Clinical science Characteristics of and risk factors for COVID-19 breakthrough infections in idiopathic inflammatory myopathies: results from the COVAD study Leonardo Santos Hoff1, Naveen Ravichandran 2, Parikshit Sen3, Jessica Day 4,5,6, Mrudula Joshi7, Arvind Nune 8, Elena Nikiphorou9,10, Sreoshy Saha11, Ai Lyn Tan 12,13, Samuel Katsuyuki Shinjo14, Nelly Ziade 15,16, Tsvetelina Velikova17, Marcin Milchert 18, Kshitij Jagtap19, Ioannis Parodis 20,21, Abraham Edgar Gracia-Ramos 22, Lorenzo Cavagna23, Masataka Kuwana 24, Johannes Knitza 25, Yi Ming Chen26,27, Ashima Makol28, Vishwesh Agarwal29, Aarat Patel30, John D. Pauling 31,32, Chris Wincup 33,34, Bhupen Barman35, Erick Adrian Zamora Tehozol36, Jorge Rojas Serrano37, Ignacio Garc�ıa-De La Torre38, Iris J. Colunga-Pedraza 39, Javier Merayo-Chalico 40, Okwara Celestine Chibuzo41, Wanruchada Katchamart42, Phonpen Akarawatcharangura Goo43, Russka Shumnalieva44, Lina El Kibbi45, Hussein Halabi46, Binit Vaidya47, Syahrul Sazliyana Shaharir48, A. T. M. Tanveer Hasan49, Dzifa Dey50, Carlos Enrique Toro Guti�errez51, Carlo V. Caballero-Uribe52, James B. Lilleker 53,54, Babur Salim55, Tamer Gheita 56, Tulika Chatterjee57, Oliver Distler 58, Miguel A. Saavedra59, Hector Chinoy 60,61,62, Vikas Agarwal 63, Rohit Aggarwal 64,‡, Latika Gupta 65,66,67,�,‡, COVAD Study Group§ 1Department of Medicine, School of Medicine, Universidade Potiguar (UnP), Natal, Brazil 2Department of Clinical Immunology and Rheumatology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India 3Maulana Azad Medical College, New Delhi, Delhi, India 4Department of Rheumatology, Royal Melbourne Hospital, Parkville, VIC, Australia 5Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia 6Department of Medical Biology, University of Melbourne, Parkville, VIC, Australia 7Byramjee Jeejeebhoy Government Medical College and Sassoon General Hospitals, Pune, India 8Department of Rheumatology, Southport and Ormskirk Hospital NHS Trust, Southport, UK 9Centre for Rheumatic Diseases, King’s College London, London, UK 10Rheumatology Department, King’s College Hospital, London, UK 11Mymensingh Medical College, Mymensingh, Bangladesh 12NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals Trust, Leeds, UK 13Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, UK 14Division of Rheumatology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil 15Rheumatology Department, Saint-Joseph University, Beirut, Lebanon 16Rheumatology Department, Hotel-Dieu de France Hospital, Beirut, Lebanon 17Medical Faculty, Sofia University St Kliment Ohridski, Sofia, Bulgaria 18Department of Internal Medicine, Rheumatology, Diabetology, Geriatrics and Clinical Immunology, Pomeranian Medical University in Szczecin, Szczecin, Poland 19Seth Gordhandhas Sunderdas Medical College and King Edwards Memorial Hospital, Mumbai, Maharashtra, India 20Division of Rheumatology, Department of Medicine Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden 21Department of Rheumatology, Faculty of Medicine and Health, €Orebro University, €Orebro, Sweden 22Department of Internal Medicine, General Hospital, National Medical Center, La Raza, Instituto Mexicano del Seguro Social, Mexico City, Mexico 23Rheumatology Unit, Dipartimento di Medicine Interna e Terapia Medica, Universit�a degli studi di Pavia, Pavia, Lombardy, Italy 24Department of Allergy and Rheumatology, Nippon Medical School Graduate School of Medicine, Tokyo, Japan 25Medizinische Klinik 3—Rheumatologie und Immunologie, Universit€atsklinikum Erlangen, Friedrich-Alexander-Universit€at Erlangen- N€urnberg, Erlangen, Deutschland 26Division of Allergy, Immunology and Rheumatology, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung City, Taiwan 27Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan 28Division of Rheumatology, Mayo Clinic, Rochester, MN, USA 29Mahatma Gandhi Mission Medical College, Navi Mumbai, Maharashtra, India Received: 24 February 2023. Accepted: 8 February 2024 # The Author(s) 2024. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com Rheumatology, 2025, 64, 597–606 https://doi.org/10.1093/rheumatology/keae128 Advance access publication 2 March 2024 Original Article Rheumatology D ow nloaded from https://academ ic.oup.com /rheum atology/article/64/2/597/7617840 by U niversity of G hana. Balm e Library user on 18 M arch 2025 https://orcid.org/0000-0003-2014-3925 https://orcid.org/0000-0001-8528-4361 https://orcid.org/0000-0002-3849-614X https://orcid.org/0000-0002-9158-7243 https://orcid.org/0000-0002-4479-7678 https://orcid.org/0000-0002-0943-8768 https://orcid.org/0000-0002-4875-5395 https://orcid.org/0000-0003-1842-2554 https://orcid.org/0000-0001-8352-6136 https://orcid.org/0000-0001-9695-0657 https://orcid.org/0000-0002-2793-2364 https://orcid.org/0000-0002-8742-8311 https://orcid.org/0000-0002-2786-5843 https://orcid.org/0000-0002-5870-0523 https://orcid.org/0000-0002-9230-4137 https://orcid.org/0000-0002-1155-9729 https://orcid.org/0000-0002-0546-8310 https://orcid.org/0000-0001-6492-1288 https://orcid.org/0000-0002-2089-027X https://orcid.org/0000-0001-7531-8038 https://orcid.org/0000-0003-2753-2990 30Bon Secours Rheumatology Center and Division of Pediatric Rheumatology, Department of Pediatrics, University of Virginia School of Medicine, Charlottesville, VA, USA 31Bristol Medical School Translational Health Sciences, University of Bristol, Bristol, UK 32Department of Rheumatology, North Bristol NHS Trust, Bristol, UK 33Department of Rheumatology, Division of Medicine, Rayne Institute, University College London, London, UK 34Centre for Adolescent Rheumatology Versus Arthritis at UCL, UCLH, GOSH, London, UK 35Department of General Medicine, All India Institute of Medical Sciences (AIIMS), Guwahati, India 36Rheumatology, Medical Care & Research, Centro Medico Pensiones Hospital, Instituto Mexicano del Seguro Social Delegaci�on Yucat�an, Yucat�an, Mexico 37Rheumatologist and Clinical Investigator, Interstitial Lung Disease and Rheumatology Unit, Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico 38Departamento de Inmunolog�ıa y Reumatolog�ıa, Hospital General de Occidente and Universidad de Guadalajara, Guadalajara, Jalisco, Mexico 39Rheumatology, Hospital Universitario Dr Jose Eleuterio Gonzalez, Monterrey, Mexico 40Department of Immunology and Rheumatology, Instituto Nacional de Ciencias M�edicas y Nutrici�on Salvador Zubir�an, Mexico City, Mexico 41Department of Medicine, University of Nigeria Teaching Hospital, Ituku-Ozalla/University of Nigeria, Enugu Campus, Enugu, Nigeria 42Division of Rheumatology, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand 43Department of Medicine, Queen Savang Vadhana Memorial Hospital, Chonburi, Thailand 44Department of Rheumatology, Clinic of Rheumatology, University Hospital “St Ivan Rilski”, Medical University-Sofia, Sofia, Bulgaria 45Rheumatology Unit, Internal Medicine Department, Specialized Medical Center, Riyadh, Saudi Arabia 46Department of Internal Medicine, Section of Rheumatology, King Faisal Specialist Hospital and Research Center, Jeddah, Saudi Arabia 47National Center for Rheumatic Diseases (NCRD), Ratopul, Kathmandu, Nepal 48Faculty of Medicine, Universiti Kebangsaan Malaysia, Cheras, Kuala Lumpur, Malaysia 49Department of Rheumatology, Enam Medical College & Hospital, Dhaka, Bangladesh 50Rheumatology Unit, Department of Medicine and Therapeutics, University of Ghana Medical School, College of Health Sciences, Accra, Ghana 51General Director, Reference Center for Osteoporosis, Rheumatology and Dermatology, Pontifica Universidad Javeriana Cali, Valle del Cauca, Colombia 52Department of Medicine, Hospital Universidad del Norte, Barranquilla, Atlantico, Colombia 53Division of Musculoskeletal and Dermatological Sciences, Centre for Musculoskeletal Research, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK 54Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Salford, UK 55Rheumatology Department, Fauji Foundation Hospital, Rawalpindi, Pakistan 56Rheumatology Department, Kasr Al Ainy School of Medicine, Cairo University, Cairo, Egypt 57Department of Internal Medicine, University of Illinois College of Medicine at Peoria, Illinois, USA 58Department of Rheumatology, University Hospital Z€urich, University of Z€urich, Z€urich, Switzerland 59Departamento de Reumatolog�ıa, Hospital de Especialidades Dr Antonio Fraga Mouret, Centro M�edico Nacional La Raza, IMSS, Mexico City, Mexico 60Division of Musculoskeletal and Dermatological Sciences, Centre for Musculoskeletal Research, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK 61National Institute for Health Research Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, The University of Manchester, Manchester, UK 62Department of Rheumatology, Salford Royal Hospital, Northern Care Alliance NHS Foundation Trust, Salford, UK 63Department of Clinical Immunology and Rheumatology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India 64Division of Rheumatology and Clinical Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA 65Department of Rheumatology, Royal Wolverhampton Hospitals NHS Trust, Wolverhampton, UK 66City Hospital, Sandwell and West Birmingham Hospitals NHS Trust, Birmingham, UK 67Division of Musculoskeletal and Dermatological Sciences, Centre for Musculoskeletal Research, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK �Correspondence to: Latika Gupta, Department of Rheumatology, Royal Wolverhampton Hospitals NHS Trust, Wolverhampton WV10 0QP, UK. E-mail: drlatikagupta@gmail.com ‡R.A. and L.G. co-senior authors. §See supplementary material available at Rheumatology online for a list of the authors who are part of the COVAD Study Group, along with their affiliations. Abstract Objectives: The objective of this study was to explore the prevalence, characteristics and risk factors of COVID-19 breakthrough infections (BIs) in idiopathic inflammatory myopathies (IIMs) using data from the COVID-19 Vaccination in Autoimmune Diseases (COVAD) study. Methods: A validated patient self-reporting e-survey was circulated by the COVAD study group to collect data on COVID-19 infection and vacci nation in 2022. BIs were defined as COVID-19 occurring �14 days after two vaccine doses. We compared BI characteristics and severity among patients with IIMs, patients with other autoimmune rheumatic and non-rheumatic diseases (AIRD, nrAID), and healthy controls (HCs). Multivariable Cox regression models were used to assess the risk factors for BI, severe BI ,and hospitalizations among patients with IIMs. Results: Among the 9449 included responses, BIs occurred in 1447 respondents (15.3%). The median age was 44 years [interquartile range (IQR) 21], 77.4% were female, and 182 BIs (12.9%) occurred among the 1406 patients with IIMs. Multivariable Cox regression among the data for patients with IIMs showed increasing age to be a protective factor for BIs [hazard ratio (HR)¼ 0.98, 95% CI¼ 0.97–0.99], and HCQ and SSZ use were risk factors (HR¼ 1.81, 95% CI¼ 1.24–2.64, and HR¼ 3.79, 95% CI¼1.69–8.42, respectively). Glucocorticoid use was a risk factor for a severe BI (HR¼3.61, 95% CI¼ 1.09–11.8). Non-white ethnicity (HR¼ 2.61, 95% CI¼1.03–6.59) was a risk factor for hospitalization. Compared with other groups, patients with IIMs required more supplemental oxygen therapy (IIMs¼6.0% vs AIRDs¼1.8%, nrAIDs¼ 2.2% and HCs¼0.9%), intensive care unit admission (IIMs¼2.2% vs AIRDs¼0.6%, nrAIDs and HCs¼ 0%), advanced treatment with antiviral or monoclonal antibodies (IIMs¼34.1% vs AIRDs¼ 25.8%, nrAIDs¼ 14.6% and HCs¼ 12.8%) and had more hospitalization (IIMs¼7.7% vs AIRDs¼4.6%, nrAIDs¼1.1% and HCs¼ 1.5%). 598 Leonardo Santos Hoff et al. D ow nloaded from https://academ ic.oup.com /rheum atology/article/64/2/597/7617840 by U niversity of G hana. Balm e Library user on 18 M arch 2025 https://academic.oup.com/rheumatology/article-lookup/doi/10.1093/rheumatology/keae128#supplementary-data Conclusion: Patients with IIMs are susceptible to severe COVID-19 BIs. Age and immunosuppressive treatments were related to the risk of BIs. Keywords: idiopathic inflammatory myopathies, COVID-19, breakthrough infection, autoimmune diseases, hospitalization. Introduction Vaccines have emerged as a safe and effective intervention for reducing severe COVID-19 outcomes [1]. However, emerging evidence of vaccine breakthrough COVID-19 infections (BIs) suggest that the protection offered may wane with time, though reassuringly BIs appear to be less severe than for pre- vaccination COVID-19 [2–4]. However, given the suscepti bility of patients with autoimmune rheumatic diseases (AIRDs), particularly idiopathic inflammatory myopathies (IIMs), to poor COVID-19 outcomes, owing to frequent AIRD sequelae, comorbidities, and immunosuppression, even relatively milder BIs may represent a cause for concern in this vulnerable group [4–6]. This is reflected by the rare, yet non- negligible incidence of hospitalization, the requirement for oxygen supplementation, and even mortality associated with COVID-19 BIs in these patients, though the majority of cases remain mild [4, 7]. While the characteristics and risk factors for BIs, including vaccine type, homologous/heterologous