# Factors associated with severe COVID-19 in people with idiopathic inflammatory myopathy: results from the COVID-19 Global Rheumatology Alliance physician-reported registry

Su-Ann Yeoh, Milena Gianfrancesco, Saskia Lawson-Tovey, Kimme L Hyrich, Anja Strangfeld, Laure Gossec, Loreto Carmona, Elsa F Mateus, Martin Schäfer, Christophe Richez, et al.

► To cite this version:

Su-Ann Yeoh, Milena Gianfrancesco, Saskia Lawson-Tovey, Kimme L Hyrich, Anja Strangfeld, et al. Factors associated with severe COVID-19 in people with idiopathic inflammatory myopathy: results from the COVID-19 Global Rheumatology Alliance physician-reported registry. RMD Open, 2022, 8 (2), pp.e002508. 10.1136/rmdopen-2022-002508. hal-03957941

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ORIGINAL RESEARCH

# Factors associated with severe COVID-19 in people with idiopathic inflammatory myopathy: results from the COVID-19 Global Rheumatology Alliance physician-reported registry

Su-Ann Yeoh ID,¹,² Milena Gianfrancesco,³ Saskia Lawson-Tovey ID,⁴,⁵

Kimme L Hyrich,⁵,⁶ Anja Strangfeld ID,⁷ Laure Gossec ID,⁸,⁹

Loreto Carmona ID,¹⁰ Elsa F Mateus,¹¹ Martin Schäfer ID,⁷

Christophe Richez ID,¹²,¹³ Eric Hachulla ID,¹⁴,¹⁵ Marie Holmqvist ID,¹⁶

Carlo Alberto Scirè ID,¹⁷ Hanns-Martin Lorenz,¹⁸ Reinhard E Voll,¹⁹

Rebecca Hasseli ID,²⁰ Arundathi Jayatilleke,²¹ Tiffany Y-T Hsu ID,²²

Kristin M D'Silva,²³ Victor R Pimentel-Quiroz ID,²⁴,²⁵

Monica Vasquez del Mercado,²⁶ Samuel Katsuyuki Shinjo,²⁷

Edgard Torres dos Reis Neto,²⁸ Laurindo Ferreira da Rocha Junior,²⁹

Ana Carolina de Oliveira e Silva Montandon,³⁰ Guillermo J Pons-Estel,³¹

Sofía Ornella,³² Maria Eugenia D'Angelo Exeni,³³ Edson Velozo,³⁴ Paula Jordan,³⁵

Emily Sirotich ID,³⁶,³⁷ Jonathan S Hausmann ID,³⁸,³⁹ Jean W Liew,⁴⁰

Lindsay Jacobsohn,³ Monique Gore-Massy,⁴¹ Paul Sufka,⁴² Rebecca Grainger,⁴³

Suleman Bhana,⁴⁴ Zachary Wallace,²³,⁴⁵ Philip C Robinson ID,⁴⁶,⁴⁷

Jinoos Yazdany,³ Pedro M Machado ID,¹,⁴⁸,⁴⁹,⁵⁰ On behalf of the COVID-19 Global Rheumatology Alliance

**To cite:** Yeoh S-A, Gianfrancesco M, Lawson-Tovey S, et al. Factors associated with severe COVID-19 in people with idiopathic inflammatory myopathy: results from the COVID-19 Global Rheumatology Alliance physician-reported registry. *RMD Open* 2022;8:e002508. doi:10.1136/rmdopen-2022-002508

► Additional supplemental material is published online only. To view, please visit the journal online (http://dx.doi.org/10.1136/rmdopen-2022-002508).

Received 10 June 2022
Accepted 29 August 2022

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© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

For numbered affiliations see end of article.

**Correspondence to**
Dr Pedro M Machado;
p.machado@ucl.ac.uk

## ABSTRACT

**Objectives** To investigate factors associated with severe COVID-19 in people with idiopathic inflammatory myopathy (IIM).

**Methods** Demographic data, clinical characteristics and COVID-19 outcome severity of adults with IIM were obtained from the COVID-19 Global Rheumatology Alliance physician-reported registry. A 3-point ordinal COVID-19 severity scale was defined: (1) no hospitalisation, (2) hospitalisation (and no death) and (3) death. ORs were estimated using multivariable ordinal logistic regression. Sensitivity analyses were performed using a 4-point ordinal scale: (1) no hospitalisation, (2) hospitalisation with no oxygen (and no death), (3) hospitalisation with oxygen/ventilation (and no death) and (4) death.

**Results** Of 348 patients, 48% were not hospitalised, 39% were hospitalised (and did not die) and 13% died. Older age (OR=1.59/decade, 95% CI 1.31 to 1.91), high disease activity (OR=3.50, 95% CI 1.25 to 9.83; vs remission), ≥2 comorbidities (OR=2.63, 95% CI 1.39 to 4.98; vs none), prednisolone-equivalent dose >7.5 mg/day (OR=2.40, 95% CI 1.09 to 5.28; vs no intake) and exposure to rituximab (OR=2.71, 95% CI 1.28 to 5.72; vs conventional synthetic disease-modifying antirheumatic drugs only) were independently associated with severe COVID-19. In addition to these variables, in the sensitivity

## WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT?

⇒ There is a paucity of data about the factors associated with a severe outcome of COVID-19 for people with idiopathic inflammatory myopathy (IIM).

## WHAT DOES THIS STUDY ADD?

⇒ This is the first international data set of people with IIM with COVID-19.

⇒ Older age, male sex, higher comorbidity burden, high disease activity, prednisolone-equivalent glucocorticoid dose >7.5 mg/day and exposure to rituximab were factors associated with severe COVID-19.

