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Background:Busy rheumatologists may assess disease activity and risk for radiographic progression (RP) in RA with informal, qualitative versions of evaluator and/or patient global assessments (EGA and PGA). RA patient care may be improved by having a convenient, objective disease activity measure that predicts risk for RP more accurately than EGA or PGA.Objectives:To compare the abilities of MBDA score, patient global assessment and evaluator global assessment to assess risk for radiographic progression (RP), and to assess the ability of MBDA score to predict RP among patients with concordant or discordant PGA and EGA.Methods:Patients were pooled from two RCTs of patients with recent onset RA treated with conventional and biologic DMARDs (OPERA and SWEFOT, N=386) and from a registry of patients with predominantly established RA and diverse treatments (BRASS, N=380). Pearson correlations were determined between MBDA scores (adjusted for the effects of age, sex and adiposity) (scale 1-100), PGA and EGA (each on a scale of 1-10) at baseline. PGA and EGA were considered discordant when they differed by >2.5. Univariable logistic regression assessed ability to predict RP (change in TSS >5 over 1 year) for MBDA score, PGA and EGA as continuous variables; and for discordance of PGA and EGA as 2-level (concordant vs. discordant) or 3-level (PGA>EGA, concordant, EGA>PGA) categorical variables. Multivariable regression considered the main effect and interaction terms of the MBDA score, as a continuous variable, paired with each other variable, to test the ability of each pair to assess risk of RP. All models included a random effect on cohort. Odds ratios were reported for every 10-unit increase in MBDA score. Frequency of RP was determined in subgroups with MBDA score low (44) for patient groups based on PGA/EGA concordance or discordance.Results:The 766 patients studied were 76% female, 76% positive for RF and/or anti-CCP Ab, with mean age 55 years, DAS28-CRP 4.7, CRP 22 mg/L, CDAI 26, SJC 9.1, PGA 4.4, EGA 3.4, MBDA score 53. No interaction was seen between MBDA score and type of cohort (early vs established RA). PGA and EGA were discordant in 294 of 766 (38%) patients and were weakly to moderately correlated (r=0.38). Among discordant patients, PGA was >EGA in 227 cases and EGA was >PGA in 67 cases. Correlations between MBDA score and PGA or EGA were r=0.41 and r=0.34, respectively. In univariable analyses, MBDA score was a statistically significant predictor of radiographic progression (OR=1.53, p=6.3x10-8) whereas PGA, EGA, 2-level discordance and 3-level discordance were not (p=0.38, 0.47, 0.74, 0.83, respectively). In multivariable analyses, significant interactions were observed between MBDA score and discordance (2-level, p=0.0029; 3-level, p=0.0087). The interaction analysis demonstrated, in PGA/EGA-concordant patients, low risk of radiographic progression when MBDA score was low and elevated risk when it was high (OR=1.33 [1.1, 1.59]). A relationship between MBDA score and RP risk was also demonstrated, with heightened trend, among discordant patients with PGA >EGA (OR=2.04 [1.53, 2.81]) and EGA >PGA (OR=3.43 [1.37, 13.8]) (Figure 1).Conclusion:MBDA score was a significant predictor of radiographic progression, whereas PGA and EGA were not. MBDA score predicted progression whether PGA and EGA were concordant or discordant. These results suggest that MBDA score detects joint-damaging disease activity more accurately than PGA and EGA and it does so whether or not PGA and EGA are in agreement.Disclosure of Interests:Leonard Calabrese Grant/research support from: AbbVie, Bristol-Myers Squibb, Cresecendo, Genentech, Gilead, GlaxoSmithKline, Horizon, Janssen, Novartis, and Sanofi., Michael E. Weinblatt Shareholder of: Canfite, Inmedix, Scipher, and Vorso, Consultant of: AbbVie, Aclaris, Amgen, Bayer, Bristol-Myers Squibb, Crescendo Bioscience, Corrona, EqRX, GSK,Genosco, Gilead, Lilly, Novartis, Pfizer, Roche, Set Point, Grant/research support from: Bristol-Myers Squibb, Myriad Genetics, Inc.,Eli Lilly and Sanofi, Nancy Shadick Consultant of: BMS, Grant/research support from: Lilly, mallinckrodt, BMS, Amgen and Sanofi, Cecilie Heegaard Brahe: None declared, Mikkel Østergaard Consultant of: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Centocor, GSK, Hospira, Janssen, Merck, Novartis, Orion, Pfizer, Regeneron, Roche, Takeda, and UCB, Grant/research support from: AbbVie, BMS, Celgene, Myriad Genetics, Inc., Janssen, and Merck, Merete L. Hetland Speakers bureau: Orion, Grant/research support from: AbbVie, Biogen, BMS, CelltrionRoche, Myriad Genetics, Inc., Eli Lily, MSD, Pfizer, and UCB, Megan Horton Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Darl Flake Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Eric Sasso Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Autoimmune

