Abstract
Objective
To investigate baseline use of biologic or targeted synthetic (b/ts) disease-modifying antirheumatic drugs (DMARDs) and COVID-19 outcomes in rheumatoid arthritis (RA).
Methods
We analysed the COVID-19 Global Rheumatology Alliance physician registry (from 24 March 2020 to 12 April 2021). We investigated b/tsDMARD use for RA at the clinical onset of COVID-19 (baseline): abatacept (ABA), rituximab (RTX), Janus kinase inhibitors (JAKi), interleukin 6 inhibitors (IL-6i) or tumour necrosis factor inhibitors (TNFi, reference group). The ordinal COVID-19 severity outcome was (1) no hospitalisation, (2) hospitalisation without oxygen, (3) hospitalisation with oxygen/ventilation or (4) death. We used ordinal logistic regression to estimate the OR (odds of being one level higher on the ordinal outcome) for each drug class compared with TNFi, adjusting for potential baseline confounders.
Results
Of 2869 people with RA (mean age 56.7 years, 80.8% female) on b/tsDMARD at the onset of COVID-19, there were 237 on ABA, 364 on RTX, 317 on IL-6i, 563 on JAKi and 1388 on TNFi. Overall, 613 (21%) were hospitalised and 157 (5.5%) died. RTX (OR 4.15, 95% CI 3.16 to 5.44) and JAKi (OR 2.06, 95% CI 1.60 to 2.65) were each associated with worse COVID-19 severity compared with TNFi. There were no associations between ABA or IL6i and COVID-19 severity.
Conclusions
People with RA treated with RTX or JAKi had worse COVID-19 severity than those on TNFi. The strong association of RTX and JAKi use with poor COVID-19 outcomes highlights prioritisation of risk mitigation strategies for these people.
Keywords: Covid-19, rheumatoid arthritis, tumour necrosis factor inhibitors, rituximab, abatacept
Key messages.
What is already known about this subject?
A previous international registry study of the COVID-19 Global Rheumatology Alliance (C19-GRA) suggested that people with systemic rheumatic diseases on biologic or targeted synthetic (b/ts) disease-modifying antirheumatic drugs (DMARDs) had lower odds of hospitalisation than those not using DMARDs.
Previous studies reported that people with systemic rheumatic diseases using rituximab had higher odds of COVID-19-related mortality than those using alternative DMARDs such as methotrexate.
What does this study add?
Using the C19-GRA, we analysed people with rheumatoid arthritis (RA) using b/tsDMARD (to limit the potential for confounding) at the time of COVID-19 onset and investigated an ordinal outcome that encompassed a range of COVID-19 outcomes.
People with RA using rituximab or Janus kinase (JAK) inhibitors at COVID-19 onset were more likely to experience poor COVID-19 outcomes, ranging from hospitalisation to death, compared with use of tumour necrosis factor inhibitors.
How might this impact on clinical practice or future developments?
People using rituximab or JAK inhibitors for RA are more likely to experience poor COVID-19 outcomes and should be prioritised for risk mitigation strategies.
Introduction
The ongoing COVID-19 pandemic has had a significant impact on people with rheumatoid arthritis (RA), many of whom are treated with biologic or targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs).1 While b/tsDMARDs are important for controlling RA disease activity, their influence on COVID-19 outcomes in people with RA remains unclear. This uncertainty has led to anxiety, social isolation due to shielding practices and b/tsDMARD discontinuation, which may contribute to RA flares.2–4 Addressing the knowledge gaps around the influence of b/tsDMARDs on COVID-19 outcomes is a priority for people with RA and their providers.
The impact of b/tsDMARDs on COVID-19 outcomes is of particular interest since some of these medications, such as tocilizumab and baricitinib, have been studied as repurposed treatments for COVID-19. Some evidence suggests that baseline use of certain b/tsDMARDs, like tumour necrosis factor inhibitors (TNFi), for inflammatory disorders may be associated with less severe COVID-19 outcomes.5 In addition, among patients with COVID-19, treatment with interleukin 6 inhibitors (IL-6i) and baricitinib led to improved outcomes in some clinical trials.6–9 However, there are also concerns that baseline use of certain b/tsDMARDs, such as rituximab or abatacept, may be associated with worse COVID-19 outcomes due to impaired viral immune defences.10 11
Due to sample size limitations, previous studies of b/tsDMARD use and COVID-19 outcomes have combined heterogeneous rheumatic diseases and medications and/or investigated a single outcome, such as hospitalisation.5 12 Therefore, we used the COVID-19 Global Rheumatology Alliance (C19-GRA) physician registry to evaluate the associations of different classes of b/tsDMARDs with a range of COVID-19 outcomes in people with RA.
Methods
Data source and study sample assembly
People with rheumatic disease and COVID-19 from the C19-GRA registry and the European Alliance of Associations for Rheumatology (EULAR) COVID-19 database were included in the analyses. We included cases entered between 24 March 2020 and 12 April 2021. The C19-GRA and EULAR databases include people with rheumatic diseases diagnosed with COVID-19, as reported by rheumatology providers via two international data entry portals. The details of these registries have been previously reported.5 12–17 We analysed people with RA on b/tsDMARD at the time of COVID-19 clinical onset. As of 12 April 2021, a total of 15 127 people with rheumatic diseases and COVID-19 have been reported. We included people with RA who were taking one of the following medication classes: Cytotoxic T lymphocyte-associated antigen immunoglobulin (CTLA4-Ig: abatacept), anti-CD20 (rituximab), IL-6i (tocilizumab, sarilumab), Janus kinase inhibitors (JAKi: tofacitinib, baricitinib or upadacitinib) or TNFi (infliximab, etanercept, adalimumab, certolizumab pegol and golimumab). The drug class of b/tsDMARD was collected, rather than individual drugs. We did not include IL-1 inhibitors since these were infrequently used for RA. Prior studies using the C19-GRA and EULAR databases have included some patients also reported in this study, but the analyses included in this study and observations reported are novel. In addition, follow-up for this study is more current than previous publications using these data.
Data quality was assessed by the University of California, San Francisco and the University of Manchester, UK, which both confirmed that there were no duplicates in the data entries.
Baseline b/tsDMARD exposures
The exposure of interest was baseline use of a b/tsDMARD at the time of COVID-19 clinical onset. As in previous C19-GRA investigations, we included confirmed and presumptive cases of COVID-19.5 12 14 We limited this analysis to users of abatacept, rituximab, IL-6i, JAKi or TNFi to limit the cohort to people with similar RA disease severity and minimise the impact of confounding by indication. We included b/tsDMARD users regardless of whether they also used a conventional synthetic (cs) DMARD or glucocorticoids, but did not include people on csDMARDs (eg, hydroxychloroquine, methotrexate, sulfasalazine, leflunomide) monotherapy, as monotherapy may indicate less severe RA or be due to care access barriers or socioeconomic factors. TNFi users were the reference group since TNFis are the most frequently used b/tsDMARD in RA. People with RA who were reported to be on more than one b/tsDMARD were excluded from the analysis.
COVID-19 outcomes
The primary outcome of interest was a mutually exclusive ordinal COVID-19 severity outcome: (1) no hospitalisation, (2) hospitalisation with no oxygenation, (3) hospitalisation with any oxygenation or mechanical ventilation, and (4) death. We chose this primary outcome to estimate the association of b/tsDMARD exposure with general odds of worse COVID-19 severity rather than a single outcome. A similar outcome was developed by the WHO to capture the spectrum of disease and is used in clinical trials evaluating COVID-19 therapeutics.18 If a patient met multiple levels of the outcome, they were only included at the highest level. At the time of analysis, all patients were required to have a resolved clinical course.
Covariates
Details regarding demographics, including age, race/ethnicity and continent, and patient characteristics, including obesity, smoking, comorbidities (interstitial lung disease (ILD), history of cancer, hypertension, cardiovascular disease, chronic kidney disease/end-stage kidney disease, diabetes, non-ILD pulmonary disease), RA disease activity (as judged by the reporting physician), glucocorticoid dose for RA at the time of COVID-19 onset and use of concomitant csDMARD (methotrexate, sulfasalazine, hydroxychloroquine), were by physician report. For glucocorticoid dose, the amount of prednisone-equivalent glucocorticoid prescribed was treated as a categorical variable (none, >0–5 mg/day, 6–9 mg/day and ≥10 mg/day). Hypertension and cardiovascular disease were collapsed as a single comorbidity due to collinearity.
