Rheumatology

BackgroundRisk factors and screening strategies for rheumatoid arthritis-associated interstitial lung disease (RA-ILD) have received limited evaluation in patients with early RA. We investigated RA-ILD prevalence, risk factors, and the performance of proposed RA-ILD screening methodologies in a multicenter, prospective study of patients with early RA. MethodsParticipants with early RA, defined as being within two years of RA diagnosis, were enrolled at five US sites and assessed with high-resolution computed tomography (HRCT) chest imaging, pulmonary function tests, and autoantibodies. RA-ILD presence was determined through independent HRCT review by thoracic radiologists. We investigated RA-ILD risk factors using multivariable logistic regression and reported the predictive performance of RA-ILD screening strategies (ANCHOR-RA, 2023 ACR/CHEST, Four Factor Score, and ESPOIR). ResultsAmong 172 participants (74% female, 82% seropositive, median RA duration 0.79 years, mean age 55.3 years), 19 (11%) had ILD on HRCT. Moderate/high RA disease activity by DAS28-ESR (OR 7.00 [1.95, 25.1]) and age [≥]60 years (OR 3.87 [1.33, 11.3]) were associated with RA-ILD. Sensitivity and specificity of screening strategies ranged from 0.32-0.95 and 0.32-0.81, respectively. The number of early RA patients needing screening to detect one ILD case ranged from 3.6 to 6.4. DiscussionIn this prospective, multicenter study, ILD prevalence in early RA was 11%. Disease activity and older age were strongly associated with ILD in early RA, and several proposed ILD screening strategies performed showed promise for enabling ILD screening in early RA. KEY MESSAGESO_ST_ABSWhat is already known on this topicC_ST_ABSO_LISeveral risk factors for rheumatoid arthritis-associated interstitial lung disease have been identified. However, most prior studies have focused on patients with established RA. C_LIO_LISeveral approaches to RA-ILD screening have been proposed, including the recent 2023 ACR/CHEST guidelines. However, none have been specifically evaluated in patients with early RA. C_LI What this study addsO_LIIn a multicenter, prospective cohort of patients with early RA (diagnosed within 2 years of enrollment), moderate or high RA disease activity and older age were significantly associated with evidence of interstitial lung disease on high resolution CT chest imaging. C_LIO_LISeveral proposed RA-ILD screening criteria performed well in the early RA period. The simplest screening strategy included older age, male sex, and moderate/high RA disease activity and had a number needed to screen of 3.6 patients to detect one RA-ILD case. C_LI How this study might affect research, practice or policyO_LISimple screening strategies using demographic and clinical data may enable selection of early RA patients for RA-ILD screening. C_LI

IntroductionCoronavirus disease 2019 (COVID-19) has infected over 22 million individuals worldwide. It remains unclear whether patients with COVID-19 and Rheumatoid Arthritis (RA) experience worse clinical outcomes compared to similar patients with COVID-19 without RA. AimThe aim of this study is to provide insights on how COVID-19 impacted patients with RA given the nature of the disease and medication used. MethodsRA cases were identified via International Classification of Diseases (ICD) codes and COVID-19 cases by laboratory results in the U.S. based TriNetX network. Patients with COVID-19 and RA were propensity-score matched based on demographics with patients with COVID-19 without RA at a 1:3 ratio. A hospitalized sub-population was defined by procedure codes. ResultsWe identified 1,014 COVID-19 patients with RA and 3,042 non-RA matches selected from 137,757 patients. The odds of hospitalization (non-RA:23%, RA:24.6%, OR:1.08, 95% CI: 0.88 to 1.33) or mortality (non-RA:5.4%, RA:6%, OR:0.93, 95% CI: 0.65 to 1.34) were not significantly different. The hospitalized sub-population included 249 patients with COVID-19 and RA and 745 non-RA matches selected from 21,435 patients. The risk of intensive care unit (ICU) admission (non-RA:18.8%, RA:18.1%, OR:0.94, 95% CI: 0.60 to 1.45), and inpatient mortality (non-RA:14.4%, RA:14.5%, OR:0.86, 95% CI: 0.53 to 1.40) were not significantly different. ConclusionWe didnt find evidence suggesting patients with COVID-19 and RA are more likely to have severe outcomes than patients with COVID-19 without RA. Key Messages- Patients with Rheumatoid Arthritis (RA) tend to be older, and often have co-morbidities which could put them at greater risk of severe COVID-19 outcomes. - This study is one of the largest studies of COVID-19 infected RA populations to date. We did not find increased risk of hospitalization, ICU admission, or mortality among RA patients vs. matched non-RA patients. - Patients previously exposed to anti-coagulants experienced higher risks of hospitalization and overall mortality. Extra attention is needed for treating such patients.

