Factors associated with disease flare following SARS-CoV-2 vaccination in people with inflammatory rheumatic and musculoskeletal diseases: results from the physician-reported EULAR Coronavirus Vaccine (COVAX) Registry.

OBJECTIVES: To investigate the frequency and factors associated with disease flare following vaccination against SARS-CoV-2 in people with inflammatory/autoimmune rheumatic and musculoskeletal diseases (I-RMDs). METHODS: Data from the European Alliance of Associations for Rheumatology Coronavirus Vaccine physician-reported registry were used. Factors associated with flare in patients with I-RMDs were investigated using multivariable logistic regression adjusted for demographic and clinical factors. RESULTS: The study included 7336 patients with I-RMD, with 272 of 7336 (3.7%) experiencing flares and 121 of 7336 (1.6%) experiencing flares requiring starting a new medication or increasing the dosage of an existing medication. Factors independently associated with increased odds of flare were: female sex (OR=1.40, 95% CI=1.05 to 1.87), active disease at the time of vaccination (low disease activity (LDA), OR=1.45, 95% CI=1.08 to 1.94; moderate/high disease activity (M/HDA), OR=1.37, 95% CI=0.97 to 1.95; vs remission), and cessation/reduction of antirheumatic medication before or after vaccination (OR=4.76, 95% CI=3.44 to 6.58); factors associated with decreased odds of flare were: higher age (OR=0.90, 95% CI=0.83 to 0.98), non-Pfizer/AstraZeneca/Moderna vaccines (OR=0.10, 95% CI=0.01 to 0.74; vs Pfizer), and exposure to methotrexate (OR=0.57, 95% CI=0.37 to 0.90), tumour necrosis factor inhibitors (OR=0.55, 95% CI=0.36 to 0.85) or rituximab (OR=0.27, 95% CI=0.11 to 0.66), versus no antirheumatic treatment. In a multivariable model using new medication or dosage increase due to flare as the dependent variable, only the following independent associations were observed: active disease (LDA, OR=1.47, 95% CI=0.94 to 2.29; M/HDA, OR=3.08, 95% CI=1.91 to 4.97; vs remission), cessation/reduction of antirheumatic medication before or after vaccination (OR=2.24, 95% CI=1.33 to 3.78), and exposure to methotrexate (OR=0.48, 95% CI=0.26 to 0.89) or rituximab (OR=0.10, 95% CI=0.01 to 0.77), versus no antirheumatic treatment. CONCLUSION: I-RMD flares following SARS-CoV-2 vaccination were uncommon. Factors associated with flares were identified, namely higher disease activity and cessation/reduction of antirheumatic medications before or after vaccination.

Characteristics associated with poor COVID-19 outcomes in people with psoriasis, psoriatic arthritis and axial spondyloarthritis: data from the COVID-19 PsoProtect and Global Rheumatology Alliance physician-reported registries.

OBJECTIVES: To investigate factors associated with severe COVID-19 in people with psoriasis (PsO), psoriatic arthritis (PsA) and axial spondyloarthritis (axSpA). METHODS: Demographic data, clinical characteristics and COVID-19 outcome severity of adults with PsO, PsA and axSpA were obtained from two international physician-reported registries. A three-point ordinal COVID-19 severity scale was defined: no hospitalisation, hospitalisation (and no death) and death. ORs were estimated using multivariable ordinal logistic regression. RESULTS: Of 5045 cases, 18.3% had PsO, 45.5% PsA and 36.3% axSpA. Most (83.6%) were not hospitalised, 14.6% were hospitalised and 1.8% died. Older age was non-linearly associated with COVID-19 severity. Male sex (OR 1.54, 95% CI 1.30 to 1.83), cardiovascular, respiratory, renal, metabolic and cancer comorbidities (ORs 1.25-2.89), moderate/high disease activity and/or glucocorticoid use (ORs 1.39-2.23, vs remission/low disease activity and no glucocorticoids) were associated with increased odds of severe COVID-19. Later pandemic time periods (ORs 0.42-0.52, vs until 15 June 2020), PsO (OR 0.49, 95% CI 0.37 to 0.65, vs PsA) and baseline exposure to TNFi, IL17i and IL-23i/IL-12+23i (OR 0.57, 95% CI 0.44 to 0.73; OR 0.62, 95% CI 0.45 to 0.87; OR 0.67, 95% CI 0.45 to 0.98; respectively; vs no disease-modifying antirheumatic drug) were associated with reduced odds of severe COVID-19. CONCLUSION: Older age, male sex, comorbidity burden, higher disease activity and glucocorticoid intake were associated with more severe COVID-19. Later pandemic time periods, PsO and exposure to TNFi, IL17i and IL-23i/IL-12+23i were associated with less severe COVID-19. These findings will enable risk stratification and inform management decisions for patients with PsO, PsA and axSpA during COVID-19 waves or similar future respiratory pandemics.

