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A treat-to-target (TTT) approach improves outcomes in rheumatoid arthritis (RA). In prior work, we found that a learning collaborative (LC) program improved implementation of TTT. We conducted a shorter virtual LC to assess the feasibility and effectiveness of this model for quality improvement and to assess TTT during virtual visits.We tested a 6-month virtual LC in ambulatory care. The LC was conducted during the 2020-2021 COVID-19 pandemic when many patient visits were conducted virtually. All LC meetings used videoconferencing and a website to share data. The LC comprised a 6-hour kickoff session and 6 monthly webinars. The LC discussed TTT in RA, its rationale, and rapid cycle improvement as a method for implementing TTT. Practices provided de-identified patient visit data. Monthly webinars reinforced topics and demonstrated data on TTT adherence. This was measured as the percentage of TTT processes completed. We compared TTT adherence between in-person visits versus virtual visits.Eighteen sites participated in the LC, representing 45 rheumatology clinicians. Sites inputted data on 1,826 patient visits, 78% of which were conducted in-person and 22% of which were held in a virtual setting. Adherence with TTT improved from a mean of 51% at baseline to 84% at month 6 (P for trend 0.001). Each aspect of TTT also improved. Adherence with TTT during virtual visits was lower (65%) than during in-person visits (79%) (P 0.0001).Implementation of TTT for RA can be improved through a relatively low-cost virtual LC. This improvement in TTT implementation was observed despite the COVID-19 pandemic, but we did observe differences in TTT adherence between in-person visits and virtual visits.

Objective Patients with rheumatoid arthritis (RA) are 1.5 times more likely to develop cardiovascular disease (CVD) attributed to chronic inflammation. A decrease in inflammation in patients with RA is associated with increased low-density lipoprotein (LDL) cholesterol. This study was undertaken to prospectively evaluate the changes in lipid levels among RA patients experiencing changes in inflammation and determine the association with concomitant temporal patterns in markers of myocardial injury. Methods A total of 196 patients were evaluated in a longitudinal RA cohort, with blood samples and high-sensitivity C-reactive protein (hsCRP) levels measured annually. Patients were stratified based on whether they experienced either a significant increase in inflammation (an increase in hsCRP of ≥10 mg/liter between any 2 time points 1 year apart; designated the increased inflammation cohort [n = 103]) or decrease in inflammation (a decrease in hsCRP of ≥10 mg/liter between any 2 time points 1 year apart; designated the decreased inflammation cohort [n = 93]). Routine and advanced lipids, markers of inflammation (interleukin-6, hsCRP, soluble tumor necrosis factor receptor II), and markers of subclinical myocardial injury (high-sensitivity cardiac troponin T [hs-cTnT], N-terminal pro-brain natriuretic peptide) were measured. Results Among the patients in the increased inflammation cohort, the mean age was 59 years, 81% were women, and the mean RA disease duration was 17.9 years. The average increase in hsCRP levels was 36 mg/liter, and this increase was associated with significant reductions in LDL cholesterol, triglycerides, total cholesterol, apolipoprotein (Apo B), and Apo A-I levels. In the increased inflammation cohort at baseline, 45.6% of patients (47 of 103) had detectable circulating hs-cTnT, which further increased during inflammation (P = 0.02). In the decreased inflammation cohort, hs-cTnT levels remained stable despite a reduction in inflammation over follow-up. In both cohorts, hs-cTnT levels were associated with the overall estimated risk of CVD. Conclusion Among RA patients who experienced an increase in inflammation, a significant decrease in routinely measured lipids, including LDL cholesterol, and an increase in markers of subclinical myocardial injury were observed. These findings highlight the divergence in biomarkers of CVD risk and suggest a role in future studies examining the benefit of including hs-cTnT for CVD risk stratification in RA.

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.

