25 research outputs found
Association Between Race/Ethnicity and COVID-19 Outcomes in Systemic Lupus Erythematosus Patients From the United States: Data From the COVID-19 Global Rheumatology Alliance
OBJECTIVE: To determine the association between race/ethnicity and COVID-19 outcomes in individuals with systemic lupus erythematosus (SLE). METHODS: Individuals with SLE from the US with data entered into the COVID-19 Global Rheumatology Alliance registry between March 24, 2020 and August 27, 2021 were included. Variables included age, sex, race, and ethnicity (White, Black, Hispanic, other), comorbidities, disease activity, pandemic time period, glucocorticoid dose, antimalarials, and immunosuppressive drug use. The ordinal outcome categories were: not hospitalized, hospitalized with no oxygenation, hospitalized with any ventilation or oxygenation, and death. We constructed ordinal logistic regression models evaluating the relationship between race/ethnicity and COVID-19 severity, adjusting for possible confounders. RESULTS: We included 523 patients; 473 (90.4%) were female and the mean ± SD age was 46.6 ± 14.0 years. A total of 358 patients (74.6%) were not hospitalized; 40 patients (8.3%) were hospitalized without oxygen, 64 patients (13.3%) were hospitalized with any oxygenation, and 18 (3.8%) died. In a multivariable model, Black (odds ratio [OR] 2.73 [95% confidence interval (95% CI) 1.36–5.53]) and Hispanic (OR 2.76 [95% CI 1.34–5.69]) individuals had higher odds of more severe outcomes than White individuals. CONCLUSION: Black and Hispanic individuals with SLE experienced more severe COVID-19 outcomes, which is consistent with findings in the US general population. These results likely reflect socioeconomic and health disparities and suggest that more aggressive efforts are needed to prevent and treat infection in this population
SARS-CoV-2 breakthrough infections among vaccinated individuals with rheumatic disease : Results from the COVID-19 Global Rheumatology Alliance provider registry
Funding Information: members of the COVID-19 Global Rheumatology Alliance and do not necessarily represent the views of the American College of Rheumatology (ACR), EULAR, the UK National Health Service (NHS), the National Institute for Health Research (NIHR), the UK Department of Health or any other organisation. Competing interests KLH reports she has received non-personal speaker’s fees from AbbVie and grant income from BMS, UCB and Pfizer, all unrelated to this manuscript; KLH is supported by the NIHR Manchester Biomedical Research Centre. LG reports personal consultant fees from AbbVie, Amgen, BMS, Biogen, Celgene, Gilead, Janssen, Lilly, Novartis, Pfizer, Samsung Bioepis, Sanofi-Aventis and UCB, and grants from Amgen, Lilly, Janssen, Pfizer, Sandoz, Sanofi and Galapagos, all unrelated to this manuscript. AS reports research grants from a consortium of 14 companies (among them AbbVie, BMS, Celltrion, Fresenius Funding Information: Kabi, Gilead/Galapagos, Lilly, Mylan/Viatris, Hexal, MSD, Pfizer, Roche, Samsung, Sanofi-Aventis and UCB) supporting the German RABBIT register and personal fees from lectures for AbbVie, MSD, Roche, BMS, Lilly and Pfizer, all unrelated to this manuscript. LC has not received fees or personal grants from any laboratory, but her institute works by contract for laboratories among other institutions, such as 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. EF-M reports personal consultant fees from Boehringer Ingelheim Portugal and that LPCDR received support for specific activities: grants from AbbVie, Novartis, Janssen-Cilag, Lilly Portugal, Sanofi, Grünenthal, MSD, Celgene, Medac, Pharmakern and GAfPA; grants and non-financial support from Pfizer; and non-financial support from Grünenthal, outside the submitted work. IB reports personal consultant fees from AbbVie, Novartis, Pfizer and Janssen, all unrelated to this manuscript. JZ reports speaker fees from AbbVie, Novartis and Janssen/Johnson & Johnson, all unrelated to this manuscript. GR-C reports personal consultant fees from Eli Lilly and Novartis, all unrelated to this manuscript. JS is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (grant numbers: R01 AR077607, P30 AR070253 and P30 AR072577), and the R Bruce and Joan M Mickey Research Scholar Fund. JS 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. LW receives speaker’s bureau fees from Aurinia Pharma, unrelated to this manuscript. SB reports no competing interests related to this work. He reports non-branded consulting fees for AbbVie, Horizon and Novartis (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). ESi reports non-financial support from Canadian Arthritis Patient Alliance, outside the submitted work. PS reports personal fees from the American College of Rheumatology/Wiley Publishing, outside the submitted work. ZW 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. PMM has received consulting/speaker’s fees from AbbVie, BMS, Celgene, Eli Lilly, Galapagos, Janssen, MSD, Novartis, Orphazyme, Pfizer, Roche and UCB, all unrelated to this study. 