vaccination, newer SARS-CoV-2 variants, employment in health-care profes sions, and immunosuppressants have been described in the general population and AIRDs, BIs in patients with IIMs re main understudied [2–4, 8–11]. In a retrospective study of 11 468 rheumatic disease patients, patients on B cell–deplet ing therapy, CTLA4-antibody, MMF, IL-6 inhibitors, and JAK inhibitors reported higher frequency of BIs compared with the users of HCQ [9]. Important aspects of AIRDs, such as disease type and immunosuppressant drugs, the corner stone of the management of these patients, remain underex plored as potential risk factors for BIs, including severe BIs [4, 7, 9–11]. In another study, immunosuppressed patients were found to be at three times higher risk of contracting BIs [11]. IIMs are heterogeneous diseases with a higher interferon signature and higher use of steroids and immunosuppression compared with other AIRDs [12, 13]. There is no data on the prevalence and characteristics of BIs after booster vaccination and advanced treatment for COVID among patients with IIMs, other than the preliminary insights into early BIs pub lished by the COVAD group previously [4]. Thus, the primary aim of this study was to investigate the prevalence and characteristics of BIs, severe BIs, and all-cause hospitalization in a large sample of patients with IIMs. The sec ondary aim was to identify risk factors for BIs among patients with IIMs and compare the prevalence and characteristics of BIs in patients with IIMs with those for patients with other AIRDs, non-rheumatic autoimmune diseases (nrAIDs) and healthy con trols (HCs). We further explored BIs among patients with sub types of IIMs, and the characteristics of a second BI. Methods Study design and ethics We analysed data from the 2nd COVAD study, an interna tional multicentre cross-sectional patient self-reporting elec tronic survey [14]. Respondents were informed regarding the survey via cover letter at the beginning of the survey, and they consented electronically in lieu of written consent [15]. No financial incentives were offered for survey completion, and we obtained prior ethical approval from the institutional ethics committee of Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India [16]. We adhered to The Checklist for Reporting Results of the Internet E-Surveys (CHERRIES) when reporting results [17]. Data collection and eligibility criteria The validated COVAD-2 study questionnaire was hosted on the www.surveymonkey.com platform in multiple languages; it was circulated by the global study group of 157 collabora tors across 106 countries in their clinics, across patient sup port groups, and on social media platforms. We collected data on demographics, AIRD details (including diagnosis, treatment history, and current symptom status), COVID-19 infection history, including symptoms, duration, and compli cations (hospitalization due to COVID-19 and requirement of oxygen therapy), and COVID-19 vaccination details in patients with autoimmune diseases and HCs from 1 January 2022, to 31 July 2022. Our methods are further detailed in the previously published protocol [14, 18]. We included a convenience sample of all adult participants (�18 years old) with IIMs, AIRDs, nrAIDs and HCs who had received at least two COVID-19 vaccine doses in the analysis. Participants answered a closed-ended question ‘Did you ever test positive for COVID-19?’ and specified the number of events and the dates of occurrence. Incomplete responses, those vaccinated prior to June 2020 (probable trial partici pants), and patients who received the primary series with a single vaccine dose were excluded. Respondents without au toimmune diseases were considered HCs. The definitions of IIMs, AIRDs and nrAIDs are detailed in the Supplementary Material online. Outcome measures and covariates BIs were defined as COVID-19 infections occurring �14 days after the second vaccine dose [19]. BIs requiring hospitaliza tion, intensive care unit (ICU) or high-dependency unit (HDU) admission, oxygen requirement, or advanced treat ment (antivirals or mAbs) were defined as severe. Hospitalizations due to COVID-19 included respondents Rheumatology key messages � Severe cases of COVID-19 BIs were more common in patients with IIMs than in other groups. � The risk of a severe BI was higher among IIM patients on glucocorticoids and among non-white participants. COVID-19 breakthrough infections in IIMs 599 D ow nloaded from https://academ ic.oup.com /rheum atology/article/64/2/597/7617840 by U niversity of G hana. Balm e Library user on 18 M arch 2025 http://www.surveymonkey.com https://academic.oup.com/rheumatology/article-lookup/doi/10.1093/rheumatology/keae128#supplementary-data https://academic.oup.com/rheumatology/article-lookup/doi/10.1093/rheumatology/keae128#supplementary-data who were hospitalized for COVID-19 infections or BIs. Data on age, gender, ethnicity, comorbidities, country by Human Development Index, first vaccine dose, vaccine type, number of vaccine doses, myositis subtype, and immunosuppressive medications (not mutually exclusive groups) were collected and analysed as covariates. We used the validated Patient Reported Outcomes Measurement Information System (PROMIS®) Fatigue 4a tool to assess fatigue in the past 7 days prior to survey completion through four questions, with a total score ranging from 4 (low est fatigue) to 20 (highest fatigue) [20, 21]. Therefore, the cur rent fatigue status was considered a long-term outcome following BIs and was compared among patients with IIMs af ter several vaccine doses. Statistical methods The characteristics of the major subgroups of participants with BIs were compared using the Mann–Whitney U test for continuous variables (age, days until the first BI) and the v2 test for categorical variables. Predictors of BIs, severe BIs, and hospitalization among patients with IIMs were evaluated by univariable and multi variable Cox regression, and the results were presented as hazard ratios (HRs) with a 95% CI. The multivariable Cox regression models were adjusted for age, gender, ethnicity, and those covariates with a P< 0.2 in the univariable analy sis. Those covariates not following the proportional hazards assumption (model using time-dependent interaction terms) were excluded from the model. COVID-19 BI symptoms and severity among patients with IIMs were compared with those for patients with AIRDs, patients with nrAIDs, and HCs individually using the Kruskal– Wallis test, with Bonferroni’s posthoc test for continuous variables (days until