## HOW MIGHT THIS IMPACT ON CLINICAL PRACTICE OR FUTURE DEVELOPMENTS?

⇒ The findings from this study will enable risk stratification for patients with IIM.

⇒ These findings will inform the development of tailored management strategies and evidence-based recommendations for patients with IIM.

analyses, male sex (OR range: 1.65–1.83; vs female) was also significantly associated with severe outcomes, while COVID-19 diagnosis after 1 October 2020 (OR range:
<figure><img src="image_1.png" /></figure>

0.51–0.59; vs on/before 15 June 2020) was significantly associated with less severe outcomes, but these associations were not significant in the main model (OR=1.57, 95% CI 0.95 to 2.59; and OR=0.61, 95% CI 0.37 to 1.00; respectively).

**Conclusions** This is the first large registry data on outcomes of COVID-19 in people with IIM. Older age, male sex, higher comorbidity burden, high disease activity, prednisolone-equivalent dose >7.5 mg/day and rituximab exposure were associated with severe COVID-19. These findings will enable risk stratification and inform management decisions for patients with IIM.

## INTRODUCTION

Idiopathic inflammatory myopathies (IIMs) are a group of rare inflammatory muscle diseases, including dermatomyositis, polymyositis, anti-synthetase syndrome, immune-mediated necrotising myopathies and inclusion body myositis. People with IIM have been included in reports on patients with rheumatic diseases infected with SARS-CoV-2,¹⁻⁶ but there are little granular data in the literature specifically about outcomes for people with IIM with SARS-CoV-2 infection, probably due to its low prevalence. People with IIM may be at an increased risk of poor COVID-19 outcomes due to being treated with immunosuppressives, especially rituximab and glucocorticoids, having IIM-associated features such as interstitial lung disease, and the increased incidence of IIM as age increases.⁷

Our aim was to investigate factors associated with severe COVID-19 in people with IIM.

## METHODS

### Data source

Data were obtained from the collaborative COVID-19 Global Rheumatology Alliance and European Alliance of Associations for Rheumatology (EULAR) registry, an observational, voluntary, physician-reported database containing anonymous data on patients with a pre-existing rheumatic condition and a confirmed/presumptive COVID-19 diagnosis.⁸⁹

Patients with a physician-reported diagnosis of IIM, diagnosed with COVID-19 between 5 March 2020 and 27 August 2021, were included in the analyses. The database hosts, University of California San Francisco (USA) and University of Manchester (UK), checked the data to ensure no duplicates in the data entries.

### Treatment prior to COVID-19 infection

Data on exposure to antirheumatic therapies for IIM at the time of COVID-19 infection were collected: conventional synthetic disease-modifying antirheumatic drugs (csDMARDs—hydroxychloroquine, leflunomide, methotrexate, sulfasalazine), immunosuppressive drugs (azathioprine, cyclophosphamide, ciclosporin, mycophenolate mofetil/mycophenolic acid, tacrolimus), biological DMARDs (bDMARDs—abatacept, anakinra, canakinumab, tocilizumab, sarilumab, ixekizumab, secukinumab, adalimumab, certolizumab, etanercept,

golimumab, infliximab, rituximab), targeted synthetic DMARDs (Janus kinase inhibitors (JAKi) and apremilast), intravenous immunoglobulin (IVIg), and glucocorticoid treatment (prednisolone-equivalent dose).

### COVID-19 outcome

The primary outcome of interest was an ordinal COVID-19 severity scale, which included the following mutually exclusive groups: (1) no hospitalisation, (2) hospitalisation (without death), and (3) death.

### Statistical analysis

Categorical variables were summarised as number and percentage while continuous variables were summarised as mean and SD.

Multivariable ordinal logistic regression was used to analyse the data. Associations were estimated using ORs, 95% CIs and p values. The effect size of a categorical predictor gives the chance in odds of being one level higher on the ordinal COVID-19 severity scale compared with the reference category of the predictor variable, while for a continuous predictor, it gives the chance in odds of being one level higher on the ordinal COVID-19 severity scale for a unit increase in the continuous predictor. Cases without outcome data were excluded from the models. Missing data were assumed to be missing at random. Multiple imputation of missing data was performed to get pooled estimates for glucocorticoid dose, disease activity, hypertension/cardiovascular disease, diabetes mellitus and chronic renal disease.

Model covariates included age (continuous, analysed by decade), sex (female or male), pandemic calendar period (17 March 2020 to 15 June 2020, 16 June 2020 to 30 September 2020, 1 October 2020 to 27 August 2021), the number of comorbidities (none, one, two or more) or the individual comorbidities (hypertension or other cardiovascular disease (coronary artery disease, congestive heart failure, arrhythmia), interstitial lung disease, other chronic lung disease (obstructive lung disease (COPD/asthma), restrictive lung disease, other lung disease), diabetes mellitus, chronic renal disease (chronic renal insufficiency and end stage renal disease), cancer and obesity (defined by body mass index (BMI)≥30 kg/m²)), disease activity at the time of COVID-19 diagnosis using physician's global assessment (remission, low, moderate, high) and region (Europe, North America, other). Medication was categorised as follows for the multivariable ordinal logistic regression analysis (mutually exclusive categories): (1) no DMARD; (2) csDMARD only (monotherapy or combination therapy; used as reference category); (3) azathioprine monotherapy; (4) mycophenolate monotherapy; (5) azathioprine/mycophenolate combination therapy (except combination with b/tsDMARDs, including rituximab); (6) any other immunosuppressive monotherapy or combination therapy (except combination with b/tsDMARDs, including rituximab); (7) b/tsDMARD monotherapy or combination therapy (except rituximab, grouped separately); (8)
rituximab (monotherapy or combination therapy with any other drug). IVIg and prednisolone-equivalent dose (0 mg/day, 0–7.5 mg/day, >7.5 mg/day) were analysed separately in the multivariable model.