Obstetric outcomes in women with rheumatic disease and COVID-19 in the context of vaccination status.

OBJECTIVE: To describe obstetric outcomes based on COVID-19 vaccination status, in women with rheumatic and musculoskeletal diseases (RMDs) who developed COVID-19 during pregnancy. METHODS: Data regarding pregnant women entered into the COVID-19 Global Rheumatology Alliance registry from 24 March 2020-25 February 2022 were analysed. Obstetric outcomes were stratified by number of COVID-19 vaccine doses received prior to COVID-19 infection in pregnancy. Descriptive differences between groups were tested using the chi-squared or Fisher's exact test. RESULTS: There were 73 pregnancies in 73 women with RMD and COVID-19. Overall, 24.7% (18) of pregnancies were ongoing, while of the 55 completed pregnancies, 90.9% (50) of pregnancies resulted in livebirths. At the time of COVID-19 diagnosis, 60.3% (n = 44) of women were unvaccinated, 4.1% (n = 3) had received one vaccine dose while 35.6% (n = 26) had two or more doses. Although 83.6% (n = 61) of women required no treatment for COVID-19, 20.5% (n = 15) required hospital admission. COVID-19 resulted in delivery in 6.8% (n = 3) of unvaccinated women and 3.8% (n = 1) of fully vaccinated women. There was a greater number of preterm births (PTB) in unvaccinated women compared with fully vaccinated 29.5% (n = 13) vs 18.2% (n = 2). CONCLUSIONS: In this descriptive study, unvaccinated pregnant women with RMD and COVID-19 had a greater number of PTB compared with those fully vaccinated against COVID-19. Additionally, the need for COVID-19 pharmacological treatment was uncommon in pregnant women with RMD regardless of vaccination status. These results support active promotion of COVID-19 vaccination in women with RMD who are pregnant or planning a pregnancy.

Outcomes of SARS-CoV-2 infection among children and young people with pre-existing rheumatic and musculoskeletal diseases.

OBJECTIVES: Some adults with rheumatic and musculoskeletal diseases (RMDs) are at increased risk of COVID-19-related death. Excluding post-COVID-19 multisystem inflammatory syndrome of children, children and young people (CYP) are overall less prone to severe COVID-19 and most experience a mild or asymptomatic course. However, it is unknown if CYP with RMDs are more likely to have more severe COVID-19. This analysis aims to describe outcomes among CYP with underlying RMDs with COVID-19. METHODS: Using the European Alliance of Associations for Rheumatology COVID-19 Registry, the Childhood Arthritis and Rheumatology Research Alliance (CARRA) Registry, and the CARRA-sponsored COVID-19 Global Paediatric Rheumatology Database, we obtained data on CYP with RMDs who reported SARS-CoV-2 infection (presumptive or confirmed). Patient characteristics and illness severity were described, and factors associated with COVID-19 hospitalisation were investigated. RESULTS: 607 CYP with RMDs <19 years old from 25 different countries with SARS-CoV-2 infection were included, the majority with juvenile idiopathic arthritis (JIA; n=378; 62%). Forty-three (7%) patients were hospitalised; three of these patients died. Compared with JIA, diagnosis of systemic lupus erythematosus, mixed connective tissue disease, vasculitis, or other RMD (OR 4.3; 95% CI 1.7 to 11) or autoinflammatory syndrome (OR 3.0; 95% CI 1.1 to 8.6) was associated with hospitalisation, as was obesity (OR 4.0; 95% CI 1.3 to 12). CONCLUSIONS: This is the most significant investigation to date of COVID-19 in CYP with RMDs. It is important to note that the majority of CYP were not hospitalised, although those with severe systemic RMDs and obesity were more likely to be hospitalised.