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 PCR reports personal fees from AbbVie, Atom Bioscience, Eli Lilly, Gilead, GlaxoSmithKline, Janssen, Kukdong, Novartis, UCB, Roche and Pfizer; meeting attendance support from BMS, Pfizer and UCB; and grant funding from Janssen, Novartis, Pfizer and UCB Pharma (all <$10 000). JY reports no competing interests related to this work. Her work is supported by grants from the National Institutes of Health (K24 AR074534 and P30 AR070155). Outside of this work, she has received research grants or performed consulting for Gilead, BMS Foundation, Pfizer, Aurinia and AstraZeneca. Funding Information: Twitter Jean Liew @rheum_cat, Loreto Carmona @carmona_loreto, Pedro M Machado @pedrommcmachado and Philip C Robinson @philipcrobinson Contributors All authors contributed to the study design, data collection, interpretation of results and review/approval of the final submitted manuscript. JL and MG are guarantors for this manuscript. Funding MG reports grants from the National Institutes of Health, NIAMS, outside the submitted work. KLH is supported by the NIHR Manchester Biomedical Research Centre. JS is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (grant numbers: R01 AR077607, P30 AR070253 and P30 AR072577), and the R Bruce and Joan M Mickey Research Scholar Fund. JH is supported by grants from the Rheumatology Research Foundation. ZW is supported by grants from the National Institutes of Health. PMM is supported by the National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre (BRC). JY is supported by grants from the National Institutes of Health (K24 AR074534 and P30 AR070155). Publisher Copyright: ©Objective. While COVID-19 vaccination prevents severe infections, poor immunogenicity in immunocompromised people threatens vaccine effectiveness. We analysed the clinical characteristics of patients with rheumatic disease who developed breakthrough COVID-19 after vaccination against SARS-CoV-2. Methods. We included people partially or fully vaccinated against SARS-CoV-2 who developed COVID-19 between 5 January and 30 September 2021 and were reported to the Global Rheumatology Alliance registry. Breakthrough infections were defined as occurring ≥14 days after completion of the vaccination series, specifically 14 days after the second dose in a two-dose series or 14 days after a single-dose vaccine. We analysed patients' demographic and clinical characteristics and COVID-19 symptoms and outcomes. Results SARS-CoV-2 infection was reported in 197 partially or fully vaccinated people with rheumatic disease (mean age 54 years, 77% female, 56% white). The majority (n=140/197, 71%) received messenger RNA vaccines. Among the fully vaccinated (n=87), infection occurred a mean of 112 (±60) days after the second vaccine dose. Among those fully vaccinated and hospitalised (n=22, age range 36-83 years), nine had used B cell-depleting therapy (BCDT), with six as monotherapy, at the time of vaccination. Three were on mycophenolate. The majority (n=14/22, 64%) were not taking systemic glucocorticoids. Eight patients had pre-existing lung disease and five patients died. Conclusion. More than half of fully vaccinated individuals with breakthrough infections requiring hospitalisation were on BCDT or mycophenolate. Further risk mitigation strategies are likely needed to protect this selected high-risk population.publishersversionPeer reviewe
Results From the Global Rheumatology Alliance Registry