Objective Previous attempts to estimate rheumatoid arthritis (RA) disease activity using claims data only did not yield high performance. We aimed to assess whether supplementing claims data with readily available electronic medical record (EMR) data might result in improvement. Methods We used a subset of the Brigham and Women's Hospital Rheumatoid Arthritis Sequential Study (BRASS) that had linked Medicare claims. The disease activity score in 28 joints with C-reactive protein (DAS28-CRP) was considered the gold standard of measure. Variables in the linked Medicare claims, as well as EMR recorded in the preceding one-year period were used as potential explanatory variables. We constructed three models: "Claims-Only," "Claims + Medications," and "Claims + Medications + Labs (laboratory data from EMR). We selected variables via adaptive LASSO. Model performance was measured with adjusted R2 for continuous DAS28-CRP and C-statistics for binary category classification (high/moderate vs low disease activity/remission). Results We identified 300 patients with laboratory data and linked Medicare claims. The mean age was 68 years and 80% were female. The mean (SD) DAS28-CRP was 3.6 (1.6) and 51% had high or moderate DAS28-CRP. For the continuous estimation, the adjusted R2 was 0.02 for Claims-Only, 0.09 for Claims + Medications, and 0.18 for Claims + Medications + Labs. The C-statistics for discriminating the binary categories were 0.61 for Claims-Only, 0.68 for Claims + Medications, and 0.76 for Claims + Medications + Labs. Conclusion Adding EMR-derived variables to claims-derived variables resulted in modest improvement. Even with EMR variables, we were unable to estimate continuous DAS28-CRP satisfactorily. However, in claims-EMR models, we were able to discriminate between binary categories of disease activity with reasonable accuracy.

Author(s): Shadick, Nancy A; Katz, Patricia; Iannaccone, Christine I; Maica, Gabriela; Coblyn, Jonathan; Weinblatt, Michael E; Cui, Jing | Abstract: ObjectiveLifestyle factors, such as inactivity and obesity, contribute to cognitive decline in the general population, but little is known about how these factors may affect individuals with a chronic inflammatory condition such as rheumatoid arthritis (RA). We studied the clinical and functional risk factors related to a worsening of perceived cognitive function in patients with RA.MethodsWe collected clinical and functional questionnaire data over 10 years in a prospective RA cohort including yearly self-reported memory, concentration, and word-finding difficulties graded from "never" to "often." Generalized estimating equation models examined the role of exercise (defined as those meeting the Department of Health and Human Services physical activity guidelines of 75 minutes of vigorous or 150 minutes of moderate aerobic activity per week), body mass index (BMI), sleep, depression (Mental Health Index-Depression), Disease Activity Score (DAS)28-c-reactive protein (CRP)3 score, disease-modifying antirheumatic drug, and corticosteroid use from the previous year as predictors of cognitive complaints that progressed to "often" compared with the previous year (the first year (T i ) progressed to "often" 1 year later (T i+1)).ResultsOf 1219 RA subjects, 127 (10.4%) described either poor memory, concentration, or word-finding difficulties as affecting them "often" at study entry. RA patients (n = 1092, mean age = 56.5 years, 82% female, 58% college educated) were less likely to report word-finding difficulties, poor memory, and concentration as "often" if they were physically active (p = 0.0001, P = 0.01, P l 0.0001, respectively). Female RA patients developed more concentration complaints compared with males (P = 0.03); patients taking an anti-tumor necrosis factor therapy were less likely to complain of poor memory (P = 0.01). Sleep, BMI, fatigue, depression, DAS28-CRP3, methotrexate, and corticosteroid use were not independently associated with a worsening of any cognitive complaints.ConclusionRA patients who are physically active are less likely to report cognitive difficulties. Our study suggests potential modifiable risk factors for the prevention of cognitive dysfunction in RA.