The primary model included the number of comorbidities as a predictor variable (as a reflection of the overall comorbidity burden) and a secondary model was built listing each individual comorbidity as a predictor. Sensitivity analyses were performed using a 4-point mutually exclusive ordinal COVID-19 severity outcome scale defined by (1) no hospitalisation, (2) hospitalisation with no oxygen (without death), (3) hospitalisation with oxygen/ventilation (without death), and (4) death.

Results were considered statistically significant when p value <0.05. Data clean-up was performed using RStudio4 and data were analysed using R V.4.0.2.

# RESULTS

## Patient characteristics

Complete hospitalisation and death outcome data were available for 348 individuals with IIM. None of the patients had inclusion body myositis. Four-fifths of cases (81.9%) originated from Europe and North America (table 1 and online supplemental table 1). Mean age was 53 (15.5) years, and most people in the study were female (64.1%) and of white ethnicity/race (55.3%). Common comorbidities included cardiovascular disease or hypertension (40.1%), interstitial lung disease (25%) and obesity (21.8%) (table 1). Most patients had a laboratory-confirmed diagnosis of COVID-19 (87.1%). About a quarter (27.5%) were reported to be taking between 0 and 7.5 mg/day prednisolone-equivalent dose, whereas 36.1% were reported to be taking >7.5 mg/day prednisolone. Just over two-thirds of patients were in remission/low disease activity (70.5%). The most prescribed DMARDs/immunosuppressants were methotrexate (25%), mycophenolate (20.4%), rituximab (18.1%), hydroxychloroquine (14.9%) and azathioprine (14.7%).

## COVID-19 severity

There were 12.9% (45/348) deaths and 39.1% (136/348) were hospitalised, while 48.0% (167/348) were not hospitalised. Of those who were hospitalised, oxygenation/ventilation status was known for 100 individuals (73.5%): 34% (34/100) were hospitalised with no oxygenation/ventilation required, while 66% (66/100) required oxygenation/ventilation (table 2).

In the primary analysis (table 3), there were higher odds of severe COVID-19 with increasing age (OR=1.59 for each additional decade of life, 95% CI 1.31 to 1.91), case reporting from a region other than North America or Europe (OR=4.55, 95% CI 2.37 to 8.76; vs Europe), history of two or more comorbidities (OR=2.63, 95% CI 1.39 to 4.98; vs none), presence of high disease activity (OR=3.50, 95% CI 1.25 to 9.83; vs remission), glucocorticoid intake >7.5 mg/day of prednisolone-equivalent dose (OR=2.40, 95% CI 1.09 to 5.28; vs none) and rituximab

<table><caption>**Table 1** Demographics and clinical characteristics of patients with idiopathic inflammatory myopathy and COVID-19 (N=348)</caption><thead><tr><th colspan="2">Characteristics</th></tr></thead><tbody><tr><td>Age, mean (SD), years</td><td>53.0 (15.5)</td></tr><tr><td>Age group, n (%)</td><td></td></tr><tr><td>&lt;30</td><td>26 (7.5)</td></tr><tr><td>30–49</td><td>108 (31.0)</td></tr><tr><td>50–65</td><td>136 (39.1)</td></tr><tr><td>&gt;65</td><td>78 (22.4)</td></tr><tr><td>Gender, n (%)</td><td></td></tr><tr><td>Female</td><td>223 (64.1)</td></tr><tr><td>Race/ethnicity, n (%)*</td><td></td></tr><tr><td>White</td><td>157 (55.3)</td></tr><tr><td>Black</td><td>34 (12.0)</td></tr><tr><td>Latinx</td><td>68 (23.9)</td></tr><tr><td>Other</td><td>25 (8.8)</td></tr><tr><td>Missing data</td><td>64</td></tr><tr><td>Region, n (%)</td><td></td></tr><tr><td>Europe</td><td>162 (46.6)</td></tr><tr><td>North America</td><td>123 (35.3)</td></tr><tr><td>South America</td><td>43 (12.4)</td></tr><tr><td>Other‡</td><td>20 (5.7)</td></tr><tr><td>Pandemic calendar period, n (%)</td><td></td></tr><tr><td>17 March 2020 to 15 June 2020</td><td>129 (37.2)</td></tr><tr><td>16 June 2020 to 30 September 2020</td><td>51 (14.7)</td></tr><tr><td>1 October 2020 to 27 August 2021</td><td>167 (48.1)</td></tr><tr><td>Comorbidities, n (%)</td><td></td></tr><tr><td>Hypertension</td><td>125 (25.9)</td></tr><tr><td>Other cardiovascular disease</td><td>46 (36.2)</td></tr><tr><td>Hypertension or other cardiovascular disease</td><td>139 (40.1)</td></tr><tr><td>Diabetes</td><td>59 (17.0)</td></tr><tr><td>Chronic renal disease</td><td>16 (4.6)</td></tr><tr><td>Interstitial lung disease</td><td>87 (25.0)</td></tr><tr><td>Other chronic lung disease</td><td>26 (7.5)</td></tr><tr><td>Cancer</td><td>24 (6.9)</td></tr><tr><td>Obesity</td><td>76 (21.8)</td></tr><tr><td>Ever smoker</td><td>84 (31.1)</td></tr><tr><td>Comorbid count†, n (%)</td><td></td></tr><tr><td>None</td><td>139 (39.9)</td></tr><tr><td>One</td><td>101 (29.0)</td></tr><tr><td>Two or more</td><td>108 (31.0)</td></tr><tr><td>Disease activity, n (%)*</td><td></td></tr><tr><td>Remission</td><td>91 (29.8)</td></tr><tr><td>Low disease activity</td><td>124 (40.7)</td></tr><tr><td>Moderate disease activity</td><td>62 (20.3)</td></tr><tr><td>High disease activity</td><td>28 (9.2)</td></tr><tr><td>Missing data</td><td>43</td></tr><tr><td>csDMARDs, n (%)</td><td></td></tr><tr><td>MTX</td><td>87 (25.0)</td></tr></tbody></table>

