Abstract
Objectives
We aimed to compare the spectrum and severity of COVID-19 and vaccine breakthrough infections (BIs) among patients with IIMs, other systemic autoimmune and inflammatory diseases (SAIDs), and healthy controls (HCs).
Methods
This is a cross-sectional study with data from the COVAD study, a self-reported online global survey that collected demographics, COVID-19 history, and vaccination details from April to September 2021. Adult patients with at least one COVID-19 vaccine dose were included. BIs were defined as infections occurring > 2 weeks after any dose of vaccine. Characteristics associated with BI were analyzed with a multivariate regression analysis.
Results
Among 10,900 respondents [42 (30–55) years, 74%-females, 45%-Caucasians] HCs were (47%), SAIDs (42%) and IIMs (11%). Patients with IIMs reported fewer COVID-19 cases before vaccination (6.2%-IIM vs 10.5%-SAIDs vs 14.6%-HC; OR = 0.6, 95% CI 0.4–0.8, and OR = 0.3, 95% CI 0.2–0.5, respectively). BIs were uncommon (1.4%-IIM; 1.9%-SAIDs; 3.2%-HC) and occurred in 17 IIM patients, 13 of whom were on immunosuppressants, and 3(18%) required hospitalization. All-cause hospitalization was higher in patients with IIM compared to HCs [23 (30%) vs 59 (8%), OR = 2.5, 95% CI 1.2–5.1 before vaccination, and 3 (18%) vs 9 (5%), OR = 2.6, 95% CI 1.3–5.3 in BI]. In a multivariate regression analysis, age 30–60 years was associated with a lower odds of BI (OR = 0.7, 95% CI 0.5–1.0), while the use of immunosuppressants had a higher odds of BI (OR = 1.6, 95% CI 1.1–2.7).
Conclusions
Patients with IIMs reported fewer COVID-19 cases than HCs and other SAIDs, but had higher odds of all-cause hospitalization from COVID-19 than HCs. BIs were associated with the use of immunosuppressants and were uncommon in IIMs.
Supplementary Information
The online version contains supplementary material available at 10.1007/s00296-022-05229-7.
Keywords: Autoimmune diseases, Breakthrough infection, COVID-19, Idiopathic inflammatory myopathies, SARS-CoV-2 vaccination
Introduction
The coronavirus disease 2019 (COVID-19) pandemic and the attendant risk of infection have been a serious cause for concern among patients with idiopathic inflammatory myopathies (IIMs) and other systemic autoimmune and inflammatory diseases (SAIDs) [1]. Patients with IIMs represent a unique vulnerable subgroup, as they typically require long-term treatment with multiple immunosuppressive and immunomodulatory (IS/IM) therapy [2, 3], which is associated with impaired host response to infections [3, 4]. Patients with IIMs may also have multiple sequelae of their disease (e.g., impaired strength, lung fibrosis) and frequent comorbidities (e.g., cardiovascular disease, obesity, and diabetes) [5]. Thus, this patient subgroup may be more susceptible to COVID-19 infection and at greater risk of severe COVID-19 complications than healthy controls and most other SAIDs [6].
Large cohort studies have indeed indicated higher COVID-19 associated mortality and poorer clinical outcomes in patients with autoimmune rheumatic diseases compared to the general population [7–9], with a hospitalization rate of 58% and fatality of 7% in these patients according to a meta-analysis [10], as opposed to a hospitalization rate in intensive care unit of 11% [11] and a fatality rate of only 1% in the general population [12]. Furthermore, despite some contradictory data regarding the incidence of COVID-19 infection among patients with autoimmune rheumatic diseases versus the general population, a recent systematic review and meta-analysis of 100 studies has demonstrated that patients with rheumatic and musculoskeletal diseases have a higher rate of SARS-CoV-2 infection and increased odds of mortality [13]. COVID-19 characteristics and outcomes are usually studied in patients with SAIDs as a large group [1, 5–10, 13], but specific data about COVID-19 in the subset of IIMs patients are scarce [14].
While there is a paucity of long-term safety and efficacy data regarding COVID-19 vaccination in patients with SAIDs, current evidence suggests that the benefits of vaccination far outweigh the potential risks of adverse effects and vaccination-induced disease flares in this vulnerable patient group [15–17]. Thus, prominent medical organizations have recommended COVID-19 vaccination in patients with autoimmune rheumatic diseases [18–21]. Of major concern is the possibility of attenuated immunogenicity and, consequently, reduced efficacy of vaccines induced by the concomitant use of IS/IM therapies in these patients, which could leave them vulnerable to breakthrough COVID-19 infections [16]. Little is currently known about the incidence and the severity of breakthrough infections (BI) in patients with IIMs and other SAIDs vaccinated against COVID-19, mainly because these patients were excluded from most trials of COVID-19 vaccines [16]. Vaccine safety and efficacy data are especially limited in patients with IIMs, and scarce data on the specific risks of COVID-19 vaccination in this patient group are currently available [22].
This study aimed to compare the frequency, profile, and severity of COVID-19 infection both prior to and post-vaccination in patients with IIMs, other SAIDs, and healthy controls (HCs).
Materials and methods
Study design and ethics statement
This is a cross-sectional study with secondary data from the COVID-19 Vaccination in Autoimmune Diseases (COVAD) study. COVAD study is an ongoing online questionnaire-based study that evaluates COVID-19 characteristics and vaccine safety in adult participants (older than 18 years old) diagnosed with SAIDs and healthy controls [23]. Before answering the questionnaire, participants are asked to provide their informed consent and no financial support is offered for survey completion. COVAD study was approved by the local ethics committee of Sanjay Gandhi Postgraduate Institute, Lucknow (IEC Code: 2021-143-IP-EXP-39). The current manuscript is reported according to the Checklist for Reporting Results of the Internet E-Surveys [24, 25].