Safety of vaccination against SARS-CoV-2 in people with rheumatic and musculoskeletal diseases: results from the EULAR Coronavirus Vaccine (COVAX) physician-reported registry.

OBJECTIVES: To describe the safety of vaccines against SARS-CoV-2 in people with inflammatory/autoimmune rheumatic and musculoskeletal disease (I-RMD). METHODS: Physician-reported registry of I-RMD and non-inflammatory RMD (NI-RMDs) patients vaccinated against SARS-CoV-2. From 5 February 2021 to 27 July 2021, we collected data on demographics, vaccination, RMD diagnosis, disease activity, immunomodulatory/immunosuppressive treatments, flares, adverse events (AEs) and SARS-CoV-2 breakthrough infections. Data were analysed descriptively. RESULTS: The study included 5121 participants from 30 countries, 90% with I-RMDs (n=4604, 68% female, mean age 60.5 years) and 10% with NI-RMDs (n=517, 77% female, mean age 71.4). Inflammatory joint diseases (58%), connective tissue diseases (18%) and vasculitis (12%) were the most frequent diagnostic groups; 54% received conventional synthetic disease-modifying antirheumatic drugs (DMARDs), 42% biological DMARDs and 35% immunosuppressants. Most patients received the Pfizer/BioNTech vaccine (70%), 17% AstraZeneca/Oxford and 8% Moderna. In fully vaccinated cases, breakthrough infections were reported in 0.7% of I-RMD patients and 1.1% of NI-RMD patients. I-RMD flares were reported in 4.4% of cases (0.6% severe), 1.5% resulting in medication changes. AEs were reported in 37% of cases (37% I-RMD, 40% NI-RMD), serious AEs in 0.5% (0.4% I-RMD, 1.9% NI-RMD). CONCLUSION: The safety profiles of SARS-CoV-2 vaccines in patients with I-RMD was reassuring and comparable with patients with NI-RMDs. The majority of patients tolerated their vaccination well with rare reports of I-RMD flare and very rare reports of serious AEs. These findings should provide reassurance to rheumatologists and vaccine recipients and promote confidence in SARS-CoV-2 vaccine safety in I-RMD patients.

Factors associated with COVID-19-related death in people with rheumatic diseases: results from the COVID-19 Global Rheumatology Alliance physician-reported registry.

OBJECTIVES: To determine factors associated with COVID-19-related death in people with rheumatic diseases. METHODS: Physician-reported registry of adults with rheumatic disease and confirmed or presumptive COVID-19 (from 24 March to 1 July 2020). The primary outcome was COVID-19-related death. Age, sex, smoking status, comorbidities, rheumatic disease diagnosis, disease activity and medications were included as covariates in multivariable logistic regression models. Analyses were further stratified according to rheumatic disease category. RESULTS: Of 3729 patients (mean age 57 years, 68% female), 390 (10.5%) died. Independent factors associated with COVID-19-related death were age (66-75 years: OR 3.00, 95% CI 2.13 to 4.22; >75 years: 6.18, 4.47 to 8.53; both vs ≤65 years), male sex (1.46, 1.11 to 1.91), hypertension combined with cardiovascular disease (1.89, 1.31 to 2.73), chronic lung disease (1.68, 1.26 to 2.25) and prednisolone-equivalent dosage >10 mg/day (1.69, 1.18 to 2.41; vs no glucocorticoid intake). Moderate/high disease activity (vs remission/low disease activity) was associated with higher odds of death (1.87, 1.27 to 2.77). Rituximab (4.04, 2.32 to 7.03), sulfasalazine (3.60, 1.66 to 7.78), immunosuppressants (azathioprine, cyclophosphamide, ciclosporin, mycophenolate or tacrolimus: 2.22, 1.43 to 3.46) and not receiving any disease-modifying anti-rheumatic drug (DMARD) (2.11, 1.48 to 3.01) were associated with higher odds of death, compared with methotrexate monotherapy. Other synthetic/biological DMARDs were not associated with COVID-19-related death. CONCLUSION: Among people with rheumatic disease, COVID-19-related death was associated with known general factors (older age, male sex and specific comorbidities) and disease-specific factors (disease activity and specific medications). The association with moderate/high disease activity highlights the importance of adequate disease control with DMARDs, preferably without increasing glucocorticoid dosages. Caution may be required with rituximab, sulfasalazine and some immunosuppressants.