Objective To investigate the incidence and predictors of dyspnea on exertion among subjects with rheumatoid arthritis (RA). Methods We investigated dyspnea on exertion using a prospective cohort, the Brigham RA Sequential Study (BRASS). Clinically significant dyspnea on exertion was defined as a score of ≥ 3 (unable to ambulate without breathlessness or worse) on the validated Medical Research Council (MRC) scale (range 0‐5). We analyzed subjects with MRC score < 3 at BRASS baseline and at ≥ 1 year of follow‐up. The MRC scale was administered annually. We determined the incidence rate (IR) of dyspnea on exertion. We used Cox regression to estimate the hazard ration (HR) for dyspnea on exertion occurring one year after potential predictors were assessed. Results We analyzed 829 subjects with RA and no clinically significant dyspnea on exertion during a mean follow‐up period of 3.0 years (SD 1.9). At baseline, mean age was 55.7 years (SD 13.6), 82.4% of subjects were female, and median RA duration was 8 years. During follow‐up, 112 subjects (13.5%) developed incident dyspnea on exertion during 2476 person‐years of follow‐up (incidence rate 45.2 per 1000 person‐years). Independent predictors of incident dyspnea on exertion were older age (HR 1.03 per year, 95% CI, 1.01‐1.04), female sex (HR 2.22, 95% CI, 1.14‐4.29), mild dyspnea (HR 2.62, 95% CI, 1.60‐4.28), and worsened Multi‐Dimensional Health Assessment Questionnaire score (HR 2.36 per unit, 95% CI, 1.54‐3.60). Methotrexate use, RA disease activity, and seropositivity were not associated with incident dyspnea on exertion after accounting for other dyspnea risk factors. Conclusion Dyspnea on exertion occurred commonly in patients with RA. Older women with impaired physical function were especially vulnerable to developing dyspnea on exertion.

OBJECTIVE Current validated cardiovascular (CV) risk estimates were developed in populations with relatively stable levels of inflammation, whereas patients with rheumatoid arthritis (RA) routinely experience significant changes in inflammation. This study was undertaken to test whether changes in inflammation affect estimated CV risk as measured using validated population-based risk calculators. METHODS Participants in a prospective RA cohort who experienced a decrease or an increase of ≥10 mg/liter in the C-reactive protein (CRP) level at 2 consecutive time points 1 year apart (CRP decrease group and CRP increase group, respectively) were included in this study. We estimated 10-year CV risk using the following calculators: Framingham Risk Score, 2013 American College of Cardiology/American Heart Association Atherosclerotic Cardiovascular Disease Risk Score, Reynolds Risk Score (RRS), and QRISK2. Of these calculators, only the RRS includes a variable addressing the CRP level. Paired t-tests were performed to compare risk scores at baseline and 1-year follow-up. We calculated the correlations between the changes in risk scores and changes in pro-B-type natriuretic peptide (pro BNP), a surrogate marker of CV risk. RESULTS One hundred eighty RA patients were included in the study (mean age 57.8 years, 84% female, 80% seropositive). Of the calculators studied, only the RRS was sensitive to changes in inflammation; an increase in inflammation was associated with increased estimated CV risk (P < 0.0001), and only the RRS was correlated with changes in proBNP (r = 0.17, P = 0.03). CONCLUSION Our data showed no significant change in CV risk estimated using validated general population CV risk calculators except for the RRS. These findings suggest that CV risk may be modulated by changes in inflammation in RA, which is not typically considered when using existing CV risk calculators.

Objective Patients with rheumatoid arthritis (RA) often ask whether specific foods, popularized as inflammatory or antiinflammatory, can improve or worsen their RA. Patients with RA took a survey on diet and RA symptoms, and the survey data were collected and analyzed. Methods A dietary survey was mailed to 300 subjects in a single-center RA registry at a large academic center. Subjects were asked about their consumption of 20 foods and whether these foods make their RA symptoms better, worse, or unchanged. Semiannual registry data include demographics, medications, comorbidities, and disease activity scores. Fisher's exact test and Wilcoxon's rank sum tests evaluated associations between subject characteristics from the most recent registry assessment and changes in RA symptoms from specific foods. Results Of the 217 subjects (72% response rate), 83% were female; the median RA duration was 17 years (interquartile range 9–27 years), and 58% were taking a biologic disease-modifying antirheumatic drug. Twenty-four percent of subjects reported that foods affect their RA symptoms, with 15% reporting improvement and 19% reporting worsening. Blueberries and spinach were the foods most often reported to improve RA symptoms, while soda with sugar and desserts were those most often reported to worsen RA symptoms. Younger age and noting that sleep, warm room temperature, and vitamin/mineral supplements improve RA were each associated with reporting that foods affect RA symptoms. Medication use, sex, body mass index, smoking, disease duration, disease activity scores, and self-reported RA flares were not associated with reporting that foods affect RA. Conclusion Nearly one-quarter of RA subjects with longstanding disease reported that diet had an effect on their RA symptoms.

