C-9. Cohort characteristics of the sample were typical for MS, being majority female (73.1%), predominantly younger than 50 years (66.3%), and largely of RRMS phenotype (84.3%) and EDSS <6 (81.8%, Table 1). The most commonly used DMTs were ocrelizumab (19.8%), rituximab (11.4%), and dimethyl fumarate (11.1%). In the subgroup of participants with data on these parameters, 2,479 of 4,890 (50.7%) were of MS duration >10 years, 1,932 of 4,347 (44.4%) had comorbidities, 1,089 of 2,998 (36.3%) were of obese BMI, 141 of 3,635 (3.9%) were taking glucocorticoid medication, and 1,209 of 5,568 (21.7%) were current smokers. Of the total sample, 14.6% were hospitalized, 3.7% admitted to ICU, 3.4% required artificial ventilation, and 1.6% died (Table 2). Similar proportions were seen on restriction to confirmed COVID-19.
Table 1

COVID-19 and Demographic Cohort Characteristics

Table 2

Clinical Cohort Characteristics

COVID-19 and Demographic Cohort Characteristics Clinical Cohort Characteristics

Characteristics of COVID-19 Severity According to MS Therapy

We first evaluated the demographic and clinical characteristics of COVID-19 severity as an ordered polychotomous term, ranging from no hospitalization, hospitalization, ICU admission/requiring artificial ventilation, and death. Evaluating the predicted probabilities of these outcomes by patient characteristics, female patients were less likely to have more severe COVID-19 (adjusted β [aβ] −0.21, 95% CI −0.31 to −0.12), while older age (>50–70 years: aβ 0.31, 95% CI 0.21–0.40; >70 years: aβ 0.56, 95% CI 0.30–0.81), progressive MS phenotype (aβ 0.22, 95% CI 0.08–0.35), and higher disability (aβ 0.69, 95% CI 0.56–0.81) were associated with more severe COVID-19 (Table 2), persisting on restriction to confirmed COVID-19 (eTable 1, links.lww.com/NXI/A739). Similar results were seen evaluating the 4 outcomes as separate dichotomous terms by multilevel mixed-effects logistic regression (eTables 2–5). In the analyses where data were available, glucocorticoids and comorbidities were associated with all 4 dichotomous outcomes, while higher BMI was associated with increased risks of hospitalization, ICU admission, and requiring artificial ventilation, and smoking was associated with increased risk of death (Tables 3 and 4). Demographic/Clinical Characteristics of COVID-19 Severity by Ordered Probit Regression, Suspected + Confirmed DMT Characteristics of COVID-19 Severity by Ordered Probit Regression, Suspected + Confirmed Evaluating individual DMTs relative to glatiramer acetate, the untreated were 5% (95% CI 2–8) more likely to be hospitalized, 3% (95% CI 1–5) more likely to require ICU admission/ventilation, and 1% (95% CI 0–3) more likely to die (Table 2). Patients on treatment with ocrelizumab and rituximab were 4% (95% CI 1–7) and 7% (95% CI 4–11) more likely to be hospitalized (Figure 1), 2% (95% CI 0–4) and 4% (95% CI 2–6) more likely to require ICU admission/artificial ventilation (Figure 2), and 1% (95% CI 0–2) and 2% (95% CI 1–4) more likely to die (Figure 3). Compared with pooled other DMTs combined, ocrelizumab and rituximab users were 5% (95% CI 3–7) and 8% (95% CI 6–11) more likely to admit to hospital, 3% (95% CI 1–4) and 5% (95% CI 3–6) more likely to require ICU admission/artificial ventilation, and 1% (95% CI 0–2) and 2% (95% CI 1–4) more likely to die. Compared with natalizumab, ocrelizumab and rituximab users were 7% (95% CI 4–10) and 11% (95% CI 8–15) more likely to admit to hospital, 4% (95% CI 2–6) and 6% (95% CI 3–9) more likely to require ICU admission/artificial ventilation, and 1% (95% CI 0–3) and 2% (95% CI 1–4) more likely to die. On restriction to confirmed COVID-19, the results were generally comparable, although probabilities for the anti-CD20 s were slightly enhanced (eTable 1, links.lww.com/NXI/A739). Similar results were seen evaluating the 4 outcomes as separate dichotomous terms by multilevel mixed-effects logistic regression (eTables 6–7).
Figure 1