Background:Bronchiectasis is a known extra-articular manifestation of rheumatoid arthritis (RA) and can lead to decreased quality of life as well as increased risk for infection and mortality. Understanding the burden of bronchiectasis in RA may lead to a better understanding of pathogenesis and improved management. We performed a systematic review and meta-analysis to determine the prevalence of bronchiectasis in RA.Objectives:We investigated the prevalence of RA-related bronchiectasis (RA-BR) using a systematic review and meta-analysis.Methods:We followed the PRISMA-P 2015 guideline for systematic reviews and registered this analysis (ID#199080) on PROSPERO. We queried PubMed and EMBASE databases using the search strategy “rheumatoid arthritis; AND; bronchiectasis” as of July 31, 2020. The inclusion and exclusion criteria were assessed for study eligibility by two independent abstractors. Exclusion criteria included: (1) non-primary literature (i.e., review articles, editorials); (2) case reports involving less than 5 patients; (3) published in a language other than English; (4) did not relate to both RA and bronchiectasis; and (5) studies not involving humans (e.g., mouse models). After the initial screen, we conducted a full text review to verify that inclusion criteria were met: (1) reported frequency of RA-BR and denominator of all RA patients in the study sample. Data including type of study design, method of RA-BR detection, and RA characteristics were extracted by two independent abstractors. We performed meta-analyses using random effects models to estimate prevalence of RA-BR among RA overall and restricted to retrospective or prospective studies.Results:Out of a total of 208 studies, 37 studies were identified that reported frequency of RA-BR among RA. The included studies had heterogeneous methods to identify RA-BR that were based on either clinical or research chest computed tomography (CT) imaging and had varying methods to adjudicate images. Some studies focused on patients with respiratory symptoms or suspected RA-associated interstitial lung disease (RA-ILD). There were a total of 8,646 patients with RA, and 612 were identified as having RA-BR. The pooled overall prevalence of RA-BR in the random effects meta-analysis was 18.2% (95%CI 13.3-23.7%, Figure 1). Among prospective studies (n=24), the prevalence of RA-BR in the meta-analysis was 20.7% (95% CI 14.7-27.4%). Among retrospective studies (n=13) reporting RA-BR, the prevalence was 14.5% (95% CI 7.2-23.7%). Prevalence was lowest in retrospective studies where RA-BR was identified through clinical care (e.g., two large retrospective studies that investigated 4,000 and 1,129 RA patients reported RA-BR prevalence of 0.6% and 2.7%, respectively). The two largest prospective studies that incorporated a research protocol performing chest CT imaging on all enrolled patients investigated 150 and 332 patients with RA and reported a RA-BR prevalence of 8.0% and 9.6%, respectively. Smaller studies of both study design types generally reported higher prevalence of RA-BR.Figure 1.Pooled prevalence of RA-related bronchiectasis in RA among all studies identified (n=37).Conclusion:The prevalence of RA-BR in this systematic review and meta-analysis was 18.2%, emphasizing that bronchiectasis is a common extra-articular feature of RA. However, some studies may have identified subclinical RA-BR through research imaging or RA-BR may have been secondary to RA-ILD. Future studies should standardize methods to identify RA-BR cases and investigate the natural history and clinical course given the relatively high prevalence that we report.Disclosure of Interests:Lily Martin: None declared, Lauren Prisco: None declared, Weixing Huang: None declared, Gregory McDermott: None declared, Nancy Shadick Consultant of: Consultant < 5K Bristol-Myers Squibb, Grant/research support from: BMS Amgen Lilly, Mallinckrodt, and Sanofi, Tracy Doyle Consultant of: Boehringer Ingelheim (

