Chinoy, Hector

Abstract Objective To determine COVID-19 vaccine-related adverse events (AEs) in the seven-day post-vaccination period in patients with SLE vs autoimmune rheumatic diseases (AIRDs), non-rheumatic autoimmune diseases (nrAIDs), and healthy controls (HC). Methods Data were captured through the COVID-19 Vaccination in Autoimmune Diseases (COVAD) questionnaire (March–December 2021). Multivariable regression models accounted for age, gender, ethnicity, vaccine type and background treatment. Results Among 9462 complete respondents, 583 (6.2%) were SLE patients (mean age: 40.1 years; 94.5% females; 40.5% Asian; 42.9% Pfizer-recipients). Minor AEs were reported by 83.0% of SLE patients, major by 2.6%, hospitalization by 0.2%. AE and hospitalization frequencies were similar between patients with active and inactive SLE. Rashes were more frequent in SLE patients vs HC (OR; 95% CI: 1.2; 1.0, 1.5), chills less frequent in SLE vs AIRDs (0.6; 0.4, 0.8) and nrAIDs (0.5; 0.3, 0.8), and fatigue less frequent in SLE vs nrAIDs (0.6; 0.4, 0.9). Pfizer-recipients reported higher overall AE (2.2; 1.1, 4.2) and injection site pain (2.9; 1.6, 5.0) frequencies than recipients of other vaccines, Oxford/AstraZeneca-recipients more body ache, fever, chills (OR: 2.5, 3.0), Moderna-recipients more body ache, fever, chills, rashes (OR: 2.6, 4.3). Hospitalization frequencies were similar across vaccine types. AE frequencies were similar across treatment groups, although chills were less frequent in antimalarial users vs non-users (0.5; 0.3, 0.9). Conclusion While COVID-19 vaccination-related AEs were reported by four-fifths of SLE patients, those were mostly minor and comparable to AEs reported by healthy individuals, providing reassurance regarding COVID-19 vaccination safety in SLE.

Abstract Objectives The COVID-19 vaccination in autoimmune diseases (COVAD) study aimed to assess short-term COVID-19 vaccination-related adverse events (AEs) in RA patients. Methods An online self-reported questionnaire (March–December 2021) was used to capture data related to COVID-19 vaccination-related AEs in RA, other autoimmune rheumatic diseases (AIRDs) (excluding RA and inflammatory myositis), non-rheumatic autoimmune diseases (nrAIDs) and healthy controls (HCs). Descriptive and multivariable regression analyses were performed. Results Of the 9462 complete respondents, 14.2% (n = 1347) had been diagnosed with RA; they had a mean (s.d.) age of 50.7 (13.7) years, 74.2% were women and 49.3% were Caucasian. In total, 76.9% and 4.2% of patients with RA reported minor and major AEs, respectively. Patients with active and inactive RA had similar AE and hospitalization frequencies. Overall, AEs were reported more frequently by BNT162b2 and mRNA-1273 recipients and less frequently by BBV152 recipients compared with the rest. Major AE and hospitalization frequencies were similar across recipients of different vaccines. Patients receiving methotrexate and hydroxychloroquine reported fewer minor AEs than those patients not on them. Compared with HCs and patients with other AIRDs, patients with RA reported similar total AEs, overall minor AEs, and hospitalizations. Compared with nrAIDs, patients with RA reported lower frequencies of overall AEs, minor AEs (both odds ratio [OR] = 0.7; 95% CI: 0.5, 0.9), and injection site pain (OR = 0.6; 95% CI: 0.5, 0.8) with similar major AE and hospitalization frequencies. Conclusion Despite the differences in AE frequency across different COVID-19 vaccines, all were well tolerated in patients with RA and were comparable to HCs, providing reassurance as to the safety of COVID-19 vaccination.