Marginal Effects of Hospitalization vs None by DMT Type Relative to Glatiramer Acetate

Adjusted for age, sex, MS phenotype, and disability. Full lines include suspected + confirmed COVID-19, while dashed lines are confirmed COVID-19 only. COVID-19 = coronavirus disease 2019; DMT = disease-modifying therapy; MS = multiple sclerosis; * = p < 0.05; ** = p < 0.001.

Figure 2

Marginal Effects of ICU Admission/Artificial Ventilation vs None by DMT Type Relative to Glatiramer Acetate

Adjusted for age, sex, MS phenotype, and disability. Full lines include suspected + confirmed COVID-19, while dashed lines are confirmed COVID-19 only. COVID-19 = coronavirus disease 2019; DMT = disease-modifying therapy; ICU = intensive care unit; MS = multiple sclerosis; * = p < 0.05; ** = p < 0.001.

Figure 3

Marginal Effects of Death vs None by DMT Type Relative to Glatiramer Acetate

Adjusted for age, sex, MS phenotype, and disability. Full lines include suspected + confirmed COVID-19, while dashed lines are confirmed COVID-19 only. COVID-19 = coronavirus disease 2019; DMT = disease-modifying therapy; MS = multiple sclerosis; * = p < 0.05.

Marginal Effects of Hospitalization vs None by DMT Type Relative to Glatiramer Acetate

Adjusted for age, sex, MS phenotype, and disability. Full lines include suspected + confirmed COVID-19, while dashed lines are confirmed COVID-19 only. COVID-19 = coronavirus disease 2019; DMT = disease-modifying therapy; MS = multiple sclerosis; * = p < 0.05; ** = p < 0.001.

Marginal Effects of ICU Admission/Artificial Ventilation vs None by DMT Type Relative to Glatiramer Acetate

Adjusted for age, sex, MS phenotype, and disability. Full lines include suspected + confirmed COVID-19, while dashed lines are confirmed COVID-19 only. COVID-19 = coronavirus disease 2019; DMT = disease-modifying therapy; ICU = intensive care unit; MS = multiple sclerosis; * = p < 0.05; ** = p < 0.001.

Marginal Effects of Death vs None by DMT Type Relative to Glatiramer Acetate

Adjusted for age, sex, MS phenotype, and disability. Full lines include suspected + confirmed COVID-19, while dashed lines are confirmed COVID-19 only. COVID-19 = coronavirus disease 2019; DMT = disease-modifying therapy; MS = multiple sclerosis; * = p < 0.05. Adjustment for BMI in the subgroup where data were available found BMI to be a weak positive confounder (eTable 8, links.lww.com/NXI/A739).

Stratified Analyses by Age, MS Type, and Disability

With a goal to assess whether DMT associations with COVID-19 severity reflected underlying disease propensity, we next evaluated models of DMTs stratified by age (≥70 vs <70 years), MS phenotype (progressive vs RRMS), and EDSS (>6 vs ≤6). Among participants with suspected + confirmed and confirmed-only COVID-19, in the ordered probit regression analyses, there was no indication that the associations of anti-CD20 DMTs with the COVID-19 severity level were a function of underlying demographic/clinical risk profile (eTables 9 and 10, links.lww.com/NXI/A739), nor did associations with hospitalization, ICU admission, requiring artificial ventilation, and death either seem solely evident among persons in the lower risk group (<70 years) (eTables 11 and 12), RRMS phenotype (eTables 13 and 14), EDSS ≤6 (eTables 15 and 16) or did not statistically differ.