symptoms resolution) and the v2 test for categorical variables. Comparison of Fatigue 4a scores between the BIs in patients with IIMs after different number of vaccine doses were adjusted for time since BI using a linear regres sion model. Additional exploratory analysis of COVID-19 BIs after dif ferent number of vaccine doses, comparison of symptoms and severity among IIMs subgroups (DM, anti-synthetase syndrome, IBM, necrotizing autoimmune myositis, overlap myositis and PM), and characteristics of the second BI among the major subgroups of participants was performed using v2 for categorical variables and the Kruskal–Wallis test for con tinuous variables. Statistical significance was defined as a two-sided P-value <0.05 unless otherwise stated. Statistical analyses were performed using IBM SPSS version 28.0. Results Study population Among the total 17 612 survey respondents, 10 783 com pleted the survey in full. From these, we excluded the unvac cinated (n¼ 734), single COVID-19 vaccine dose recipients (n¼319), primary series vaccination with a single vaccine dose (n¼ 277), and those vaccinated prior to June 2020 (probable trial participants) (n¼4), finally including 9449 respondents who had received at least two vaccine doses in the final analysis. BI prevalence and characteristics COVID-19 BIs occurred in 1447 (15.3%) respondents in to tal, median age 44 years [interquartile range (IQR) 35, 56], 77.4% female, 54.7% white, of whom 12.5% (n¼182) were patients with IIMs, 49.4% (n¼ 716) were patients with AIRDs, 6.1% (n¼89) were patients with nrAIDs, and 31.7% (n¼ 460) were HCs. The prevalence of BIs among patients with IIMs was 12.9% (182/1406). Comorbidities were common, with mental health disorders (28.5%), hyper tension (16.5%) and dyslipidaemia (12.1%) being the most prevalent. The first BI occurred after a median of 117 days (IQR 59, 176) following the second COVID-19 vaccine dose and did not differ between the different groups. Other base line characteristics of the respondents experiencing BIs are detailed in Table 1. Risk factors for COVID-19 BIs, severe BIs, and hospitalization among IIMs In the multivariable Cox model, increasing age (HR¼0.98, 95% CI¼ 0.97–0.99) was protective; HCQ (HR¼1.81, 95% CI¼1.24–2.64), and SSZ therapy (HR¼3.79, 95% CI¼1.69– 8.42) were associated with increased risk of BIs (Tables 2 and 3). Glucocorticoid use was associated with severe BIs, with an adjusted HR¼ 3.61 (95% CI¼1.09–11.8) in the multivariable model (Table 3). Having non-white ethnicity was an additional risk factor for hospitalization among patients with IIMs (HR¼2.61, 95% CI¼1.03–6.59) (Table 3). Comparison of BIs among patients with IIMs, patients with other autoimmune diseases, and HCs BIs symptoms and severity were different among the major groups. For instance, symptoms resolution time was longer in patients with IIMs (median 12 days) and AIRDs (11 days) compared with patients with nrAIDs (8 days) and HCs (7 days, P<0.001). Arthralgia, headache and chest pain were more common in patients with AIRDs (40.6%, 46.8% and 15.5%, respectively), while cough (67.6%) was more com mon in patients with IIMs. Difficulty breathing and nausea/ vomiting were more common in both IIMs (19.2% and 12.1%, respectively) and AIRDs (21.2% and 12.0%, respec tively). A full description of the symptoms for the various groups is depicted in Table 4. Compared with other groups, patients with IIMs required more supplemental oxygen therapy (IIMs¼6.0%, AIRDs¼1.8%, nrAIDs¼2.2%, HCs¼ 0.9%, P<0.001), in tensive care unit admission (IIMs¼ 2.2%, AIRDs¼0.6%, nrAIDs and HC¼0%, P<0.007), advanced treatment with antiviral or mAbs (IIMs¼34.1%, AIRDs¼ 25.8%, nrAIDs¼ 14.6% and HCs¼12.8%, P< 0.001), and had more all-cause hospitalization (IIMs¼7.7%, AIRDs¼4.6%, nrAIDs¼ 1.1% and HCs¼1.5%, P<0.001). BI after different vaccine doses, in patients with subtypes of IIMs BIs were reported in 47 patients (24.4%) after two doses, 105 patients (11.2%) after three doses, and 30 (10.8%) after four vaccine doses among the patients with IIMs (P<0.001 between the three groups, P<0.001 between the two- and three-dose groups, P¼0.861 between the three- and four- dose groups). Notably, the severity of BIs in patients with IIMs did not differ after two, three, or four vaccine doses (Supplementary Table 1). The fatigue 4a score for BIs after 600 Leonardo Santos Hoff et al. D ow nloaded from https://academ ic.oup.com /rheum atology/article/64/2/597/7617840 by U niversity of G hana. Balm e Library user on 18 M arch 2025 https://academic.oup.com/rheumatology/article-lookup/doi/10.1093/rheumatology/keae128#supplementary-data Table 1. Characteristics of the major subgroups of participants with breakthrough infections Characteristics during the first BI Total (n¼ 1447) IIMs (n¼ 182) AIRDs (n¼ 716) nrAIDs (n¼89) HCs (n¼ 460) Median age (25th–75th), years 44 (35–56) 56 (47–66) 46 (37–57)��� 40 (33–47)��� 38 (31–48)��� Female gender 1104 (77.4) 129 (71.7) 608 (86.1)��� 71 (81.6) 296 (65.3) Median (25th–75th) time to first BI (days) 117 (59–176) 110 (58.7–164) 120 (61–172) 112 (70–179) 113 (53–186) Race and ethnicity African 57 (3.9) 9 (4.9) 40 (5.6) 1 (1.1) 7 (1.5) Asian 229 (15.8) 22 (12.1) 119 (16.6) 10 (11.2) 78 (17.0) White 792 (54.7) 128 (70.3) 397 (55.4) 61 (68.5) 206 (44.8) Hispanic 198 (13.7) 10 (5.5) 70 (9.8) 8 (9.0) 110 (23.9) Mixed 46 (3.2) 5 (2.7) 22 (3.1) 3 (3.4) 16 (3.5) Native American 5 (0.3) 1 (0.5) 2 (0.3) 0 (0) 2 (0.4) Others 74 (5.1) 3 (1.6) 43 (6.0) 4 (4.5) 24 (5.2) Did not wish to disclose 46 (3.2) 4 (2.2) 23 (3.2) 2 (2.2) 17 (3.7) Number of vaccine doses Two 449 (31.0) 47 (25.8) 196 (27.3) 29 (32.6) 177 (38.4) Three 721 (49.8) 105 (57.6) 339 (47.3) 46 (51.7) 231 (50.2) Four 277 (19.1) 30 (16.4) 181 (25.2) 14 (15.7) 52 (11.3) Comorbidities Any comorbidities 601 (41.5) 124 (68.1) 329 (45.9)��� 37 (41.6)��� 111 (24.1)��� Asthma 168 (11.6) 36 (19.8) 86 (12.0)� 9 (10.1) 37 (8.0)��� Chronic kidney disease 46 (3.2) 9 (4.9) 35 (4.9) 0 (0)a 2 (0.4)��� Chronic liver disease 17 (1.2) 4 (2.2) 8 (1.1) 2 (2.2) 3 (0.7) COPD 30 (2.1) 8 (4.4) 18 (2.5) 0 (0) 4 (0.9)�� Interstitial lung disease 52 (3.6) 35 (19.2) 15 (2.1)��� 0 (0)��� 2 (0.4)��� Coronary artery disease 31 (2.1) 11 (6.0) 16 (2.2)� 1 (1.1) 3 (0.7)��� Diabetes mellitus 83 (5.7) 32 (17.6) 34 (4.7)��� 7 (7.9)� 10 (2.2)��� Dyslipidaemia 174 (12.0) 45 (24.7) 95 (13.3)��� 7 (7.9)��� 27 (5.9)��� HIV-AIDS 3 (0.2) 2 (1.1) 1 (0.1) 0 (0) 0 (0) Hypertension 239 (16.5) 48 (26.4) 134 (18.7)� 16 (18.0) 41 (8.9)��� Stroke 15 (1.0) 4 (2.2) 9 (1.3) 2 (2.2) 0 (0) b Mental health disorders 413 (28.5) 71 (39.0) 