AbstractObjectivesThe assessment of physical function is fundamental in the management of patients with idiopathic inflammatory myopathies (IIMs). We aimed to investigate the physical function of patients with IIMs compared with those with non-IIM autoimmune rheumatic diseases (AIRDs) utilizing Patient-Reported Outcome Measurement Information System (PROMIS) Physical Function (PF) data obtained in the COVAD study, an international self-reported e-survey assessing the safety of COVID-19 vaccines in AIRDs.MethodsDemographics, AIRD diagnosis, disease activity, and PROMIS PF short form-10a data were extracted from the COVAD database. PROMIS PF-10a scores were compared between disease categories and stratified by disease activity. Factors affecting PROMIS PF-10a scores other than disease activity were identified by multivariable regression analysis in patients with inactive disease.ResultsA total of 1057 IIM patients, 3635 non-IIM AIRD patients and 3981 healthy controls (HCs) responded to the COVAD e-survey from April to August 2021. Using a binomial regression model, the predicted mean of PROMIS PF-10a scores was significantly lower in IIM patients compared with non-IIM AIRD patients or HCs [36.3 (95% CI 35.5, 37.1) vs 41.3 (95% CI 40.2, 42.5) vs 46.2 (95% CI 45.8, 46.6), P < 0.001], irrespective of disease activity. The independent factors for lower PROMIS PF-10a scores in patients with inactive disease were older age, female, longer disease duration, and a diagnosis of inclusion body myositis or polymyositis.ConclusionPhysical function is significantly impaired in IIMs compared with non-IIM AIRDs or HCs, even in patients with inactive disease. Our study highlights a critical need for better strategies to minimize functional disability in patients with IIMs.

AbstractIntroduction/AimsIn this study we investigated COVID‐19 vaccination–related adverse events (ADEs) 7 days postvaccination in patients with idiopathic inflammatory myopathies (IIMs) and other systemic autoimmune and inflammatory disorders (SAIDs).MethodsSeven‐day vaccine ADEs were collected in an international patient self‐reported e‐survey. Descriptive statistics were obtained and multivariable regression was performed.ResultsTen thousand nine hundred respondents were analyzed (1227 IIM cases, 4640 SAID cases, and 5033 healthy controls [HCs]; median age, 42 [interquartile range, 30‐455] years; 74% female; 45% Caucasian; 69% completely vaccinated). Major ADEs were reported by 76.3% of the IIM patients and 4.6% reported major ADEs. Patients with active IIMs reported more frequent major (odds ratio [OR], 2.7; interquartile range [IQR], 1.04‐7.3) and minor (OR, 1.5; IQR, 1.1‐2.2) ADEs than patients with inactive IIMs. Rashes were more frequent in IIMs (OR, 2.3; IQR, 1.2‐4.2) than HCs. ADEs were not impacted by steroid dose, although hydroxychloroquine and intravenous/subcutaneous immunoglobulins were associated with a higher risk of minor ADEs (OR, 1.9; IQR, 1.1‐3.3; and OR, 2.2; IQR, 1.1‐4.3, respectively). Overall, ADEs were less frequent in inclusion‐body myositis (IBM) and BNT162b2 (Pfizer) vaccine recipients.DiscussionSeven‐day postvaccination ADEs were comparable in patients with IIMs, SAIDs, and HCs, except for a higher risk of rash in IIMs. Patients with dermatomyositis with active disease may be at higher risk, and IBM patients may be at lower risk of specific ADEs. Overall, the benefit of preventing severe COVID‐19 through vaccination likely outweighs the risk of vaccine‐related ADEs. Our results may inform future guidelines regarding COVID‐19 vaccination in patients with SAIDs, specifically in those with IIMs. Studies to evaluate long‐term outcomes and disease flares are needed to shed more light on developing future COVID‐19 vaccination guidelines.

Objective To describe the methodology used to develop new classification criteria for adult and juvenile idiopathic inflammatory myopathies (IIMs) and their major subgroups. Methods An international, multidisciplinary group of myositis experts produced a set of 93 potentially relevant variables to be tested for inclusion in the criteria. Rheumatology, dermatology, neurology and paediatric clinics worldwide collected data on 976 IIM cases (74% adults, 26% children) and 624 non-IIM comparator cases with mimicking conditions (82% adults, 18% children). The participating clinicians classified each case as IIM or non-IIM. Generally, the classification of any given patient was based on few variables, leaving remaining variables unmeasured. We investigated the strength of the association between all variables and between these and the disease status as determined by the physician. We considered three approaches: (1) a probability-score approach, (2) a sum-of-items approach criteria and (3) a classification-tree approach. Results The approaches yielded several candidate models that were scrutinised with respect to statistical performance and clinical relevance. The probability-score approach showed superior statistical performance and clinical practicability and was therefore preferred over the others. We developed a classification tree for subclassification of patients with IIM. A calculator for electronic devices, such as computers and smartphones, facilitates the use of the European League Against Rheumatism/American College of Rheumatology (EULAR/ACR) classification criteria. Conclusions The new EULAR/ACR classification criteria provide a patient’s probability of having IIM for use in clinical and research settings. The probability is based on a score obtained by summing the weights associated with a set of criteria items.