Discussion

Evaluating COVID-19 severity as a single ordered 4-level outcome upheld our previous findings[6] showing demographic and clinical characteristics, particularly DMT exposure, were associated with increased COVID-19 severity in people with MS. Regardless of the comparator, rituximab and ocrelizumab were associated with more severe COVID-19, although associations of rituximab were consistently of greater magnitudes. This is consistent with our previous comparison against dimethyl fumarate[6] and persists across both polychotomous and separate dichotomous analysis methods. Our results are consistent with both our and other groups' previously reported findings.[1-4,6] Indeed, despite a fairly heterogeneous set of comparators used across the studies, including glatiramer acetate/interferons,[1] dimethyl fumarate,[2,6] the untreated,[2-4] and glatiramer acetate, the anti-CD20 DMTs have shown a remarkable consistency in being associated with more severe COVID-19. Moreover, anti-CD20 DMTs associations with COVID-19 severity were not only seen among those of older age, progressive MS phenotype, and disability but were more pronounced in the low-risk groups, suggesting these associations were not merely reflective of underlying clinical predisposition. Thus, although these characteristics are factors to consider when describing the severity of COVID-19, the anti-CD20 DMTs, particularly rituximab, independently contribute to the risk of more severe COVID-19. Taken together, this internal and external consistency is strongly indicative of a greater risk of more severe COVID-19 course among patients treated with anti-CD20 DMTs. Our previous study evaluated each of the 4 severity outcomes as separate dichotomous variables.[6] This method fails to capture the interrelated nature of these outcome levels, with increasing severity necessarily a function of the preceding severity increments. Some of the previous studies have endeavored to reflect this in their methods but with some limitations, either having to consolidate outcome ICU and death or not capturing the ordered nature of their outcome variable. In this article, we have improved on the methods of previous studies, evaluating a 4-level ordered COVID-19 severity variable by statistical methods that capture this ordered nature. The ordered probit regression method estimates marginal probabilities, rather than odds ratios, and so precludes direct comparison of magnitudes with previous studies. It is necessary to evaluate the magnitudes in the context of their particular outcome. That is, differences in the probabilities of outcomes must be considered relative to the average predicted probabilities of each. Therefore, for example, the marginal probabilities for rituximab vs glatiramer acetate for hospitalization (7%), ICU admission/ventilation (4%), and death (2%) are not indicative of weaker effects on ICU/ventilation and death but rather should be considered relative to the total average probabilities of these outcomes of 13%, 5%, and 3%. In that context, the associations of rituximab with the more severe outcomes are actually stronger than those seen for hospitalization despite the smaller marginal probabilities; this in line with the results seen where individual dichotomous outcomes are assessed. This statistical methodology is superior to the separate dichotomous outcomes methods which have primarily been used in previous studies, making more efficient and comprehensive use of the ordered nature of the data. It is important that, however, regardless of the method applied, results are consistent in the deleterious nature of the demographic and characteristics of COVID-19 severity found, particularly anti-CD20 DMTs. Rituximab consistently showed stronger associations with the COVID-19 outcomes than ocrelizumab, in agreement with our previous study[6] and other studies.[2-4,10,11] As discussed previously,[6] the binding characteristics of rituximab differ from ocrelizumab, including a differing provenance and particularly a stronger affinity to CD20 at the epitope both DMTs bind.[12] In addition, although in our present analysis, ocrelizumab shows a positive trend with the need for artificial ventilation, rituximab shows consistent associations with COVID-19 outcomes, including death. Although it is possible that these differences could result from an unmeasured confounding, particularly here where our ability to control for covariates is limited to those in the questionnaire, the consistency of this difference in associations across cohorts and over time is intriguing. Therefore, relationships of the new anti-CD20 DMT, ofatumumab, which binds a different locus on the CD20 protein,[12] with COVID-19 severity are of interest for future research. It is interesting to compare the results of this work with the reports of anti–severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine response because studies have shown that people with MS on some DMTs have deficient serologic response to both the SARS-CoV-2 pathogen and vaccines, including the anti-CD20 DMTs and the S1PR modulators.