Funding Information: We acknowledge financial support from the ACR and EULAR. The ACR and EULAR were not involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Publisher Copyright: © 2022 The Authors. ACR Open Rheumatology published by Wiley Periodicals LLC on behalf of American College of Rheumatology.Objective: Some patients with rheumatic diseases might be at higher risk for coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS). We aimed to develop a prediction model for COVID-19 ARDS in this population and to create a simple risk score calculator for use in clinical settings. Methods: Data were derived from the COVID-19 Global Rheumatology Alliance Registry from March 24, 2020, to May 12, 2021. Seven machine learning classifiers were trained on ARDS outcomes using 83 variables obtained at COVID-19 diagnosis. Predictive performance was assessed in a US test set and was validated in patients from four countries with independent registries using area under the curve (AUC), accuracy, sensitivity, and specificity. A simple risk score calculator was developed using a regression model incorporating the most influential predictors from the best performing classifier. Results: The study included 8633 patients from 74 countries, of whom 523 (6%) had ARDS. Gradient boosting had the highest mean AUC (0.78; 95% confidence interval [CI]: 0.67-0.88) and was considered the top performing classifier. Ten predictors were identified as key risk factors and were included in a regression model. The regression model that predicted ARDS with 71% (95% CI: 61%-83%) sensitivity in the test set, and with sensitivities ranging from 61% to 80% in countries with independent registries, was used to develop the risk score calculator. Conclusion: We were able to predict ARDS with good sensitivity using information readily available at COVID-19 diagnosis. The proposed risk score calculator has the potential to guide risk stratification for treatments, such as monoclonal antibodies, that have potential to reduce COVID-19 disease progression.publishersversionepub_ahead_of_prin
Associations of baseline use of biologic or targeted synthetic DMARDs with COVID-19 severity in rheumatoid arthritis : Results from the COVID-19 Global Rheumatology Alliance physician registry
Funding Information: Competing interests JAS is supported by the National Institute of Arthritis and Funding Information: 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). 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). 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). 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. Publisher Copyright: © Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.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.publishersversionPeer reviewe
Factors associated with COVID-19-related death in people with rheumatic diseases: results from the COVID-19 Global Rheumatology Alliance physician-reported registry.
OBJECTIVES: To determine factors associated with COVID-19-related death in people with rheumatic diseases. METHODS: Physician-reported registry of adults with rheumatic disease and confirmed or presumptive COVID-19 (from 24 March to 1 July 2020). The primary outcome was COVID-19-related death. Age, sex, smoking status, comorbidities, rheumatic disease diagnosis, disease activity and medications were included as covariates in multivariable logistic regression models. Analyses were further stratified according to rheumatic disease category. RESULTS: Of 3729 patients (mean age 57 years, 68% female), 390 (10.5%) died. Independent factors associated with COVID-19-related death were age (66-75 years: OR 3.00, 95% CI 2.13 to 4.22; >75 years: 6.18, 4.47 to 8.53; both vs ≤65 years), male sex (1.46, 1.11 to 1.91), hypertension combined with cardiovascular disease (1.89, 1.31 to 2.73), chronic lung disease (1.68, 1.26 to 2.25) and prednisolone-equivalent dosage >10 mg/day (1.69, 1.18 to 2.41; vs no glucocorticoid intake). Moderate/high disease activity (vs remission/low disease activity) was associated with higher odds of death (1.87, 1.27 to 2.77). Rituximab (4.04, 2.32 to 7.03), sulfasalazine (3.60, 1.66 to 7.78), immunosuppressants (azathioprine, cyclophosphamide, ciclosporin, mycophenolate or tacrolimus: 2.22, 1.43 to 3.46) and not receiving any disease-modifying anti-rheumatic drug (DMARD) (2.11, 1.48 to 3.01) were associated with higher odds of death, compared with methotrexate monotherapy. Other synthetic/biological DMARDs were not associated with COVID-19-related death. CONCLUSION: Among people with rheumatic disease, COVID-19-related death was associated with known general factors (older age, male sex and specific comorbidities) and disease-specific factors (disease activity and specific medications). The association with moderate/high disease activity highlights the importance of adequate disease control with DMARDs, preferably without increasing glucocorticoid dosages. Caution may be required with rituximab, sulfasalazine and some immunosuppressants
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Using the technology acceptance model to assess clinician perceptions and experiences with a rheumatoid arthritis outcomes dashboard: qualitative study.