227 (31.7)� 29 (32.6) 86 (18.7)��� AID multimorbidity 270 (18.7) 62 (34.1) 174 (24.3)� 34 (38.2) 0 (0) Immunosuppression received MTX 261 (18.0) 47 (25.8) 209 (29.2) 3 (3.4)��� – MMF 97 (6.7) 44 (24.2) 52 (7.3)��� 1 (1.1)��� – AZA 69 (4.8) 14 (7.7) 52 (7.3) 3 (3.4) – HCQ 281 (19.4) 45 (24.7) 231 (32.3) 2 (2.2)��� – SSZ 72 (5.0) 7 (3.8) 62 (8.7) 3 (3.4) – LEF 34 (2.3) 2 (1.1) 31 (4.3)� 1 (1.1) – Oral tacrolimus 13 (0.9) 5 (2.7) 6 (0.8) 1 (1.1) – CSA 19 (1.3) 4 (2.2) 13 (1.8) 0 (0) – IVIG 31 (2.1) 27 (14.8) 3 (0.4)��� 0 (0)��� – CYC 13 (0.9) 1 (0.5) 11 (1.5) 1 (1.1) – Rituximab 69 (4.8) 26 (14.3) 41 (5.7)��� 1 (1.1)��� – Anti-TNF agents 96 (6.6) 3 (1.6) 85 (11.9)��� 6 (6.7)� – JAK inhibitors 22 (1.5) 2 (1.1) 19 (2.7) 1 (1.1) – Glucocorticoid (prednisone equivalent) No glucocorticoid 669 (46.2) 97 (53.3) 461 (64.4)��� 73 (82.0)��� – <10 mg a day 252 (17.4) 55 (30.2) 184 (25.7) 7 (7.9) – 10–20 mg a day 73 (5.0) 15 (8.1) 51 (7.1) 5 (5.6) – >20 mg a day 29 (2.0) 15 (8.2) 14 (2.0) 0 (0) – Vaccines received Pfizer-BioNTech (BNT162b2) 660 (45.6) 98 (53.8) 317 (44.3)� 53 (59.6) 192 (41.7)� Oxford-AstraZeneca (ChAdOx1 nCoV-19) 340 (23.5) 19 (10.4) 219 (30.6)��� 17 (19.1) 85 (18.5)� Moderna (mRNA 1273) 126 (8.7) 48 (26.4) 45 (6.3)��� 8 (9.0)��� 25 (5.4)��� Novovax (NVX-CoV2373) 1 (0.1) 0 (0) 0 (0) 0 (0) 1 (0.2) Covishield (ChAdOx1 nCoV- 19) 43 (3.0) 1 (1.1) 11 (1.5) 3 (3.4) 28 (6.1)� Covaxin (BBV152) 9 (0.6) 1 (0.5) 3 (0.4) 0 (0) 5 (1.1) Sputnik (Gam-COVID-Vac) 24 (1.7) 0 (0) 5 (0.7) 0 (0) 19 (4.1)� Sinopharm (BBIBP-CorV) 48 (3.3) 2 (1.1) 15 (2.1) 1 (1.1) 30 (6.5)�� Sinovac 90 (6.2) 6 (3.3) 40 (5.6) 5 (5.6) 39 (8.5)� Other 106 (7.3) 7 (3.8) 61 (8.5) 2 (2.2) 36 (7.8) Comparisons between IIM vs individual groups (v2 for categorical variables, Mann–Whitney U for continuous variable). � P<0.05. �� P< 0.005. ��� P<0.001. AIRDs: autoimmune rheumatic diseases; nrAIDs: non-rheumatic autoimmune diseases; BI: breakthrough infection; COPD: chronic obstructive pulmonary disease; HCs: healthy controls; IIMs: idiopathic inflammatory myopathies; JAK: Janus kinase. COVID-19 breakthrough infections in IIMs 601 D ow nloaded from https://academ ic.oup.com /rheum atology/article/64/2/597/7617840 by U niversity of G hana. Balm e Library user on 18 M arch 2025 two, three or four vaccine doses did not differ significantly af ter adjusting for time from BI (P¼ 0.705). BIs across subtypes had differences in myalgia and arthralgia, which are insignifi cant clinically (Supplementary Table 2). The second episode of COVID-19 BI Two hundred and seventy-nine respondents (2.9%) experienced a second COVID-19 BI, and the characteristics were comparable among patients with IIMs, patients with other AIRDs, patients with nrAIDs, and HCs (Supplementary Table 3). However, a second BI in patients with IIMs had the longest symptom resolution time (IIMs¼median 15 days, AIRDs¼10 days, nrAIDs¼12.5 days, and HCs¼ 7 days, P¼ 0.006). Treatment with antivirals or mAbs was also higher among patients with IIMs than in other groups (42.1%, AIRDs¼24.1%, nrAIDs¼16.7%, HCs¼ 10.5%, P¼ 0.002). Discussion In the present study, we analysed the characteristics and risk factors of COVID-19 BIs in a large and global sample of patients with IIMs. Our data showed that more than 1 in 10 patients with IIMs reported BIs after a median of 3.9 months post-vaccination. BIs were usually mild, although severe cases were more common in patients with IIMs than in patients with other AIRDs, patients with nrAIDs, and HCs. Glucocorticoid use was a risk factor for severe BIs, while having non-white ethnicity was a risk for all-cause hospitali zation. Descriptive and quantitative analysis showed that the severity of BIs did not differ between the various IIM subtypes, or with the prior number of vaccines received. Although BIs have been described previously in patients with IIMs, our study explored the important aspect of the effect of multiple vaccine doses and of following advanced treatments for COVID. [2, 4, 7, 9–11, 22]. COVID-19 BIs are common in patients with AIRDs (5–30%) and occurred in 15.3% of the current study’s participants [22, 23]. Reported BI cases are usually mild, as shown in our study, and they are increasing in frequency after the emergence of new SARS-CoV-2 variants, such as Omicron [7, 22, 23]. We found BIs occurred after a median of 3.9 months (percentiles 25th– 75th¼2.0–5.9) following the second COVID-19 vaccine; this is consistent with the most recent ACR guidance for COVID-19 vaccination in patients with rheumatic diseases, which Table 2. Univariable Cox regression analysis of risk factors for COVID-19 breakthrough infection, severe breakthrough infection, and hospitalization in patients with idiopathic inflammatory myopathies Breakthrough infection Severe BI Hospitalization due to COVID-19 HR 95% CI P HR 95% CI P HR 95% CI P Age 0.98 0.97 0.98 <0.001 0.99 0.95 1.02 0.571 0.97 0.94 0.99 0.033 Female gender (ref male) 1.12 0.80 1.57 0.487 35.00 0.36 3334.7 0.126 2.79 0.82 9.4 0.098 Ethnicity White Reference Reference Reference Non-white 1.57 1.13 2.18 0.007 2.31 0.84 6.37 0.105 3.52 1.55 8.00 0.003 Comorbidities Autoimmune multimorbidity 1.35 0.98 1.84 0.059 1.98 0.74 5.34 0.173 1.13 0.46 2.75 0.786 Any comorbidity 0.88 0.64 1.21 0.448 1.80 0.51 6.32 0.359 1.48 0.55 4.00 0.435 Mental health disorder 1.43 1.06 1.95 0.019 1.72 0.64 4.64 0.278 1.45 0.62 3.36 0.381 Country by HDI 1.18 0.95 1.47 0.125 1.50 0.86 2.61 0.153 1.54 0.99 2.40 0.053 First vaccine dose Adenovirus vector Reference Reference Reference mRNA 0.97 0.60 1.57 0.927 1.84 0.24 14.0 0.553 1.36 0.32 5.85 0.673 Other 1.53 0.71 3.31 0.273 0.00 0.00 –a 0.983 0.00 0.00 –a 0.979 Number of vaccine doses Two Reference Reference Reference Three 0.76 0.53 1.09 0.142 0.69 0.23 2.04 0.505 0.60 0.24 1.48 0.268 Four 2.13 1.27 3.58 0.004 0.00 0.00 –a 0.976 0.46 0.05 3.96 0.485 Immunosuppression MTX 1.31 0.93 1.85 0.112 1.75 0.60 5.04 0.300 1.71 0.70 4.16 0.236 MMF 1.50 1.06 2.13 0.020 2.14 0.74 6.17 0.157 2.56 1.08 6.04 0.032 AZA 0.90 0.51 1.59 0.730 0.75 0.09 5.72 0.781 1.14 0.26 4.94 0.853 HCQ 2.08 1.47 2.93 <0.001 1.45 0.41 5.13 0.561 0.96 0.28 3.25 0.951 SSZ 4.30 2.01 9.12 <0.001 0.04 0.00 –a 0.790 0.04 0.00 –a 0.751 LEF 0.80 0.11 5.74 0.828 0.04 0.00 –a 0.814 0.04 0.00 –a 0.778 Tacrolimus 1.56 0.64 3.80 0.325 3.74 0.49 28.4 0.202 5.23 1.22 22.4 0.026 CSA 1.03 0.38 2.79 0.944 0.04 0.00 –a 0.699 0.04 0.00 –a 0.631 IVIG 0.87 0.57 1.33 0.528 0.35 0.04 2.68 0.315 0.78 0.23 2.65 0.701 CYC 0.72 0.10 5.19 0.751 0.04 0.00 –a 0.811 0.04 0.00 –a 0.779 Rituximab 1.28 0.83 1.97 0.260 2.72 0.87 8.50 0.084 3.75 1.53 9.18 0.004 TNF inhibitors 1.49 0.47 4.66 0.494 0.04 0.00 –a 0.778 0.04 0.00 –a 0.737 JAK inhibitors 0.77 0.19 3.12 0.721 0.04 0.00 –a 0.739 0.04 0.00 –a 0.688 Any glucocorticoid dose 1.34 0.99 1.81 0.051 4.86 1.56 15.11 0.006 3.79 1.55 9.23 0.003 Univariable Cox regression analysis performed. a Those with wide CI (very high upper limits of 95% CI). BI: breakthrough infection; HDI: Human Development Index; HR: hazard ratio; JAK: Janus kinase; severe BI: hospitalization due to COVID-19 or oxygen requirement or ICU/HDU admission or need for advanced treatment. 