Statistical analysis
We reported baseline characteristics and outcomes across the exposure categories of baseline b/tsDMARD use with descriptive statistics.
Ordinal logistic regression models were used to assess the association between each b/tsDMARD compared with TNFi use and the severity of COVID-19 on an ordinal scale in unadjusted and multivariable analyses to estimate ORs and 95% CIs. The effect size of the ordinal outcome can be interpreted as the odds of being one level higher on the ordinal COVID-19 severity scale than the reference group. We assessed the proportional odds assumption for the ordinal regression model using the Brant test.19 Models in which the proportional odds assumption was not met were refitted using the partial proportional odds model which relaxes the assumption of proportionality for offending predictors.20 We considered potential confounders known to be associated with either b/tsDMARD use or COVID-19 severity. Covariates included in multivariable models included sociodemographic features (age, sex), obesity, smoking status (ever vs never), concomitant csDMARD use (methotrexate, hydroxychloroquine, sulfasalazine, or leflunomide), categorical glucocorticoid use/dose, categorical comorbidity count (0, 1, 2 of the following: chronic kidney insufficiency/end-stage kidney disease, diabetes, non-ILD pulmonary disease), other key comorbidities as individual variables (hypertension/cardiovascular disease, ILD and cancer), disease activity (moderate/high vs remission/low), continent (Europe, North America, South America, other) and calendar time (January–15 June 2020 vs 16 June 2020–12 April 2021).21 These time periods were selected based on the initial publication of the RECOVERY trial, which reported a survival benefit associated with dexamethasone and influenced subsequent practice.22 We assumed that missing data were ‘missing at random’. We then performed multiple imputation five times to get pooled estimates to impute missing values for disease activity, race/ethnicity, glucocorticoid dose, smoking, hypertension/cardiovascular disease and comorbidity count. After imputation, we compared the distribution of imputed values with the distribution of variables before imputation to confirm that distributions were similar before and after imputation.
To confirm the robustness of our findings, we performed several sensitivity analyses. First, we excluded patients with ILD or cancer from the analysis since rituximab is commonly used in these patients, who may also be susceptible to poor COVID-19 outcomes. Second, given data showing a strong association between race/ethnicity and COVID-19 outcomes in the USA, we performed an analysis adjusting for this variable among US patients in the registry. The race/ethnicity variable was categorised as white, black, Hispanic, Asian or other/mixed race. However, for the model with IL-6i, there were few outcomes within the race/ethnicity variable so we were unable to perform the model. Third, we used propensity score matching to further address potential confounding by indication. We estimated propensity scores for b/tsDMARD use based on age, sex, obesity, smoking, concomitant csDMARDs, glucocorticoid use/dose, number of comorbidities, disease activity, region and calendar time. Covariate balance between each b/tsDMARD drug class and TNFi was assessed using Love plots (online supplemental figures 1–4), which showed that most of the covariates were matched with an absolute standardised mean difference less than 0.1, denoting sufficient matching performance.23 Ordinal logistic regression was then performed after matching. Fourth, we repeated our primary analysis after excluding patients with a presumptive diagnosis of COVID-19. Presumptive cases were those that lacked one of the following: positive PCR or antigen test for SARS-CoV-2 or typical chest imaging findings. Fifth, we repeated the analysis but stratified by calendar time (before or after 15 June 2020 when RECOVERY trial’s results were announced) and by continent (North America or Europe) in case calendar time and geography may have influenced the results. Sixth, we used a revised version of the ordinal COVID-19 severity outcome that considered mechanical ventilation as its own category.
annrheumdis-2021-220418supp001.pdf (603.5KB, pdf)
We then repeated our primary analyses using dichotomised outcomes rather than the ordinal COVID-19 severity scale to investigate whether there were particular outcomes driving the associations we observed. For example, we investigated whether each b/tsDMARD was associated with hospitalisation (yes/no) compared with TNFi use.
We used the Brant test to assess whether the observed deviations from the ordinal logistic regression are larger than what could be attributed to chance alone. If the p values are greater than the alpha level of 0.05, then the covariates satisfy the proportional odds assumption. This assumption states that the estimate between each pair of outcomes across the response levels regardless of the partition that we consider. For abatacept and JAKis, both age and glucocorticoid dose violated the assumption, and for IL-6is and rituximab, age, gender and glucocorticoid dose violated the assumption. In order to address the lack of proportionality for these covariates, partial proportional odds models were run to relax this assumption for the respective covariates for each medication category (online supplemental table 1). We found that the estimates were similar when comparing the proportional odds models and the non-proportional odds model, so we reported the model without relaxing the assumption.
Results were considered statistically significant at two-sided p<0.05. Analyses were conducted in R V.4.0.2.
Results
Study sample and baseline characteristics
From a total of 6132 RA cases reported to the registry, we identified 2869 who were on abatacept (n=237), rituximab (n=364), IL-6i (n=317), JAKi (n=563) or TNFi (n=1388) at the time of clinical COVID-19 onset. The baseline clinical characteristics are shown in table 1. The sample was predominantly female (80.8%) and the mean age was 56.7 years (SD 13.4). Most patients were from Europe (51.8%) and North America (35.0%). Overall, 354 (12.3%) were obese, 582 (20.3%) were ever smokers, 810 (28.2%) were on glucocorticoids, 1409 (49.1%) were on concomitant csDMARDs, and 510 (17.8%) had moderate/high RA disease activity. Among b/tsDMARD users, rituximab users were more likely than TNFi users to have ILD (11.0% vs 1.4%) or a history of cancer (7.4% vs 0.9%); JAKi users were slightly more likely than TNFi users to be obese (15.1% vs 10.3%).
Table 1.