Continued
<table><caption>**Table 1** Continued</caption><thead><tr><th>Characteristics</th><th></th></tr></thead><tbody><tr><td>LEF</td><td>7 (2.0)</td></tr><tr><td>SSZ</td><td>1 (0.3)</td></tr><tr><td>HCQ</td><td>52 (14.9)</td></tr><tr><td>Immunosuppressants, n (%)</td><td></td></tr><tr><td>AZA</td><td>51 (14.7)</td></tr><tr><td>CSA</td><td>10 (2.9)</td></tr><tr><td>MMF</td><td>71 (20.4)</td></tr><tr><td>TAC</td><td>5 (1.4)</td></tr><tr><td>CYC</td><td>10 (2.9)</td></tr><tr><td>bDMARDs, n (%)</td><td></td></tr><tr><td>RTX</td><td>63 (18.1)</td></tr><tr><td>Abatacept</td><td>5 (1.4)</td></tr><tr><td>Anti-IL1</td><td>2 (0.6)</td></tr><tr><td>Anti-IL17</td><td>1 (0.3)</td></tr><tr><td>Anti-TNF</td><td>1 (0.3)</td></tr><tr><td>tsDMARDs</td><td></td></tr><tr><td>Apremilast</td><td>2 (0.6)</td></tr><tr><td>JAKi, n (%)</td><td>4 (1.1)</td></tr><tr><td>IVIg, n (%)</td><td>26 (7.5)</td></tr><tr><td>Glucocorticoids (prednisolone-equivalent dose)</td><td></td></tr><tr><td>No glucocorticoids</td><td>111 (36.4)</td></tr><tr><td>>0 to 7.5 mg/day</td><td>84 (27.5)</td></tr><tr><td>>7.5 mg/day</td><td>110 (36.1)</td></tr><tr><td>DMARD/immunosuppressant medication category, n (%)</td><td></td></tr><tr><td>No DMARD/immunosuppressant</td><td>70 (20.1)</td></tr><tr><td>csDMARD only (HCQ/MTX/SSZ/LEF monotherapy or combination therapy)</td><td>81 (23.3)</td></tr><tr><td>AZA monotherapy</td><td>32 (9.2)</td></tr><tr><td>MMF monotherapy</td><td>43 (12.4)</td></tr><tr><td>AZA/MMF combination therapy (except combination with RTX or b/tsDMARDs)</td><td>27 (7.8)</td></tr><tr><td>CSA/CYC/TAC monotherapy or combination therapy (except RTX/b/tsDMARDs)</td><td>17 (4.9)</td></tr><tr><td>b/tsDMARD monotherapy or combination therapy (except RTX)</td><td>15 (4.3)</td></tr><tr><td>RTX (monotherapy or combination therapy with any other drug)</td><td>63 (18.1)</td></tr></tbody></table><p>*Missing data excluded from the denominator when calculating percentages.</p><p>†Comorbid count includes hypertension, other cardiovascular disease, diabetes, chronic renal disease, chronic lung disease, cancer and obesity (BMI≥30).</p><p>‡Other regions with available patient data included South America, Eastern Mediterranean, South-East Asia and Western Pacific. AZA, azathioprine; bDMARD, biologic DMARD; BMI, body mass index; CSA, ciclosporin; csDMARD, conventional synthetic DMARD; CYC, cyclophosphamide; DMARD, disease-modifying antirheumatic drug; HCQ, hydroxychloroquine; IL, interleukin; IVIg, intravenous immunoglobulin; JAKi, Janus kinase inhibitors; LEF, leflunomide; MMF, mycophenolate mofetil; MTX, methotrexate; RTX, rituximab; SSZ, sulfasalazine; TAC, tacrolimus; TNF, tumour necrosis factor; tsDMARD, targeted synthetic DMARD.</p>

<table><caption>**Table 2** Frequencies and proportions of outcomes in the ordinal COVID-19 severity scale (N=348)</caption><thead><tr><th>Outcomes</th><th>n (%)</th></tr></thead><tbody><tr><td>No hospitalisation</td><td>167 (48.0)</td></tr><tr><td>Hospitalisation</td><td>136 (39.1)</td></tr><tr><td>No oxygenation</td><td>34 (34)*</td></tr><tr><td>Oxygenation/ventilation</td><td>66 (66)*</td></tr><tr><td>Missing data</td><td>36</td></tr><tr><td>Death</td><td>45 (12.9)</td></tr></tbody></table><p>*Missing data excluded from the denominator when calculating percentages.</p>

exposure (OR=2.71, 95% CI 1.28 to 5.72; vs csDMARD exposure only). Male gender (OR=1.59, 95% CI 0.95 to 2.59) was also associated with worst COVID-19, whereas COVID-19 diagnosis after 1 October 2020 was associated with less severe COVID-19 (OR=0.61, 95% CI 0.37 to 1.00), although these two associations were not statistically significant.