[13-17] At the same time, others have evaluated post–vaccine-dose near-term reactions, finding reactions to be lower among those treated with S1PR modulators, whereas anti-CD20 DMTs were not associated with the vaccine reaction.[18] In our study, fingolimod was generally associated with less COVID-19 severity, although the other S1PR modulator, siponimod, showed no such inverse associations. Further investigation of the effect of DMTs on humoral and cellular immune response to the SARS-CoV-2 pathogen and vaccine and its protective role are needed to better understand these relationships and guide decision-making regarding DMTs and COVID-19, including vaccination. The untreated patients also showed associations with more severe COVID-19, especially in the ordered probit regression analyses of the polychotomous outcome. However, in the individual dichotomous outcome analyses, this association only remained consistent when compared with pooled other DMTs. These results are in agreement with other studies, including the Covisep study which found almost 3 times greater risk of more severe COVID-19 among the untreated vs treated,[1] and the Musc-19 study which found 50–66% lower risks of more severe COVID-19 in treated vs the untreated.[2] It is likely that these associations result from unmeasured confounding in a highly selected group of untreated patients with MS. Accordingly, although we did evaluate the untreated in comparison with glatiramer acetate and with the pooled other DMTs, we did not regard these as appropriate to compare other DMTs with in the fashion performed elsewhere.[2-4] This study's robustness and generalizability are strengthened by a particularly large global sample used to examine the severity of COVID-19 course in people with MS. This, in tandem with a comprehensive assessment of the most critical clinical and demographic characteristics relevant to COVID-19, gives us a powerful platform with which to examine the outcomes of COVID-19. In addition, our larger data set enabled us to examine DMT associations with COVID-19 severity relative to glatiramer acetate, rather than dimethyl fumarate.[6] As a non–immunosuppressive immunomodulator, glatiramer acetate can be considered a more neutral comparator in its effect on infection risk and severity than dimethyl fumarate. It should be noted that the untreated group is typically a highly selected group in regions with good access to DMTs. In addition, our use of multiple comparison adjustment by the Holm step-down method gives confidence to the veracity of the observed associations, most of which were robust to type I error. We have used 2 complementary statistical methods to assess relationships with COVID-19 severity, expressed as an ordered polychotomous outcome, as well as the series of dichotomous outcomes for hospitalization, ICU admission, requiring artificial ventilation, and death used in our previous analysis.[6] The use of the single ordered polychotomous term, which we evaluated by ordered probit regression, allowed us to estimate marginal effects of the studied covariates across all levels of COVID-19 severity simultaneously. The consistency between these methods gives confidence in the validity of these findings. On the other hand, the scope of the questionnaire used to collate the analyzed data is limited in comparison with clinic-based registries such as the Covisep or Musc-19 studies.[1,2,4] Our data set lacks some potentially relevant information, e.g., DMT dose or frequency, pre-COVID-19 MS treatment, other MS severity measures (relapse rate or MRI), or other risk factors beyond those queried. We did endeavor in this iteration of the study to query B-cell counts and duration on DMT since last DMT treatment. However, due to high data missingness, quantitative assessments of these variables were not feasible. Our method of data aggregation was heterogeneous, utilizing individual patient data from the platform and individual registries but also multidimensional contingency tables. It is this latter data source which thus limited some aspects of our model covariates to simplified forms, including simplified categorical information about MS phenotype, disability, age, and glucocorticoid treatment. This precluded our assessment of some potentially relevant characteristics—BMI, smoking, MS duration, and exposure to glucocorticoids in the ordered probit analyses. Owing to the anonymous nature of data collection, it is possible there may be some duplication of patient entries, both over time and between data sources. Finally, the data about the dates of hospital or ICU admission/discharge were insufficient to enable analyses of the outcomes as time-dependent variables. This is so far the largest study of COVID-19 severity outcomes in people with MS. It confirms that older age, higher disability, and progressive MS phenotype are associated with more severe course of COVID-19. Regarding DMTs, severe COVID-19 course is more frequent among patients treated with anti-CD20 DMTs, rituximab and ocrelizumab. These relationships are not merely a function of underlying clinical/demographic risk profile but indicate a deleterious effect of CD20 depletion. The COVID-19 risk should be considered in choosing the most appropriate DMT for people with MS.
Table 3