ObjectiveTo develop an automatic gout register to improve gout management. MethodsWe analysed the electronic health records (EHR) of all patients >18 years old from a tertiary academic hospital (2013-2022) based on six criteria: International Classification of Diseases 10 (ICD-10) gout diagnosis, urate-lowering therapy (ULT) prescription, uric acid crystal in joint aspiration and gout-related terms in problem lists, clinical or imaging reports. We assessed the positive and negative predictive value (PPV and NPV) of the query by chart reviews. ResultsOf 2,110,902 out- and inpatients, 10,289 had at least one criterion for gout. The combination of joint aspiration OR diagnostic in the problem list OR [≥] 2 other criteria created a register of 5,138 patients, with a PPV of 92.4% (95%CI: 88.5 to 95.0), and an NPV of 94.3% (95%CI: 91.9 to 96.0). PPV and NPV were similar amongst outpatients and inpatients. Incidence was 2.9 per 1000 person-year and dropped by 30% from the COVID-19 pandemic onward. Patients with gout were on average 71.2 years old (SD 14.9), mainly male (76.5%), overweight (69.5%) and polymorbid (mean number of comorbidities of 3, IQR 1-5). More than half (57.4%) had received a urate lowering treatment, 6.7% had a gout that led to a hospitalisation or [≥]2 flares within a year, and 32.9% received a rheumatology consultation. ConclusionAn automatic EHR-based gout register is feasible, valid and could be used to evaluate and improve gout management. Interestingly, the register uncovered a marked underdiagnosis or underreporting of gout since the COVID-19 pandemic. Key messagesWhat is already known on this topic? - Gout is the most prevalent inflammatory arthritis, but it remains undertreated despite affordable and effective treatment options. - Quantifying this undertreatment and detecting its causes and risk factors to pilot quality improvement initiative requires an extensive register of gout patients. What this study adds? - This is the first automatic EHR-based gout register, allowing frequent, inexpensive, and sustainable updates. - The automated queries show high positive and negative predictive values to identify gout patients. How this study might affect research, practice or policy? - This register can facilitate the assessment of the adequacy of gout management and the monitoring of quality indicators following improvement projects, or change in policies - It provides an easy platform for cohort studies or adaptive trials - Its methodology is reproducible, facilitating the establishment of gout or other disease registers within different EHR systems

ObjectivesWe aimed to estimate how rheumatology healthcare use has changed since the COVID-19 pandemic and determine demographic characteristics associated with observed changes in healthcare use. MethodsUsing three primary and secondary care electronic health record datasets in England (with the approval of NHS England), Scotland, and Wales, we identified individuals with a diagnosis of rheumatoid arthritis (RA) before 01/04/2019. We determined the proportion of people with rheumatology hospital outpatient appointments each month (April 2019-December 2022 (Wales and Scotland), April 2019-November 2023 (England)) and quantified changes using interrupted time-series analysis. We used logistic regression to determine characteristics associated with having fewer appointments compared to 2019. ResultsWe identified 145,065, 3,813 and 13,637 individuals coded with RA in England, Scotland, and Wales, respectively. At the start of the COVID-19 pandemic the number of rheumatology outpatient appointments dropped sharply across all nations. In England and Scotland, the percentage of monthly appointments has continued to decline. In Wales, while there was a gradual recovery, rheumatology services have not returned to pre-pandemic levels. In contrast, the number of appointments for all other specialist outpatient appointments have recovered in all nations. Ethnic minorities, those living in more deprived areas and urban areas had fewer appointments after the start of the pandemic compared to 2019. ConclusionFor the first time, we compared healthcare use across three UK nations and found that rheumatology outpatient appointments had not recovered to pre-COVID-19 pandemic levels, particularly in Scotland and England. Certain patient groups had fewer appointments during the study period. Key messagesO_LIRheumatology outpatient appointments remain below pre-pandemic levels, particularly in England and Scotland, unlike other specialties. C_LIO_LIEthnic minorities, deprived communities, and urban residents had fewer rheumatology appointments post-pandemic than in 2019. Rheumatology services need data-driven strategies to provide better support, tailored to local community needs. C_LI