BACKGROUND: Improving shared decision-making using a treat-to-target approach, including the use of clinical outcome measures, is important to providing high quality care for rheumatoid arthritis (RA). We developed an Electronic Health Record (EHR) integrated, patient-facing sidecar dashboard application that displays RA outcomes, medications, and lab results for use during clinical visits (RA PRO dashboard). The purpose of this study was to assess clinician perceptions and experiences using the dashboard in a university rheumatology clinic. METHODS: We conducted focus group (FG) discussions with clinicians who had access to the dashboard as part of a randomized, stepped-wedge pragmatic trial. FGs explored clinician perceptions towards the usability, acceptability, and usefulness of the dashboard. FG data were analyzed thematically using deductive and inductive techniques; generated themes were categorized into the domains of the Technology Acceptance Model (TAM). RESULTS: 3 FG discussions were conducted with a total of 13 clinicians. Overall, clinicians were enthusiastic about the dashboard and expressed the usefulness of visualizing RA outcome trajectories in a graphical format for motivating patients, enhancing patient understanding of their RA outcomes, and improving communication about medications. Major themes that emerged from the FG analysis as barriers to using the dashboard included inconsistent collection of RA outcomes leading to sparse data in the dashboard and concerns about explaining RA outcomes, especially to patients with fibromyalgia. Other challenges included time constraints and technical difficulties refreshing the dashboard to display real-time data. Methods for integrating the dashboard into the visit varied: some clinicians used the dashboard at the beginning of the visit as they documented RA outcomes; others used it at the end to justify changes to therapy; and a few shared it only with stable patients. CONCLUSIONS: The study provides valuable insights into clinicians perceptions and experiences with the RA PRO dashboard. The dashboard showed promise in enhancing patient-clinician communication, shared decision-making, and overall acceptance among clinicians. Addressing challenges related to data collection, education, and tailoring dashboard use to specific patient populations will be crucial for maximizing its potential impact on RA care. Further research and ongoing improvements in dashboard design and implementation are warranted to ensure its successful integration into routine clinical practice
The Development of the Rheumatology Informatics System for Effectiveness Learning Collaborative for Improving Patient-Reported Outcome Collection and Patient-Centered Communication in Adult Rheumatology.
ObjectivePatient-reported outcomes (PROs) are an integral part of treat-to-target approaches in managing rheumatoid arthritis (RA). In clinical practice, however, routine collection, documentation, and discussion of PROs with patients are highly variable. The RISE LC (Rheumatology Informatics System for Effectiveness Learning Collaborative) was established to develop and share best practices in PRO collection and use across adult rheumatology practices in the United States METHODS: The goals of the RISE LC were developed through site surveys and in-person meetings. Participants completed a baseline survey on PRO collection and use in their practices. RISE LC learning sessions focused on improving communication around PROs with patients and enhancing shared decision-making in treatment plans. During the coronavirus disease 2019 (COVID-19) pandemic, the RISE LC pivoted to adapt PRO tools for telehealth.ResultsAt baseline, all responding sites (n = 15) had established workflows for collecting PROs. Most sites used paper forms alone. PRO documentation in electronic health records was variable, with only half of the sites using structured data fields. To standardize and improve the use of PROs, participants iteratively developed a Clinical Disease Activity Index-based RA Disease Activity Communication Tool to solicit treatment goals and improve shared decision-making across sites. The COVID-19 pandemic necessitated developing a tool to gauge PROs via telehealth.ConclusionThe RISE LC is a continuous, structured method for implementing strategies to improve PRO collection and use in rheumatological care, initially adapting from the Learning Collaborative model and extending to include features of a learning network. Future directions include measuring the impact of standardized PRO collection and discussion on shared decision-making and RA outcomes
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Characteristics associated with hospitalisation for COVID-19 in people with rheumatic disease: data from the COVID-19 Global Rheumatology Alliance physician-reported registry.