Case definition
Participants answered the question “Did you ever test positive for COVID-19?” and specified the number of events and the dates of occurrence; they also stated the dates of vaccination. BI was defined as an infection occurring more than 2 weeks after receipt of a first or second dose of a COVID-19 vaccine. Though CDC currently defines BI as an infection occurring after receipt of the second dose of a COVID-19 vaccine, we included infections occurring after the first primary dose because most people globally had only received a single vaccine dose at the time of survey dissemination, and the definition of BI was still evolving [26]. Regarding diagnostic tests, we did not confirm COVID-19 serology or vaccine immunogenicity, and this is included as a limitation of the study in the Discussion section.
Data collection and participants
Participants answered an electronic survey consisting of 36 COVID-19 and SAIDs-related questions, which included demographics, diagnosis confirmed by a physician, current disease activity status, and treatment, COVID-19 infection history (symptoms and complications like all-cause hospitalization and requirement of oxygen), COVID-19 vaccination status and adverse effects, and outcome measures as per the Patient-Reported Outcomes Measurement Information System (PROMIS) tool [27]. The survey was developed by international rheumatology experts and was disseminated on an online platform (surveymonkey.com) after pilot testing and translation into 18 languages. Over 110 physicians from 94 countries participated in the COVAD study group and supported the dissemination of the survey on social media and online patient advocacy organizations. The questions analyzed in the current study were closed-ended. Detailed methods of the COVAD study protocol have been published elsewhere [23].
Data were retrieved from April 1st 2021 to 30th September 2021. We have chosen to analyze data from this time interval because it is considered the “first wave” of the COVAD study, comprising the period that we began to disseminate the survey and the moment we had enough answers to analyze multiple scenarios and outcomes.
Inclusion and exclusion criteria
All respondents who received at least a single dose of the COVID-19 vaccine and fully completed the survey were included in the final analysis. Duplicate responses from a single respondent were identified using electronic protocols. Participants who were not vaccinated against COVID-19 at the time of survey completion and those who did not fully answer the survey were excluded from the analysis.
Statistical analysis
Median and interquartile range (IQR) were reported for variables with non-normal distribution. Categorical variables were presented as frequencies and proportions. When comparing the frequency of COVID-19 and the severity of COVID-19 among IIM, other SAIDs, and HC, odds ratio (OR) adjusted for age, gender, ethnicity, and stratified by country of origin was presented. We performed a univariate regression analysis to explore if age, gender, ethnicity, vaccination status, diagnosis, corticosteroid use, and immunosuppressive or immunomodulatory therapies (IS/IM) were associated with BI. The multivariable regression analysis was stratified by country of origin and adjusted for age, gender, and covariates with a P < 0.1 in the univariate analysis. A P value < 0.05 was considered statistically significant. Scale variables were compared with Mann–Whitney U test and regression analysis. Statistical analysis was performed using the SPSS version 26 and Software R 3.5.3 (R Core Team 2020).
Results
Population characteristics
Out of 16,328 respondents, 2866 did not receive any COVID-19 vaccine at the time of questionnaire fulfillment and 2562 did not entirely complete the surveyl therefore, they were excluded from the final analysis. The flow diagram with the 10,900 vaccinated respondents with complete responses included in the analysis is shown in Fig. 1. Patients with IIMs were 1227 (11.2%), while patients with other SAIDs were 4640 (42.6%), and 5033 (46.2%) were HCs. The respondents resided in 96 countries as follows: 14.9% in Turkey, 12.5% in Mexico, 13.1% in India, 11.6% in the United Kingdom, 9.9% in the United States of America, 5.5% in Italy, and 32.5% in other countries (Supplementary Table 1).
The most common SAID was rheumatoid arthritis (13%, n = 1459), followed by IIMs (11%, n = 1227), and Graves’ or Hashimoto’s disease (9%, n = 1051). Patients with IIMs included those with dermatomyositis, polymyositis, inclusion body myositis, antisynthetase syndrome, necrotizing autoimmune myopathy, juvenile dermatomyositis, and overlap myositis. A similar proportion of patients with IIMs (12%) and other SAIDs (13%) discontinued their IS/IM therapy prior to vaccination (Supplementary Table 2).
All respondents included in the final analysis had received at least a single dose of the vaccine at the time of survey completion and 7559 (69%) respondents had received two doses. The largest number of respondents received the BNT162b2 (Pfizer)-BioNTech vaccine (39.8%, n = 4333), followed by the BBIBP-CorV Sinopharm (16.7%, n = 1821), ChadOx1 nCOV-19 (Oxford/AstraZeneca) (13.4%, n = 1456), and ChAdOx1 nCoV-19 (Covishield Serum Institute India) (10.9%, n = 1194) vaccines (Supplementary Table 2).
The majority of COVID-19 cases occurred prior to vaccination, as seen in Table 1as follows: 1297 cases (78%) occurred prior to vaccination, 92 (6%) occurred within 2 weeks of receiving COVID-19 vaccination, and 267 (16%) occurred after the first- or second-dose of vaccination and were, therefore, considered BI. Interestingly, patients with IIMs reported fewer COVID-19 cases before vaccination (76 cases, 6.2%) than patients with other SAIDs (488 cases, 10.5%) and HCs (733 cases, 14.6%) (OR = 0.6, 95% CI 0.4–0.8, p = 0.002, and OR = 0.3, 95% CI 0.2–0.5, p < 0.001, respectively).
Table 1.