Baseline characteristics according to use of biologic or targeted synthetic disease-modifying antirheumatic drugs for rheumatoid arthritis at the time of COVID-19 onset
| Overall N=2869 |
Abatacept n=237 |
Rituximab n=364 |
IL-6 inhibitors n=317 |
JAK inhibitors n=563 |
TNF inhibitors n=1388 |
|
| Demographics | ||||||
| Mean age (years), SD | 56.7 (13.4) | 61.4 (14.0) | 58.0 (12.9) | 56.4 (12.0) | 58.0 (12.3) | 55.2 (14.0) |
| Female | 2316 (80.8) | 188 (79.3) | 299 (82.1) | 257 (81.3) | 470 (83.5) | 1102 (79.4) |
| Race/ethnicity | ||||||
| White | 1670 (69.0) | 78 (69.5) | 187 (64.5) | 169 (67.9) | 360 (73.2) | 829 (69.3) |
| Black | 113 (4.7) | 5 (3.2) | 14 (4.8) | 11 (4.4) | 22 (4.5) | 60 (5.0) |
| Hispanic | 472 (19.5) | 32 (20.8) | 66 (22.8) | 46 (18.5) | 79 (16.1) | 233 (19.5) |
| East Asian | 81 (3.3) | 8 (5.2) | 10 (3.4) | 12 (4.8) | 10 (2.0) | 37 (3.1) |
| Other | 85 (3.3) | 2 (1.3) | 13 (4.5) | 11 (4.4) | 21 (4.3) | 38 (3.2) |
| Continent | ||||||
| Europe | 1486 (51.8) | 103 (43.5) | 218 (59.9) | 183 (57.7) | 283 (50.3) | 699 (50.4) |
| North America | 1005 (35.0) | 105 (44.3) | 111 (30.5) | 83 (26.2) | 208 (36.9) | 498 (35.9) |
| South America | 276 (9.6) | 20 (8.4) | 23 (6.3) | 33 (10.4) | 55 (9.8) | 145 (10.4) |
| Other | 302 (10.5) | 9 (3.8) | 12 (3.3) | 18 (5.7) | 17 (3.0) | 46 (3.3) |
| Comorbidity count* | ||||||
| 0 | 1494 (52.1) | 113 (47.7) | 161 (44.2) | 161 (50.8) | 270 (48.0) | 789 (56.8) |
| 1 | 837 (29.2) | 70 (29.5) | 119 (32.7) | 99 (31.2) | 176 (31.3) | 373 (26.9) |
| 2 | 538 (18.8) | 54 (22.8) | 84 (23.1) | 57 (18.0) | 117 (20.8) | 226 (16.3) |
| Individual comorbidities | ||||||
| Hypertension | 983 (34.3) | 91 (38.4) | 121 (33.2) | 108 (34.1) | 221 (39.3) | 442 (31.8) |
| Cardiovascular disease | 247 (8.6) | 29 (12.2) | 36 (9.9) | 32 (10.1) | 51 (9.1) | 99 (7.1) |
| Diabetes | 356 (12.5) | 30 (12.8) | 54 (14.9) | 43 (13.6) | 74 (13.2) | 155 (11.3) |
| Chronic kidney disease | 98 (3.4) | 11 (4.7) | 11 (3.0) | 14 (4.4) | 22 (3.9) | 40 (2.9) |
| Lung disease† | 432 (15.2) | 41 (17.4) | 87 (24.0) | 44 (13.9) | 92 (16.4) | 168 (12.3) |
| Interstitial lung disease | 103 (3.6) | 15 (6.3) | 40 (11.0) | 15 (4.7) | 13 (2.3) | 20 (1.4) |
| Cancer | 40 (1.5) | 5 (2.5) | 27 (7.4) | 6 (2.2) | 5 (1.0) | 11 (0.9) |
| Obesity | 354 (12.3) | 31 (13.1) | 52 (14.3) | 43 (13.6) | 85 (15.1) | 143 (10.3) |
| Smoking status | ||||||
| Ever | 582 (20.3) | 104 (43.9) | 70 (19.2) | 57 (18.0) | 99 (17.6) | 300 (21.6) |
| Never | 1369 (47.7) | 56 (23.6) | 142 (39.0) | 152 (47.9) | 262 (46.5) | 694 (50.) |
| Missing | 918 (32.0) | 77 (32.5) | 137 (37.6) | 107 (33.8) | 202 (35.9) | 394 (28.4) |
| Concomitant RA medications | ||||||
| Any conventional synthetic DMARD | 1409 (49.1) | 118 (49.8) | 194 (53.3) | 102 (32.2) | 228 (40.5) | 767 (55.3) |
| Methotrexate | 1188 (41.4) | 92 (38.8) | 146 (40.1) | 91 (28.7) | 188 (33.4) | 671 (48.3) |
| Sulfasalazine | 136 (4.7) | 9 (3.8) | 26 (7.1) | 8 (2.5) | 18 (3.2) | 75 (5.4) |
| Hydroxychloroquine | 260 (9.1) | 25 (10.5) | 58 (15.9) | 18 (5.7) | 43 (7.6) | 116 (8.4) |
| Leflunomide | 176 (10.5) | 26 (11.0) | 49 (13.5) | 20 (6.3) | 29 (5.2) | 117 (8.4) |
| Glucocorticoid dose, median (IQR) | 5.0 (4.0–6.0) | 5.0 (4.0–5.5) | 5.0 (5.0–7.5) | 5.0 (4.5–7.0) | 5.0 (3.0–5.0) | 5.0 (5.0–7.0) |
| Categorical glucocorticoid use/dose | ||||||
| No glucocorticoid use | 1756 (61.2) | 120 (56.9) | 186 (51.1) | 173 (54.6) | 320 (63.5) | 957 (76.1) |
| Glucocorticoid >0–5 mg/day prednisone equivalent | 600 (20.9) | 68 (32.2) | 93 (25.5) | 69 (21.8) | 149 (29.6) | 221 (17.6) |
| Glucocorticoid 6–9 mg/day prednisone equivalent | 68 (2.4) | 8 (3.8) | 10 (2.7) | 15 (4.7) | 12 (2.4) | 23 (1.8) |
| Glucocorticoid ≥10 mg/day prednisone equivalent | 142 (4.9) | 15 (7.1) | 28 (7.7) | 19 (6.0) | 23 (4.6) | 57 (4.5) |
| Missing | 303 (10.6) | 26 (11.0) | 47 (12.9) | 41 (12.9) | 59 (10.5) | 130 (9.4) |
| RA disease activity by global physician assessment | ||||||
| Remission or low | 1949 (67.9) | 147 (74.2) | 226 (76.1) | 198 (77.3) | 388 (78.7) | 990 (81.5) |
| Moderate or high | 510 (17.8) | 51 (25.8) | 71 (23.9) | 58 (22.7) | 105 (21.3) | 225 (18.5) |
| Missing | 410 (14.3) | 39 (16.5) | 67 (18.4) | 61 (19.2) | 70 (12.4) | 173 (12.5) |
| Confirmed COVID-19 | 2333 (81.3) | 201 (84.8) | 304 (83.5) | 244 (77.0) | 475 (84.4) | 1109 (79.9) |
n (%) presented unless otherwise specified.
*Comorbidity count included diabetes, lung disease and chronic kidney disease.
†Interstitial lung disease, chronic obstructive pulmonary disease, asthma or other lung disease.
DMARDs, disease-modifying antirheumatic drugs; IL-6, interleukin 6; JAK, Janus kinase; RA, rheumatoid arthritis; TNF, tumour necrosis factor.
COVID-19 outcomes
Outcomes according to the COVID-19 severity scale are shown in table 2. The majority of patients (78.6%) were not hospitalised, 137 (4.8%) were hospitalised without oxygenation, 319 (11.1%) were hospitalised with any oxygen or ventilation requirement, and 157 (5.5%) died. Among rituximab users, 80 (22.0%) required hospitalisation with any oxygen or ventilation and 54 (14.8%) died compared with 103 (7.4%) and 36 (2.6%) TNFi users, respectively. Among JAKi users, 86 (15.3%) were hospitalised with oxygen/ventilation and 40 (7.1%) died. Only 9 (2.8%) patients on baseline IL-6i died.
Table 2.
Frequencies and proportions of outcomes in the ordinal COVID-19 severity scale according to baseline use of biologic or targeted synthetic disease-modifying antirheumatic drug for patients with rheumatoid arthritis at the time of COVID-19 onset (N=2869)
| COVID-19 severity scale | Overall N=2869 n (%) |
Abatacept n=237 n (%) |
Rituximab n=364 n (%) |
IL-6 inhibitors n=317 n (%) |
JAK inhibitors n=563 n (%) |
TNF inhibitors n=1388 n (%) |
| Not hospitalised | 2256 (78.6) | 181 (76.4) | 210 (57.7) | 271 (85.5) | 409 (72.6) | 1185 (85.4) |
| Hospitalised without oxygenation | 137 (4.8) | 12 (5.1) | 20 (5.5) | 13 (4.1) | 28 (5.0) | 64 (4.6) |
| Hospitalised with any oxygen or ventilation | 319 (11.1) | 26 (11.0) | 80 (22.0) | 24 (7.6) | 86 (15.3) | 103 (7.4) |
| Death | 157 (5.5) | 18 (7.6) | 54 (14.8) | 9 (2.8) | 40 (7.1) | 36 (2.6) |
IL-6, interleukin 6; JAK, Janus kinase; TNF, tumour necrosis factor.
Associations of b/tsDMARDs with COVID-19 severity
The multivariable ordinal logistic regression model is shown in table 3. Compared with TNFi users, rituximab users had 4.15 (95% CI 3.40 to 3.80) greater odds of worse COVID-19 severity as compared with patients taking TNFi, while JAKi users had 2.06 (95% CI 1.60 to 2.65) greater odds of worse COVID-19 severity. No significant associations were found with respect to abatacept or IL-6i compared with TNFi in the primary analysis.
Table 3.