ObjectiveThis systematic review aimed to assess the diagnostic accuracy of algorithms used to identify rheumatoid arthritis (RA) and juvenile idiopathic arthritis (JIA) in electronic health records (EHRs). MethodsWe searched MEDLINE, Embase, and CENTRAL databases and included studies that validated case definitions against a reference standard such as rheumatologist-confirmed diagnosis or ACR/EULAR classification criteria. Title/abstract screening, full-text review, data extraction and quality assessment were all completed in duplicate. Results were synthesised narratively and using a bivariate random-effects meta-analysis of sensitivity and specificity. ResultsA total of 35 studies were included. Algorithms varied widely in complexity, ranging from single ICD codes to combinations including disease-modifying antirheumatic drugs (DMARDs), hospitalisation records, and specialist diagnosis. Algorithms combining ICD codes with DMARD prescriptions (pooled sensitivity= 0.79 95% CI 0.61-0.90, specificity= 0.96 95% CI 0.72-1.00, PPV= 0.78 95% CI 0.63-0.88) or requiring an ICD code assigned by a rheumatologist (pooled sensitivity= 0.91 95% CI 0.70-0.98, specificity= 0.94 95% CI 0.49-1.00, PPV= 0.70 95% CI 0.64-0.75) showed the highest accuracy, with balanced sensitivity, specificity, and positive predictive value (PPV). Less restrictive algorithms demonstrated high sensitivity but lower PPV. Substantial heterogeneity was observed across studies, likely due to differences in algorithm structure, data sources, and validation methods. Despite this variability, we used conceptually coherent categories to allow for meaningful synthesis, prioritising clinical interpretability. ConclusionsThese findings support the use of more specific algorithms when diagnostic certainty is essential and highlight the need for further validation of high-performing algorithms across diverse healthcare systems. Significance and Innovations{blacksquare} This is the first comprehensive systematic review to evaluate and synthesize the accuracy of algorithms used to identify rheumatoid arthritis and juvenile idiopathic arthritis in electronic health records (EHRs), addressing a growing need as real-world data become increasingly central in rheumatology research. {blacksquare}The findings provide critical guidance for researchers and clinicians on the strengths and limitations of commonly used case definitions, helping improve validity of studies using administrative or EHR data. {blacksquare}By categorizing algorithms based on their components and reference standards, this review offers a practical framework for selecting the most appropriate algorithm depending on the study purpose and data source. {blacksquare}The review highlight gaps in validation efforts and emphasizes the need to validate high-performing algorithms across diverse healthcare settings and evolving coding systems, ensuring accurate disease identification in current and future research.

ObjectivesTo compare physical function in systemic sclerosis (SSc, scleroderma) to general population normative data and identify associated factors. MethodsScleroderma Patient-centered Intervention Network Cohort participants completed the Physical Function domain of the Patient-Reported Outcomes Measurement Information System Version 2 upon enrollment. Multivariable linear regression was used to assess associations of sociodemographic, lifestyle, and disease-related variables. ResultsAmong 2,385 participants, mean physical function T-score (43.7, SD = 8.9) was approximately 2/3 of a standard deviation (SD) below the US general population (mean = 50, SD = 10). Factors associated in multivariable analysis included older age (-0.74 points per SD years, 95% CI -0.78 to -1.08), female sex (-1.35, -2.37 to -0.34), fewer years of education (-0.41 points per SD in years, -0.75 to -0.07), being single, divorced, or widowed (-0.76, -1.48 to -0.03), smoking (-3.14, -4.42 to -1.85), alcohol consumption (0.79 points per SD drinks per week, 0.45 to 1.14), BMI (-1.41 points per SD, -1.75 to -1.07), diffuse subtype (-1.43, -2.23 to -0.62), gastrointestinal involvement (-2.58, -3.53 to -1.62), digital ulcers (-1.96, -2.94 to -0.98), moderate (-1.94, -2.94 to -0.93) and severe (-1.76, -3.24 to -0.28) small joint contractures, moderate (-2.10, -3.44 to -0.76) and severe (-2.54, -4.64 to -0.44) large joint contractures, interstitial lung disease (-1.52, -2.27 to -0.77); pulmonary arterial hypertension (-3.72, -4.91 to -2.52); rheumatoid arthritis (-2.10, -3.64 to -0.56) and idiopathic inflammatory myositis (-2.10, -3.63 to -0.56). ConclusionPhysical function is impaired for many individuals with SSc and associated with multiple disease factors. KEY MESSAGESO_LIIndividuals with systemic sclerosis (SSc) face many challenges that can impact their physical function C_LIO_LILevels of physical function in individuals with SSc are impaired compared to the general population C_LIO_LIMultiple disease factors are significantly associated with worse physical function in SSc C_LI

Background. Polypharmacy is common in autoimmune rheumatic diseases (ARDs) and increases adverse drug events (ADEs), but comparative evidence across diseases is limited. We aimed to quantify ADE burden and identify medications associated with ADE risk across six ARDs, and to examine shared and disease specific patterns across diseases. Methods. We conducted a retrospective cohort study at a tertiary medical center (2010 to 2024). Adults with ankylosing spondylitis (AS), psoriatic arthritis (PsA), rheumatoid arthritis (RA), Sjogren's disease (SjD), systemic lupus erythematosus (SLE), or systemic sclerosis (SSc) were identified using diagnostic codes. ADEs were ascertained using validated case definitions. Medications were mapped to Anatomical Therapeutic Chemical classes; active exposure was defined within 30 days before the index date. Polypharmacy was defined as more than 5 concurrent medications (minor 5 to 10; major >10). Within each ARD, nested case control analyses matched on encounter type (1:4) were performed, and adjusted odds ratios (aORs) were estimated using conditional logistic regression. Findings. Among 10,578 patients, 3,154 (29.8%) experienced at least one ADE. ADE burden varied across diseases, with the highest prevalence observed in SSc (35.9%). Polypharmacy was common (57.3% minor, 39.4% major) and medication burden was consistently higher in ADE cases across encounter types (eg, SLE outpatient median 12 vs 6; inpatient 20 vs 10; emergency 17 vs 8). Across ARDs, the strongest associations with ADEs were observed for supportive and symptom directed therapies (acid suppressors, pain adjuncts, and sedative hypnotic/psychotropic medications), whereas conventional disease-modifying antirheumatic drugs (DMARDs) showed weaker associations. Disease-specific signatures included gastrointestinal agents in SSc (metoclopramide aOR 12.32), antibiotics and respiratory agents in AS (ciprofloxacin aOR 13.71, fluticasone aOR 8.88). Interpretation ADEs affect nearly one third of ARD patients and increase with medication burden. Risk concentrates in supportive and symptom directed therapies rather than DMARDs, with both shared and disease-specific patterns. Optimizing prescribing, particularly for pain management and corticosteroid use, can reduce medication-related harm.