In the secondary analysis with comorbidities as individual covariates, male sex (OR=1.65, 95% CI 1.01 to 2.71) and calendar period on/after 1 October 2020 (OR=0.59, 95% CI 0.35 to 0.97) emerged as significant variables in the model (online supplemental table 2). All the previously identified variables were also associated with severe outcomes in this model: age, region, high disease activity, glucocorticoids >7.5 mg/day and rituximab exposure (online supplemental table 2).

Results of the sensitivity analyses are presented in online supplemental tables 3 and 4. Similarly to the results of the primary analysis, age, male sex, history of two or more comorbidities, high disease activity, glucocorticoids >7.5 mg/day and rituximab exposure were associated with severe COVID-19, whereas COVID-19 diagnosis after 1 October 2020 was associated with less severe COVID-19.

## DISCUSSION

In our study of 348 patients with IIM, we have identified factors associated with severe COVID-19, namely, older age, male sex, region other than North America/Europe, history of two or more comorbidities, high disease activity, prednisolone-equivalent intake of >7.5 mg/day and rituximab exposure. COVID-19 diagnosis later in the pandemic was associated with less severe COVID-19.

The increased odds of more severe COVID-19 in people with IIM with age is consistent with reports on people with other rheumatic diseases<sup>10-12</sup> and non-rheumatic populations.<sup>13-15</sup> An increased number of comorbidities being a contributor to COVID-19 severity has also been reported in inflammatory bowel disease<sup>16</sup> and in the general population.<sup>10-12</sup> Increased glucocorticoid use and high disease activity are also associated with an increased risk of COVID-19 severity consistent with other rheumatic<sup>10 12</sup> and non-rheumatic diseases, such as inflammatory bowel disease,<sup>16</sup> although the possibility of
<table><caption>**Table 3** Multivariable ordinal logistic regression analysis of factors associated with the 3-point ordinal COVID-19 severity outcome scale (no hospitalisation, hospitalisation, death), with comorbidity count instead of comorbidities listed individually (N=348, primary analysis)</caption><thead><tr><th></th><th>OR (95% CI)</th><th>P value</th></tr></thead><tbody><tr><td>Age (per decade)</td><td><strong>1.59 (1.31 to 1.91)</strong></td><td><strong>&lt;0.001</strong></td></tr><tr><td>Male sex</td><td>1.57 (0.95 to 2.59)</td><td>0.076</td></tr><tr><td>Region</td><td></td><td></td></tr><tr><td>Europe</td><td>REF</td><td>n/a</td></tr><tr><td>North America</td><td>0.87 (0.48 to 1.58)</td><td>0.648</td></tr><tr><td>Other</td><td><strong>4.55 (2.37 to 8.76)</strong></td><td><strong>&lt;0.001</strong></td></tr><tr><td>Pandemic calendar period</td><td></td><td></td></tr><tr><td>On/before 15 June 2020</td><td>REF</td><td>n/a</td></tr><tr><td>16 June to 30 September 2020</td><td>0.55 (0.26 to 1.20)</td><td>0.132</td></tr><tr><td>On/after 1 October 2020</td><td>0.61 (0.37 to 1.00)</td><td>0.051</td></tr><tr><td>Comorbidities</td><td></td><td></td></tr><tr><td>None</td><td>REF</td><td>n/a</td></tr><tr><td>One</td><td>1.41 (0.73 to 2.74)</td><td>0.305</td></tr><tr><td>Two or more</td><td><strong>2.63 (1.39 to 4.98)</strong></td><td><strong>0.003</strong></td></tr><tr><td>Disease activity</td><td></td><td></td></tr><tr><td>Remission</td><td>REF</td><td>n/a</td></tr><tr><td>Low/moderate disease activity</td><td>1.19 (0.63 to 2.25)</td><td>0.594</td></tr><tr><td>High disease activity</td><td><strong>3.50 (1.25 to 9.83)</strong></td><td><strong>0.018</strong></td></tr><tr><td>Glucocorticoid (prednisolone-equivalent dose)</td><td></td><td></td></tr><tr><td>No glucocorticoids</td><td>REF</td><td>n/a</td></tr><tr><td>&gt;0 to 7.5 mg/day</td><td>1.08 (0.57 to 2.05)</td><td>0.820</td></tr><tr><td>&gt;7.5 mg/day</td><td><strong>2.40 (1.09 to 5.28)</strong></td><td><strong>0.031</strong></td></tr><tr><td>IVIg</td><td>0.42 (0.15 to 1.18)</td><td>0.101</td></tr><tr><td>DMARD/immunosuppressant medication category</td><td></td><td></td></tr><tr><td>csDMARD only (HCQ/MTX/SSZ/LEF monotherapy or combination therapy)</td><td>REF</td><td>n/a</td></tr><tr><td>No DMARD/immunosuppressant</td><td>1.85 (0.90 to 3.78)</td><td>0.094</td></tr><tr><td>AZA monotherapy</td><td>1.78 (0.71 to 4.43)</td><td>0.216</td></tr><tr><td>MMF monotherapy</td><td>1.25 (0.54 to 2.89)</td><td>0.601</td></tr><tr><td>AZA/MMF combination therapy (except combination with RTX or b/ tsDMARDs)</td><td>0.77 (0.27 to 2.15)</td><td>0.615</td></tr><tr><td>CSA/CYC/TAC monotherapy or combination therapy (except RTX/b/ tsDMARDs)</td><td>1.61 (0.54 to 4.79)</td><td>0.386</td></tr><tr><td>b/tsDMARD monotherapy or combination therapy (except RTX)</td><td>1.65 (0.50 to 5.43)</td><td>0.411</td></tr><tr><td>RTX (monotherapy or combination therapy with any other drug)</td><td><strong>2.71 (1.28 to 5.72)</strong></td><td><strong>0.009</strong></td></tr></tbody></table>

Statistically significant OR are highlighted in bold.