Results of primary and sensitivity analyses investigating the associations of baseline use of biologic or targeted synthetic disease-modifying antirheumatic drugs with COVID-19 severity (N=2869)
| Abatacept | Rituximab | IL-6i | JAKi | TNFi | |||||
| OR (95% CI) | P value | OR (95% CI) | P value | OR (95% CI) | P value | OR (95% CI) | P value | Ref | |
| Unadjusted | 1.88 (1.35 to 2.63) | <0.01 | 4.63 (3.60 to 5.96) | <0.01 | 1.00 (0.71 to 1.41) | 0.99 | 2.28 (1.80 to 2.88) | <0.01 | Ref |
| Age-adjusted and sex-adjusted | 1.40 (0.99 to 1.99) | 0.06 | 4.45 (3.43 to 5.77) | <0.01 | 1.06 (0.68 to 1.37) | 0.84 | 2.10 (1.64 to 2.68) | <0.01 | Ref |
| Multivariable-adjusted (primary analysis) | 1.26 (0.88 to 1.80) | 0.21 | 4.15 (3.16 to 5.44) | <0.01 | 0.81 (0.56 to 1.18) | 0.55 | 2.06 (1.60 to 2.65) | <0.01 | Ref |
| Confirmed cases only* | 1.14 (0.77 to 1.68) | 0.52 | 4.25 (3.17 to 5.69) | <0.01 | 0.74 (0.49 to 1.11) | 0.15 | 2.05 (1.57 to 2.69) | <0.01 | Ref |
| Excluding patients with ILD or cancer† | 1.18 (0.79 to 1.76) | 0.43 | 4.34 (3.23 to 5.82) | <0.01 | 0.81 (0.54 to 1.21) | 0.30 | 2.14 (1.64 to 2.79) | <0.01 | Ref |
| Restricted to USA and additionally adjusted for race‡ | 1.16 (0.79 to 1.69) | 0.45 | 4.77 (3.57 to 6.38) | <0.01† | ¶ | ¶ | 2.86 (1.76 to 4.65) | <0.01† | Ref |
| Propensity score-matched§ | 1.60 (1.02 to 2.51) | 0.04 | 4.70 (3.31 to 6.65) | <0.01 | 0.76 (0.46 to 1.23) | 0.26 | 2.09 (1.50 to 2.90) | <0.01 | Ref |
The effect size is the odds of being one level higher on the ordinal COVID-19 severity scale than the reference group (TNFi users).
Adjusted for age, sex, region, calendar time, obesity, smoking, concomitant csDMARD use, glucocorticoid use/dose, comorbidity count, hypertension/cardiovascular disease, interstitial lung disease, cancer and rheumatoid arthritis disease activity except as otherwise indicated.
*n=2333 in the analysis analysing only confirmed COVID-19 cases.
†n=2704 in the analysis excluding ILD and cancer.
‡n=868 in the USA-only analysis.
§n for each pair of propensity score-matched analyses: abatacept: 236, TNFi: 1376; rituximab: 364, TNFi: 1382; IL-6i: 313, TNFi: 1387; JAKi: 560, TNFi: 1379.
¶Due to the small number of events in the covariate of race, the IL-6i model could not be analysed.
csDMARDs, conventional synthetic disease-modifying antirheumatic drugs; ILD, interstitial lung disease; IL6i, interleukin 6 inhibitor; JAKi, Janus kinase inhibitor; Ref, reference; TNFi, tumour necrosis factor inhibitors.
Sensitivity analyses
Sensitivity analyses of the drug class comparisons are shown in table 3. After excluding patients with ILD or cancer, the association between rituximab with poor COVID-19 outcomes when compared with TNFi use remained strong (OR 4.34, 95% CI 3.23 to 5.82). Among patients with RA in the USA, results were also similar when additionally adjusting for race/ethnicity. We also performed a propensity score-matched analysis instead of multivariable ordinal logistic regression. The sample for each propensity score-matched analysis is illustrated in online supplemental figure 5. Rituximab users (OR 3.36, 95% CI 2.11 to 5.34) and JAKi users (OR 1.56, 95% CI 1.01 to 2.42) had increased COVID-19 severity compared with TNFi users in this analysis. In the propensity score-matched analysis, abatacept had an OR of 1.60 (95% CI 1.02 to 2.51) for the ordinal COVID-19 severity outcome compared with TNFi. IL-6i use was not associated with COVID-19 severity in any of the analyses. Brant tests indicated that the proportional odds assumption did not hold for propensity score models; therefore, partial proportional odds models were used and confirmed that the effect estimates remained consistent (data not shown).
When stratified by calendar time (before or after 15 June 2020) and restricted to Europe or North America, the results were similar (online supplemental table 2).
Individual COVID-19 outcomes
We also performed analyses for each binary level of the COVID-19 severity scale (table 4). Rituximab and JAKi use were each associated with increased odds for each COVID-19 outcome compared with TNFi use. For example, rituximab use had increased odds for hospitalisation (OR 4.53, 95% CI 3.32 to 6.18) as well as death (OR 4.57, 95% CI 3.32 to 9.01) compared with TNFi use. JAKi use was associated with all outcomes considered, including hospitalisation requiring any oxygen or ventilation or death (OR 1.55, 95% CI 1.04 to 2.18) and death (OR 2.04, 95% CI 1.58 to 2.65) compared with TNFi. In these analyses, there were no statistically significant associations between abatacept or IL-6i use and the dichotomised outcomes when compared with TNFi use.
Table 4.
Multivariable* OR of biologic or targeted synthetic disease-modifying antirheumatic drugs at each binary level of the COVID-19 severity scale (N=2869)
| COVID-19 outcome | Abatacept | Rituximab | IL-6 inhibitors | JAK inhibitors | TNF inhibitors | ||||
| OR (95% CI) |
P value | OR (95% CI) |
P value | OR (95% CI) |
P value | OR (95% CI) |
P value | ||
| Hospitalised | 1.18 (0.76 to 1.82) | 0.47 | 4.53 (3.32 to 6.18) | <0.01 | 0.84 (0.53 to 1.33) | 0.45 | 2.40 (1.78 to 3.24) | <0.01 | Ref |
| Hospitalised with oxygenation/ventilation or death | 1.12 (0.70 to 1.81) | 0.63 | 2.87 (2.03 to 4.06) | <0.01 | 0.72 (0.43 to 1.20) | 0.20 | 1.55 (1.04 to 2.18) | 0.01 | Ref |
| Death | 1.46 (0.72 to 2.89) | 0.30 | 4.57 (3.32 to 9.01) | <0.01 | 1.13 (0.50 to 2.59) | 0.77 | 2.04 (1.58 to 2.65) | <0.01 | Ref |
| Mechanical ventilation (restricted to only hospitalised patients, n=613) | 1.41 (0.94 to 2.10) | 0.09 | 4.05 (3.08 to 5.33) | <0.01 | 0.75 (0.51 to 1.10) | 0.14 | 2.03 (1.56 to 2.62) | <0.01 | Ref |
| Mechanical ventilation or death | 1.14 (0.78 to 1.66) | 0.50 | 4.44 (3.39 to 5.82) | <0.01 | 0.74 (0.50 to 1.09) | 0.12 | 2.02 (1.56 to 2.61) | <0.01 | Ref |
*Adjusted for age, sex, region, calendar time, obesity, smoking, concomitant csDMARD use, glucocorticoid use/dose, comorbidity count, hypertension/cardiovascular disease, interstitial lung disease, cancer and rheumatoid arthritis disease activity.
csDMARD, conventional synthetic disease-modifying antirheumatic drug; IL-6, interleukin 6; JAK, Janus kinase; Ref, reference; TNF, tumour necrosis factor.
We considered a revised version of the ordinal outcome that included mechanical ventilation as a separate level. There were relatively few patients who survived after requiring mechanical ventilation (online supplemental table 2). Results were similar using this revised ordinal outcome (online supplemental tables 3 and 4).