ObjectivesInvestigate the prevalence and mortality impact of interstitial lung abnormalities (ILA) in rheumatoid arthritis (RA) and non-RA comparators. MethodsWe analyzed associations between ILA, RA, and mortality in COPDGene, a multicenter prospective cohort study of current or former smokers, excluding known interstitial lung disease (ILD) or bronchiectasis. All participants had research chest high-resolution computed tomography (HRCT) reviewed by a sequential reading method to classify ILA as present, indeterminate, or absent as well as fibrotic or nonfibrotic ILA subtype. RA cases were identified by self-report RA and DMARD use; non-RA comparators had neither an RA diagnosis nor used DMARDs. We examined the association and mortality risk of RA and ILA using multivariable logistic regression and Cox regression. ResultsWe identified 83 RA cases and 8725 non-RA comparators with HRCT performed for research purposes. ILA prevalence was 16.9% in RA cases and 5.0% in non-RA comparators. After adjusting for potential confounders including genetics, smoking, and other lifestyle factors, ILA were more common among those with RA compared to non-RA (OR 4.76 95%CI 2.54 to 8.92). RA with ILA or indeterminate for ILA was associated with higher mortality compared to non-RA without ILA (HR 3.16, 95%CI 2.11 to 4.74) and RA cases without ILA (HR 3.02, 95%CI 1.36 to 6.75). ConclusionsRA was associated with ILA and this persisted after adjustment for smoking and genetic/lifestyle risk factors. RA with ILA in chronic heavy smokers had 3-fold increased mortality, emphasizing the importance of further screening and treatment strategies for subclinical ILD in RA. KEY MESSAGESO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIUp to a third of patients with rheumatoid arthritis (RA) may have evidence of subclinical interstitial lung abnormalities on computed tomography (CT) scans of the chest. C_LIO_LICigarette smoking and the MUC5B promoter variant are known risk factors for RA-associated interstitial lung disease. C_LI What this study addsO_LIWe found that 17% of RA patients had subclinical interstitial lung abnormalities. RA had 4-fold higher odds of interstitial lung abnormalities than non-RA comparators, adjusted for smoking, the MUC5B promoter variant, and other factors. C_LIO_LIParticipants with RA and no interstitial lung abnormalities were not at increased mortality risk while those with interstitial lung abnormalities or indeterminate for ILA had a three-fold increased risk of mortality compared to RA and non-RA patients without interstitial lung abnormalities. C_LI How this study might affect research, practice or policyO_LIThe presence of subclinical interstitial lung abnormalities confers significant mortality risk in RA and emphasizes the need to establish the clinical utility of screening, prevention, and treatment strategies targeting subclinical lung disease. C_LI

ObjectiveTo clinically evaluate a digital biomarker, the Finger Fold Index (FFI), derived from the ratio of joint diameter to finger fold surface area in hand photographs, for assessing joint swelling in inflammatory arthritis. MethodsSmartphone hand photographs from two routine care cohorts of patients with rheumatoid (RA) and psoriatic arthritis (PsA) were analyzed using a machine learning pipeline for automated detection and processing of proximal interphalangeal (PIP) joints. The FFI was clinically evaluated by correlation with joint swelling scores (0-3) and DAS28-CRP. A healthy cohort was used to establish FFI reference ranges, which were then compared to the arthritis cohorts. ResultsA total of 1275 PIP joint images of 124 arthritis patients and 53 healthy individuals were included. FFI values correlated with swelling scores in the arthritis population with r = 0.443 (95% CI 0.384-0.498). A correlation was observed between the mean FFI and DAS28-CRP dichotomized at 3.2 (r = 0.310, 95% CI 0.123-0.475). FFI values exceeding the healthy reference ranges were associated with swelling (Cramers V = 0.400-0.631; p < 0.001). ConclusionFFI values derived from hand photographs showed a significant association with clinical joint swelling and disease activity in RA and PsA patients. Longitudinal studies are needed to assess sensitivity to change and to establish whether this biomarker can be reliably used for remote patient monitoring.