Objective Previous cross-sectional studies have shown that rheumatoid arthritis (RA) patients with fibromyalgia (FM) have higher disease activity, greater medical costs, and worse quality of life compared to RA patients without FM. We determined the impact of FM on 2-year changes in the functional status of RA patients in a prospective study. Methods Subjects included participants in the Brigham Rheumatoid Arthritis Sequential Study who were enrolled in a substudy of the effects of pain in RA. Subjects completed questionnaires, including the Multi-Dimensional Health Assessment Questionnaire (MDHAQ) and Polysymptomatic Distress (PSD) scale, semiannually, and underwent physical examination and laboratory tests yearly. Results Of the 156 included RA subjects, 16.7% had FM, while 83.3% did not. In a multivariable linear regression model adjusted for age, sex, race, baseline MDHAQ score, disease duration, rheumatoid factor/cyclic citrullinated peptide antibody seropositivity, disease activity, and psychological distress, RA patients with FM had a 0.14 greater 2-year increase in MDHAQ score than RA patients without FM (P = 0.021). In secondary analyses examining the association between continuous PSD scale score and change in MDHAQ, higher PSD scale scores were significantly associated with greater 2-year increases in MDHAQ score (β coefficient 0.013, P = 0.011). Conclusion Both the presence of FM and increasing number of FM symptoms predicted worsening of functional status among individuals with RA. Among individuals with RA and FM, the magnitude of the difference in changes in MDHAQ was 4- to 7-fold higher than typical changes in MDHAQ score among individuals with established RA.

Objective: To characterize physical activity (PA) participation (meeting ≥150-minutes of moderate intensity or 75-minutes of vigorous (MVPA/week)), examine associations between disease activity and MVPA and identify MVPA correlates in adults with rheumatoid arthritis (RA) over 3 years. Methods: This study included 573 RA patients (94% Caucasian, 83% female, mean age 61 years, mean RA duration 19.5 years) with ≥1 annual registry visit and who completed the PA questionnaire. Baseline and annual measures included: demographics/medical history, self-efficacy for disease management, quality of life, patient/physician global assessment, physical function, and self-reported PA. A logistic repeated measures model using the Generalized Estimation Equation examined the relationship between disease activity and MVPA. Results: Average disease activity (DAS28-CRP3) was 3.1 (SD, 1.4), 36% were physically inactive and 29% met MVPA recommendations. There was a negative borderline association with disease activity (OR=0.89; 95%CI 0.79–1.00). Correlates of meeting MVPA recommendations, adjusting for disease activity, were being Caucasian (OR=2.95; 95%CI 1.29–6.75), older age (age >69 OR=0.58; 95%CI 0.36–0.92) poor mental health (OR=0.63; 95%CI 0.41–0.95), poor physical function (OR=0.59; 95%CI 0.34–1.01), overweight/obese (body mass index >25–30 OR=0.69; 95%CI 0.50–0.95; >30–39.9 OR=0.60; 95%CI 0.41–0.88; ≤40 OR=0.24; 95%CI 0.08–0.74) and patient global assessment (≥10-20) OR=0.57; 95%CI 0.39–0.83). Conclusions: A small proportion met MVPA recommendations despite well-controlled disease. Disease activity was negatively associated with PA over time. PA correlates were linked to lifestyle, mental health and patient perceptions of disease, suggesting PA interventions that address patient perspectives may facilitate RA management. This article is protected by copyright. All rights reserved.