Discussion
Among patients with RA on b/tsDMARDs at the onset of COVID-19, rituximab and JAKi users were at increased odds for worse COVID-19 outcomes compared with TNFi users. In contrast, we did not find an association between abatacept or IL-6i use with worse COVID-19 outcomes when compared with TNFi users. These observations can inform decision making for providers and patients during the ongoing COVID-19 pandemic. Given the association between rituximab and JAKi use with poor outcomes, vaccination and public health measures such as mask wearing and social distancing for COVID-19 risk mitigation remain paramount. In addition, other specific interventions (eg, monoclonal antibody treatment) might be considered in these patients with COVID-19 exposure or early infection.24
Our observations, which use the largest sample of individuals with RA and COVID-19 assembled to date, regarding rituximab exposure confirm findings from prior studies suggesting an association between baseline use of B cell depleting therapies and worse COVID-19 outcomes in people with rheumatic diseases12 25 26 and multiple sclerosis.27 We also expand on prior observations using the C19-GRA and EULAR databases by evaluating the association of rituximab with COVID-19 severity rather than only mortality and by using an alternative reference group (TNFi rather than methotrexate) and performing propensity score analyses to further address confounding by indication. By focusing on a single disease, we also were able to identify a novel association of JAKis with COVID-19 severity. Mechanistically, the impact of B cell depletion on antibody production would be expected to impair the immune system’s normal response to a viral infection. Indeed, the antibody response to COVID-19 is critical for controlling the initial infection and preventing reinfection.28 We lacked details regarding the timing of rituximab exposure in relation to the COVID-19 infection or the duration of B cell depletion at the time of infection, which may be particularly relevant when considering the risk of a poor outcome following rituximab exposure. It is also possible that glucocorticoids given as a premedication to rituximab infusions may have contributed to the increased risk of poor COVID-19 outcomes in patients with RA on rituximab. While the results were robust to several sensitivity analyses, it is possible that the result could be confounded by factors such as unrecognised ILD.
Our findings are of particular interest given recent clinical trials and observational studies suggesting that IL-6i6–8 29–32 and JAKi9 may improve outcomes for patients in the general population with COVID-19. We found no association of baseline IL-6i use in RA with COVID-19 severity compared with TNFi use. In contrast, while baricitinib treatment may have some benefit on time to recovery for patients with more severe COVID-19,9 we observed worse outcomes associated with baseline use of JAKi. This was also suggested in a recent population-based study investigating RA and other inflammatory joint diseases in Sweden.25 Glucocorticoids are known to have benefits when initiated for moderate-to-severe COVID-19, but are also associated with worse outcomes among those on baseline glucocorticoids at the time of infection,5 12 although this may be explained by residual disease activity.33 Therefore, the timing of JAKi use relative to the COVID-19 disease course may explain our findings. Similar to glucocorticoids, baseline use of JAKi at the time of SARS-CoV-2 infection may enhance viral reproduction and dampen a healthy immune response, while JAKi initiation at clinical deterioration may dampen an aberrant systemic inflammatory response. Alternatively, there may be relevant differences in COVID-19 outcomes depending on the type of JAKi used given that JAKis like tofacitinib, baricitinib and upadacitinib target different Janus kinases. We were unable to perform analyses of each individual JAKi since these were collected as a class. While the primary analysis found no association of abatacept with COVID-19 severity, there was a statistical association in the propensity score-matched analysis. Further research is needed on the safety of abatacept for infection risk and severity since its mechanism of action may impair adaptive immune response.
Our study has a number of strengths, including the international nature of the registry and the large sample size. Additionally, we used an active comparator (TNFi), which was also a b/tsDMARD in a single rheumatic disease, as well as two different modelling approaches (multivariable logistic regression and propensity score matching) among other sensitivity analyses to account for confounding by indication and to confirm the robustness of our findings. Our observations expand on prior general population and RA cohort studies that identified older age, greater comorbidity burden and other factors associated with worse COVID-19 and must also be considered when assessing an individual’s risk.
Our study also has certain limitations. First, the Global Rheumatology Alliance and EULAR registries are voluntary and require a provider to submit the details of a case, perhaps biasing our sample towards more severe cases. As such, the proportion of events reported across exposure groups may be an overestimate of that observed among all patients with RA in real-world practice and should be interpreted in that context. However, the effect size estimates do have clinical interpretation in potentially identifying patients with RA who could be susceptible to poor COVID-19 outcomes. While we designed the study to limit the potential impact of selection bias and confounding by indication by examining advanced therapies in a single rheumatic disease, it is possible that selective reporting could have varied across different b/tsDMARD classes as the exposure of interest. This potential bias may have caused an upward deflection in the effect size estimate if more severe cases of a particular b/tsDMARD class were systematically reported compared with others, and this could contribute to the findings that we report. We further mitigated this possibility by adjusting for differences in concomitant medication use, disease activity and comorbidities, as well as performing an analysis removing patients with ILD or cancer. Our findings remained when we excluded presumptive cases of COVID-19. Second, although we were able to adjust for a number of potential confounders of our observed associations, there is the potential for residual unmeasured confounding. Analysing only patients on b/tsDMARD may have helped minimise some unmeasured confounding related to access to care since all analysed patients with RA were able to receive these targeted medications. In addition, the consistent results observed in sensitivity analyses excluding patients with ILD or cancer who may be more likely to receive rituximab support the robustness of our results. However, we did not have data available on RA duration or previous RA medications (eg, previous TNFi use in patients on other classes of b/tsDMARDs), which may have affected the results. Medications were collected by DMARD class, so we were unable to compare individual medications within the same class. However, the goal of the study was to compare different biologic mechanisms of action for COVID-19 severity. Additionally, it is also possible that TNFi use may protect against severe COVID-19 outcomes. Thus, these results should be interpreted cautiously and additional studies are needed to confirm our observed associations. Third, while we leveraged the largest cohort of patients with rheumatic disease with COVID-19, a somewhat small number of outcomes of interest occurred in some subgroups, which may have limited our power to detect significant differences among abatacept users, in particular. In addition, we were unable to investigate individual JAKi or TNFi. Finally, we did not examine medication changes after COVID-19 onset since this occurred after baseline and may have mediated the relationship we report. Most of the drugs have lengthy biologic effects (especially rituximab), while JAKis have short half-lives. Some clinicians may have chosen to continue IL-6is after COVID-19 onset, as suggested by the American College of Rheumatology.34 Future studies are needed to investigate the association of medication changes with COVID-19 outcomes.
In conclusion, use of rituximab or JAKi, but not abatacept or IL-6i, at the time of COVID-19 infection was associated with worse COVID-19 outcomes compared with TNFi among patients with RA. Additional studies are warranted to confirm these observations. Strategies are needed to improve outcomes following COVID-19 RA on rituximab or JAKis.
Acknowledgments
We wish to thank all rheumatology providers who entered data into the registry.
Footnotes
Handling editor: Josef S Smolen
Twitter: @jeffsparks, @zach_wallace_md, @carmona_loreto, @saskiaamber, @gponsestel, @kmdsilvaMD, @rthritis, @Mota_licia_reum, @PhilippeDieude, @ElenaNikiUK, @mugartegil, @Akpabioakanimo, @hausmannmd, @rheum_cat, @emilysirotich, @philipcrobinson, @pedrommcmachado
JAS and ZSW contributed equally.
Correction notice: This article has been corrected since it published Online First. Collaborator names have been updated.