ObjectivesSystemic sclerosis (SSc) heart involvement (SHI) is an enigmatic disease manifestation associated with high mortality. The Scleroderma Clinical Trials Consortium (SCTC) Cardiac Working Group developed SHI classification criteria to enable systematic investigation of this condition. MethodsAn international, inter-disciplinary working group was assembled. Using consensus methods and existing literature, provisional SHI classification criteria items were developed. Continuous consensus exercises and a discrete choice experiment were performed to reduce items and derive individual item weights. The sensitivity and specificity of the classification criteria were tested in an independent cohort (n=168) of SHI (cases) and non-SSc heart disease (controls). ResultsThe working group agreed that the SCTC SHI Classification Criteria should identify the direct effects of SSc on the heart and exclude the complications of other SSc manifestations or cardiac co-morbidities. The final classification criteria include 23 items measuring cardiac fibrosis, inflammation, arrhythmias and small vessel vasculopathy. No single item is pathognomonic for SHI, with a requirement for the presence of abnormalities across multiple histopathological, imaging, serological and, or clinical domains to be present to secure a diagnosis. A classification criteria score of [&ge;]11 identified SHI with a sensitivity of 78% and specificity of 96%, with an area under the curve of 0.87 (0.80-0.93). This threshold correctly identified >90% of cases of SHI. ConclusionThe newly derived SCTC SHI Classification Criteria have high sensitivity and specificity for SHI. Application of these criteria will enable standardised classification of patients in studies to facilitate future investigation of this important disease manifestation. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/25339972v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@4276fdorg.highwire.dtl.DTLVardef@191eb90org.highwire.dtl.DTLVardef@1004a1aorg.highwire.dtl.DTLVardef@11d95_HPS_FORMAT_FIGEXP M_FIG Abbreviations: AUC: area under the curve; IHD: ischaemic heart disease; PAH: pulmonary arterial hypertension; SHI: systemic sclerosis heart involvement; SRC: scleroderma renal crisis Alt text: Flow chart representing the steps to define systemic sclerosis heart involvement criteria, staring from scope and planning, item generation, item reduction and weighting and concluding with defining a classification threshold and testing performance of criteria. A criteria score of 11 or greater classifies a patient as having systemic sclerosis heart involvement. C_FIG Key messagesO_LIThis study presents the first classification criteria for the identification of systemic sclerosis heart involvement. C_LIO_LIA score of [&ge;]11 identifies systemic sclerosis heart involvement with high sensitivity and specificity. C_LIO_LIStandardised criteria enable identification of biomarkers and risk predictions models and lead to effective treatments for heart involvement. C_LI

ObjectiveQuantitative computed tomography (QCT) can automatically quantify parenchymal abnormalities on chest CT imaging using deep learning. We leveraged QCT to detect pulmonary abnormalities in patients with early rheumatoid arthritis (RA) compared to healthy controls. MethodsWe analyzed high-resolution CT chest imaging from participants with early RA in the prospective, multicenter, SAIL-RA study and healthy non-smoking controls from the COPDGene study. A deep learning classifier quantified the percentage of normal lung, interstitial abnormalities, and emphysema for each participant. We compared the percentage of QCT features between early RA participants and healthy comparators and examined associations using multivariable linear regression. ResultsWe analyzed 200 participants with early RA (median RA duration 8.3 months, mean age 55.7 years, 74.5% female) and 104 healthy controls (mean age 62.0 years, 68.3% female). The median percentage of interstitial abnormalities on QCT was 3.7% (IQR 2.1, 6.1%) for early RA and 1.6% (IQR 0.8, 2.4%) for healthy controls (p<0.0001). Early RA was associated with 9.3% less normal lung on QCT than healthy controls, adjusted for age and sex (p<0.0001). Among RA participants, QCT interstitial abnormalities were associated with older age (multivariable {beta}=0.1 per year, 95%CI 0.07-0.2, p<0.0001) and higher DAS28-ESR (multivariable {beta}=0.6 per unit, 95%CI 0.01-1.3, p=0.046). ConclusionParticipants with early RA had less normal lung and more interstitial abnormalities on a deep learning-derived QCT measure than healthy controls. These results suggest that loss of normal lung is already present in early RA and emphasizes the urgent need for strategies to preserve lung health in RA.