602 Leonardo Santos Hoff et al. D ow nloaded from https://academ ic.oup.com /rheum atology/article/64/2/597/7617840 by U niversity of G hana. Balm e Library user on 18 M arch 2025 https://academic.oup.com/rheumatology/article-lookup/doi/10.1093/rheumatology/keae128#supplementary-data https://academic.oup.com/rheumatology/article-lookup/doi/10.1093/rheumatology/keae128#supplementary-data https://academic.oup.com/rheumatology/article-lookup/doi/10.1093/rheumatology/keae128#supplementary-data recommends a booster shot 3–4 months after completion of the primary vaccine series [24]. However, the timing for a booster dose is a complex matter that may vary according to the approach of the local authorities, the previous vaccine received, immunosuppression status, and the emergence of new variants [24, 25]. Table 3. Multivariable Cox regression analysis of risk factors for COVID-19 breakthrough infection, severe breakthrough infection, and hospitalization in patients with idiopathic inflammatory myopathies Breakthrough infection Severe BI Hospitalization due to COVID-19 HR 95% CI HR 95% CI HR 95% CI Age 0.98� 0.97� 0.99� 1.00 0.96 1.03 0.99 0.96 1.02 Female gender 0.77 0.53 1.11 – – – 1.65 0.47 5.82 Ethnicity – – – – – – – – – White Reference Reference Reference Non-white 1.17 0.80 1.71 – – – 2.61 1.03 6.59 Comorbidities Autoimmune multimorbidity 1.11 0.79 1.56 1.76 0.62 4.95 – – – Mental health disorder 1.20 0.87 1.65 – – – – – – Immunosuppression MTX 1.07 0.73 1.56 – – – – – – MMF 1.34 0.91 1.96 1.47 0.46 4.64 1.60 0.62 4.16 HCQ 1.81� 1.24� 2.64� – – – – – – SSZ 3.79� 1.69� 8.42� – – – – – – Tacrolimus – – – – – – 1.82 0.38 8.73 Rituximab – – – 1.67 0.48 5.73 1.87 0.69 5.08 Any glucocorticoid dose 0.98 0.71 1.36 3.61� 1.09� 11.8� 2.34 0.90 6.08 Cox regression analysis adjusted for age, gender, ethnicity, and other covariates significant in univariable analysis (or P< 0.2), and eliminating those with a wide CI was used. Some covariates, like number of vaccine doses, country by HDI, that did not follow the proportional hazards assumption were eliminated from the model. � P<0.05 was considered significant (indicated in bold typeface). BI: breakthrough infection; HDI: Human Development Index; HR: hazard ratio; JAK: Janus kinase; severe BI: hospitalization due to COVID-19 or oxygen requirement or ICU/HDU admission or need for advanced treatment. Table 4. Comparison of COVID-19 breakthrough infections symptoms and severity among participants IIMs (n¼ 182) AIRDs (n¼716) nrAIDs (n¼ 89) HCs (n¼ 460) Pa Median symptoms resolution time, days (25th–75th) 12 (7–24) 11 (6–20) 8 (4–15.5)� 7 (4–14)��� <0.001 Any symptoms 179 (98.4) 687 (96.0) 84 (94.4) 434 (94.3) 0.135 Fever 90 (49.5) 366 (51.1) 40 (44.9) 214 (46.5) 0.390 Fatigue 116 (63.7) 453 (63.3) 49 (55.1) 272 (59.1) 0.263 Muscle aches 86 (47.3) 335 (46.8) 39 (43.8) 233 (50.7) 0.498 Joint pains 51 (28.0) 291 (40.6) 21 (21.3) 119 (25.9) <0.001 Cough 123 (67.6) 423 (59.1) 42 (47.2) 235 (51.1) <0.001 Difficulty breathing 35 (19.2) 152 (21.2) 14 (15.7) 55 (12.0) <0.001 Loss of smell 32 (17.6) 161 (22.5) 20 (22.5) 102 (22.2) 0.540 Loss of taste 38 (21.0) 150 (21.0) 14 (15.7) 82 (17.8) 0.427 Running nose 87 (47.8) 320 (44.7) 35 (39.3) 170 (37.0) 0.022 Congestion 74 (40.7) 249 (34.8) 25 (28.1) 148 (32.2) 0.123 Throat pain/scratchiness 89 (48.9) 363 (50.7) 45 (50.6) 209 (45.0) 0.285 Chest pain 20 (11.0) 111 (15.5) 5 (5.6) 41 (8.9) 0.001 Diarrhoea 29 (15.9) 114 (16.0) 8 (9.0) 62 (13.5) 0.269 Headache 77 (42.3) 335 (46.8) 27 (30.3) 170 (37.0) <0.001 Oral ulcers 6 (3.3) 27 (3.8) 2 (2.2) 8 (1.7) 0.237 Nausea/vomiting 22 (12.1) 86 (12.0) 2 (2.2) 29 (6.3) <0.001 Abdominal pain 12 (6.6) 72 (10.1) 4 (4.5) 27 (5.9) 0.030 Skin rashes 6 (3.3) 27 (3.8) 2 (2.2) 8 (1.7) 0.237 Outcomes All-cause hospitalization 14 (7.7) 33 (4.6) 1 (1.1) 7 (1.5) <0.001 ICU care or other HDU 4 (2.2) 4 (0.6) 0 (0) 0 (0) 0.007 Oxygen requirement 11 (6.0) 13 (1.8) 2 (2.2) 4 (0.9) <0.001 Advanced treatment for COVID-19 infection 62 (34.1) 185 (25.8) 13 (14.6) 59 (12.8) <0.001 Data are expressed as median (25th–75th percentiles) or frequency (%). a Kruskal Wallis for continuous variables and v2 for categorical variables. P< 0.0125 is significant after Bonferroni correction. � P<0.05. �� P< 0.005. ��� P<0.001 by Dunn–Bonferroni post hoc test comparing IIM vs the particular group. Advanced treatment: antiviral or monoclonal antibodies; AIRDs: autoimmune rheumatic diseases; nrAIDs: non-rheumatic autoimmune diseases; HCs: healthy controls; HDU: high-dependency unit; ICU: intensive care unit; IIMs: idiopathic inflammatory myopathies; IQR: interquartile range; PROMIS: Patient Reported Outcomes Measurement Information System. COVID-19 breakthrough infections in IIMs 603 D ow nloaded from https://academ ic.oup.com /rheum atology/article/64/2/597/7617840 by U niversity of G hana. Balm e Library user on 18 M arch 2025 We found that HCQ use was associated with higher risk of BIs, unlike the findings in previous studies. While our study was not designed to study the effect of immunosuppression on COVID-19, we cannot fully discount the possibility of disease heterogeneity, alongside a global sample of patients that may result in varied prescription practices, accounting for differen ces in our results from those of other groups [12]. In addition, this is the largest series of patients with IIMs for whom data on BIs have been published to date. IIMs are known to exhibit an active IFN axis, which may influence viral clearance in these patients [13]. Our group has previously reported that BIs were less common in patients with IIMs, albeit the BIs are more severe when testing positive for COVID-19 [4]. We also found an increased risk of severe COVID-19 among patients with IIMs on glucocorticoids, drugs well known for being associated with unfavourable outcomes among patients with au toimmune diseases and SARS-CoV-2 infection [6, 26, 27]. Finally, having non-white ethnicity was a risk factor for all-cause hospitalization, which may be explained by inequity in access