COVID-19 cases: all subjects | Total (n = 10900) | IIMs (n = 1227) | Other SAIDs (n = 4640) | HCs (n = 5033) | IIMs versus Other SAIDs | IIMs versus HCs | ||
---|---|---|---|---|---|---|---|---|
OR (95% CI) | P value | OR (95% CI) | P value | |||||
Before vaccination | 1297 (11.9) | 76 (6.2) | 488 (10.5) | 733 (14.6) | 0.6 (0.4–0.8) | 0.002 | 0.3 (0.2–0.5) | < 0.001 |
≤ Two weeks after first or second primary vaccine dose | 92 (0.8) | 10 (0.8) | 40 (0.9) | 42 (0.8) | 0.7 (0.1–2.6) | 0.613 | 0.6 (0.2–2.2) | 0.497 |
> Two weeks after first or second primary vaccine dose (breakthrough infection) | 267 (2.5) | 17 (1.4) | 89 (1.9) | 161 (3.2) | 0.7 (0.4–1.5) | 0.480 | 0.5 (0.2–1.1) | 0.070 |
Total | 1656 (15.2) | 103 (8.4) | 617 (13.3) | 936 (18.6) | 0.6 (0.4–0.8) | 0.001 | 0.4 (0.3–0.5) | < 0.001 |
CI confidence interval, HCs healthy controls, IIMs idiopathic inflammatory myopathies, OR odds ratio, NS not significant, SAIDs systemic autoimmune and inflammatory diseases
*Odds ratio adjusted for age, gender, ethnicity, and stratified by country of origin
Breakthrough infections (BIs)
BIs were seen in 17 (1.4%) of IIM patients, 89 (1.9%) of other SAID patients, and 161 (3.2%) of HC. Among the IIM patients with BI, nine were dermatomyositis (DM), three were anti-synthetase syndrome (ASSD), two polymyositis (PM), one overlap myositis (OM), one necrotizing autoimmune myositis (NAM), and one juvenile dermatomyositis (JDM) (Table 2). ChAdOx1 nCoV-19 (Covishield Serum Institute India) (n = 5) followed by BNT162b2 (Pfizer)-BioNTech vaccine (n = 4) takers were most frequent vaccine received by them prior to BI. Fever, fatigue, myalgia, and cough were the most common symptoms seen in them. Three (18%) were asymptomatic. The median disease duration was 7 (3–10) days. Three patients (18%) were hospitalized with or without O2 requirement following BI. Among the 89 patients with BI in SAIDs, thyroid disease (n = 18) and type one diabetes mellitus (n = 10) were the most common. Six patients (7%) were asymptomatic among them. ChAdOx1 nCoV-19 (Covishield Serum Institute India) (n = 24) and BNT162b2 (Pfizer)-BioNTech (n = 22) were the most frequent vaccine received prior to BI in them. Median disease duration was 11 (5–20) days. Ten patients (11%) had required hospitalization following BI. Among the 161 HC with BI, asymptomatic infection was seen in 20 (12%). BBIBP-CorV (Sinopharm) (n = 60) and ChAdOx1 nCoV-19 (Covishield Serum Institute India) (n = 45) were the most common vaccine received by them prior to BI. The median disease duration was 7 (3–12) days. All cause hospitalization were seen in 9 (5%) of them (Table 3).
Table 2.
N | Vaccine received | Age | Gender | Country | IIMs type | Symptoms duration (days) | COVID-19 symptoms | Hospitalization or O2 support | IS received prior infection | Whether IS was discontinued during infection | Days between BI and vaccination |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | ChAdOx1 nCoV-19 (Covishield Serum Institute India) | 45 | F | India | DM | 3 | Fever, fatigue, myalgia, cough, diarrhea | No | None | – | 19 |
2 | BNT162b2 (Pfizer)-BioNTech | 26 | F | Mexico | DM | 6 | Headache, anosmia | No | Mtx, Aza, Prednisolone (< 10 mg/day) | Yes (Mtx for 7 days) | 19 |
3 | BNT162b2 (Pfizer)-BioNTech | 62 | M | USA | NAM | 0 | Loss of taste | No | IVIG, prednisolone (> 20 mg/day) | No | 21 |
4 | ChAdOx1 nCoV-19 (Covishield Serum Institute India) | 62 | F | India | DM | 5 | Fever, fatigue, cough, breathlessness | No | MMF, prednisolone (< 10 mg/day) | No | 22 |
5 | mRNA-1273 (Moderna) | 58 | F | USA | DM | 8 | Fever, fatigue, myalgia, cough, skin rashes | No | HCQ, Rtx | Yes (Rtx for 7 days) | 25 |
6 | ChadOx1 nCOV-19 (Oxford/AstraZeneca) | – | – | – | JDM | 47 | Myalgia, breathlessness | Yes | None | – | 30 |
7 | BNT162b2 (Pfizer)-BioNTech | 54 | F | USA | DM | 7 | Fatigue | No | MMF, HCQ, IVIG | No | 30 |
8 | ChAdOx1 nCoV-19 (Covishield Serum Institute India) | – | – | – | PM | 11 | Diarrhea, headache | Yes | Mtx | No | 34 |
9 | Coronovac | 29 | F | Brazil | ASSD | 10 | Fatigue, myalgia, chest pain, headache | No | Aza | No | 35 |
10 | ChadOx1 nCOV-19 (Oxford/AstraZeneca) | 52 | F | UK | ASSD | 0 | Fatigue, anosmia | No | Cyclo, prednisolone (> 20 mg/day) | No | 47 |
11 | mRNA-1273 (Moderna) | 43 | F | USA | DM | 7 | Fever, fatigue, cough, breathlessness, diarrhea | Yes | MMF, Rtx, prednisolone (10 mg/day) | No | 48 |
12 | BNT162b2 (Pfizer)-BioNTech | 54 | F | USA | OM | 0 | None | No | MMF, HCQ | No | 48 |
13 | ChAdOx1 nCoV-19 (Covishield Serum Institute India) | – | – | – | DM | 9 | None | No | Mtx | No | 53 |
14 | ChAdOx1 nCoV-19 (Covishield Serum Institute India) | – | – | – | DM | 12 | Fatigue | No | None | – | 56 |
15 | BBIBP-CorV (Sinopharm) | – | – | – | PM | 0 | None | No | None | – | 57 |
16 | BBV152 (Covaxin Bharat Biotech) | 21 | M | India | DM | 11 | Fever, fatigue, myalgia, cough | No | Mtx, prednisolone (< 10 mg/day) | No | 94 |
17 | ChadOx1 nCOV-19 (Oxford/AstraZeneca) | 44 | F | UK | ASSD | 5 | Fever, fatigue, myalgia, cough, breathlessness, chest pain, headache, nausea/vomiting | No | MMF, HCQ, prednisolone (< 10 mg/day) | Yes (MMF for 14 days) | 141 |
ASSD antisynthetase syndrome, Aza azathioprine, BI breakthrough infection, DM dermatomyositis, F female, HCQ hydroxychloroquine, IIM idiopathic inflammatory myopathies, IS immunosuppressor, IVIG intravenous immunoglobulin, JDM juvenile dermatomyositis, M male, MMF mycophenolate mofetil, Mtx methotrexate, NAM necrotizing myositis, OM overlap myositis, PM polymyositis, Rtx rituximab, UK United Kingdom, USA United States of America
Table 3.