Background: Itch in systemic sclerosis (SSc) is thought to be most significant in early disease, but no longitudinal studies have examined itch course. We estimated itch presence and severity from SSc disease onset, accounting for participant age and time since onset at each assessment. Methods: People with SSc from the multinational Scleroderma Patient-centred Intervention Network Cohort completed past-week itch severity assessments (0 to 10 numerical rating scale) at enrolment and longitudinally at 3-month intervals. To estimate itch probability (score > 0) and, if present, itch severity, we used two-stage mixed effects models with basis splines to address non-linearity. The primary predictor was age at each assessment, partitioned into age at non-Raynaud phenomenon symptom onset and time since onset. We estimated prevalence and severity for onset ages of 20, 30, 40, 50 and 60 years and, for each onset age, at 2 years, 3 years, 4 years, 5 years, 7 years, and 5-year intervals 10 years to 35 years post-onset. Findings: We included 2173 participants with 19 733 itch assessments (mean [standard deviation] 9.1 [6.9] assessments). 1896 of 2173 (87.3%) participants were women. Mean age at enrolment was 54.7 (SD 12.7) years. 873 (40.2%) participants had diffuse cutaneous SSc. Predicted itch probability was between 35.0% (95% CI 31.8% to 38.5%) and 36.8% (95% CI 33.3% to 40.4%) at all onset age and disease duration combinations. Mean itch severity, when present, was moderate, between 4.1 (95% CI 4.1 to 4.1) and 4.4 (95% CI 4.3 to 4.4), for all age and duration combinations. Interpretation: Itch prevalence and mean severity were stable across onset ages and over time within onset ages. Findings suggest that itch is common in SSc and not as closely related to disease duration as previously thought. Research is needed to elucidate itch pathophysiology and identify effective management strategies.

ObjectiveDisease activity plays a central role in rheumatoid arthritis (RA) clinical studies. However, RA disease activity is inconsistently recorded in real-world electronic health records (EHR) data limiting the generation of real-world evidence (RWE). This study aimed to develop and validate scalable machine learning (ML) models to infer RA disease activity from EHR data. MethodsWe conducted studies from EHR data from Mass General Brigham (MGB) and the Veterans Affairs (VA); both have RA registries with prospectively collected disease activity score 28 (DAS28). The features for the algorithm were extracted from the EHR including structured data, e.g., ICD codes and narrative data using natural language processing (NLP). Machine learning models were trained on the registry-collected DAS28.We tested within-institution trained model performance and across systems transportability. The association between inferred disease activity and major adverse cardiovascular events (MACE) was tested with stratified Cox models to test face-validity. ResultsWe studied 1105 MGB and 2631 VA RA patients. Models with structured data models achieved an AUC of 0.68-0.70; models incorporating structured and NLP achieved higher performance (AUC=0.843, MGB; 0.833, VA). Cross-site validation demonstrated reduced transportability (AUC=0.679, MGB[-&gt;]VA; 0.718, VA[-&gt;]MGB), due to differences in the important feature. Within institution, inferred disease activity was significantly associated with increased risk for incident MACE (MGB: HR=1.12; VA: HR=1.14). ConclusionRA disease activity can be inferred at scale from within-institution EHR data, though cross-institution performance is limited. The inferred disease activity replicated association between RA and MACE and supports its use in future studies to generate RWE.

ObjectiveDespite significant improvements in diagnosis delay and treatment strategies, the burden of Systemic Lupus Erythematosus (SLE) remains high. The objective of the study was to assess the association between diagnosis delay, disease activity and burden on daily life (BoDL) in a large sample of European patients with SLE. MethodsIn May 2020, Lupus Europe, the European umbrella patient association for SLE, conducted a multilingual anonymous online cross-sectional study to individuals with a self-reported physicians diagnosis of SLE living in Europe. The BoDL score was computed using 1 to 5 Likert scales on 5 domains (mobility, anxiety/depression, self-care, daily activities and pain/discomfort) and the sum was rescaled on a 0 (minimum Burden on daily life) to 100 (maximum BoDL) scale. Comparisons between independent groups were made using the Mann-Whitney test for continuous outcomes and the Chi-2 test (or Fishers exact test) for quantitative data. ResultsData of 4,150 SLE patients from 35 European countries were analysed. Those with a diagnosis of SLE within 2 years of first symptoms had significantly lower mean BoDL scores than those diagnosed after 5 years (33.6 versus 44.0, p<0.001). The BoDL score was better in SLE patients feeling that their lupus had been under control during the last 3 months versus the others (34.0% versus 47.6%, p<0.001). ConclusionThis large international study highlights the association between diagnosis delay and self-perceived disease activity with the burden of the disease on the daily life of people living with SLE. Healthcare pathways, which may accelerate diagnosis and optimize therapeutic management, are necessary to improve patients outcomes in SLE.