to health-care services and socio-economic disparity of ethnic minor ities, though we did not assess these other covariates [28]. Non- white ethnicity has also been described as a risk factor for severe COVID-19 in patients with neuromuscular diseases, including IIMs [29]. All-cause hospitalization related to BIs was more common in patients with IIMs compared with patients with other AIRDs, patients with nrAIDs, and HCs, consistent with previ ous data [4]. This may be explained by the increased suscepti bility of patients with IIMs to infections, owing to the frequent need for immunosuppression, multi-organ particularly pulmo nary disease sequelae [30], and underlying activation of IFN pathways that may give rise to deleterious virus–host interac tions [13]. On the contrary, a recent registry-based cohort analysis found COVID-19 outcomes to be more favourable in patients with DM than HCs, though the cohort had a consid erably distinct ethnicity and comorbidity profile compared with ours [31]. A global registry study did not find any specific rheumatic disease to be a risk factor for COVID-19 hospitali zation in people with rheumatic diseases, although patients with IIMs were not included as a covariate in the multivariable regression model used in that study [32]. The large sample size of our study enabled us to meaning fully compare BIs in various subtypes of IIMs, an aspect not explored in previous studies [6, 31]. We found that while the severity of BIs did not, reassuringly, differ, there were subtle differences in the incidence of myalgia and joint pain, which may possibly be attributed to the exacerbation of distinct un derlying disease processes in the different subtypes by COVID-19, manifesting as varied symptom profiles [33]. With our large sample, we could also analyse both descrip tively and quantitatively the characteristics of the second BI, which had longer symptoms and required more treatment with antiviral or mAbs in patients with IIMs than in other groups. Though less severe than the first episode of a BI, these findings emphasize that patients with IIMs are more vulnera ble to severe COVID-19 BIs than patients with other AIDRs, patients with nrAIDs, and HCs. Our study has limitations. Whether COVID-19 first infec tion or BI was not confirmed specifically by RT-PCR, although a positive diagnostic test was required to confirm COVID-19 infection. We did not assess the effect of educational level, in come, hybrid immunity (immunity due to both COVID-19 in fection and vaccination), or specific SARS-CoV-2 variants of concern on the risk of developing BIs or all-cause hospitaliza tion. Although we did not collect data about virus sequencing and genotyping from our participants, the main variants of concern circulating during the study were Delta, Omicron BA.1 and Omicron BA.5 [34]. Additionally, patients who re ceived the primary series with a single vaccine dose were ex cluded from the analysis to facilitate the interpretation and analysis of data on subsequent vaccine doses, although they represented only a small percentage of the available sample. We are also prone to recall and report bias associated with self-reported surveys of this nature, though we tried to mini mize this through the inclusion of controls and analysis of stratified subsets. Additionally, the multivariable regression model included some variables with small numbers (like the medication SSZ) giving some significant results which needs to be interpreted with caution. Disease activity or flares were not assessed as outcomes of interest following BIs, although recent studies from our group have shown that disease flares follow ing vaccination occur in 11.3% and are mild among patients with AIRDs [35], while 30.4% of patients with IIMs reported a flare following COVID-19 infection [36]. We analysed COVID-19 BIs in a large ethnically and geo graphically diverse sample of IIMs and explored understudied aspects, including the role of multiple vaccinations and IIM subtypes. In the current landscape of booster doses, the results still hold significance, since they address various crucial facets of the COVID-19 vaccination. Patients with IIMs required more supplemental oxygen therapy, intensive care unit admis sion, advanced treatment with antiviral or monoclonal anti bodies, and had more all-cause hospitalization than their counterparts. Therefore, they can be considered a vulnerable subgroup for severe BIs. Future prospective studies with longer follow-ups are needed to better elucidate clinical and demo graphic factors associated with COVID-19 BIs and unfavoura ble outcomes among vaccinated patients with IIMs. Supplementary material Supplementary material is available at Rheumatology online. Data availability The datasets generated and/or analysed during the current study are not publicly available but are available from the corresponding author upon reasonable request. Contribution statement L.G., S.S.A., P.S. and N.R contributed to conceptualization of the study. All authors contributed to data curation and to reviewing and editing of the manuscript. S.S.A., P.S. and L.G. wrote the original draft of the manuscript. Formal analysis was undertaken by N.R. Investigation was undertaken by L. G., S.S.A., P.S. and N.R. The methodology was designed by L.G., V.A. and N.R. The software was used by L.G. Validation was undertaken by V.A., R.A., J.B.L. and H.C. Visualization was carried out by R.A, V.A. and L.G. Funding No specific funding was received from any funding bodies in the public, commercial, or not-for-profit sectors to carry out the work described in this manuscript. 