Parameters | COVID-19 before vaccination | IIMs versus other SAIDs | IIMs versus HCs | ||||
---|---|---|---|---|---|---|---|
IIMs (n = 76) | Other SAIDs (n = 488) | HCs (n = 733) | ORa (95% CI) | P value | ORa (95% CI) | P value | |
COVID-19 symptoms, n (%) | 68 (89) | 458 (94) | 677 (92) | 0.7 (0.3–1.7) | 0.470 | 1.6 (0.5–4.7) | 0.372 |
Different types of symptomsb | – | – | – | NS | NS | NS | NS |
Duration of COVID-19 symptoms, median (IQR), days | 10 (7, 20) | 12 (7, 21) | 10 (5, 15) | 1.01 (0.9–1.02) | 0.117 | 0.9 (0.9–1.1) | 0.578 |
Asymptomatic infection | 8 (11) | 30 (6) | 56 (8) | 1.3 (0.5–3.2) | 0.470 | 0.6 (0.2–1.7) | 0.372 |
All-cause hospitalization and O2 therapy, n (%) | 12 (16) | 36 (7) | 21 (3) | 0.4 (0.2–1.05) | 0.066 | 3.5 (1.3–8.9) | 0.008 |
All-cause hospitalization (with or without O2 therapy), n (%) | 23 (30) | 84 (17) | 59 (8) | 0.7 (0.4–1.4) | 0.454 | 2.5 (1.2–5.1) | 0.011 |
Parameters | COVID-19 breakthrough infectionc | IIMs versus Other SAIDs | IIMs versus HCs | ||||
---|---|---|---|---|---|---|---|
IIMs (n = 17) | Other SAIDs (n = 89) | HCs (n = 161) | ORa (95% CI) | P value | ORa (95% CI) | P value | |
COVID-19 symptoms, n (%) | 14 (82) | 83 (93) | 141 (88) | 0.6 (0.1–8.7) | 0.767 | 0.6 (0.2–1.4) | 0.276 |
Headache | 4 (24) | 44 (49) | 54 (34) | 0.2 (0.1–0.9) | 0.045 | 0.6 (0.3–1.0) | 0.066 |
Other symptomsb | – | – | – | NS | NS | NS | NS |
Duration of COVID-19 symptoms, median (IQR), days | 7 (3, 10) | 11 (5, 20) | 7 (3, 12) | 0.8 (0.7–0.9) | 0.021 | 1.0 (0.9–1.1) | 0.624 |
Asymptomatic infection | 3 (18) | 6 (7) | 20 (12) | 1.4 (0.1–1.8) | 0.767 | 1.6 (0.6–3.7) | 0.276 |
All-cause hospitalization and O2 therapy, n (%) | 1 (6) | 4 (4) | 5 (3) | 1.8 (0.1–2.0) | 0.609 | 3.8 (1.5–9.0) | 0.004 |
All-cause hospitalization (with or without O2 therapy), n (%) | 3 (18) | 10 (11) | 9 (5) | 1.5 (0.1–1.8) | 0.714 | 2.6 (1.3–5.3) | 0.006 |
CI confidence interval, HCs healthy control, IIMs idiopathic inflammatory myopathies, IQR interquartile range, OR odds ratio, NS not significant, SAIDs systemic autoimmune and inflammatory diseases
aOdds ratio adjusted for age, gender, ethnicity, and stratified by country of origin
bCOVID-19 symptoms individually assessed were as follows: fever, fatigue, myalgia, cough, breathlessness, chest pain, diarrhea, headache, oral ulcers, nausea/vomiting, arthralgia, skin rashes, or others
cBreakthrough infection was defined as an infection occurring more than two weeks after receipt of a first or second dose of a COVID-19 vaccine
COVID-19 severity among IIM, other SAIDs, and HCs
Patients with IIMs had higher odds of all-cause hospitalization in comparison to HCs either in COVID-19 cases that occurred prior to vaccination (OR = 2.5, 95% CI 1.2, 5.1, p = 0.011) or in BI (OR = 2.6, 95% CI 1.3–5.3, p = 0.006). Hospitalization with supplemental oxygen requirement was also higher in patients with IIMs versus HCs in both situations (prior to vaccination and BI, OR = 3.5, 95% CI 1.3–8.9, p = 0.008, and OR = 3.8, 95% CI 1.5–9.0, p = 0.004, respectively). However, all-cause hospitalization was similar in IIM in comparison to SAIDs. The specific COVID-19 symptoms and disease duration were comparable among the three groups, except for headache and the duration of breakthrough COVID-19 infections, which were less frequent and of shorter duration in IIMs than in patients with other SAIDs (OR = 0.2, 95% CI 0.1–0.9, p = 0.045, and OR = 0.8, 95% CI 0.7–0.9, p = 0.021, respectively) (Table 3).