Objective To develop and validate new classification criteria for adult and juvenile idiopathic inflammatory myopathies (IIM) and their major subgroups. Methods Candidate variables were assembled from published criteria and expert opinion using consensus methodology. Data were collected from 47 rheumatology, dermatology, neurology, and pediatric clinics worldwide. Several statistical methods were utilized to derive the classification criteria. Results Based on data from 976 IIM patients (74% adults; 26% children) and 624 non‐IIM patients with mimicking conditions (82% adults; 18% children), new criteria were derived. Each item is assigned a weighted score. The total score corresponds to a probability of having IIM. Subclassification is performed using a classification tree. A probability cutoff of 55%, corresponding to a score of 5.5 (6.7 with muscle biopsy) “probable IIM,” had best sensitivity/specificity (87%/82% without biopsies, 93%/88% with biopsies) and is recommended as a minimum to classify a patient as having IIM. A probability of ≥90%, corresponding to a score of ≥7.5 (≥8.7 with muscle biopsy), corresponds to “definite IIM.” A probability of <50%, corresponding to a score of <5.3 (<6.5 with muscle biopsy), rules out IIM, leaving a probability of ≥50–<55% as “possible IIM.” Conclusion The European League Against Rheumatism/American College of Rheumatology (EULAR/ACR) classification criteria for IIM have been endorsed by international rheumatology, dermatology, neurology, and pediatric groups. They employ easily accessible and operationally defined elements, and have been partially validated. They allow classification of “definite,” “probable,” and “possible” IIM, in addition to the major subgroups of IIM, including juvenile IIM. They generally perform better than existing criteria.

ObjectiveTo develop response criteria for adult dermatomyositis (DM) and polymyositis (PM).MethodsExpert surveys, logistic regression, and conjoint analysis were used to develop 287 definitions using core set measures. Myositis experts rated greater improvement among multiple pairwise scenarios in conjoint analysis surveys, where different levels of improvement in 2 core set measures were presented. The PAPRIKA (Potentially All Pairwise Rankings of All Possible Alternatives) method determined the relative weights of core set measures and conjoint analysis definitions. The performance characteristics of the definitions were evaluated on patient profiles using expert consensus (gold standard) and were validated using data from a clinical trial. The nominal group technique was used to reach consensus.ResultsConsensus was reached for a conjoint analysis–based continuous model using absolute percent change in core set measures (physician, patient, and extramuscular global activity, muscle strength, Health Assessment Questionnaire, and muscle enzyme levels). A total improvement score (range 0–100), determined by summing scores for each core set measure, was based on improvement in and relative weight of each core set measure. Thresholds for minimal, moderate, and major improvement were ≥20, ≥40, and ≥60 points in the total improvement score. The same criteria were chosen for juvenile DM, with different improvement thresholds. Sensitivity and specificity in DM/PM patient cohorts were 85% and 92%, 90% and 96%, and 92% and 98% for minimal, moderate, and major improvement, respectively. Definitions were validated in the clinical trial analysis for differentiating the physician rating of improvement (P < 0.001).ConclusionThe response criteria for adult DM/PM consisted of the conjoint analysis model based on absolute percent change in 6 core set measures, with thresholds for minimal, moderate, and major improvement.

ObjectiveTo identify new genetic associations with juvenile and adult dermatomyositis (DM).MethodsWe performed a genome‐wide association study (GWAS) of adult and juvenile DM patients of European ancestry (n = 1,178) and controls (n = 4,724). To assess genetic overlap with other autoimmune disorders, we examined whether 141 single‐nucleotide polymorphisms (SNPs) outside the major histocompatibility complex (MHC) locus, and previously associated with autoimmune diseases, predispose to DM.ResultsCompared to controls, patients with DM had a strong signal in the MHC region consisting of GWAS‐level significance (P < 5 × 10–8) at 80 genotyped SNPs. An analysis of 141 non‐MHC SNPs previously associated with autoimmune diseases showed that 3 SNPs linked with 3 genes were associated with DM, with a false discovery rate (FDR) of <0.05. These genes were phospholipase C–like 1 (PLCL1; rs6738825, FDR = 0.00089), B lymphoid tyrosine kinase (BLK; rs2736340, FDR = 0.0031), and chemokine (C‐C motif) ligand 21 (CCL21; rs951005, FDR = 0.0076). None of these genes was previously reported to be associated with DM.ConclusionOur findings confirm the MHC as the major genetic region associated with DM and indicate that DM shares non‐MHC genetic features with other autoimmune diseases, suggesting the presence of additional novel risk loci. This first identification of autoimmune disease genetic predispositions shared with DM may lead to enhanced understanding of pathogenesis and novel diagnostic and therapeutic approaches.