Collaborators: Brahim Dahou (Association Rhumatologues Algériens Privés (ARAP), Algeria), Rosana Quintana, Gimena Gómez, Karen Roberts, Roberto Miguel Baez, Vanessa Castro Coello, María J Haye Salinas, Federico Nicolas Maldonado, Alvaro Andres Reyes Torres, Gelsomina Alle, Romina Tanten, Hernán Maldonado Ficco, Romina Nieto, Carla Gobbi, Yohana Tissera, Cecilia Pisoni, Alba Paula, Juan Alejandro Albiero, Maria Marcela Schmid, Micaela Cosatti, Maria Julieta Gamba, Carlevaris Leandro, María Alejandra Cusa, Noelia German, Veronica Bellomio, Lorena Takashima, Mariana Pera, Karina Cogo, Maria Soledad Gálvez Elkin, María Alejandra Medina, Veronica Savio, Ivana Romina Rojas Tessel, Rodolfo Perez Alamino, Marina Laura Werner, Sofía Ornella, Luciana Casalla, Maria de la Vega, María Severina, Mercedes García, Luciana Gonzalez Lucero, Cecilia Romeo, Sebastián Moyano, Tatiana Barbich, Ana Bertoli, Andrea Baños, Sandra Petruzzelli, Carla Matellan, Silvana Conti, Ma Alicia Lazaro, Gustavo Fabián Rodriguez Gil, Fabian Risueño, Maria Isabel Quaglia, Julia Scafati, Natalia Lili Cuchiaro, Jonathan Eliseo Rebak, Susana Isabel Pineda, María Elena Calvo, Eugenia Picco, Josefina Gallino Yanzi, Pablo Maid, Debora Guaglianone, Julieta Silvana Morbiducci, Sabrina Porta, Natalia Herscovich, José Luis Velasco Zamora, Boris Kisluk, Maria Sol Castaños Menescardi, Rosana Gallo, María Victoria Martire, Carla Maldini, Cecilia Goizueta, Sabrina Solange de la vega Fernandez, Carolina Aeschlimann Argentina, Gisela Subils (Argentine Society of Rheumatology, Argentina), Eva Rath (Hanusch Krankenhaus, Vienna, Austria), Yves Piette (AZ Sint-Jan Brugge, Belgium), Mieke Devinck (AZ Sint-Lucas Brugge, Belgium), Bea Maeyaert (AZ Sint-Lucas Brugge, Hospital Universitário Pedro Ernesto Universidade do, Belgium), Francinne Machado Ribeiro (Estado do Rio de Janeiro, Brazil), Sandra Lucia Euzebio Ribeiro (Federal University of Amazonas, Universidade Federal De São Paulo Escola Paulista de, Brazil), Marcelo Pinheiro (Medicina e Escola Paulista de Enfermagem, Brazil), Sebastián Ibáñez (Clínica Alemana de Santiago, Chile), Anne-Marie Chassin-Trubert (Complejo Hospitalario San José, Chile), Lingli Dong (Tongji Hospital, China), Lui Cajas (Clinica Universitaria Colombia - Centro Medico Providencia Sanitas, Colombia), Marko Barešić (University Hospital Center Zagreb, Croatia), Branimir Anić (Div Clin Immunol Rheumatol; Dept Int Med, School of Med Zagreb, University Hospital Center Zagreb, Croatia), Melanie-Ivana Čulo (University Hospital Dubrava, Zagreb, Croatia), Tea Ahel Pavelić (Clinical Hospital Center Rijeka, Croatia), Kristina Kovačević (Stranski University hospital Osijek, Croatia), Boris Karanovic (UHC Zagreb, Croatia), Jiri Vencovsky (Institute of Rheumatology, Prague, Czechia), Marta Píchová (Medipont plus s.ro., České Budějovice, Czechia), Maria Filkova (Institute of Rheumatology, Prague, Czechia), Hesham Hamoud (Al Azhar University Hospitals, Egypt), Dimitrios Vassilopoulos (Hippokration General Hospital, Athens, Greece), Gabriela Maria Guzman Melgar (Hospital del Valle, Honduras, Honduras), Ho So (Chinese University of Hong Kong, Hong Kong), Márta Király (Petz Aladár University Teaching Hospital, Győr, Hungary), Mahdi Vojdanian (Iran Rheumatology Center, Iran), Alexandra Balbir-Gurman (Rambam Rheumatology Institute, Haifa, Israel), Fatemah Abutiban (Kuwait Rheumatology Association, Kuwait), Julija Zepa, Inita Bulina (Pauls Stradins Clinical University Hospital, Riga, Latvia), Loreta Bukauskiene (Klaipeda university hospital, Lithuania), Beatriz Elena Zazueta-Montiel (Centro Medico del Angel, Mexico), Angel Alejandro Castillo-Ortiz (Centro Medico Las Americas, Mexico), Erick Zamora-Tehozol (Centro Medico Pensiones, Mexico), David Vega-Morales (Hospital General de Zona #17, Instituto Nacional de Ciencias Médicas y Nutrición, Mexico), Diana Cervántes Rosete, Eduardo Martín-Nares, Tatiana Sofia Rodriguez-Reyna (Salvador Zubirán, Instituto Nacional de Ciencias Médicas y Nutrición, Mexico), Marina Rull Gabayet (Salvador Zubirán, Mexico), Deshiré Alpízar-Rodríguez (Mexican College of Rheumatology, Mexico), Fedra Irazoque (Private Practice, Mexico), Xochitl Jimenez (Centro Medico Naval, Mexico), Lenny Geurts-van Bon (Ziekenhuisgroep Twente, The Netherlands), Theo Zijlstra (Isala Hospital, Zwolle The Netherlands), Monique Hoekstra (Isala Hospital, Zwolle The Netherlands), Nasra Al-Adhoubi (Royal Hospital, Oman), Babur Salim (Fauji Foundation Hospital, Pakistan), Enrique Giraldo (Complejo Hospitalario, Panama), Ariel Salinas (Hospital Essalud Alberto Sabogal Sologuren, Universidad Científica del Sur-Hospital Guillermo, Peru), Manuel Ugarte-Gil (Almenara Irigoyen, Peru), Jarosław Nowakowski (University Hospital, Krakow, Poland), Samar Al-Emadi (Hamad Medical Corporation, Qatar), Richard Conway (St James' Hospital, Dublin, Republic of Ireland), Rachael Flood (Tallaght University Hospital, Republic of Ireland), Geraldine McCarthy (Mater Misericordiae University Hospital, Republic of Ireland), Ioana Felea, Ileana Filipescu, Simona Rednic (County Emergency Hospital, Cluj Napoca, Romania), Laura Groseanu (Sf Maria Clinical Hospital, Bucharest, Romania), Maria Magdelena (Tamas County Emergency Hospital, Cluj Napoca, Romania), Vanda, Mlynarikova (National Institute of Rheumatic Diseases, Piešťany, Slovak Republic), Martina Skamlova (FNSPFDR, Banská Bystrica, Slovak Republic), Martin Zlnay, Dagmar Mičeková (National Institute of Rheumatic Diseases, Piešťany, Slovak Republic), Lubica Capova (University Hospital, Bratislava, Slovak Republic), Zelmira Macejova (University Hospital, Košice, Slovak Republic), Emőke Šteňová (University Hospital Bratislava, Slovak Republic), Helena Raffayova (National Institute of Rheumatic Diseases, Piešťany, Slovak Republic), Gabriela Belakova (Medman s.r.o., Martin, Slovak Republic), Eva Strakova (Faculty hospital Prešov, Slovak Republic), Marieta Senčarová (Louis Pasteur University Hospital, Košice, Slovak Republic), Soňa Žlnayová (Poliklinika MarMedico, s.r.o., Nové Mesto nad Váhom Slovak Republic súkromná reumatologická ambulancia, Vranov nad, Slovak Republic), Anna Sabová (Topľou, Slovak Republic), Daniela Spisakova (University Hospital od L. Pasteur Kosice, Slovak Republic), Mária Oetterová (Safarik University hospital, Kosice, Slovak Republic), Olga Lukacova (National Institute of Rheumatic Diseases, Piešťany, Slovak Republic), Martina Bakosova (UNB Nemocnica Stare Mesto, Bratislava, Slovak Republic), Alojzija Hocevar (UMC Ljubljana, Slovenia), Natalia de la Torre-Rubio (Hospital Universitario Puerta de Hierro Majadahonda, Spain), Juan José Alegre Sancho (Hospital Universitari Dr Peset, Valencia, Spain), Montserrat Corteguera Coro (Complejo Asistencial Avila, Spain), Juan Carlos Cobeta Garcia (Hospital Ernest Lluch, Calatayud, Spain), Maria Carmen Torres Martin (Hospital Nuestra Senora Sonsoles, Avila, Spain), Jose Campos (Hospital Universitario Puerta de Hierro, Spain), Jose A Gomez Puerta (Hospital Clinic Barcelona, Spain), Gozd Kubra Yardımcı, Servet Akar (Hacettepe University Faculty of Medicine, Ankara, Izmir Katip Celebi University Atatürk Training and Research Hospital, Izmir, Turkey), Ozan Cemal Icacan (Bakırköy Dr. Sadi Konuk Research And Training Hospital, Istanbul, Turkey), Selda ÇELİK (Bakirkoy Dr Sadi Konuk Educational And Research Hospital, Rheumatology Department, Turkey), Viktoriia Vasylets (Multifield Medical Centre, Odessa, Ukraine), Su-Ann Yeoh (University College London Hospital, London, UK), Claire Vandevelde (Leeds Teaching Hospitals NHS Trust, UK), Sasha Dunt (Countess of Chester NHS Foundation Trust, UK), Jane Leeder (Norfolk & Norwich University Hospital, UK), Elizabeth Macphie (Lancashire and South Cumbria NHS Foundation Trust, UK), Rosaria Salerno (King's College Hospital, UK), Christine Graver (Hampshire Hospitals NHS Trust, UK), Katie Williams (York District Hospital, UK), Sheila O'Reilly (Royal Derby Hospital, UK), Kirsty Devine (York/Scarborough Hospitals, UK), Jennifer Tyler (Royal United Hospital, Bath, UK), Elizabeth Warner (Lister Hospital, UK), James Pilcher (University Hospital Lewisham, UK), Samir Patel (Queen Elizabeth hospital Woolwich, UK), Elena Nikiphorou (King's College Hospital, UK), Laura Chadwick (St Helens & Knowsley NHS Foundation Trust, UK), Caroline Mulvaney Jones (Llandudno Hospital, UK), Beverley Harrison (Salford Royal NHS FT, UK), Lucy Thornton (Bradford Royal Infirmary, UK), Diana O'Kane (RNHRD at Royal United Hospital Bath, UK), Lucia Fusi (King's College Hospital, UK), Audrey Low (Salford Royal NHS FT, UK), Sarah Horton (Minerva Health