Background:Rheumatoid arthritis (RA) has been shown a strong genetic association with particularHLA–DRB1alleles containing shared epitope (SE). However, whether SE is clinically useful in treatment choices is insufficiently investigated1and previous studies have presented mixed findings in the role of SE in the response of TNFi therapies2,3.Objectives:To assess the role of SE in response to TNFi treatment in real-world RA patients (pts).Methods:Pts enrolled in a large RA registry, Brigham and Women’s Hospital RA Sequential Study, with known SE and received TNFi therapies were included for the analysis. TNFi pts were identified by the first-time use of the drugs between March 2003 to June 2018. For this analysis, all pts were followed up to 1 year. Summary statistics are reported for demographics, serostatus and disease activity (DA) at baseline and follow-up, stratified by SE status. Given the strong association of SE and anti-citrullinated protein antibody (ACPA), the analysis was further stratified by ACPA status. The effect of SE on change in DA was assessed using linear regression model with age, gender, RA disease duration, baseline DA, smoking status, SE, ACPA and ACPA-SE interaction as covariates.Results:Of the 484 TNFi pts included in the study, 68.8% were SE+. SE+ pts (vs SE-) were more likely to be rheumatoid factor positive, have erosive disease and a higher disease duration, irrespective of ACPA status. No difference in the change of DA was observed by SE. In SE- pts, ACPA+ pts had a greater reduction of DA than ACPA- pts (Table 1). After accounting for baseline differences, there was no significant effect of SE status on the mean change from baseline in any of the 3 DA measures.(Figure 1) The change in DA was not associated with ACPA but was significantly affected by disease duration and baseline DA.Table 1.Disease Activity in TNFi Patients, Stratified by SE and ACPA StatusParameterSE+ (1 & 2 alleles, n=333)SE- (n=151)ACPA+ACPA–OverallACPA+ACPA-Overall(n=264)(n=69)(n=333)(n=90)(n=61)(n=151)Baseline, Mean (SD)DAS28 CRP3.94 (1.69)3.57 (1.61)3.86 (1.67)3.85 (1.49)3.45 (1.65)3.69 (1.57)CDAI23.06 (18.13)18.95 (15.96)22.25 (17.78)21.91 (15.96)17.72 (17.06)20.26 (16.48)SDAI24.08 (18.82)19.96 (16.59)23.27 (18.45)22.58 (16.34)18.55 (17.87)20.99 (17.01)Follow-up, Mean (SD)DAS28 CRP3.42 (1.55)2.69 (1.32)3.27 (1.53)3.19 (1.43)3.11 (1.53)3.16 (1.47)CDAI17.61 (15.53)12.11 (12.65)16.51 (15.14)15.15 (13.35)14.94 (14.73)15.07 (13.84)SDAI18.35 (15.73)12.45 (12.78)17.15 (15.34)15.31 (13.81)15.71 (15.45)15.46 (14.38)Change, Mean (SD)DAS28 CRP-0.48 (1.31)-0.65 (1.53)-0.52 (1.36)-0.52 (1.50)-0.24 (0.93)-0.42 (1.34)CDAI-4.29 (13.16)-4.79 (13.13)-4.39 (13.12)-6.45 (13.56)-2.63 (9.58)-4.99 (12.28)SDAI-4.74 (14.13)-5.07 (13.90)-4.80 (14.05)-6.87 (14.21)-2.97 (10.32)-5.41 (12.98)Figure 1.Linear Regression Model for Change in Disease Activity*Estimates, p-values are shown as data labels on the graphs; The above model is adjusted for age, gender, RA duration, smoking status, SE status, baseline DA, ACPA and ACPA*SE statusConclusion:This real-world study validates the finding from previous studies conducted in clinical settings that SE does not differentiate treatment response for TNFi therapies.References:[1]Saruhan-Direskeneli G, et al.Rheumatology (Oxford) 2007;46(12):1842-44[2]Skapenko A, et al.Clin Exp Rheumatol2019;37(5):783-790[3]Rigby W, et al.Annals of the Rheumatic Diseases2019;78(2):263-264Disclosure of Interests:Joe Zhuo Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Joshua Bryson Shareholder of: I own shares of Bristol-Myers Squibb Company, Employee of: I am a paid employee of Bristol-Myers Squibb Company, Qian Xia Shareholder of: I own shares of Bristol-Myers Squibb Company, Employee of: I am a paid employee of Bristol-Myers Squibb Company, Niyati Sharma Consultant of: I work as a consultant for Bristol-Myers Squibb Company, Chidananda Samal Consultant of: I work as a consultant for Bristol-Myers Squibb Company, Sonie Lama Shareholder of: I own shares of Bristol-Myers Squibb Company., Employee of: I am a paid employee of Bristol-Myers Squibb Company., Michael E. Weinblatt Grant/research support from: BMS, Amgen, Lilly, Crescendo and Sonofi-Regeneron, Consultant of: Horizon Therapeutics, Bristol-Myers Squibb, Amgen, Abbvie, Crescendo, Lilly, Pfizer, Roche, Gilead, Nancy Shadick Grant/research support from: Mallinckrodt, BMS, Lilly, Amgen, Crescendo Biosciences, and Sanofi-Regeneron, Consultant of: BMS