Demographic/Clinical Characteristics of COVID-19 Severity by Ordered Probit Regression, Suspected + Confirmed

Table 4

DMT Characteristics of COVID-19 Severity by Ordered Probit Regression, Suspected + Confirmed

  18 in total

1.  Author response to: Correspondence to humoral immune response to COVID-19 mRNA vaccine in patients with multiple sclerosis treated with high-efficacy disease-modifying therapies.

Authors:  Anat Achiron; Mathilda Mandel; Sapir Dreyer-Alster; Gil Harari; David Magalashvili; Polina Sonis; Mark Dolev; Shay Menascu; Shlomo Flechter; Rina Falb; Michael Gurevich
Journal:  Ther Adv Neurol Disord       Date:  2021-05-29       Impact factor: 6.570

Review 2.  B cell depletion in the treatment of multiple sclerosis.

Authors:  Kjell-Morten Myhr; Øivind Torkildsen; Andreas Lossius; Lars Bø; Trygve Holmøy
Journal:  Expert Opin Biol Ther       Date:  2019-01-23       Impact factor: 4.388

3.  Clinical Characteristics and Outcomes in Patients With Coronavirus Disease 2019 and Multiple Sclerosis.

Authors:  Céline Louapre; Nicolas Collongues; Bruno Stankoff; Claire Giannesini; Caroline Papeix; Caroline Bensa; Romain Deschamps; Alain Créange; Abir Wahab; Jean Pelletier; Olivier Heinzlef; Pierre Labauge; Laurent Guilloton; Guido Ahle; Mathilde Goudot; Kevin Bigaut; David-Axel Laplaud; Sandra Vukusic; Catherine Lubetzki; Jérôme De Sèze; Fayçal Derouiche; Ayman Tourbah; Guillaume Mathey; Marie Théaudin; François Sellal; Marie-Hélène Dugay; Helene Zéphir; Patrick Vermersch; Françoise Durand-Dubief; Romain Françoise; Géraldine Androdias-Condemine; Julie Pique; Pékès Codjia; Caroline Tilikete; Véronique Marcaud; Christine Lebrun-Frenay; Mikael Cohen; Aurelian Ungureanu; Elisabeth Maillart; Ysoline Beigneux; Thomas Roux; Jean-Christophe Corvol; Amandine Bordet; Yanica Mathieu; Frédérique Le Breton; Dalia Dimitri Boulos; Olivier Gout; Antoine Guéguen; Antoine Moulignier; Marine Boudot; Audrey Chardain; Sarah Coulette; Eric Manchon; Samar S. Ayache; Thibault Moreau; Pierre-Yves Garcia; Deiva Kumaran; Giovanni Castelnovo; Eric Thouvenot; Julien Poupart; Arnaud Kwiatkowski; Gilles Defer; Nathalie Derache; Pierre Branger; Damien Biotti; Jonathan Ciron; Christine Clerc; Mathieu Vaillant; Laurent Magy; Alexis Montcuquet; Philippe Kerschen; Marc Coustans; Anne-Marie Guennoc; Bruno Brochet; Jean-Christophe Ouallet; Aurélie Ruet; Cécile Dulau; Sandrine Wiertlewski; Eric Berger; Dan Buch; Bertrand Bourre; Maud Pallix-Guiot; Aude Maurousset; Bertrand Audoin; Audrey Rico; Adil Maarouf; Gilles Edan; Jérémie Papassin; Dorothée Videt
Journal:  JAMA Neurol       Date:  2020-09-01       Impact factor: 18.302

4.  Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS).