Objective To quantify differences and determine the factors contributing to the difference in patient global assessment of rheumatoid arthritis (RA) disease activity (PtGA) between RA patients with multiple morbidities (RA-MM) and those with RA only. Methods We compared the PtGA between RA-MM patients and those with RA only, followed up in a longitudinal cohort (n = 1,040). In analyses performed on RA-MM patients (n = 575) and those with RA only (matched for swollen joint count, tender joint count, evaluator global assessment, and disease duration), the mean difference in PtGA (ΔPtGA) between the 2 groups was assessed. The contribution of patient characteristics to the explained variation of ΔPtGA in the matched cohort was calculated as semipartial R2 and summarized as the percentage of the total R2 in linear regression models. Results RA-MM patients reported higher (or worse) PtGA, with an increased PtGA associated with more morbidities (P for linear trend

Objective Patient registries have contributed substantially to progress in clinical research in rheumatic diseases. However, not much is known about how to optimize the patient experience in such registries. We assessed patient views, motivations, and potential barriers towards participation in registry research to better understand how registries can be improved to maximize patient engagement. Methods Focus groups were held with 23 patients (mean ± SD age 59 ± 13 years) from the Boston area and led by a bilingual moderator trained in focus group methodology, using a semistructured moderator guide. Three separate focus groups were conducted to thematic saturation: patients with rheumatoid arthritis (RA) who had registry experience, patients with any chronic illness, and Spanish-speaking patients with RA or osteoarthritis. Patients in the latter 2 groups had no prior registry experience. Focus groups were audiotaped and transcribed. Four researchers independently analyzed transcripts using open data coding to identify themes. A normative group process was used to consolidate and refine themes. Results Seven major themes were identified, including personalization/convenience of data collection, trust and confidentiality, camaraderie, learning about yourself and your disease, altruism, material motivators, and capturing mental health and other elements of the lived experience. We observed distinct differences in the discussion content of the Spanish-speaking patients compared to the English-speaking patients. Conclusion This study identified patient attitudes towards registry research among those with and without prior experience in a registry. The results provide insight into strategies for registry design to maximize patient engagement, which can lead to more robust registry data.

Objective To evaluate associations between achieving guideline‐recommended targets of disease activity, defined by the Disease Activity Score in 28 joints using C‐reactive protein level (DAS28‐CRP)

Purpose This study examined the accuracy of claims-based algorithms to identify smoking against self-reported smoking data. Methods Medicare patients enrolled in the Brigham and Women's Hospital Rheumatoid Arthritis Sequential Study were identified. For each patient, self-reported smoking status was extracted from Women's Hospital Rheumatoid Arthritis Sequential Study and the date of this measurement was defined as the index-date. Two algorithms identified smoking in Medicare claims: (i) only using diagnoses and procedure codes and (ii) using anti-smoking prescriptions in addition to diagnoses and procedure codes. Both algorithms were implemented: first, only using 365-days pre-index claims and then using all available pre-index claims. Considering self-reported smoking status as the gold standard, we calculated specificity, sensitivity, positive predictive value, negative predictive value (NPV), and area under the curve (AUC). Results A total of 128 patients were included in this study, of which 48% reported smoking. The algorithm only using diagnosis and procedure codes had the lowest sensitivity (9.8%, 95%CI 2.4%–17.3%), NPV (54.9%, 95%CI 46.1%–63.9%), and AUC (0.55, 95%CI 0.51–0.59) when applied in the period of 365 days pre-index. Incorporating pharmacy claims and using all available pre-index information improved the sensitivity (27.9%, 95%CI 16.6%–39.1%), NPV (60.4%, 95%CI 51.3%–69.5%), and AUC (0.64, 95%CI 0.58–0.70). The specificity and positive predictive value was 100% for all the algorithms tested. Conclusion Claims-based algorithms can identify smokers with limited sensitivity but very high specificity. In the absence of other reliable means, use of a claims-based algorithm to identify smoking could be cautiously considered in observational studies. Copyright © 2016 John Wiley & Sons, Ltd.

