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Objective: Rheumatoid arthritis-associated interstitial lung disease (RA-ILD) includes multiple subtypes with varying histopathology, prognosis, and potential treatments. Limited research has investigated risk factors for different RA-ILD subtypes. Therefore, we examined demographic, serologic, and lifestyle associations with RA-ILD subtypes., Methods: We systematically identified RA-ILD cases and RA controls without ILD (RA-noILD) in the Brigham RA Sequential Study and Mass General Brigham Biobank RA cohort. We determined RA-ILD subtype (usual interstitial pneumonia [UIP], nonspecific interstitial pneumonia [NSIP], and other/indeterminate) through chest high-resolution computed tomography imaging pattern. We investigated associations of demographic, lifestyle, and serologic factors with major RA-ILD subtypes using multivariable logistic regression., Results: Among 3,328 patients with RA, we identified 208 RA-ILD cases and 547 RA-noILD controls. RA-UIP was associated with older age (odds ratio [OR] 1.03 per year, 95% confidence interval [95% CI] 1.01-1.05), male sex (OR 2.15, 95% CI 1.33-3.48), and seropositivity (OR 2.08, 95% CI 1.24-3.48), whereas RA-NSIP was significantly associated only with seropositive status (OR 3.21, 95% CI 1.36-7.56). Nonfibrotic ILDs were significantly associated with smoking (OR 2.81, 95% CI 1.52-5.21). Having three RA-ILD risk factors (male, seropositive, smoking) had an OR of 6.89 (95% CI 2.41-19.7) for RA-UIP compared with having no RA-ILD risk factors., Conclusion: Older age, seropositivity, and male sex were strongly associated with RA-UIP, whereas RA-related autoantibodies were associated with RA-NSIP. These findings suggest RA-ILD sex differences may be driven by RA-UIP and emphasize the importance of further studies to clarify RA-ILD heterogeneity and optimize screening and treatment approaches., (© 2024 American College of Rheumatology.)

Objective: To use unbiased, data-driven, principal component (PC) and cluster analysis to identify patient phenotypes of rheumatoid arthritis (RA) that might exhibit distinct trajectories of disease progression, response to treatment, and risk for adverse events., Methods: Patient demographic, socioeconomic, health, and disease characteristics recorded at entry into a large, single-center, prospective observational registry cohort, the Brigham and Women's Rheumatoid Arthritis Sequential Study (BRASS), were harmonized using PC analysis to reduce dimensionality and collinearity. The number of PCs was established by eigenvalue >1, cumulative variance, and interpretability. The resulting PCs were used to cluster patients using a K-means approach. Longitudinal clinical outcomes were compared between the clusters over 2 years., Results: Analysis of 142 variables from 1,443 patients identified 41 PCs that accounted for 77% of the cumulative variance in the data set. Cluster analysis distinguished 5 patient clusters: 1) less RA disease activity/multimorbidity, shorter RA duration, lower incidence of comorbidities; 2) less RA disease activity/multimorbidity, longer RA duration, more infections, psychiatric comorbidities, health care utilization; 3) moderate RA disease activity/multimorbidity, more neurologic comorbidity; 4) more RA disease activity/multimorbidity, shorter RA duration, more metabolic comorbidity, higher body mass index; 5) more RA disease activity/multimorbidity, longer RA duration, more hepatic, orthopedic comorbidity and RA-related surgeries. The clusters exhibited differences in clinical outcomes over 2 years of follow-up., Conclusion: Data-driven analysis of the BRASS registry identified 5 distinct phenotypes of RA. These results illustrate the potential of data-driven patient profiling as a tool to support personalized medicine in RA. Validation in an independent data set is ongoing., (© 2020 The Authors. Arthritis Care & Research published by Wiley Periodicals LLC on behalf of American College of Rheumatology.)

Objective: Seropositivity for anti-citrullinated protein antibody (ACPA)/rheumatoid factor (RF) in rheumatoid arthritis (RA) is associated with increased overall mortality; however, the association between antibody titers and mortality is not well established. Investigating relationships between antibody titers and mortality may clarify their role in RA pathogenesis. This study was undertaken to evaluate the association of antibody titers with mortality and its modification by disease-modifying antirheumatic drugs (DMARDs)., Methods: Eligible patients with established RA were identified through administrative claims data linked to laboratory results (2005-2016). Patients were categorized by positivity status for ACPA, RF, or both. Patients were further divided into groups by autoantibody titers. DMARD-exposed patients were categorized into biologic DMARD (bDMARD) and conventional DMARD (cDMARD) subcohorts. Crude mortality rates/1,000 patient-years and Kaplan-Meier curves were compared between antibody categories. Adjusted Cox proportional hazards regression and sensitivity (propensity-matched patients) analyses were conducted., Results: Overall, 53,849 and 79,926 patients had evaluable ACPA and RF status, respectively. For both autoantibodies, mortality rates were significantly higher in seropositive versus seronegative patients (risk increase of 48.0% and 44.0% in ACPA- and RF-positive patients, respectively; P < 0.001 each). Mortality rates were greatest in patients with higher versus lower autoantibody titers (ACPA hazard ratio [HR] 1.60 [95% confidence interval (95% CI]) 1.45-1.76]; RF HR 1.78 [95% CI 1.66-1.91]). In cDMARD-exposed patients, HRs were higher in seropositive versus seronegative cohorts; in bDMARD-exposed patients, there was no difference in mortality by serostatus., Conclusion: Elevated ACPA/RF titers were independently associated with increased mortality among patients with RA and persisted in patients treated with cDMARDs but not with bDMARDs., (© 2019, Bristol Myers Squibb. Arthritis Care & Research published by Wiley Periodicals, Inc. on behalf of American College of Rheumatology.)

Objective: Loss of participants in longitudinal data collection can affect the validity of outcomes in rheumatoid arthritis (RA) registries. Prior research indicates that demographics and socioeconomic and psychosocial factors contribute to attrition. This study analyzed the characteristics of an RA registry that may contribute to attrition in a hospital-based population., Methods: Subjects consisted of RA patients enrolled in the Brigham and Women's Rheumatoid Arthritis Sequential Study. Demographics and clinical and psychological factors were evaluated in univariate analyses to determine differences between participants who dropped out and those who completed 5 years of followup. Univariate factors with a P value <0.1 were used in a survival analysis to determine significant factors associated with attrition. A secondary analysis looked at patients who dropped out during the first year., Results: A total of 1,144 RA participants were enrolled (509 completed 5 years of followup, 227 were still actively enrolled, and 408 dropped out). The attrition rate was 4.31% per 6-month cycle. Shorter disease duration, higher disease activity (3-variable Disease Activity Score in 28 joints using the C-reactive protein level), less education, RA drug therapy, and lower arthritis self-efficacy were statistically significant in multivariate survival analyses. In a secondary analysis, sex and age were the only additional factors found that contributed to attrition., Conclusion: The attrition rate for this registry was similar to rates reported by other registries. Shorter disease duration, higher disease activity, and several other socioeconomic factors were associated. Men and younger patients tended to drop out during the first year. Population differences in each registry may result in different attrition patterns and ultimately, each longitudinal registry should consider conducting its own analyses., (Copyright © 2013 by the American College of Rheumatology.)