Background:The multi-biomarker disease activity (MBDA) score, adjusted for age, sex and adiposity (MBDAadj), has been shown to be better than several conventional disease activity measures for predicting risk for radiographic progression (RP) in patients with rheumatoid arthritis (RA).1Serologic status and other non-disease activity measures are also predictive of RP risk. Combining them with the MBDAadjshould result in a stronger prognostic test for RP than any one measure alone.Objectives:Develop a multivariate model for predicting risk for RP that includes the adjusted MBDA score and other known predictors of RP.Methods:Four RA cohorts were used, two for training (OPERA and BRASS, n=555) and two for validation (SWEFOT and Leiden, n=397). Each pair of cohorts was heterogeneous in disease duration and treatment history. BMI data were not available for one validation cohort, so a BMI surrogate was modeled using forward selection with the two training cohorts and 3 others (CERTAIN, InFoRM, RACER) (N=1411). An RP risk score was then trained using forward selection in a linear mixed-effects regression, considering disease-related and demographic variables as predictors of change in modified total Sharp score over one year (ΔmTSS), with a random effect on cohort. The RP risk score was validated as a predictor of RP with two cutoffs (ΔmTSS >3 and >5) using logistic mixed-effects regression. Odds ratios (OR) and 95% profile likelihood-based confidence intervals (CI) were calculated from the models and significance was assessed by likelihood ratio tests. Risk curves were generated to show probability of RP as a function of the RP risk score.Results:The BMI surrogate included leptin, sex, age and age2and correlated well with BMI (ρ = 0.76). In training, the most significant independent predictors of RP were MBDAadj(p = 0.00020), seropositivity (p = 9.3 x 10-5), BMI surrogate score (p = 0.013) and use of targeted therapy (p = 0.0026). The final model was: RP risk score = 0.024 x MBDAadj+ 0.093 if seropositive – 0.063 x BMI surrogate score – 0.61 if using a targeted therapy. In validation, the OR (95% CI) of the RP risk score for predicting ΔTSS >3 or >5 were 2.2 (1.6, 3.2) (p = 2.6 × 10-6) and 3.1 (2.0, 5.0) (p = 5.7 × 10-8), respectively (Figure 1). The odds of a patient having RP increases by 50% for each 21-unit or 15-unit increase in MBDAadj, for RP defined as ΔTSS >3 or >5, respectively.Figure 1.Conclusion:A multivariate model containing adjusted MBDA score, seropositivity, a BMI surrogate and use of targeted therapy has been trained and validated as a prognostic test for radiographic progression in RA.References:[1]Curtis, et al.Rheumatology [Oxford].2018;58:874Disclosure of Interests:Thomas Huizinga Grant/research support from: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Consultant of: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Michael E. Weinblatt Grant/research support from: BMS, Amgen, Lilly, Crescendo and Sonofi-Regeneron, Consultant of: Horizon Therapeutics, Bristol-Myers Squibb, Amgen, Abbvie, Crescendo, Lilly, Pfizer, Roche, Gilead, Nancy Shadick Grant/research support from: Mallinckrodt, BMS, Lilly, Amgen, Crescendo Biosciences, and Sanofi-Regeneron, Consultant of: BMS, Cecilie Heegaard Brahe: None declared, Mikkel Ǿstergaard Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Merck, and Novartis, Consultant of: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Merete L. Hetland Grant/research support from: BMS, MSD, AbbVie, Roche, Novartis, Biogen and Pfizer, Consultant of: Eli Lilly, Speakers bureau: Orion Pharma, Biogen, Pfizer, CellTrion, Merck and Samsung Bioepis, Saedis Saevarsdottir Employee of: Part-time at deCODE Genetics/Amgen Inc, working on genetic research unrelated to this project, Megan Horton Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Brent Mabey Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Darl Flake Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Rotem Ben-Shachar Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Eric Sasso Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Alexander Gutin Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Elena Hitraya Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Jerry Lanchbury Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Jeffrey Curtis Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Janssen, Lilly, Myriad, Pfizer, Regeneron, Roche, UCB, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Janssen, Lilly, Myriad, Pfizer, Regeneron, Roche, UCB