Authors:  J F Kurtzke
Journal:  Neurology       Date:  1983-11       Impact factor: 9.910

5.  COVID-19 in people with multiple sclerosis: A global data sharing initiative.

Authors:  Liesbet M Peeters; Tina Parciak; Clare Walton; Lotte Geys; Yves Moreau; Edward De Brouwer; Daniele Raimondi; Ashkan Pirmani; Tomas Kalincik; Gilles Edan; Steve Simpson-Yap; Luc De Raedt; Yann Dauxais; Clément Gautrais; Paulo R Rodrigues; Landon McKenna; Nikola Lazovski; Jan Hillert; Lars Forsberg; Tim Spelman; Robert McBurney; Hollie Schmidt; Arnfin Bergmann; Stefan Braune; Alexander Stahmann; Rodden Middleton; Amber Salter; Bruce F Bebo; Juan I Rojas; Anneke van der Walt; Helmut Butzkueven; Ingrid van der Mei; Rumen Ivanov; Kerstin Hellwig; Guilherme Sciascia do Olival; Jeffrey A Cohen; Wim Van Hecke; Ruth Dobson; Melinda Magyari; Doralina Guimarães Brum; Ricardo Alonso; Richard Nicholas; Johana Bauer; Anibal Chertcoff; Jérôme de Sèze; Céline Louapre; Giancarlo Comi; Nick Rijke
Journal:  Mult Scler       Date:  2020-07-14       Impact factor: 6.312

6.  COVID-19 in multiple sclerosis and neuromyelitis optica spectrum disorder patients in Latin America: COVID-19 in MS and NMOSD patients in LATAM.

Authors:  Ricardo Alonso; Berenice Silva; Orlando Garcea; Patricio E Correa Diaz; Giordani Rodrigues Dos Passos; Deyanira A Ramirez Navarro; Luis A Garcia Valle; Luis C Rodriguez Salinas; Laura Negrotto; Geraldine Luetic; Verónica A Tkachuk; Jimena Míguez; Fernando Hamuy Diaz de Bedoya; Lorna Galleguillos Goiry; Nicia E Ramírez Sánchez; Marcos Burgos; Judith Steinberg; Maria E Balbuena; Priscilla Monterrey Alvarez; Pablo A López; María C Ysrraelit; Rosalba A León; Aron Benzadon Cohen; Fernando Gracia; Omaira Molina; Magdalena Casas; Norma H Deri; Agustín Pappolla; Liliana Patrucco; Edgardo Cristiano; Dario Tavolini; Debora Nadur; Ana M Toral Granda; Roberto Weiser; Fátima Pagani Cassará; Vladimiro Sinay; Claudia Cárcamo Rodríguez; Luciana G Lazaro; María L Menichini; Raúl Piedrabuena; Geraldine Orozco Escobar; Adriana Carrá; Anibal Chertcoff; Biany Santos Pujols; Carlos Vrech; Adriana Tarulla; René Carvajal; Carolina Mainella; Jefferson Becker; Liesbet M Peeters; Clare Walton; Marina Alonso Serena; Sebastián Nuñez; Juan I Rojas
Journal:  Mult Scler Relat Disord       Date:  2021-03-07       Impact factor: 4.339

7.  Multiple sclerosis, rituximab, and COVID-19.

Authors:  Annette Langer-Gould; Jessica B Smith; Bonnie H Li
Journal:  Ann Clin Transl Neurol       Date:  2021-03-30       Impact factor: 4.511

8.  Outcomes and Risk Factors Associated With SARS-CoV-2 Infection in a North American Registry of Patients With Multiple Sclerosis.

Authors:  Amber Salter; Robert J Fox; Scott D Newsome; June Halper; David K B Li; Pamela Kanellis; Kathleen Costello; Bruce Bebo; Kottil Rammohan; Gary R Cutter; Anne H Cross
Journal:  JAMA Neurol       Date:  2021-06-01       Impact factor: 18.302

9.  Humoral- and T-Cell-Specific Immune Responses to SARS-CoV-2 mRNA Vaccination in Patients With MS Using Different Disease-Modifying Therapies.