Associations of baseline use of biologic or targeted synthetic DMARDs with COVID-19 severity in rheumatoid arthritis: Results from the COVID-19 Global Rheumatology Alliance physician registry.

OBJECTIVE: To investigate baseline use of biologic or targeted synthetic (b/ts) disease-modifying antirheumatic drugs (DMARDs) and COVID-19 outcomes in rheumatoid arthritis (RA). METHODS: We analysed the COVID-19 Global Rheumatology Alliance physician registry (from 24 March 2020 to 12 April 2021). We investigated b/tsDMARD use for RA at the clinical onset of COVID-19 (baseline): abatacept (ABA), rituximab (RTX), Janus kinase inhibitors (JAKi), interleukin 6 inhibitors (IL-6i) or tumour necrosis factor inhibitors (TNFi, reference group). The ordinal COVID-19 severity outcome was (1) no hospitalisation, (2) hospitalisation without oxygen, (3) hospitalisation with oxygen/ventilation or (4) death. We used ordinal logistic regression to estimate the OR (odds of being one level higher on the ordinal outcome) for each drug class compared with TNFi, adjusting for potential baseline confounders. RESULTS: Of 2869 people with RA (mean age 56.7 years, 80.8% female) on b/tsDMARD at the onset of COVID-19, there were 237 on ABA, 364 on RTX, 317 on IL-6i, 563 on JAKi and 1388 on TNFi. Overall, 613 (21%) were hospitalised and 157 (5.5%) died. RTX (OR 4.15, 95% CI 3.16 to 5.44) and JAKi (OR 2.06, 95% CI 1.60 to 2.65) were each associated with worse COVID-19 severity compared with TNFi. There were no associations between ABA or IL6i and COVID-19 severity. CONCLUSIONS: People with RA treated with RTX or JAKi had worse COVID-19 severity than those on TNFi. The strong association of RTX and JAKi use with poor COVID-19 outcomes highlights prioritisation of risk mitigation strategies for these people.

Characteristics associated with hospitalisation for COVID-19 in people with rheumatic disease: data from the COVID-19 Global Rheumatology Alliance physician-reported registry.

OBJECTIVES: COVID-19 outcomes in people with rheumatic diseases remain poorly understood. The aim was to examine demographic and clinical factors associated with COVID-19 hospitalisation status in people with rheumatic disease. METHODS: Case series of individuals with rheumatic disease and COVID-19 from the COVID-19 Global Rheumatology Alliance registry: 24 March 2020 to 20 April 2020. Multivariable logistic regression was used to estimate ORs and 95% CIs of hospitalisation. Age, sex, smoking status, rheumatic disease diagnosis, comorbidities and rheumatic disease medications taken immediately prior to infection were analysed. RESULTS: A total of 600 cases from 40 countries were included. Nearly half of the cases were hospitalised (277, 46%) and 55 (9%) died. In multivariable-adjusted models, prednisone dose ≥10 mg/day was associated with higher odds of hospitalisation (OR 2.05, 95% CI 1.06 to 3.96). Use of conventional disease-modifying antirheumatic drug (DMARD) alone or in combination with biologics/Janus Kinase inhibitors was not associated with hospitalisation (OR 1.23, 95% CI 0.70 to 2.17 and OR 0.74, 95% CI 0.37 to 1.46, respectively). Non-steroidal anti-inflammatory drug (NSAID) use was not associated with hospitalisation status (OR 0.64, 95% CI 0.39 to 1.06). Tumour necrosis factor inhibitor (anti-TNF) use was associated with a reduced odds of hospitalisation (OR 0.40, 95% CI 0.19 to 0.81), while no association with antimalarial use (OR 0.94, 95% CI 0.57 to 1.57) was observed. CONCLUSIONS: We found that glucocorticoid exposure of ≥10 mg/day is associated with a higher odds of hospitalisation and anti-TNF with a decreased odds of hospitalisation in patients with rheumatic disease. Neither exposure to DMARDs nor NSAIDs were associated with increased odds of hospitalisation.