Background Prior studies have demonstrated challenges in developing and validating claims-based algorithms that accurately predict RA disease activity.1 2 The ability to adjust for and predict RA disease activity would be a powerful epidemiological tool for studies that lack direct disease activity measures such as the DAS28. Objectives We used machine-learning methods to incorporate claims and electronic medical record (EMR) data to develop models to predict DAS28 (CRP) as a continuous measure, and to distinguish moderate-to-high disease activity from low activity/remission. Methods We identified 300 adults (≥18 years of age) with RA enrolled in a single academic centre cohort with ≥1 year of linked Medicare insurance claims preceding a DAS28 (CRP) measurement between 2006 and 2010. Of these, 95 had Medicare Part D pharmacy data. From claims we included demographics, co-morbidities, joint replacement surgery, physical therapy visits, numbers of RA-related codes, laboratory values and imaging studies, and healthcare utilisation. For those with Part D pharmacy data we included medications (steroids, analgesics, DMARDs) and switches between drugs. From the EMRs we obtained smoking status, BMI, blood pressure, medication use, laboratory values for seropositivity (RF or anti-cyclic citrullinated peptide antibodies), haematocrit, ESR and CRP. We constructed models with claims only, claims with medications and claims with EMR data. We examined these models with DAS28 (CRP) as a continuous measure and as a binary outcome (moderate/high activity vs low activity/remission). We used adaptive least absolute shrinkage and selection operator (LASSO), which avoids model overfitting by penalising large coefficients and selects a subset of variables by shrinking some coefficients to zero. We used adjusted R2 to compare continuous model fit and C-statistics to compare binary models. Results In models that included DAS28 as a continuous measure, using claims alone explained 11% of the DAS28 variability. Adding medications and EMR data to claims improved the adjusted R2 by 6% (table 1). In models that included DAS28 as a binary outcome (moderate/high activity vs low activity/remission), our claims-only model yielded a C-statistic of 0.68, which increased to 0.79 after inclusion of medications and EMR data. Conclusions Incorporating medications, EMR data and laboratory values into a claims-based index did not significantly improve the ability to predict DAS28 scores as a continuous measure. However, models that include claims, medications and EMR data may be used to reasonably distinguish moderate-to-high disease activity from low disease activity/remission. References [1] Sauer BC, et al. Arthritis Res Ther2017;19:86. [2] Desai RJ, et al. Arthritis Res Ther2015;17:83. Disclosure of Interest C. Feldman Grant/research support from: Bristol-Myers Squibb, Pfizer, K. Yoshida Grant/research support from: Tuition support from Harvard T.H. Chan School of Public Health (partially supported by training grants from Pfizer, Takeda, Bayer and PhRMA)., B. Pan: None declared, M. Frits: None declared, N. Shadick Grant/research support from: BRASS registry, Amgen, Bristol-Myers Squibb, and Mallinckrodt, Consultant for: Bristol-Myers Squibb, M. Weinblatt Grant/research support from: Bristol-Myers Squibb, Amgen, Crescendo Bioscience, Sanofi, Consultant for: Bristol-Myers Squibb, Amgen, Crescendo Bioscience, AbbVie, Eli Lilly, Pfizer, Roche, Merck, Samsung, Novartis, S. Connolly Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, E. Alemao Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, D. Solomon Grant/research support from: Bristol-Myers Squibb, Pfizer, Amgen, Genentech

Background High anti-citrullinated protein antibody (ACPA) concentration, beyond ACPA positivity, is indicative of more aggressive radiographic progression in patients (pts) with RA. 1 However, there is limited information on changes in ACPA levels in clinical practice settings, and the association of changes in ACPA with measures of resource use and/or disease activity. Objectives To evaluate the association between change in ACPA levels with hospitalizations/durable medical equipment (DME) use and change in disease activity. Methods Pts enrolled in a tertiary care centre RA registry, established in 2003, were analysed. The registry mostly comprises pts with established RA who