604 Leonardo Santos Hoff et al. D ow nloaded from https://academ ic.oup.com /rheum atology/article/64/2/597/7617840 by U niversity of G hana. Balm e Library user on 18 M arch 2025 https://academic.oup.com/rheumatology/article-lookup/doi/10.1093/rheumatology/keae128#supplementary-data Disclosure statement: A.L.T. has received honoraria for advi sory boards and speaking from Abbvie, Gilead, Janssen, Lilly, Novartis, Pfizer, and UCB. E.N. has received speaker honoraria/participated in advisory boards for Celltrion, Pfizer, Sanofi, Gilead, Galapagos, AbbVie, and Lilly, and holds research grants from Pfizer and Lilly. H.C. has received grant support from Eli Lilly and UCB, consulting fees from Novartis, Eli Lilly, Orphazyme, and Astra Zeneca, speaker fees from UCB, and Biogen. I.P. has received research funding and/or honoraria from Amgen, AstraZeneca, Aurinia Pharmaceuticals, Elli Lilly and Company, Gilead Sciences, GlaxoSmithKline, Janssen Pharmaceuticals, Novartis and F. Hoffmann-La Roche AG. J.B.L. has received speaker hono raria from/participated in advisory boards for Sanofi Genzyme, Roche, and Biogen; none are related to this manu script. J.D.P. has undertaken consultancy work for and/or re ceived speaker honoraria from Astra Zenaca, Boehringer Ingelgheim, Sojournix Pharma, Permeatus Inc, Janssen and IsoMab Pharmacueticals. J.D. has received research funding from CSL Limited. M.K. has received speaker honoraria from/participated in advisory boards for Abbvie, Asahi- Kasei, Astellas, AstraZeneca, Boehringer-Ingelheim, Chugai, Corbus, Eisai, GSK, Horizon, Kissei, BML, Mochida, Nippon Shinyaku, Ono Pharmaceuticals, and Tanabe- Mitsubishi. N.Z. has received speaker fees, advisory board fees, and research grants from Pfizer, Roche, Abbvie, Eli Lilly, NewBridge, Sanofi-Aventis, Boehringer Ingelheim, Janssen, and Pierre Fabre; none are related to this manu script. O.D. has had a consultancy relationship with and/or has received research funding from and/or has served as a speaker for the following companies in the area of potential treatments for SSc and its complications in the last three cal endar years: 4P-Pharma, Abbvie, Acceleron, Alcimed, Altavant, Amgen, AnaMar, Arxx, AstraZeneca, Baecon, Blade, Bayer, Boehringer Ingelheim, Corbus, CSL Behring, Galderma, Galapagos, Glenmark, Gossamer, iQvia, Horizon, Inventiva, Janssen, Kymera, Lupin, Medscape, Merck, Miltenyi Biotec, Mitsubishi Tanabe, Novartis, Prometheus, Redxpharma, Roivant, Sanofi and Topadur, and has a patent issued: ‘mir-29 for the treatment of systemic sclerosis’ (US8247389, EP2331143). R.A. has a consultancy relation ship with and/or has received research funding from the fol lowing companies: Bristol Myers-Squibb, Pfizer, Genentech, Octapharma, CSL Behring, Mallinckrodt, AstraZeneca, Corbus, Kezar, Abbvie, Janssen, Kyverna Alexion, Argenx, Q32, EMD-Serono, Boehringer Ingelheim, Roivant, Merck, Galapagos, Actigraph, Scipher, Horizon Therepeutics, Teva, Beigene, ANI Pharmaceuticals, Biogen, Nuvig, Capella Bioscience, and CabalettaBio. T.V. has received speaker hon oraria from Pfizer and AstraZeneca. H.C. was supported by the National Institution for Health Research Manchester Biomedical Research Centre Funding Scheme. The views expressed in this publication are those of the authors and not necessarily those of the NHS, National Institute for Health Research, or Department of Health. The other authors have declared no conflicts of interest. Acknowledgements The authors are grateful to all respondents for completing the questionnaire. The authors also thank the Myositis Association, Myositis India, Myositis UK, Myositis Support and Understanding, the Myositis Global Network, Deutsche Gesellschaft f€ur Muskelkranke e. V. (DGM), Dutch and Swedish Myositis patient support groups, Cure JM, Cure IBM, Sj€ogren’s India Foundation, Patients Engage, Scleroderma India, Lupus UK, Lupus Sweden, Emirates Arthritis Foundation, EULAR PARE, ArLAR research group, AAAA pa tient group, Myositis Association of Australia, APLAR myositis special interest group, Thai Rheumatism association, PANLAR, AFLAR NRAS, Anti-Synthetase Syndrome support group, and various other patient support groups and organizations for their contribution to the dissemination of this survey. Finally, the authors wish to thank all members of the COVAD study group for their invaluable role in the data collection. COVAD Study Group Authors: Esha Kadam, Sinan Kardes, Laura Andreoli, Daniele Lini, Karen Schreiber, Melinda Nagy Vince, Yogesh Preet Singh, Rajiv Ranjan, Avinash Jain, Sapan C. Pandya, Rakesh Kumar Pilania, Aman Sharma, Manesh Manoj M., Vikas Gupta, Chengappa G. Kavadichanda, Pradeepta Sekhar Patro, Sajal Ajmani, Sanat Phatak, Rudra Prosad Goswami, Abhra Chandra Chowdhury, Ashish Jacob Mathew, Padnamabha Shenoy, Ajay Asranna, Keerthi Talari Bommakanti, Anuj Shukla, Arunkumar R. Pande, Kunal Chandwar, Akanksha Ghodke, Hiya Boro, Armen Yuri Gasparyan, Zoha Zahid Fazal, D€ond€u €Usk€udar Cansu, Reşit Yıldırım, Nicoletta Del Papa, Gianluca Sambataro, Atzeni Fabiola, Marcello Govoni, Simone Parisi, Elena Bartoloni Bocci, Gian Domenico Sebastiani, Enrico Fusaro, Marco Sebastiani, Luca Quartuccio, Franco Franceschini, Pier Paolo Sainaghi, Giovanni Orsolini, Rossella De Angelis, Maria Giovanna Danielli, Vincenzo Venerito, Silvia Grignaschi, Alessandro Giollo, Alessia Alluno, Florenzo Ioannone, Marco Fornaro, Lisa S. Traboco, Suryo Anggoro Kusumo Wibowo, Jes�us Loarce-Martos, Sergio Prieto-Gonz�alez, Raquel Aranega Gonzalez, Akira Yoshida, Ran Nakashima, Shinji Sato, Naoki Kimura, Yuko Kaneko, Takahisa Gono, Stylianos Tomaras, Fabian Nikolai Proft, Marie-Therese Holzer, Margarita Aleksandrovna Gromova, Or Aharonov, Zolt�an Griger, Ihsane Hmamouchi, Imane El bouchti, Zineb Baba, Margherita Giannini, François Maurier, Julien Campagne, Alain Meyer, Daman Langguth, Vidya Limaye, Merrilee Needham, Nilesh Srivastav, Marie Hudson, Oc�eane Landon-Cardinal, Wilmer Gerardo Rojas Zuleta, �Alvaro Arbel�aez, Javier Cajas, Jos�e Ant�onio Pereira Silva, Jo~ao Eurico Fonseca, Olena Zimba, Doskaliuk Bohdana, Uyi Ima-Edomwonyi, Ibukunoluwa Dedeke, Emorinken Airenakho, Nwankwo Henry Madu, Abubakar Yerima, Hakeem Olaosebikan, Becky A., Oruma Devi Koussougbo, Elisa Palalane, Ho So, Manuel Francisco Ugarte-Gil, Lyn Chinchay, Jos�e Proa~no Bernaola, Victorio Pimentel, Hanan Mohammed Fathi, Reem Hamdy A. 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Rheumatology (Oxford) 2023;62:e263–8. 606 Leonardo Santos Hoff et al. D ow nloaded from https://academ ic.oup.com /rheum atology/article/64/2/597/7617840 by U niversity of G hana. Balm e Library user on 18 M arch 2025 https://www.icmr.gov.in/pdf/covid/techdoc/EC_Guidance_COVID19_06052020.pdf https://www.icmr.gov.in/pdf/covid/techdoc/EC_Guidance_COVID19_06052020.pdf https://heal.nih.gov/files/CDEs/2023-07/promis-short-form-4a-fatigue-crf.pdf https://heal.nih.gov/files/CDEs/2023-07/promis-short-form-4a-fatigue-crf.pdf https://ourworldindata.org/grapher/covid-variants-bar https://ourworldindata.org/grapher/covid-variants-bar # The Author(s) 2024. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com Rheumatology, 2025, 64, 597–606 https://doi.org/10.1093/rheumatology/keae128 Original Article D ow nloaded from https://academ ic.oup.com /rheum atology/article/64/2/597/7617840 by U niversity of G hana. Balm e Library user on 18 M arch 2025 Active Content List Introduction Methods Results Discussion Supplementary material Data availability Contribution statement Funding Acknowledgements References