AZA, azathioprine; bDMARD, biologic DMARD; CSA, ciclosporin; csDMARD, conventional synthetic DMARD; CYC, cyclophosphamide; DMARD, disease-modifying antirheumatic drug; HCQ, hydroxychloroquine; IL, interleukin; IVIg, intravenous immunoglobulin; IVIg, intravenous immunoglobulin; JAKi, Janus kinase inhibitors; LEF, leflunomide; MMF, mycophenolate mofetil; MTX, methotrexate; RTX, rituximab; SSZ, sulfasalazine; TAC, tacrolimus; TNF, tumour necrosis factor; tsDMARD, targeted synthetic DMARD.

confounding by indication has been raised as a potential explanation for the glucocorticoid association.¹⁷ In our data set, patients with high disease activity were 3.5 times more likely to have severe COVID-19 outcome compared with those in remission, and those on doses of >7.5 mg/day of prednisolone-equivalent glucocorticoids were 2.4 times more likely to have a severe COVID-19 outcome. Other studies have also identified rituximab as

an important risk factor of COVID-19 adverse outcomes in other conditions.¹⁻³

The strength of this study is the collaborative work by rheumatologists that allowed the collection of a large number of entries into the registry in a short space of time for what is considered a relatively rare condition.¹⁸ There is a higher representation of patients from the USA and Europe in this study, possibly due to reporting
bias from increased provider awareness of this database. Physicians may also be more aware of hospitalisations and deaths of their patients due to COVID-19 rather than those who were not hospitalised, as well as more aware of patients who are sicker at baseline or have more complex disease (regardless of outcome), which may contribute to reporting bias. Another limitation of our study is the absence of a control group. Therefore, this study cannot be used to comment on hospitalisation or death rates, as selection bias may exist, and comparisons with hospitalisation or death rates in other subgroups of patients or with the general population should not be made. Moreover, we caution against interpreting our estimates causally. There is likely unmeasured confounding dependent on the particularities of health systems and case reporting differences. We tried to address this by limiting the research questions to those that could be answered with this data set and by accounting for potential confounders in our analyses. The WHO clinical progression scale<fnref n="19" /> was not used in our study, limiting direct comparisons to be made with other studies. This was due to the absence of data granularity and statistical feasibility. However, the ordinal severity scale used in our study includes merged components from the WHO clinical progression scale and minimises missing data and data overfitting. Another limitation of the study is that the cause of hospitalisation was not explicitly included in the dataset. However, it may be inferred that COVID-19 was the cause of hospitalisation as this physician-reported database captures COVID-19 cases in patients with rheumatic diseases where physicians inputting data were asked “Was the patient hospitalised during the illness?” and “What was the maximum level of care required during the illness?”. Due to the nature of this registry, granular data about auto-antibody profiles are not available. Vaccination status was not available for the patients in this dataset. However, the calendar period used in this study (1 October 2020 to 27 August 2021) may act as a surrogate for the COVID-19 vaccine era being the time period in which the vaccination roll-out commenced.

In conclusion, analysis of this large registry data set has identified factors associated with severe outcomes due to COVID-19 in adult patients with IIM, consistent with the reported literature in other rheumatic diseases, providing insights into future risk stratification of patients with IIM.

Author affiliations

<footnote n="1">¹Centre for Rheumatology, University College London, London, UK</footnote>

<footnote n="2">²Department of Rheumatology, University College London University Hospitals NHS Foundation Trust, London, UK</footnote>

<footnote n="3">³Division of Rheumatology, Department of Medicine, University of California San Francisco, San Francisco, CA, USA</footnote>

<footnote n="4">⁴Centre for Genetics and Genomics Versus Arthritis, University of Manchester, Manchester, UK</footnote>

<footnote n="5">⁵National Institute of Health Research Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester, UK</footnote>

<footnote n="6">⁶Centre for Epidemiology Versus Arthritis, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK</footnote>

<footnote n="7">⁷German Rheumatism Research Center (DRFZ Berlin), Epidemiology and Health Services Research, Berlin, Germany</footnote>

<footnote n="8">⁸Institut Pierre Louis d'Epidémiologie et de Santé Publique, INSERM, Sorbonne Université, Paris, France</footnote>

<footnote n="9">⁹Department of Rheumatology, APHP, Pitié-Salpêtrière Hospital, Paris, France</footnote>

<footnote n="10">¹⁰Instituto de Salud Musculoesquelética (INMUSC), Madrid, Spain</footnote>

<footnote n="11">¹¹Portuguese League Against Rheumatic Diseases (LPCDR), Lisbon, Portugal</footnote>

<footnote n="12">¹²Département de Rheumatologie, Referral Center for Rare Systemic Autoimmune Diseases RESO, CHU de Bordeaux, Bordeaux, France</footnote>

<footnote n="13">¹³UMR CNRS 5164, Université de Bordeaux, Bordeaux, France</footnote>

<footnote n="14">¹⁴Lille Inflammation Research International Center (LIRIC), University of Lille, Lille, France</footnote>

<footnote n="15">¹⁵Département de Médecine Interne et Immunologie Clinique, Referral Center for Rare Systemic Autoimmune Diseases North and Northwest of France (CeRAINO), INSERM U995, CHU Lille, Lille, France</footnote>

<footnote n="16">¹⁶Clinical Epidemiology Unit, Karolinska Institute, Stockholm, Sweden</footnote>