Characteristics associated with BIs
We assessed whether age, gender, ethnicity, vaccination status, diagnosis, corticosteroid use, and other IS/IM therapies were associated with BI. In a multivariate model adjusted for covariates with a p < 0.1 in the univariate analysis, the following covariates had an association with BI: age 30–60 years (OR = 0.7, 95% CI 0.5–1.0, p = 0.041), two or more COVID-19 vaccine doses (OR = 2.0, 95% CI 1.4–2.8, p < 0.001), and exposure to IS/IM therapies (OR = 1.6, 95% CI 1.1–2.7, p = 0.029) (Table 4).
Table 4.
Variable | Category | Univariate | Multivariatea | ||
---|---|---|---|---|---|
OR (95% CI) | P value | OR (95% CI) | P value | ||
Age | < 30 years | Reference | Reference | Reference | Reference |
30–60 years | 1.1 (0.9–1.2) | 0.098 | 0.7 (0.5–1.0) | 0.041 | |
> 60 years | 1.4 (0.8–2.4) | 0.155 | 1.3 (0.7–2.2) | 0.312 | |
Gender | Male | Reference | Reference | Reference | Reference |
Female | 0.8 (0.6–1.1) | 0.225 | 0.8 (0.6–1.1) | 0.379 | |
Ethnicity | Caucasian | Reference | Reference | Reference | Reference |
Not caucasian | 1.1 (0.8–1.4) | 0.546 | 1.0 (0.7–1.4) | 0.735 | |
COVID-19 vaccination | None | – | – | – | – |
One dose | Reference | Reference | Reference | Reference | |
≥ Two doses | 1.5 (1.2–1.9) | < 0.001 | 2.0 (1.4–2.8) | < 0.001 | |
Diagnosis | IIM | Reference | Reference | Reference | Reference |
Other SAIDs | 0.8 (0.4–1.5) | 0.581 | 0.9 (0.4–1.9) | 0.957 | |
HC | 1.0 (0.6–1.8) | 0.898 | 0.9 (0.6–1.3) | 0.882 | |
Corticosteroid use | None | Reference | Reference | Reference | Reference |
≤ 10 mg of prednisone equivalent | 0.6 (0.3–1.2) | 0.149 | 0.6 (0.3–1.2) | 0.202 | |
> 10 mg of prednisone equivalent | 0.6 (0.2–1.7) | 0.422 | 0.7 (0.2–2.2) | 0.627 | |
Other IS/IM therapies | None | Reference | Reference | Reference | Reference |
Yes | 1.5 (1.1–2.3) | 0.023 | 1.6 (1.1–2.7) | 0.029 |
Breakthrough infection was defined as an infection occurring more than 2 weeks after receipt of a first or second dose of a COVID-19 vaccine
CI confidence interval, HCs healthy control, IIMs idiopathic inflammatory myopathies, IS/IM immunosuppressive and immunomodulatory therapy, OD odds ratio, NS not significant, SAIDs systemic autoimmune and inflammatory diseases
aMultivariate regression analysis was stratified by country of origin and adjusted for age, gender, and covariates with a p < 0.1 in the univariate analysis
Discussion
In the present study, we found that patients with IIMs reported fewer COVID-19 infections prior to vaccination than patients with other SAIDs and HCs, yet they had higher odds for all-cause hospitalization than HCs. Vaccine BI was uncommon and their characteristics were comparable among the groups of IIMs, SAIDs, and HCs, except for headache and duration of COVID-19 symptoms, which was shorter in IIMs than in SAIDs. The factors associated with higher odds of BI infections were exposure to IS/IM therapies and more than two doses of COVID-19 vaccine, while age 30–60 was associated with lower odds of BI. Gender, ethnicity, steroid use, and diagnosis (IIM, SAID, HC) conferred similar odds of BI in the multivariate analysis.
Patients with SAIDs, including IIMs, are a vulnerable population at an increased risk of disease severity and poorer clinical outcomes related to COVID-19 infection and possibly a higher incidence of COVID-19 infection compared to healthy counterparts [10, 13, 14]. We found a reported frequency of COVID-19 of 6.2% in IIMs patients and 10.5% in SAIDs before vaccination, which is higher than the rate of 0.36% previously reported in a systematic review of patients with inflammatory and autoimmune rheumatic diseases [13]. This may be explained by the design of our study, which is prone to recall and selection bias, with patients willing to answer the e-survey more likely to have had COVID-19 infection and thus more likely to remember the symptoms. Surprisingly, the self-reported pre-vaccination incidence of COVID-19 infection was lower in patients with IIMs than in patients with other SAIDs and HCs, and the diagnosis of IIMs was associated with a smaller odds of COVID-19 than other SAIDs and HCs, possibly due to protective behaviors taken by this extremely vulnerable population like physical distancing and shielding [1].
In our study, all-cause hospitalizations in IIMs patients were higher than in patients with other SAIDs (30 versus 17%, respectively). Considering that IS/IM therapies are a known risk factor for worst outcomes in COVID-19 [9, 11, 14], our sample of patients with IIMs was more on IS/IM therapy than patients with other SAIDs, which may explain this finding. It is unclear why IIMs patients with BI had a lower incidence of headache and shorter duration of COVID-19 symptoms than patients with other SAIDs; this may represent a unique feature of COVID-19 in this subset of patients, which needs to be confirmed in future studies, or more probably a spurious finding owing to few BI cases in the IIMs group.