ObjectivesCOVID-19 outcomes in people with rheumatic diseases remain poorly understood. The aim was to examine demographic and clinical factors associated with COVID-19 hospitalisation status in people with rheumatic disease.MethodsCase series of individuals with rheumatic disease and COVID-19 from the COVID-19 Global Rheumatology Alliance registry: 24 March 2020 to 20 April 2020. Multivariable logistic regression was used to estimate ORs and 95% CIs of hospitalisation. Age, sex, smoking status, rheumatic disease diagnosis, comorbidities and rheumatic disease medications taken immediately prior to infection were analysed.ResultsA total of 600 cases from 40 countries were included. Nearly half of the cases were hospitalised (277, 46%) and 55 (9%) died. In multivariable-adjusted models, prednisone dose ≥10 mg/day was associated with higher odds of hospitalisation (OR 2.05, 95% CI 1.06 to 3.96). Use of conventional disease-modifying antirheumatic drug (DMARD) alone or in combination with biologics/Janus Kinase inhibitors was not associated with hospitalisation (OR 1.23, 95% CI 0.70 to 2.17 and OR 0.74, 95% CI 0.37 to 1.46, respectively). Non-steroidal anti-inflammatory drug (NSAID) use was not associated with hospitalisation status (OR 0.64, 95% CI 0.39 to 1.06). Tumour necrosis factor inhibitor (anti-TNF) use was associated with a reduced odds of hospitalisation (OR 0.40, 95% CI 0.19 to 0.81), while no association with antimalarial use (OR 0.94, 95% CI 0.57 to 1.57) was observed.ConclusionsWe found that glucocorticoid exposure of ≥10 mg/day is associated with a higher odds of hospitalisation and anti-TNF with a decreased odds of hospitalisation in patients with rheumatic disease. Neither exposure to DMARDs nor NSAIDs were associated with increased odds of hospitalisation
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Characteristics associated with hospitalization for COVID-19 in people with rheumatic disease:Data from the COVID-19 Global Rheumatology Alliance Physician-Reported Registry
Objectives: COVID-19 outcomes in people with rheumatic diseases remain poorly understood. The aim was to examine demographic and clinical factors associated with COVID-19 hospitalisation status in people with rheumatic disease. Methods: Case series of individuals with rheumatic disease and COVID-19 from the COVID-19 Global Rheumatology Alliance registry: 24 March 2020 to 20 April 2020. Multivariable logistic regression was used to estimate ORs and 95% CIs of hospitalisation. Age, sex, smoking status, rheumatic disease diagnosis, comorbidities and rheumatic disease medications taken immediately prior to infection were analysed. Results: A total of 600 cases from 40 countries were included. Nearly half of the cases were hospitalised (277, 46%) and 55 (9%) died. In multivariable-adjusted models, prednisone dose ≥10 mg/day was associated with higher odds of hospitalisation (OR 2.05, 95% CI 1.06 to 3.96). Use of conventional disease-modifying antirheumatic drug (DMARD) alone or in combination with biologics/Janus Kinase inhibitors was not associated with hospitalisation (OR 1.23, 95% CI 0.70 to 2.17 and OR 0.74, 95% CI 0.37 to 1.46, respectively). Non-steroidal anti-inflammatory drug (NSAID) use was not associated with hospitalisation status (OR 0.64, 95% CI 0.39 to 1.06). Tumour necrosis factor inhibitor (anti-TNF) use was associated with a reduced odds of hospitalisation (OR 0.40, 95% CI 0.19 to 0.81), while no association with antimalarial use (OR 0.94, 95% CI 0.57 to 1.57) was observed. Conclusions: We found that glucocorticoid exposure of ≥10 mg/day is associated with a higher odds of hospitalisation and anti-TNF with a decreased odds of hospitalisation in patients with rheumatic disease. Neither exposure to DMARDs nor NSAIDs were associated with increased odds of hospitalisation