ObjectiveCharacterize psoriatic arthritis (PsA) heterogeneity and develop a conceptual framework to model the clinical and economic value of treatments on key PsA disease domains. MethodsWe performed a narrative literature review to identify the key PsA disease domains and outcome measures for these and explore the existing evidence base of clinical and economic evaluations of current PsA treatments on key disease domains. We propose an economic modelling framework that could estimate the economic value of PsA treatments on disease domains. ResultsOur literature review identified the following key PsA disease domains: peripheral arthritis, dactylitis, enthesitis, psoriatic spondylitis, skin, and nail lesions, and associated key outcome measures. Our review of the literature, including clinical guidelines, suggests that the evidence base of specific treatment performance on modulating outcomes for a given domain was not strong. We propose an economic modelling framework to estimate the economic value of treatments for addressing specific PsA disease domains. Given existing evidence gaps, we would recommend a cohort-level model with a lifetime horizon, to estimate total social value as well as the cost per outcome and change in cost per symptom avoided. The significant patient heterogeneity in PsA would suggest an individual/patient-level simulation but is likely not feasible with existing data. ConclusionsPsA is a heterogeneous disease, with a number of key disease domains and variable presentation. A better understanding of the performance of treatments on given disease domains would help support patients, providers, payers, HTAs, and health care policy makers in making personalized treatment decisions. Key messagesO_LIPsoriatic arthritis is a heterogeneous disease, with patients presenting a variety of disease manifestations. C_LIO_LIBetter understanding of the interaction between manifestations and treatments could help inform patient and physician decision making. C_LIO_LIThe proposed model framework would help inform value-based, personalized treatment decisions in PsA. C_LI

ObjectiveRheumatoid arthritis (RA) causes chronic polyarthritis and joint dysfunction, reducing work productivity. This reduction is mainly due to presenteeism, characterized by impaired work performance despite being present at work. This study aims to investigate the impact of specific joint involvement, particularly in the upper extremities, on work disability in RA patients. MethodsAnnual surveys assessing work disability were conducted among RA outpatients enrolled in the Nagahama Riumachi Cohort at Nagahama City Hospital, using the Work Productivity and Activity Impairment Questionnaire (WPAI). A multivariate regression analysis was performed to examine the cross-sectional and longitudinal associations between presenteeism and the tender joint count (TJC) in the extremities across two WPAI surveys. ResultsThe analysis included 201 patients, 52% of whom reported presenteeism. Cross-sectional analysis revealed a significant positive correlation between three or more TJCs of the upper extremity and presenteeism, with a regression coefficient ({beta}) = 17.9 (95% confidence interval [CI]: 9.85-25.9). Among the joints evaluated, the sum of TJCs in the shoulder area ({beta} = 9.55, CI: 5.39-13.7) and the fingers ({beta} = 1.60, CI: 0.35-2.85) were significantly correlated with presenteeism. Additionally, change in presenteeism were significantly correlated with change in upper extremity TJCs ({beta} = 1.41, CI: 0.05-2.77). ConclusionsThe upper extremity TJC is strongly associated with presenteeism in RA patients. The TJC of the upper extremities serves as a valuable indicator for clinicians, helping them effectively assess a patients underlying work disability.

IntroductionInterstitial lung diseases (ILDs) are a common manifestation in certain connective tissue diseases (CTD). Our study aims to describe the prevalence and time to diagnosis of CTD-ILD in veterans. MethodsWe used the Veterans Affairs Corporate Data Warehouse to select veterans with a) age [&ge;]18 years, b) [&ge;] two ICD9 or ICD10 codes for Rheumatoid Arthritis (RA), Systemic Lupus Erythematosus, Systemic Sclerosis (SSc), Sjogrens, Dermatomyositis/Polymyositis, Overlap, and Other CTD separated by [&ge;]6 months from 1999 to 2022, c) rheumatology visit within 6 months. ILD was identified by [&ge;] one ICD9 or ICD10 code for ILD one year before CTD diagnosis or any time after. Kaplan-Meier curves and Cox regression analyses were performed. Results88,559 veterans with CTD were identified with 8.8 (+/- 5.9) years of follow up. The majority were White males with RA and an average age of 60.4 years. 8,498 patients (9.6%) were diagnosed with ILD. 29% of veterans with CTD developed ILD within 1 year. Average time to diagnosis of ILD was 5.38 (SD 5.61) years. 42% of veterans with SSc were diagnosed with ILD while only 8% of veterans with RA developed ILD. The hazard of diagnosis of ILD in veterans with RA was 0.14 times compared to SSc (95%CI 0.13-0.15) adjusted for age, race, gender, smoking status, and CTD type. ConclusionsIn veterans, RA-ILD was the most common subtype, but veterans with RA were less likely to develop ILD compared to SSc. These results can influence strategies for ILD screening in patients with CTD. Significance and InnovationsO_LIThe prevalence of ILD in a national cohort of veterans with CTD was 9.6%. C_LIO_LIThe prevalence of ILD in veterans with CTD was highest in SSc (42%) and lowest in RA at 8%. C_LIO_LI29% of veterans with CTD developed ILD within +/- 1 year timeframe of CTD diagnosis. C_LIO_LIThe average time to diagnosis of ILD after a diagnosis of CTD is approximately 6 years. C_LI