Exposure to IS/IM therapies was associated with higher odds of BI. Evidence suggests that IS/IM medications, particularly B-cell depleting agents, may impair the host response to COVID-19 vaccines, thus reducing their immunogenicity [15, 16]. In our study, few patients with BI discontinued their IS/IM treatment before vaccination, which may explain this finding. However, suspension of IS/IM therapy prior to COVID-19 vaccination may not always be clinically appropriate, and this is a decision that must be made on an individual basis [17–21].
Two or more COVID-19 vaccine doses were also associated with a higher odds of BI than one vaccine dose. The most reasonable explanation for this finding is this may represent a follow-up bias, as patients with two or more vaccine doses have a longer follow-up and, therefore, are more prone to BI than patients with a shorter follow-up. A recent systematic review has shown that COVID-19 vaccines are effective against infection, but this protection wanes over time, especially in mild to moderate cases [28]. Considering that most of COVID-19 cases described in our study were mild or even asymptomatic, this also may explain why so many patients with two or more vaccine doses presented with BI.
The type of vaccine received may also influence the risk of breakthrough COVID-19 infection, owing to their variable efficacy, mechanism of action, immunogenicity, adjuvants, and host interaction [16]. A large cohort of patients with rheumatic disease followed in almost the same period in 2021 has shown a BI rate of 0.9%, and half of these patients had received two or more vaccine doses; the authors did not explore possible risk factors for BIs in this study, nor could associate these cases with a specific type of vaccine [29]. The efficacy of different vaccines in preventing BI in patients with IIMs and other SAIDs needs to be evaluated in future studies with an appropriate design and long-term follow-up. The most recent recommendation from the American College of Rheumatology emphasizes the response to COVID-19 vaccination in patients with SAIDs receiving IS/IM drugs is likely to be blunted in comparison to the general population; therefore, it may explain a higher number of BIs in fully vaccinated patients with SAIDs [19].
COVAD is one of the largest studies about COVID-19 vaccination in patients with SAIDs, with a representative sample from 94 countries. This is a strength of the current study, contributing to the external validity of our findings. However, this study has limitations. Using the proper statistical analysis for a cross-sectional study (a multivariate regression analysis), we found that BIs were associated with exposure to IS/IM drugs. We acknowledge that we cannot assume a cause-and-effect relationship between IS/IM drugs and BI; therefore, this association should be further confirmed in cohort or randomized controlled trial studies. We did not disseminate our survey in a systematic way, so our population represents a convenience sample. We targeted our survey to patients with SAIDs in general, and there were no steps taken to make any subgroup of SAIDs representative. Considering the inherent profile of patients who can respond to an online survey, we may infer that low-income patients without internet access, severely disabled, and deceased are not represented in our study. Additionally, our conclusions are based on self-reported data that could not be checked on medical records. Furthermore, we did not explore several confounding variables that could impact the outcomes assessed, including protective behaviors against COVID-19 infection, education level, income, access to health services, multiple vaccine combinations, and comorbidities. Considering the small number of BI in our samples, we could not assess whether different types of vaccines influenced the risk of BI. Finally, we neither confirmed COVID-19 serology nor vaccine immunogenicity. Though we have used a broader definition for BI, this study provides unique insights into the protection offered by a single dose of vaccine against COVID-19.
In conclusion, unvaccinated patients with IIMs reported fewer COVID-19 cases in comparison to patients with other SAIDs and HCs, but were more vulnerable to all-cause hospitalization in comparison to HCs. Overall, COVID-19 BI was uncommon and was comparable among IIMs, other SAIDs, and HCs. Despite the aforementioned limitations, this study adds to the valuable understanding of COVID-19 severity and characteristics in vaccinated and unvaccinated patients with IIMs and other SAIDs.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
The authors are grateful to all respondents for filling out the questionnaire. The authors also thank The Myositis Association, Myositis India, Myositis UK, Myositis Support and Understanding, the Myositis Global Network, Deutsche Gesellschaft für Muskelkranke e.V. (DGM), Dutch and Swedish Myositis patient support groups, Cure JM, Cure IBM, Sjögren’s India Foundation, Patients Engage, Scleroderma India, Lupus UK, Lupus Sweden, Emirates Arthritis Foundation, EULAR PARE, ArLAR research group, AAAA patient group, APLAR myositis special interest group, Thai Rheumatism association, PANLAR, NRAS, Anti-Synthetase Syndrome support group, and various other patient support groups and organizations for their contribution in the dissemination of this survey. Finally, the authors wish to thank all members of the COVAD study group for their invaluable role in data collection. COVAD Study Group Authors: Bhupen Barman, 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, 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, Jesús Loarce-Martos, Sergio Prieto-González, Albert Gil-Vila, Raquel Aranega Gonzalez, Akira Yoshida, Ran Nakashima, Shinji Sato, Naoki Kimura, Yuko Kaneko, Stylianos Tomaras, Margarita Aleksandrovna Gromova, Or Aharonov, Ihsane Hmamouchi, Margherita Giannini, François Maurier, Julien Campagne, Alain Meyer, Melinda Nagy-Vincze, Daman Langguth, Vidya Limaye, Merrilee Needham, Nilesh Srivastav, Marie Hudson, Océane Landon-Cardinal, Syahrul Sazliyana Shaharir, Wilmer Gerardo Rojas Zuleta, José António Pereira Silva, João Eurico Fonseca, Olena Zimba.