Centre, UK), Shraddha Jatwani (Albert Einstein Medical Center, PA, USA), Sara Baig, Hammad Bajwa, Vernon Berglund, Angela Dahle, Walter Dorman, Jody Hargrove, Maren Hilton, Nicholas Lebedoff, Susan Leonard, Jennifer Morgan, Emily Pfeifer, Archibald Skemp, Jeffrey Wilson, Anne Wolff (Arthritis and Rheumatology Consultants, PA, USA), Eduardo Cepeda (Austin Diagnostic Clinic, USA), Derrick Todd (Brigham and Women's Hospital, USA), Denise Hare (Capital Health Rheumatology, USA), Cassandra Calabrese (Cleveland Clinic, USA), Christopher Adams (East Alabama Medical Center, USA), Arezou Khosroshahi (Emory University, USA), Adam Kilian (George Washington University, USA), Douglas White, Melanie Winter (Gundersen Health System, USA), Theodore Fields (Hospital for Special Surgery, USA), Caroline Siegel (Hospital for Special Surgery, USA), Nicole Daver (Institute of Rheumatic and Autoimmune Diseases, USA), Melissa Harvey (Institute of Rheumatic and Autoimmune Diseases, USA), Neil Kramer (Institute of Rheumatic and Autoimmune Diseases, USA), Concetta Lamore (Institute of Rheumatic and Autoimmune Diseases, USA), Suneya Hogarty (Integrative Arthritis and Pain Consultants, USA), Karen Yeter (Kaiser Permanente, USA), Leanna Wise (Los Angeles County + USC Medical Center, USA), Faizah Siddique (Loyola University Medical Center, USA), Byung Ban (Medstar Georgetown University Hospital, USA), Tamar Tanner (Montefiore Medical Center, USA), Eric Ruderman (Northwestern Memorial, USA), William Davis, Robert Quinet, Evangeline Scopelitis, Karen Toribio Toribio, Tameka Webb-Detiege, Jerald Zakem (Ochsner Medical Center Rheumatology Department, USA), Khurram Abbass, Gilbert Kepecs (Private Practice, USA), Lilliam Miranda (Rheumatology Center INC, USA), Michael Guma, Ammar Haikal, Sushama Mody (Riverside Medical Group, USA), Daric Mueller (Shores Rheumatology PC, USA), Arundathi Jayatilleke (Temple University Hospital, USA), JoAnn Zell (University of Colorado, USA), Alison Bays (University of Washington, Seattle, USA), Kathryn Dao, Ezzati Fatemeh (UT Southwestern Medical Center, USA), Deborah Parks (Washington University Div of Rheumatology, USA), David Karp, Guillermo Quiceno (UT Southwestern Medical Center, USA).
Contributors: JAS, ZSW, AS, MG and JY had access to the study data, developed the figures and tables, and vouch for the data and analyses. AS and MG performed the statistical analyses and contributed to data quality control, data analysis and interpretation of data. JAS, ZSW, AMS, MG, ZI, KLH, AS, LG, LC, EFM, SL-T, LT, SR, PK, GS, LJ, SAE, LW, ELG, AD-G, MOV-A, GJP-E, CAI, GAB, TY-TH, KMD’S, NJP, PD, EN, VLK, NS, MFU-G, BW, AA, RT, SB, WC, RG, JH, JL, ES, PS, PCR, PMM and JY contributed to data collection, data analysis and interpretation of data. JAS, ZSW and JY directed the work, designed the data collection methods, contributed to data collection, data analysis and interpretation of data, and had final responsibility for the decision to submit for publication. All authors contributed intellectual content during the drafting and revision of the work and approved the final version to be published.
Funding: The study received support from the American College of Rheumatology (ACR) and European Alliance of Associations for Rheumatology (EULAR).
Disclaimer: The views expressed here are those of the authors and the participating members of the COVID-19 Global Rheumatology Alliance and do not necessarily represent the views of the American College of Rheumatology (ACR), the European Alliance of Associations for Rheumatology (EULAR), the (UK) National Health Service (NHS), the National Institute for Health Research (NIHR) or the (UK) Department of Health, or any other organisation.
Competing interests: JAS is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (grant numbers K23 AR069688, R03 AR075886, L30 AR066953, P30 AR070253 and P30 AR072577), the Rheumatology Research Foundation (K Supplement Award and R Bridge Award), the Brigham Research Institute, and the R Bruce and Joan M Mickey Research Scholar Fund. JAS has received research support from Amgen and Bristol-Myers Squibb and performed consultancy for Bristol-Myers Squibb, Gilead, Inova, Janssen and Optum, unrelated to this work. ZSW reports grant support from Bristol-Myers Squibb and Principia/Sanofi and performed consultancy for Viela Bio and MedPace, outside the submitted work. His work is supported by grants from the National Institutes of Health. MG is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (grant numbers K01 AR070585 and K24 AR074534; JY). KLH reports she has received speaker’s fees from AbbVie and grant income from BMS, UCB and Pfizer, all unrelated to this study. KLH is also supported by the NIHR Manchester Biomedical Research Centre. LC has not received fees or personal grants from any laboratory, but her institute works by contract for laboratories such as, among other institutions, AbbVie Spain, Eisai, Gebro Pharma, Merck Sharp & Dohme España, Novartis Farmaceutica, Pfizer, Roche Farma, Sanofi Aventis, Astellas Pharma, Actelion Pharmaceuticals España, Grünenthal and UCB Pharma. LG reports research grants from Amgen, Galapagos, Janssen, Lilly, Pfizer, Sandoz and Sanofi; consulting fees from AbbVie, Amgen, BMS, Biogen, Celgene, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Samsung Bioepis, Sanofi Aventis and UCB, all unrelated to this study. EFM reports that LPCDR received support for specific activities: grants from AbbVie, Novartis, Janssen-Cilag, Lilly Portugal, Sanofi, Grünenthal, MSD, Celgene, Medac, Pharma Kern and GAfPA; grants and non-financial support from Pfizer; and non-financial support from Grünenthal, outside the submitted work. AS reports grants from a consortium of 13 companies (among them AbbVie, BMS, Celltrion, Fresenius Kabi, Lilly, Mylan, Hexal, MSD, Pfizer, Roche, Samsung, Sanofi Aventis and UCB) supporting the German RABBIT register, and personal fees from lectures for AbbVie, MSD, Roche, BMS and Pfizer, outside the submitted work. AD-G has no disclosures relevant to this study. His work is supported by grants from the Centers for Disease Control and Prevention and the Rheumatology Research Foundation. KMD is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (T32-AR-007258) and the Rheumatology Research Foundation. NJP is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (T32-AR-007258). PD has received research support from Bristol-Myers Squibb, Chugai and Pfizer, and performed consultancy for Boehringer Ingelheim, Bristol-Myers Squibb, Lilly, Sanofi, Pfizer, Chugai, Roche and Janssen, unrelated to this work. NS is supported by the RRF Investigator Award and the American Heart Association. MFU-G reports grant support from Janssen and Pfizer. SB reports no competing interests related to this work. He reports non-branded consulting fees for AbbVie, Horizon, Novartis and Pfizer (all <$10 000). RG reports no competing interests related to this work. Outside of this work she reports personal and/or speaking fees from AbbVie, Janssen, Novartis, Pfizer and Cornerstones, and travel assistance from Pfizer (all <$10 000). JH reports no competing interests related to this work. He is supported by grants from the Rheumatology Research Foundation and the Childhood Arthritis and Rheumatology Research Alliance. He has performed consulting for Novartis, Sobi and Biogen, all unrelated to this work (<$10 000). JL has received research funding from Pfizer, outside the submitted work. ES is a Board Member of the Canadian Arthritis Patient Alliance, a patient-run, volunteer-based organisation whose activities are largely supported by independent grants from pharmaceutical companies. PS reports no competing interests related to this work. He reports honorarium for doing social media for American College of Rheumatology journals (<$10 000). PMM has received consulting/speaker’s fees from AbbVie, BMS, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche and UCB, all unrelated to this study (all <$10 000). PMM is supported by the National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre (BRC). PCR reports no competing interests related to this work. Outside of this work he reports personal consulting and/or speaking fees from AbbVie, Eli Lilly, Janssen, Novartis, Pfizer and UCB, and travel assistance from Roche (all <$10 000). JY reports no competing interests related to this work. Her work is supported by grants from the National Institutes of Health, Centers for Disease Control, and the Agency for Healthcare Research and Quality. She has performed consulting for Eli Lilly and AstraZeneca, unrelated to this project.