Rheumatoid arthritis (RA) is the most common systemic rheumatic disease, affecting approximately 1.5 million adults in the United States (1). Historically, physicians have focused on the inflammatory components of the disease (e.g. synovitis), whereas RA patients have cited pain, fatigue, sleep problems and other quality of life outcomes as their main priorities (2). Both patients and physicians frequently assume that these symptoms are correlated with heightened systemic inflammation. However, many studies indicate significant discordance between inflammation, pain and fatigue among RA patients (3, 4). In a prospective observational cohort of established RA patients experiencing sustained inflammatory disease remission, 12% continued to report clinically significant pain (≥ 4 on a 10-point numeric rating scale) (5). A study including 2,096 RA patients in a clinical setting and 14,607 RA patients from a survey-based cohort reported weak correlations of 0.07–0.11 between fatigue and measures of inflammation (6). Similarly, van Hoogmoed found no association between fatigue and either the erythrocyte sedimentation rate or C-reactive protein (CRP) among 228 RA outpatients in the Netherlands (7). These observations suggest that patient-reported outcomes, such as pain, fatigue and sleep problems, should not automatically be attributed to inflammation in an inflammatory disease population, such as RA. Central, non-inflammatory pain conditions, such as fibromyalgia, tend to be associated with high levels of pain, fatigue and sleep problems (8, 9). Compared to the general population (10, 11), the prevalence of non-inflammatory pain conditions is significantly higher in RA, with 15–25% of RA patients also meeting criteria for fibromyalgia and an additional 7–15% meeting criteria for chronic widespread pain (12, 13). Thus, while it is not debated that RA is an inflammatory condition, many patients with RA also have features characteristic of non-inflammatory centralized pain conditions (e.g., fatigue, sleep disturbances). The objective of this study was to determine whether subgroups of RA patients could be characterized by a latent construct, representing the involvement of central, non-inflammatory pain processes. The latent construct was defined by grouping individuals based on the presence or absence of symptoms indicative of aberrant central nervous system involvement (e.g., fatigue, sleep problems, negative mood, catastrophic attributions and perception of overall illness burden) using cluster analysis. Whereas factor analysis aggregates variables into patterns based on correlations, cluster analysis categorizes individuals into non-overlapping subgroups (14). Cluster analysis is particularly valuable in identifying subgroups which differ in underlying pathogenic mechanisms and clinical outcomes (15). The identification of clinically distinct phenotypes within a heterogeneous population of RA patients would be the first step in understanding the pathogenic mechanisms underlying each symptom cluster and, ultimately, identifying potential targets for treatment. The variables used in this cluster analysis were markers of central pain processes, similar to those included in a previous cluster analysis examining the role of central, non-inflammatory pain in osteoarthritis (16). We hypothesized the presence of at least three subgroups: one group comprised of RA patients with well-controlled disease, minimal fatigue and low psychosocial distress; a second group of RA patients with active inflammatory joint pain and moderate levels of psychosocial distress, and a third group of RA patients with low swollen joint counts and high levels of pain, fatigue and other symptoms characteristic of a chronic, non-inflammatory, pain syndrome. This hypothesis was based on clinical observations, as well as studies in other painful chronic conditions. These studies have reported similar subgroups consisting of: a) participants predominantly affected by peripheral pain generators (e.g., joint inflammation and/or mechanical/structural markers), and b) participants in whom inflammation and/or mechanical factors appear to have minimal impact compared to the influence of central, non-inflammatory pain processes(16, 17). Additional subgroups may also exist. For example, other studies have described a group with high levels of depression but low levels of other symptoms (16, 17). However, given the low levels of depression in our patient population (18), we did not expect to identify this group in this cluster analysis.