Author contributions
Conceptualization: LSH, SKS, NR, JGJ, LG, RA. Data curation: All authors. Formal analysis: LSH, SKS, NR, JGJ, JD, LG, RA Funding acquisition: N/A. Investigation: Methodology: LG, RA, JBL, LSH, SKS, VA. Software: LG. Validation: All Authors. Visualization: All authors, Writing-original draft: LSH, SKS, JD, NR, PS. Writing-review & editing: All authors.
Funding
No specific funding was obtained for this manuscript.
Declarations
Conflict of interest
ALT has received honoraria for advisory boards and speaking for Abbvie, Gilead, Janssen, Lilly, Novartis, Pfizer, UCB. CW has received travel support from Abbvie, unrelated to this manuscript. EN has received speaker honoraria/participated in advisory boards for Celltrion, Pfizer, Sanofi, Gilead, Galapagos, AbbVie, Lilly and holds research grants from Pfizer and Lilly. HC has received grant support from Eli Lilly and UCB; consulting fees from Novartis, Eli Lilly, Orphazyme, Astra Zeneca; speaker for UCB, Biogen. HC is 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, the National Institute for Health Research or the Department of Health. IP 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. JD has received research funding from CSL Limited. JBL has received speaker honoraria/participated in advisory boards for Sanofi Genzyme, Roche, and Biogen. None is related to this manuscript. JP has received consulting fees, speaking fees, and/or honoraria from Actelion, Sojournix Pharma, and Boehringer Ingelheim. None is related to this manuscript. NZ has received speaker fees, advisory board fees and research grants from Pfizer, Roche, Abbvie, Eli Lilly, NewBridge, Sanofi-Aventis, Boehringer Ingelheim, Janssen, Pierre Fabre; none is related to this manuscript. OD has/had consultancy relationship with and/or has received research funding from or has served as a speaker for the following companies in the area of potential treatments for systemic sclerosis and its complications in the last three years: Abbvie, Acceleron, Alcimed, Amgen, AnaMar, Arxx, Baecon, Blade, Bayer, Boehringer Ingelheim, ChemomAb, Corbus, CSL Behring, Galapagos, Glenmark, GSK, Horizon (Curzion), Inventiva, iQvia, Kymera, Lupin, Medac, Medscape, Mitsubishi Tanabe, Novartis, Roche, Roivant, Sanofi, Serodapharm, Topadur and UCB. Patent issued “mir-29 for the treatment of systemic sclerosis” (US8247389, EP2331143). RA has/had a consultancy relationship with and/or has received research funding from the following companies-Bristol Myers-Squibb, Pfizer, Genentech, Octapharma, CSL Behring, Mallinckrodt, AstraZeneca, Corbus, Kezar, and Abbvie, Janssen, Alexion, Argenx, Q32, EMD-Serono, Boehringer Ingelheim, Roivant. Rest of the authors have no conflict of interest relevant to this manuscript.
Ethical approval
Ethical approval was obtained from the Institutional Ethics Committee of Sanjay Gandhi Postgraduate Institute of Medical Sciences, Raebareli Road, Lucknow, 226014 (IEC Code: 2021-143-IP-EXP-39).
Footnotes
Disclaimer: This study was already published as a scientific abstract in two medical congresses (https://doi.org/10.1136/annrheumdis-2022-eular.2160 and https://doi.org/10.47660/CBR.2022.1905).
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rohit Aggarwal and Latika Gupta contributed equally to this work.
References
- 1.Hausmann JS, Kennedy K, Simard JF, et al. Immediate effect of the COVID-19 pandemic on patient health, health-care use, and behaviours: results from an international survey of people with rheumatic diseases. Lancet Rheumatol. 2021;3:e707–e714. doi: 10.1016/S2665-9913(21)00175-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Hoff LS, de Souza FHC, Miossi R, et al. Long-term effects of early pulse methylprednisolone and intravenous immunoglobulin in patients with dermatomyositis and polymyositis. Rheumatol (Oxford) 2022;61:1579–1588. doi: 10.1093/rheumatology/keab597. [DOI] [PubMed] [Google Scholar]
- 3.Chatterjee R, Mehta P, Agarwal V, et al. High burden of infections in Indian patients with Idiopathic inflammatory myopathy: validation of observations from the MyoCite dataset. Rheumatol (Oxford) 2021;60:4315–4326. doi: 10.1093/rheumatology/keab015. [DOI] [PubMed] [Google Scholar]
- 4.Ge YP, Shu XM, He LR, et al. Infection is not rare in patients with idiopathic inflammatory myopathies. Clin Exp Rheumatol. 2022;40:254–259. doi: 10.55563/clinexprheumatol/yps7ai. [DOI] [PubMed] [Google Scholar]
- 5.EULAR COVID 19 Registry. https://www.eular.org/eular_covid_19_registry.cfm. Accessed 28 Dec 2021
- 6.Brito-Zerón P, Sisó-Almirall A, Flores-Chavez A, et al. SARS-CoV-2 infection in patients with systemic autoimmune diseases. Clin Exp Rheumatol. 2021;39:676–687. doi: 10.55563/clinexprheumatol/lekp1y. [DOI] [PubMed] [Google Scholar]