<footnote n="17">¹⁷Epidemiology Unit, Italian Society for Rheumatology (SIR), Milan, Italy</footnote>

<footnote n="18">¹⁸Division of Rheumatology, Department of Medicine V, University Hospital Heidelberg, Heidelberg, Baden-Württemberg, Germany</footnote>

<footnote n="19">¹⁹Department of Rheumatology and Clinical Immunology, University Medical Center, Faculty of Medicine, Albert-Ludwigs University of Freiburg, Freiburg, Germany</footnote>

<footnote n="20">²⁰Department of Internal Medicine II, University Hospitals Giessen, Justus-Liebig-University Giessen, Giessen, Germany</footnote>

<footnote n="21">²¹Section of Rheumatology, Department of Medicine, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA</footnote>

<footnote n="22">²²Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA</footnote>

<footnote n="23">²³Division of Rheumatology, Allergy, and Immunology, Massachusetts General Hospital, Boston, MA, USA</footnote>

<footnote n="24">²⁴Department of Rheumatology, Hospital Nacional Guillermo Almenara Irigoyen, Lima, Peru</footnote>

<footnote n="25">²⁵Universidad Científica del Sur, Lima, Peru</footnote>

<footnote n="26">²⁶University of Guadalajara, Guadalajara, Mexico</footnote>

<footnote n="27">²⁷Division of Rheumatology, Faculdade de Medicina (FMUSP), Universidade de São Paulo, São Paulo, Brazil</footnote>

<footnote n="28">²⁸Division of Rheumatology, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil</footnote>

<footnote n="29">²⁹Instituto de Medicina Integral Professor Fernando Figueira (IMIP), Recife, Brazil</footnote>

<footnote n="30">³⁰Hospital das Clínicas, Universidade Federal de Goias (UFG), Goiania, Brazil</footnote>

<footnote n="31">³¹Argentine Society of Rheumatology, Buenos Aires, Argentina</footnote>

<footnote n="32">³²Hospital Interzonal General de Agudos (HIGA) San Martín, La Plata, Buenos Aires, Argentina</footnote>

<footnote n="33">³³Sanatorio Parque, Córdoba, Argentina</footnote>

<footnote n="34">³⁴Sanatorio y Universidad Adventista del Plata, Libertador San Martín, Entre Ríos, Argentina</footnote>

<footnote n="35">³⁵Myositis UK, Southampton, UK</footnote>

<footnote n="36">³⁶Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada</footnote>

<footnote n="37">³⁷Canadian Arthritis Patient Alliance, Toronto, ON, Canada</footnote>

<footnote n="38">³⁸Program in Rheumatology, Boston Children's Hospital, Boston, MA, USA</footnote>

<footnote n="39">³⁹Division of Rheumatology and Clinical Immunology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA</footnote>

<footnote n="40">⁴⁰Section of Rheumatology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA</footnote>

<footnote n="41">⁴¹Lupus Foundation of America, Washington, DC, USA</footnote>

<footnote n="42">⁴²HealthPartners, St. Paul, MN, USA</footnote>

<footnote n="43">⁴³Department of Medicine, University of Otago Wellington, Wellington, New Zealand</footnote>

<footnote n="44">⁴⁴Pfizer Inc, New York, NY, USA</footnote>

<footnote n="45">⁴⁵Harvard Medical School, Boston, MA, USA</footnote>

<footnote n="46">⁴⁶Faculty of Medicine, University of Queensland School of Clinical Medicine, Herston, Queensland, Australia</footnote>

<footnote n="47">⁴⁷Department of Rheumatology, Royal Brisbane and Woman's Hospital, Metro North Hospital and Health Service, Herston, Queensland, Australia</footnote>

<footnote n="48">⁴⁸Department of Rheumatology, Northwick Park Hospital, London North West University Healthcare NHS Trust, London, UK</footnote>

<footnote n="49">⁴⁹National Institute of Health Research University College London Hospitals Biomedical Research Centre, University College London Hospitals NHS Foundation Trust, London, UK</footnote>

<footnote n="50">⁵⁰Department of Neuromuscular Diseases, University College London, London, UK</footnote>
**Twitter** Loreto Carmona @carmona_loreto, Christophe Richez @crichez33, Marie Holmqvist @marie_holmqvist, Philip C Robinson @philipcrobinson and Pedro M Machado @pedrommcmachado

**Acknowledgements** We wish to thank all healthcare providers who entered data into the registry.

**Contributors** S-AY performed the statistical analyses. S-AY and PMM had access to the study data, developed the tables and the first draft of the manuscript, vouch for the data and analyses, and had final responsibility for the decision to submit for publication. All authors contributed to data collection, data analysis and interpretation of data. All authors contributed intellectual content during the drafting and revision of the work and approved the final version to be published. PMM supervised the work and is the guarantor.

**Funding** The study received support from the American College of Rheumatology (ACR) and European Alliance of Associations for Rheumatology (EULAR).