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

Rheumatoid arthritis (RA) is a chronic disease that can cause severe joint damage and disability. During the last decades, the number of therapeutic agents and the knowledge about treatment strategies for RA have increased substantially (1). This has left clinicians with more treatment choices, but also in need of tools to identify the right patients to treat aggressively with more effective, but expensive medication with potentially serious adverse events. Risk model matrices have been proposed as clinical tools to identify RA patients at high risk of rapid radiographic progression (RRP) (2–5) or with probable response to disease modifying anti-rheumatic drug (DMARD) treatment (6). In addition, models to predict response to anti-TNF therapy in ankylosing spondylitis (AS) have been published recently (7), highlighting the interest in risk models within rheumatology. Clinicians might apply current risk models in their daily practice, but we have limited knowledge about whether the use of the models should be restricted to patient populations similar to the study populations used for the model development. Risk models are common in cardiology, with the Framingham Risk Scores (8) and the Systematic Coronary Risk Evaluation (SCORE) (9) as examples of risk models for cardiovascular disease. Several publications have discussed the validation and development of such models, focusing on statistical methods to assess model fit and compare the classification abilities of different models(10–14). Statistics have been developed to measure the degree of correct reclassification by a new model compared to a previous model, such as reclassification calibration statistics, net reclassification improvement and integrated discrimination improvement (Table 1). These methods add information to traditional discriminatory abilities, for example the c-statistics. Table 1 An overview of statistical methods to assess risk models (12;14) Risk models developed in clinical trials may not be directly applicable to daily clinical settings, as selected patient groups are included in trials, often with aggressive disease of short duration. In this paper, we assess the performance of three models for prediction of RRP in RA in an observational cohort representing a broad RA population. All three models were developed in clinical trials populations. We apply statistical methods previously used to assess risk models in other specialties.

Objective We previously observed the association of the co-occurrence of the HLA–DRB1 shared epitope (SE) and RANKL single-nucleotide polymorphisms (SNPs) with younger age at the onset of rheumatoid arthritis (RA) in 182 rheumatoid factor (RF)–positive European American patients with early-onset RA. The aim of this study was to fine-map the 48-kb RANKL region in the extended cohort of 210 European American RF-positive patients with early RA, to seek replication of RA-associated SNPs in additional RA cohorts of 501 European Americans and 298 African Americans, and to explore the functional consequences of RA-associated SNPs. Methods SNP genotyping was conducted using pyrosequencing or TaqMan polymerase chain reaction (PCR) assays. Associations of rs7984870 with RANKL expression in plasma, peripheral blood mononuclear cells, and isolated T cells were quantified using enzyme-linked immunosorbent assay and reverse transcription–PCR. Site-directed mutagenesis of rs7984870 within the 2-kb RANKL promoter was performed to drive the luciferase reporter gene in osteoblast and stromal cell lines. Interaction of DNA and protein was determined by electrophoretic mobility shift assay. Results A single promoter SNP, rs7984870, was consistently significantly associated with earlier age at the onset of RA in 3 independent seropositive (RF or anti–cyclic citrullinated peptide antibody) RA cohorts but not in seronegative RA patients. The C risk allele of rs7984870 conferred 2-fold higher plasma RANKL levels in RF-positive patients with RA, significantly elevated RANKL messenger RNA expression in activated normal T cells, and increased promoter activity after stimulation in vitro via differential binding to the transcription factor SOX5. Conclusion The RANKL promoter allele that increased transcription levels upon stimulation might promote interaction between activated T cells and dendritic cells, predisposing to a younger age at the onset of RA in seropositive European American and African American patients.

Rheumatoid arthritis (RA) is the most common autoimmune inflammatory arthritis, affecting approximately 1% of the population. Its etiology is unknown but it is presumed to be an immunologic disease with contributing genetic1–5 and environmental factors, such as cigarette smoking 6–15 and reproductive factors in women.16–18 A growing body of evidence suggests that there are three phases to the development of RA, an asymptomatic period of genetic risk, a preclinical phase in which RA-related autoantibodies can be detected 19, 20, and a clinical phase with acute signs and symptoms of inflammatory arthritis.21 Similar phases of development have been proposed in other autoimmune diseases such as type 1 diabetes and systemic lupus erythematosus.22, 23 In acute and chronic inflammation, cytokines are instrumental in regulating the magnitude and duration of the inflammatory response. Tumor necrosis factor α (TNFα), and interleukin-6 (IL-6) are pleiotropic cytokines produced predominantly by macrophages, that initiate the T cell and synovial proliferation, and are responsible for joint destruction in RA24; and levels are elevated in the serum and the joints during active RA.25–28 Since TNFα degrades rapidly in stored samples29, we studied soluble TNF Receptor 2 (sTNFR2) levels. Soluble TNFR2 expression parallels TNFα levels and is a surrogate marker for inflammation. 25, 26. We aimed to study biomarkers of inflammatory and immune activity, including high sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6) and soluble tumor necrosis factor receptor 2 (sTNFR2) during the pre-clinical phase of RA among three large female cohorts of US nurses, followed prospectively for up to 12 years after blood collection, with extensive epidemiologic data on risk factors for RA. We hypothesized that women who developed RA would have evidence of immune activation prior to the first symptoms of RA, compared to women who did not develop signs and symptoms of RA.