- 7.Tan EH, Sena AG, Prats-Uribe A, et al. COVID-19 in patients with autoimmune diseases: characteristics and outcomes in a multinational network of cohorts across three countries. Rheumatology (Oxford) 2021;60:SI37–SI50. doi: 10.1093/rheumatology/keab250. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Peach E, Rutter M, Lanyon P, et al. Risk of death among people with rare autoimmune diseases compared with the general population in England during the 2020 COVID-19 pandemic. Rheumatol (Oxford) 2021;60:1902–1909. doi: 10.1093/rheumatology/keaa855. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Raiker R, DeYoung C, Pakhchanian H, et al. Outcomes of COVID-19 in patients with rheumatoid arthritis: a multicenter research network study in the United States. Semin Arthritis Rheum. 2021;51:1057–1066. doi: 10.1016/j.semarthrit.2021.08.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Xu C, Yi Z, Cai R, et al. Clinical outcomes of COVID-19 in patients with rheumatic diseases: a systematic review and meta-analysis of global data. Autoimmun Rev. 2021;20:102778. doi: 10.1016/j.autrev.2021.102778. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Zhang JJY, Lee KS, Ang LW, et al. Risk factors for severe disease and efficacy of treatment in patients infected with COVID-19: a systematic review, meta-analysis, and meta-regression analysis. Clin Infect Dis. 2020;71:2199–2206. doi: 10.1093/cid/ciaa576. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Coronavirus disease (COVID-19) pandemic view dashboard. World Health Organisation. https://www.who.int/emergencies/diseases/novel-coronavirus-2019. Accessed 16 Jul 2022
- 13.Conway R, Grimshaw AA, Konig MF, et al. SARS-CoV-2 infection and COVID-19 outcomes in rheumatic disease: a systematic literature review and meta-analysis. Arthritis Rheumatol. 2022;74:766–775. doi: 10.1002/art.42030. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Pakhchanian H, Khan H, Raiker R, et al. COVID-19 outcomes in patients with dermatomyositis: a registry-based cohort analysis. Semin Arthritis Rheum. 2022;56:152034. doi: 10.1016/j.semarthrit.2022.152034. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Medeiros-Ribeiro AC, Aikawa NE, Saad CGS, et al. Immunogenicity and safety of the CoronaVac inactivated vaccine in patients with autoimmune rheumatic diseases: a phase 4 trial. Nat Med. 2021;27:1744–1751. doi: 10.1038/s41591-021-01469-5. [DOI] [PubMed] [Google Scholar]
- 16.Wack S, Patton T, Ferris LK. COVID-19 vaccine safety and efficacy in patients with immune-mediated inflammatory disease: review of available evidence. J Am Acad Dermatol. 2021;85:1274–1284. doi: 10.1016/j.jaad.2021.07.054. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Sattui SE, Liew JW, Kennedy K, et al. Early experience of COVID-19 vaccination in adults with systemic rheumatic diseases: results from the COVID-19 global rheumatology alliance vaccine survey. RMD Open. 2021;7:e001814. doi: 10.1136/rmdopen-2021-001814. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Hazlewood GS, Pardo JP, Barnabe C, et al. Canadian rheumatology association recommendation for the use of COVID-19 vaccination for patients with autoimmune rheumatic diseases. J Rheumatol. 2021;48:1330–1339. doi: 10.3899/jrheum.210288. [DOI] [PubMed] [Google Scholar]
- 19.Curtis JR, Johnson SR, Anthony DD, et al. American college of rheumatology guidance for COVID-19 vaccination in patients with rheumatic and musculoskeletal diseases: version 3. Arthritis Rheumatol. 2021;73:e60–e75. doi: 10.1002/art.41928. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.So H, Mok CC, Yip RML. The Hong Kong society of rheumatology consensus recommendations for COVID-19 vaccination in adult patients with autoimmune rheumatic diseases. J Clin Rheumatol Immunol. 2021;21:7–14. doi: 10.1142/S2661341721400010. [DOI] [Google Scholar]
- 21.Specker C, Aries P, Braun J, et al. Updated recommendations of the German society for rheumatology for the care of patients with inflammatory rheumatic diseases in the context of the SARS-CoV-2/COVID-19 pandemic, including recommendations for COVID-19 vaccination. Z Rheumatol. 2021;80:33–48. doi: 10.1007/s00393-021-01055-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Shinjo SK, de Souza FHC, Borges IBP, et al. Systemic autoimmune myopathies: a prospective phase 4 controlled trial of an inactivated virus vaccine against SARS-CoV-2. Rheumatol (Oxford) 2022;61:3351–3361. doi: 10.1093/rheumatology/keab773. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Sen P, Gupta L, Lilleker JB, et al. COVID-19 vaccination in autoimmune disease (COVAD) survey protocol. Rheumatol Int. 2022;42:23–29. doi: 10.1007/s00296-021-05046-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Eysenbach G. Improving the quality of web surveys: the checklist for reporting results of internet E-surveys (CHERRIES) J Med Internet Res. 2004;6:e34. doi: 10.2196/jmir.6.3.e34. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Gaur PS, Zimba O, Agarwal V, Gupta L. Reporting survey based studies—a primer for authors. J Korean Med Sci. 2020;35:e398. doi: 10.3346/jkms.2020.35.e398. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.CDCMMWR (2021) COVID-19 vaccine breakthrough infections reported to CDC—United States, January 1–April 30, 2021. MMWR Morb Mortal Wkly Rep 70:792–793. 10.15585/mmwr.mm7021e3 [DOI] [PMC free article] [PubMed]
- 27.PROMIS. https://www.healthmeasures.net/score-and-interpret/interpret-scores/promis. Accessed 7 Jan 2022
- 28.Ssentongo P, Ssentongo AE, Voleti N, et al. SARS-CoV-2 vaccine effectiveness against infection, symptomatic and severe COVID-19: a systematic review and meta-analysis. BMC Infect Dis. 2022;22:439. doi: 10.1186/s12879-022-07418-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Machado PM, Lawson-Tovey S, Strangfeld A, et al. Safety of vaccination against SARS-CoV-2 in people with rheumatic and musculoskeletal diseases: results from the EULAR Coronavirus Vaccine (COVAX) physician-reported registry. Ann Rheum Dis. 2022;81:695–709. doi: 10.1136/annrheumdis-2021-221490. [DOI] [PubMed] [Google Scholar]
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