ObjectiveTracheobronchial stenosis (TBS) occurs in 13-27% of patients with granulomatosis with polyangiitis (GPA) and may cause life-threatening airway compromise. Despite advances in treatment, TBS remains difficult to manage, with frequent relapses and high procedural burden. The objective of this study was to evaluate the relationship between immunosuppressant use and frequency of relapse in patients with TBS-GPA. MethodsWe performed retrospective review of patients with TBS-GPA seen at Johns Hopkins Medical Institutions between 2013-2024. Baseline demographic and clinical characteristics, immunosuppressant exposure, and tracheal dilation procedure dates were abstracted. A multivariate mixed effects Poisson regression model was used to assess the association between immunosuppressant exposures (rituximab, cyclophosphamide, methotrexate, azathioprine, leflunomide, and mycophenolate) and tracheal dilation incidence, adjusting for age, years since TBS diagnosis, anti-neutrophil cytoplasmic antibody (ANCA) status, GPA disease severity, and concomitant treatment with glucocorticoid injections. ResultsA total of 56 patients with TBS-GPA were included in the analysis, with a mean follow-up duration of 9.9 years. In the adjusted mixed-effects Poisson model, patient-years on leflunomide were associated with a 64% lower incidence of tracheal dilations compared to periods off leflunomide (IRR 0.36, p = 0.002). No statistically significant associations were observed for the other immunosuppressants measured. Among other tested covariates, age under 40, severe GPA, and concomitant glucocorticoid injections were associated with higher dilation frequency. ConclusionLeflunomide use was associated with a lower frequency of tracheal dilations in patients with TBS-GPA. These findings support the need for further evaluation of leflunomide as a treatment option in this population.

ObjectivesIdentifying causal biomarkers of rheumatoid arthritis (RA) to improve treatment and monitor disease progression remains a critical but elusive goal. To search for putatively causal protein biomarkers of RA, we designed an integrative genomic strategy utilizing Mendelian randomization (MR), which allows for causal inference between an exposure and an outcome by incorporating genetic variants associated with an exposure (circulating protein level) and inferring its effect on the outcome (rheumatoid arthritis). MethodsWe utilized genetic variants associated with 71 cardiovascular disease-related proteins measured in nearly 7000 Framingham Heart Study participants in conjunction with variants associated with RA in a genome-wide association study (GWAS) from the UK Medical Research Council Integrative Epidemiology Unit (19,234 cases, 61,565 controls) to identify putatively causal proteins for RA. In addition, we applied MR to study circulating rheumatoid factor (RF) levels using GWAS of RF from the UK Biobank (n=30,565) as the outcome. ResultsWe identified the soluble receptor for advanced glycation end products (sRAGE), a critical inflammatory pathway protein, as putatively causal and protective for both RA (odds ratio per 1 standard deviation increment in inverse-rank normalized sRAGE level=0.482; 95% confidence interval 0.374-0.622; p=1.85x10-08) and RF levels ({beta} [change in RF level per sRAGE increment]=-1.280; SE=0.434; p=0.003). ConclusionsBy integrating GWAS of 71 cardiovascular disease-related proteins, RA, and RF, we identified sRAGE as a putatively causal protein protective for both RA ad RF levels. These results highlight the AGER/RAGE axis as a promising new target for RA treatment.

ObjectivesTo create definitions for minimal disease activity (MDA), flare, and minimal clinically important difference (MCID) for chronic nonbacterial osteomyelitis (CNO). It is necessary to establish these criteria prior to starting clinical effectiveness trials for therapies in CNO. MethodsThree separate cohorts samples from an international observational CNO registry were presented to a panel of twenty experts in CNO, including 7 patients/caregivers via online and in-person voting using nominal group technique to define MDA, flare, and MCID, respectively. Experts classified the cases in each cohort as meeting the state for that specific cohort, ie. MDA or not, or flare or not, or meeting MCID or not. A consensus of [&gt;=]80% was required. ResultsGeneral surveys identified the most important variables to include to define MDA, flare, and MCID. Clinical improvement of 30% or more in these critical parameters and improvement of CNO Clinical Disease Activity Score (CDAS) by at least 3 were considered meaningful by providers and consensus data. Conclusions This study provides the preliminary definitions of MDA, disease flare, and MCID in CNO which can serve as targets and potential outcomes from treatments. These definitions must now be validated in other cohorts and tested in clinical trials. Key MessagesO_ST_ABSWHAT IS ALREADY KNOWN ON THIS TOPICC_ST_ABSO_LIMeasurements of minimal disease activity (MDA), worsening disease activity ( flare), and minimally clinically important differences (MCID) in CNO are not well-established. For successful execution of clinical trials to identify effective treatment strategies in patients with CNO, standardized definitions of these terms are necessary. C_LI WHAT THIS STUDY ADDSO_LIUsing data from an international real-world registry of CNO patients, we developed and validated quantitative definitions for MDA, flare, and MCID. C_LI HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICYO_LIDefinitions of MDA, flare, and MCID will serve as potential outcomes in future clinical trials to study effectiveness of therapies in CNO. C_LI