Objective With the growth in patient registries in rheumatic disease research, it is important to validate the collected information. We examined the convergent validity of self-reported medication use for rheumatoid arthritis (RA). Methods In the setting of the Brigham Rheumatoid Arthritis Sequential Study (BRASS), a large registry of patients with RA, we examined the agreement between patients' self-report of current and past RA medication use and information from medical records. For a sample of patients in BRASS, these 2 sources of information were compared using the kappa statistic as well as the percent agreement. Results The 91 patients selected for assessment were typical of a prevalent RA cohort: >80% were women and the mean disease duration was 16 years. The agreement for current medication use was excellent, ranging from 0.71 for sulfasalazine to 0.96 for methotrexate. However, for past medication use agreement was lower, ranging from 0.13 for methotrexate to 0.74 for aurothioglucose. The weighted kappa for cumulative oral glucocorticoid dose was 0.67. Conclusion Self-report of current medication use and cumulative oral glucocorticoid dose appears to have moderate to excellent validity. However, self-report of past medication use may not be valid.

Objective To determine the frequency of weight loss in patients treated with leflunomide for rheumatoid arthritis at an arthritis referral center. Methods We queried 35 rheumatologists at the Robert Breck Brigham Arthritis Center to determine if weight loss had occurred as an adverse event in patients treated with leflunomide between November 1998 and January 2000. Five such patients were identified and their clinical course was reviewed. Results Five of 70 patients who had begun leflunomide therapy had significant weight loss that could not be linked to other identifiable etiologies. The amount of weight loss was substantial in this group of patients, ranging from 19 pounds to 53 pounds. All patients had normal levels of thyroid-stimulating hormone and no other gastrointestinal complaints; evaluation revealed no other cause for the weight loss. Despite the significant weight loss, 4 of the 5 patients continued to take the drug due to its efficacy. Conclusion Significant weight loss is a potential adverse event in patients with rheumatoid arthritis treated with leflunomide. Awareness of this may obviate the need for extensive medical evaluations.

Objective Anti–tumor necrosis factor α (anti-TNF) therapy is a mainstay of treatment in rheumatoid arthritis (RA). The aim of the present study was to test established RA genetic risk factors to determine whether the same alleles also influence the response to anti-TNF therapy. Methods A total of 1,283 RA patients receiving etanercept, infliximab, or adalimumab therapy were studied from among an international collaborative consortium of 9 different RA cohorts. The primary end point compared RA patients with a good treatment response according to the European League Against Rheumatism (EULAR) response criteria (n = 505) with RA patients considered to be nonresponders (n = 316). The secondary end point was the change from baseline in the level of disease activity according to the Disease Activity Score in 28 joints (▵DAS28). Clinical factors such as age, sex, and concomitant medications were tested as possible correlates of treatment response. Thirty-one single-nucleotide polymorphisms (SNPs) associated with the risk of RA were genotyped and tested for any association with treatment response, using univariate and multivariate logistic regression models. Results Of the 31 RA-associated risk alleles, a SNP at the PTPRC (also known as CD45) gene locus (rs10919563) was associated with the primary end point, a EULAR good response versus no response (odds ratio [OR] 0.55, P = 0.0001 in the multivariate model). Similar results were obtained using the secondary end point, the ▵DAS28 (P = 0.0002). There was suggestive evidence of a stronger association in autoantibody-positive patients with RA (OR 0.55, 95% confidence interval [95% CI] 0.39–0.76) as compared with autoantibody-negative patients (OR 0.90, 95% CI 0.41–1.99). Conclusion Statistically significant associations were observed between the response to anti-TNF therapy and an RA risk allele at the PTPRC gene locus. Additional studies will be required to replicate this finding in additional patient collections.