Towards stratified treatment of JIA: machine learning identifies subtypes in response to methotrexate from four UK cohorts.

BACKGROUND: Methotrexate (MTX) is the gold-standard first-line disease-modifying anti-rheumatic drug for juvenile idiopathic arthritis (JIA), despite only being either effective or tolerated in half of children and young people (CYP). To facilitate stratified treatment of early JIA, novel methods in machine learning were used to i) identify clusters with distinct disease patterns following MTX initiation; ii) predict cluster membership; and iii) compare clusters to existing treatment response measures. METHODS: Discovery and verification cohorts included CYP who first initiated MTX before January 2018 in one of four UK multicentre prospective cohorts of JIA within the CLUSTER consortium. JADAS components (active joint count, physician (PGA) and parental (PGE) global assessments, ESR) were recorded at MTX start and over the following year. Clusters of MTX 'response' were uncovered using multivariate group-based trajectory modelling separately in discovery and verification cohorts. Clusters were compared descriptively to ACR Pedi 30/90 scores, and multivariate logistic regression models predicted cluster-group assignment. FINDINGS: The discovery cohorts included 657 CYP and verification cohorts 1241 CYP. Six clusters were identified: Fast improvers (11%), Slow Improvers (16%), Improve-Relapse (7%), Persistent Disease (44%), Persistent PGA (8%) and Persistent PGE (13%), the latter two characterised by improvement in all features except one. Factors associated with clusters included ethnicity, ILAR category, age, PGE, and ESR scores at MTX start, with predictive model area under the curve values of 0.65-0.71. Singular ACR Pedi 30/90 scores at 6 and 12 months could not capture speeds of improvement, relapsing courses or diverging disease patterns. INTERPRETATION: Six distinct patterns following initiation of MTX have been identified using methods in artificial intelligence. These clusters demonstrate the limitations in traditional yes/no treatment response assessment (e.g., ACRPedi30) and can form the basis of a stratified medicine programme in early JIA. FUNDING: Medical Research Council, Versus Arthritis, Great Ormond Street Hospital Children's Charity, Olivia's Vision, and the National Institute for Health Research.

Integration of genetic and clinical risk factors improves the risk classification of uveitis in patients with juvenile idiopathic arthritis.

OBJECTIVES: Juvenile idiopathic arthritis (JIA)-associated uveitis (JIAU) is a serious JIA comorbidity that can result in vision impairment. This study aimed to identify genetic risk factors, within the major histocompatibility complex , for JIAU and evaluate their contribution for improving risk classification when combined with clinical risk factors. METHODS: Data on single nucleotide polymorphisms, amino acids and classical human leukocyte antigen (HLA) alleles were available for 2,497 JIA patients without uveitis and 579 JIAU patients (female=2060, male=1015). Analysis was restricted to patients with inferred European ancestry. Forward conditional logistic regression identified genetic markers exceeding a Bonferroni corrected significance (6x10-6). Multivariable logistic regression estimated the effects of clinical and genetic risk factors and a likelihood ratio test calculated the improvement in model fit when adding genetic factors. Uveitis risk classification performance of a model integrating genetic and clinical risk factors was estimated using area under the receiver operator characteristic curve and compared to a model of clinical risk factors alone. RESULTS: Three genetic risk factors were identified mapping to HLA-DRB1, HLA-DPB1 and HLA-A. These markers were statistically independent from clinical risk factors and significantly improved the fit of a model when included with clinical risk factors (P = 3.3x10-23). The addition of genetic markers improved the classification of JIAU compared to a model of clinical risk factors alone (AUC 0.75 vs. 0.71). CONCLUSIONS: Integration of a genetic and clinical risk prediction model outperforms a model based solely on clinical risk factors. Future JIAU risk prediction models should include genetic risk factors.