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Contributor Information
COVID-19 Global Rheumatology Alliance:
Brahim Dahou, Rosana Quintana, Gimena Gómez, Karen Roberts, Roberto Miguel Baez, Vanessa Castro Coello, María Haye Salinas, Federico Nicolas Maldonado, Alvaro Andres Reyes, Gelsomina Alle, Romina Tanten, Hernán Maldonado Ficco, Romina Nieto, Carla Gobbi, Yohana Tissera, Cecilia Pisoni, Alba Paula, Juan Alejandro Albiero, Maria Marcela Schmid, Micaela Cosatti, Maria Julieta Gamba, Carlevaris Leandro, María Alejandra Cusa, Noelia German, Veronica Bellomio, Lorena Takashima, Mariana Pera, Karina Cogo, Maria Soledad Elkin, María Alejandra Medina, Veronica Savio, Ivana Romina Tessel, Rodolfo Perez Alamino, Marina Laura Werner, Sofía Ornella, Luciana Casalla, Maria de la Vega, María Severina, Mercedes García, Luciana Gonzalez Lucero, Cecilia Romeo, Sebastián Moyano, Tatiana Barbich, Ana Bertoli, Andrea Baños, Sandra Petruzzelli, Carla Matellan, Silvana Conti, Ma Alicia Lazaro, Gustavo Fabián Gil, Fabian Risueño, Maria Isabel Quaglia, Julia Scafati, Natalia Lili Cuchiaro, Jonathan Eliseo Rebak, Susana Isabel Pineda, María Elena Calvo, Eugenia Picco, Josefina Gallino Yanzi, Pablo Maid, Debora Guaglianone, Julieta Silvana Morbiducci, Sabrina Porta, Natalia Herscovich, José Luis Zamora, Boris Kisluk, Maria Sol Menescardi, Rosana Gallo, María Victoria Martire, Carla Maldini, Cecilia Goizueta, Sabrina Solange de Fernandez, Carolina Aeschlimann Argentina, Gisela Subils, Eva Rath, Yves Piette, Mieke Devinck, Bea Maeyaert, Francinne Machado Ribeiro, Sandra Lucia Ribeiro, Marcelo Pinheiro, Sebastián Ibáñez, Anne-Marie Chassin-Trubert, Lingli Dong, Lui Cajas, Marko Barešić, Branimir Anić, Melanie-Ivana Čulo, Tea Ahel Pavelić, Kristina Kovačević Stranski, Boris Karanovic, Jiri Vencovsky, Marta Píchová, Maria Filkova, Hesham Hamoud, Dimitrios Vassilopoulos, Gabriela Maria Melgar, Ho So, Márta Király, Mahdi Vojdanian, Alexandra Balbir-Gurman, Fatemah Abutiban, Julija Zepa, Inita Bulina, Loreta Bukauskiene, Beatriz Elena Zazueta-Montiel, Angel Alejandro Castillo-Ortiz, Erick Zamora-Tehozol, David Vega-Morales, Diana Cervántes Rosete, Eduardo Martín-Nares, Tatiana Sofia Rodriguez-Reyna, Marina Rull Gabayet, Deshiré Alpízar-Rodríguez, Fedra Irazoque, Xochitl Jimenez, Lenny Geurts-van Bon, Theo Zijlstra, Monique Hoekstra, Nasra Al-Adhoubi, Babur Salim, Enrique Giraldo, Ariel Salinas, Manuel Ugarte-Gil, Jarosław Nowakowski, Samar Al-Emadi, Richard Conway, Rachael Flood, Geraldine McCarthy, Ioana Felea, Ileana Filipescu, Simona Rednic, Laura Groseanu, Maria Magdelena Tamas, Vanda Mlynarikova, Martina Skamlova, Martin Zlnay, Dagmar Mičeková, Lubica Capova, Zelmira Macejova, Emőke Šteňová, Helena Raffayova, Gabriela Belakova, Eva Strakova, Marieta Senčarová, Anna Sabová, Daniela Spisakova, Mária Oetterová, Olga Lukacova, Martina Bakosova, Alojzija Hocevar, Natalia de la Torre-Rubio, Juan José Sancho, Montserrat Corteguera Coro, Juan Carlos Garcia, Maria Carmen Martin, Jose Campos, Jose A Puerta, Gozd Kubra Yardımcı, Servet Akar, Ozan Cemal Icacan, Selda ÇELİK, Viktoriia Vasylets, Su-Ann Yeoh, Claire Vandevelde, Sasha Dunt, Jane Leeder, Elizabeth Macphie, Rosaria Salerno, Christine Graver, Katie Williams, Sheila O'Reilly, Kirsty Devine, Jennifer Tyler, Elizabeth Warner, James Pilcher, Samir Patel, Elena Nikiphorou, Laura Chadwick, Caroline Mulvaney Jones, Beverley Harrison, Lucy Thornton, Diana O'Kane, Lucia Fusi, Audrey Low, Sarah Horton, Shraddha Jatwani, Sara Baig, Hammad Bajwa, Vernon Berglund, Angela Dahle, Walter Dorman, Jody Hargrove, Maren Hilton, Nicholas Lebedoff, Susan Leonard, Jennifer Morgan, Emily Pfeifer, Archibald Skemp, Jeffrey Wilson, Anne Wolff, Eduardo Cepeda, Derrick Todd, Denise Hare, Cassandra Calabrese, Christopher Adams, Arezou Khosroshahi, Adam Kilian, Douglas White, Melanie Winter, Theodore Fields, Caroline Siegel, Nicole Daver, Melissa Harvey, Neil Kramer, Concetta Lamore, Suneya Hogarty, Karen Yeter, Leanna Wise, Faizah Siddique, Byung Ban, Tamar Tanner, Eric Ruderman, William Davis, Robert Quinet, Evangeline Scopelitis, Karen Toribio Toribio, Tameka Webb-Detiege, Jerald Zakem, Khurram Abbass, Gilbert Kepecs, Lilliam Miranda, Michael Guma, Ammar Haikal, Sushama Mody, Daric Mueller, Arundathi Jayatilleke, JoAnn Zell, Alison Bays, Kathryn Dao, Ezzati Fatemeh, Deborah Parks, David Karp, and Guillermo Quiceno
Data availability statement
Data are available upon reasonable request. Applications to access the data should be made to the C19-GRA Steering Committee.
Ethics statements
Patient consent for publication
Not required.
Ethics approval
The C19-GRA 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.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
annrheumdis-2021-220418supp001.pdf (603.5KB, pdf)
Data Availability Statement
Data are available upon reasonable request. Applications to access the data should be made to the C19-GRA Steering Committee.