Authors:  Carla Tortorella; Alessandra Aiello; Claudio Gasperini; Chiara Agrati; Concetta Castilletti; Serena Ruggieri; Silvia Meschi; Giulia Matusali; Francesca Colavita; Chiara Farroni; Gilda Cuzzi; Eleonora Cimini; Eleonora Tartaglia; Valentina Vanini; Luca Prosperini; Shalom Haggiag; Simona Galgani; Maria Esmeralda Quartuccio; Andrea Salmi; Federica Repele; Anna Maria Gerarda Altera; Flavia Cristofanelli; Alessandra D'Abramo; Nazario Bevilacqua; Angela Corpolongo; Vincenzo Puro; Francesco Vaia; Maria Rosaria Capobianchi; Giuseppe Ippolito; Emanuele Nicastri; Delia Goletti
Journal:  Neurology       Date:  2021-11-22       Impact factor: 11.800

10.  SARS-CoV-2 Infection in Multiple Sclerosis: Results of the Spanish Neurology Society Registry.

Authors:  Georgina Arrambide; Miguel Ángel Llaneza-González; Lucienne Costa-Frossard França; Virginia Meca-Lallana; Eva Fernández- Díaz; Irene Moreno-Torres; Jose Manuel García-Domínguez; Gloria Ortega-Suero; Lucía Ayuso-Peralta; Mayra Gómez-Moreno; Javier J Sotoca-Fernández; Ana Belén Caminero-Rodríguez; Luis A Rodríguez de Antonio; Marcial Corujo-Suárez; María A Otano-Martínez; Francisco Carlos Pérez-Miralles; Virginia Reyes-Garrido; Teresa Ayuso-Blanco; José Jesús Balseiro-Gómez; Mercedes Muñoz-Pasadas; Inmaculada Pérez-Molina; Carmen Arnal-García; Ángela Domingo-Santos; Cristina Guijarro-Castro; Cristina Íñiguez-Martínez; Nieves Téllez Lara; Fernando Castellanos-Pinedo; Tamara Castillo-Triviño; Debora María Cerdán-Santacruz; Ángel Pérez-Sempere; Berta Sebastián Torres; Amaya Álvarez de Arcaya; Eva Costa-Arpín; Eduardo Durán-Ferreras; Marta Fragoso-Martínez; Montserrat González-Platas; Lamberto Landete Pascual; Jorge Millán-Pascual; Celia Oreja-Guevara; José E Meca-Lallana
Journal:  Neurol Neuroimmunol Neuroinflamm       Date:  2021-06-24
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1.  Severity of COVID19 infection among patients with multiple sclerosis treated with interferon-β.

Authors:  Steve Simpson-Yap; Ashkan Pirmani; Edward De Brouwer; Liesbet M Peeters; Lotte Geys; Tina Parciak; Anne Helme; Jan Hillert; Yves Moreau; Gilles Edan; Tim Spelman; Sifat Sharmin; Robert McBurney; Hollie Schmidt; Arnfin Bergmann; Stefan Braune; Alexander Stahmann; Rodden Middleton; Amber Salter; Bruce Bebo; Anneke van der Walt; Helmut Butzkueven; Serkan Ozakbas; Rana Karabudak; Cavit Boz; Raed Alroughani; Juan I Rojas; Ingrid van der Mei; Guilherme Sciascia do Olival; Melinda Magyari; Ricardo Alonso; Richard Nicholas; Anibal Chertcoff; Ana Zabalza; Georgina Arrambide; Nupur Nag; Annabel Descamps; Lars Costers; Ruth Dobson; Aleisha Miller; Paulo Rodrigues; Vesna Prčkovska; Giancarlo Comi; Tomas Kalincik
Journal:  Mult Scler Relat Disord       Date:  2022-07-25       Impact factor: 4.808

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