**Competing interests** S-AY is supported by vs Arthritis, Royal College of Physicians, Rosetrees Trust, University College London Hospitals Biomedical Research Centre and University College London Hospitals Charity, all unrelated to this manuscript. MG is a Pfizer employee as of March 2022. KLH has received support from EULAR for database maintenance and data extraction related to this manuscript, KLH has received grants from Pfizer and BMS for work unrelated to this manuscript, honoraria from Abbvie unrelated to this manuscript, and is supported by the NIHR Manchester Biomedical Research Centre. LC participates on a Data Safety Monitoring Board or Advisory Board of Lilly, and has a leadership or fiduciary role in EULAR, unrelated to this manuscript. CR receives consulting fees from AbbVie, Astra Zeneca, GSK, Novartis, Pfizer, honoraria from AbbVie, Amgen, Astra Zeneca, GSK, Pfizer, Biogen, BMS, Galapagos, Lilly, travel support from Amgen, Celltrion, Galapagos, patents planned, issued or pending by Astra Zeneca, and receipt of equipment, materials, drugs, medical writing, gifts or other services by Biogen and Lilly, all unrelated to this manuscript. GJP-E has received grants from Janssen, consulting fees and honoraria from GSK, Janssen, Pfizer, Werfen, travel support from GSK, Montpellier, Boehringer Ingelheim, and participates on a Data Safety Monitoring Board or Advisory Board of Pfizer, GSK and Janssen, and has received equipment, materials, drugs, medical writing, gifts or other services from Janssen, all unrelated to this manuscript. REV has received grants from BMS, Novartis, Pfizer and honoraria from Hexal, all unrelated to this manuscript. EV has received honoraria from AbbVie, Novartis, Janssen and travel support from AbbVie, Janssen, Pfizer, and participates on a Data Safety Monitoring Board or Advisory Board of AbbVie, Novartis, Janssen, and is President of Asociacion de Rumatologia del Noreste Argentino, all unrelated to this manuscript. ES receives honoraria from the COVID-19 Global Rheumatology Alliance and non-financial support from Canadian Arthritis Patient Alliance, unrelated to this manuscript. JH receives grants from the Rheumatology Research Foundation, salary support from the Childhood Arthritis and Rheumatology Research Alliance, consulting fees from Novartis, Pfizer, Sobi and Biogen, all unrelated to this manuscript. MGM is a patient consultant for Aurinia Pharmaceuticals, Boehringer Ingelheim, Johnson & Johnson, Bristol-Myers Squibb, all unrelated to this manuscript, and receives honoraria from Aurinia Pharmaceuticals, Boehringer Ingelheim, Bristol-Myers Squibb, all unrelated to this study. RG has received honoraria from Janssen, Pfizer, AbbVie, Cornerstones, Novartis, travel support from Pfizer and Janssen, and is a member of the New Zealand Rheumatology Association executive and ACR Global Engagement Special Committee, all unrelated to this manuscript. SB is a Pfizer employee and has received honoraria from AbbVie, Horizon, Novartis, Pfizer, has received travel support from Pfizer, and owns restricted stock units with Pfizer as a Pfizer employee, all unrelated to this manuscript. PCR has received grants from Pfizer, Novartis, UCB, Janssen, all unrelated to this manuscript, consulting fees from AbbVie, Janssen, UCB, Roche, Lilly, Novartis, Atom Biosciences, Gilead, Kukdong, GSK, all unrelated to this manuscript, honoraria from AbbVie, UCB, Janssen, Novartis, Lilly, GSK, Pfizer, all unrelated to this manuscript, travel support from BMS, UCB, Pfizer, Novartis, all unrelated to this manuscript. PCR reports participation on a Data Safety Monitoring Board or Advisory Board of Atom Biosciences, unrelated to this manuscript, and leadership role in the Australian Rheumatology Association and Arthritis Queensland, unrelated to this manuscript. JY has received support from NIH/NIAMS (grants to UCSF) for the present manuscript, grants from Gilead, Astra Zeneca, BMS Foundation, all unrelated to this manuscript, consulting fees from Astra Zeneca, Aurinia, Pfizer, all unrelated to this manuscript. PMM is supported by the National Institute for Health Research (NIHR), University College London Hospitals (UCLH), Biomedical Research Centre (BRC) and has received consulting fees from AbbVie, BMS, Celgene, Eli Lilly, Galapagos, Janssen, MSD, Novartis, Orphazyme, Pfizer, Roche, UCB, all unrelated to this manuscript.

**Patient consent for publication** Not applicable.

**Ethics approval** The C19-GRA/EULAR physician-reported registry was determined 'not human subjects' research' by the UK Health Research Authority and the University of Manchester, as well as under US Federal Guidelines assessed by

the University of California, San Francisco Institutional Review Board. Due to the de-identified and non-interventional nature of the study, it was determined to be exempt by each institutional review board.

**Provenance and peer review** Not commissioned; externally peer reviewed.

**Data availability statement** Data are available on reasonable request. Applications to access the data should be made to the COVID-19 Global Rheumatology Alliance Steering Committee.

**Supplemental material** This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

**Open access** This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

ORCID iDs

Su-Ann Yeoh http://orcid.org/0000-0002-4692-4669
Saskia Lawson-Tovey http://orcid.org/0000-0002-8611-162X
Anja Strangfeld http://orcid.org/0000-0002-6233-022X
Laure Gossec http://orcid.org/0000-0002-4528-310X
Loreto Carmona http://orcid.org/0000-0002-4401-2551
Martin Schäfer http://orcid.org/0000-0001-6487-3634
Christophe Richez http://orcid.org/0000-0002-3029-8739
Eric Hachulla http://orcid.org/0000-0001-7432-847X
Marie Holmqvist http://orcid.org/0000-0001-8996-5260
Carlo Alberto Scirè http://orcid.org/0000-0001-7451-0271
Rebecca Hasseli http://orcid.org/0000-0002-2982-8253
Tiffany Y-T Hsu http://orcid.org/0000-0003-1041-8040
Victor R Pimentel-Quiroz http://orcid.org/0000-0002-3638-7054
Emily Sirotich http://orcid.org/0000-0002-7087-8543
Jonathan S Hausmann http://orcid.org/0000-0003-0786-8788
Philip C Robinson http://orcid.org/0000-0002-3156-3418
Pedro M Machado http://orcid.org/0000-0002-8411-7972

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