Impact of Risk Factors on COVID-19 Outcomes in Unvaccinated People With Rheumatic Diseases: A Comparative Analysis of Pandemic Epochs Using the COVID-19 Global Rheumatology Alliance Registry.

OBJECTIVE: Approximately one third of individuals worldwide have not received a COVID-19 vaccine. Although studies have investigated risk factors linked to severe COVID-19 among unvaccinated people with rheumatic diseases (RDs), we know less about whether these factors changed as the pandemic progressed. We aimed to identify risk factors associated with severe COVID-19 in unvaccinated individuals in different pandemic epochs corresponding to major variants of concern. METHODS: Patients with RDs and COVID-19 were entered into the COVID-19 Global Rheumatology Alliance Registry between March 2020 and June 2022. An ordinal logistic regression model (not hospitalized, hospitalized, and death) was used with date of COVID-19 diagnosis, age, sex, race and/or ethnicity, comorbidities, RD activity, medications, and the human development index (HDI) as covariates. The main analysis included all unvaccinated patients across COVID-19 pandemic epochs; subanalyses stratified patients according to RD types. RESULTS: Among 19,256 unvaccinated people with RDs and COVID-19, those who were older, male, had more comorbidities, used glucocorticoids, had higher disease activity, or lived in lower HDI regions had worse outcomes across epochs. For those with rheumatoid arthritis, sulfasalazine and B-cell-depleting therapy were associated with worse outcomes, and tumor necrosis factor inhibitors were associated with improved outcomes. In those with connective tissue disease or vasculitis, B-cell-depleting therapy was associated with worse outcomes. CONCLUSION: Risk factors for severe COVID-19 outcomes were similar throughout pandemic epochs in unvaccinated people with RDs. Ongoing efforts, including vaccination, are needed to reduce COVID-19 severity in this population, particularly in those with medical and social vulnerabilities identified in this study.

The successes and challenges of harmonising juvenile idiopathic arthritis (JIA) datasets to create a large-scale JIA data resource.

BACKGROUND: CLUSTER is a UK consortium focussed on precision medicine research in JIA/JIA-Uveitis. As part of this programme, a large-scale JIA data resource was created by harmonizing and pooling existing real-world studies. Here we present challenges and progress towards creation of this unique large JIA dataset. METHODS: Four real-world studies contributed data; two clinical datasets of JIA patients starting first-line methotrexate (MTX) or tumour necrosis factor inhibitors (TNFi) were created. Variables were selected based on a previously developed core dataset, and encrypted NHS numbers were used to identify children contributing similar data across multiple studies. RESULTS: Of 7013 records (from 5435 individuals), 2882 (1304 individuals) represented the same child across studies. The final datasets contain 2899 (MTX) and 2401 (TNFi) unique patients; 1018 are in both datasets. Missingness ranged from 10 to 60% and was not improved through harmonisation. CONCLUSIONS: Combining data across studies has achieved dataset sizes rarely seen in JIA, invaluable to progressing research. Losing variable specificity and missingness, and their impact on future analyses requires further consideration.

Association Between Race/Ethnicity and COVID-19 Outcomes in Systemic Lupus Erythematosus Patients From the United States: Data From the COVID-19 Global Rheumatology Alliance.

OBJECTIVE: To determine the association between race/ethnicity and COVID-19 outcomes in individuals with systemic lupus erythematosus (SLE). METHODS: Individuals with SLE from the US with data entered into the COVID-19 Global Rheumatology Alliance registry between March 24, 2020 and August 27, 2021 were included. Variables included age, sex, race, and ethnicity (White, Black, Hispanic, other), comorbidities, disease activity, pandemic time period, glucocorticoid dose, antimalarials, and immunosuppressive drug use. The ordinal outcome categories were: not hospitalized, hospitalized with no oxygenation, hospitalized with any ventilation or oxygenation, and death. We constructed ordinal logistic regression models evaluating the relationship between race/ethnicity and COVID-19 severity, adjusting for possible confounders. RESULTS: We included 523 patients; 473 (90.4%) were female and the mean ± SD age was 46.6 ± 14.0 years. A total of 358 patients (74.6%) were not hospitalized; 40 patients (8.3%) were hospitalized without oxygen, 64 patients (13.3%) were hospitalized with any oxygenation, and 18 (3.8%) died. In a multivariable model, Black (odds ratio [OR] 2.73 [95% confidence interval (95% CI) 1.36-5.53]) and Hispanic (OR 2.76 [95% CI 1.34-5.69]) individuals had higher odds of more severe outcomes than White individuals. CONCLUSION: Black and Hispanic individuals with SLE experienced more severe COVID-19 outcomes, which is consistent with findings in the US general population. These results likely reflect socioeconomic and health disparities and suggest that more aggressive efforts are needed to prevent and treat infection in this population.

Quality improvement in juvenile idiopathic arthritis: a mixed-methods implementation pilot of the CAPTURE-JIA dataset.

BACKGROUND: A significant proportion of children and young people with juvenile idiopathic arthritis (JIA) do not achieve inactive disease during the first two years following diagnosis. Refinements to clinical care pathways have the potential to improve clinical outcomes but a lack of consistent and contemporaneous clinical data presently precludes standard setting and implementation of meaningful quality improvement programmes. This study was the first to pilot clinical data collection and analysis using the CAPTURE-JIA dataset, and to explore patient and clinician-reported feasibility and acceptability data. METHODS: A multiphase mixed-methods approach enabled prospective collection of quantitative data to examine the feasibility and efficacy of dataset collection and of qualitative data informing the context and processes of implementation. An initial paper pilot informed the design of a bespoke electronic data collection system (the Agileware system), with a subsequent electronic pilot informing the final CAPTURE-JIA data collection tool. RESULTS: Paper collection of patient data was feasible but time-consuming in the clinical setting. Phase 1 paper pilot data (121 patients) identified three themes: problematic data items (14/62 data items received >40% missing data), formatting of data collection forms and a clinician-highlighted need for digital data collection, informing Phase 2 electronic data collection tool development. Patients and families were universally supportive of the collection and analysis of anonymised patient data to inform clinical care. No apparent preference for paper / electronic data collection was reported by families. Phase 3 electronic pilot data (38 patients) appeared complete and the system reported to be easy to use. Analysis of the study dataset and a dummy longitudinal dataset confirmed that all eleven JIA national audit questions can be answered using the electronic system. CONCLUSIONS: Multicentre CAPTURE-JIA data collection is feasible and acceptable, with a bespoke data collection system highlighted as the most satisfactory solution. The study is informing ongoing work towards a streamlined and flexible national paediatric data collection system to drive quality improvement in clinical care.

Can Researchers Assess the Suitability of Datasets to Answer Their Research Questions, with Access to Metadata Only?

Health research increasingly requires effective ways to identify existing datasets and assess their suitability for research. We sought to test whether researchers could use an existing metadata catalogue to assess the suitability of datasets for addressing specified research questions. Five datasets were described in the National Institute for Health Research Health Informatics Collaborative metadata catalogue, and for each dataset five associated research questions were formulated, some of which were answerable with the dataset while others were not. Thirteen researchers each assessed whether the ten questions associated with two randomly selected datasets were answerable with the described datasets. After removing instances where participants misunderstood the question or lacked subject matter knowledge to make the assessment, we found that 87 out of 109 assessments (80%) were correct. Participants particularly struggled with one dataset which consisted of EHR data. The most common reason for incorrect assessments was the inability to find the relevant information in the metadata catalogue.