were evaluated semi-annually for multiple clinical patient-reported outcomes as well as resource utilization parameters, and annually for disease activity measures such as DAS28 (CRP), SDAI and CDAI. The current analysis is based on pts enrolled in the registry with ACPA values at the time of baseline (BL) and follow-up visits. BL and follow-up ACPA levels were based on well-documented and validated ELISAs from Euro-Diagnostica (distributed by IBL-America, Minneapolis, MN, USA). Annual mean ACPA change from BL over the first year of enrolment in the registry was calculated. Changes ([follow-up – BL]/BL x 100) in ACPA levels were categorized as decrease ( +10%). Use of DME (canes, wheelchairs, walkers and commodes) as well as hospitalizations during 12-month follow-up and annual change in disease activity (DAS28 [CRP], SDAI, CDAI, swollen painful joint counts and pain) were assessed. Multivariate logistic regression analyses for binary outcome variables (DME and hospitalizations) and linear regression for change in disease activity measures were conducted, controlling for BL covariates. Results A total of 840 (65%) pts in the registry had BL and follow-up ACPA values and were included in the analysis. Overall, 34.6% (n=291) of pts had a decrease, 31.7% (n=266) had no change and 33.7% (n=283) had an increase in ACPA levels. There were no significant differences in BL characteristics between the three groups except for disease duration. Pts with RA with an increase in ACPA levels had significantly longer disease duration at BL. In univariate analyses, DME use was 23.4%, 30.1% and 28.6%, and hospitalization rate was 13.4%, 16.5% and 20.1% in pts with a decrease, no change or an increase in ACPA levels, respectively. Unadjusted mean (SD) change from BL in DAS28 (CRP), SDAI and CDAI in pts with reductions in ACPA levels was –0.7 (1.4), –6.1 (15.7) and –5.9 (15.1), and –0.5 (1.4), –5.0 (15.7) and –4.7 (14.6) in pts with an increase in ACPA levels. After controlling for BL covariates, the odds ratio (OR) for DME in patients who had a decrease in ACPA levels (vs increase) was 0.62 (95% CI 0.40, 0.94; p=0.026), and the OR for hospitalization was 0.54 (0.33, 0.86; p=0.010). Similarly, reductions in ACPA levels were associated with greater reductions in disease activity measures (Fig). Conclusions Reductions in ACPA levels were associated with reductions in DME use and hospitalizations as well as reductions in disease activity measures. References Ronnelid J, et al. Ann Rheum Dis 2005;64:1744–9. Disclosure of Interest E. Alemao Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Z. Guo Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, C. Iannaccone: None declared, M. Frits: None declared, N. Shadick Grant/research support from: Bristol-Myers Squibb, UCB, Mallinckrodt, Amgen, Crescendo Biosciences, Consultant for: Bristol-Myers Squibb, M. Weinblatt Grant/research support from: Amgen, Bristol-Myers Squibb, Crescendo, UCB, Dxterity, Consultant for: Amgen, Bristol-Myers Squibb, Crescendo Biosciences, UCB, AbbVie, Lilly, Pfizer, Roche

Background Recent studies have indicated that being overweight or obese could reduce the effect of anti-TNF treatment in patients (pts) with RA. 1,2 Other data show that certain biologic (b)DMARDs, such as abatacept, work independently of BMI. 3,4 Additional data on the role of BMI on treatment outcomes in clinical practice settings is required to inform clinical practice. Objectives To evaluate the impact of BMI on outcomes of disease activity in pts with RA treated with TNF and non-TNF agents (conventional or other bDMARDs). Methods Pts enrolled in a tertiary care centre RA registry, established in 2003, were analysed. The registry mostly comprises pts with established RA who were evaluated semi-annually for multiple clinical patient-reported outcomes and resource utilization parameters, and annually for composite disease activity measures such as DAS28 (CRP), CDAI and SDAI. The current analysis is based on pts enrolled in the RA registry with BMI values at time of enrolment. Pts were classified into groups based on BMI: normal (BMI 2 ), overweight (BMI ≥25 to 2 ) and obese (BMI ≥30 kg/m 2 ). Outcomes evaluated included change from baseline in DAS28 (CRP), CDAI, SDAI and joint counts at 12 months from treatment exposure. Treatments were categorized into TNF and non-TNF, which included conventional DMARDs and other non-TNF biologics. Multivariate linear regression analyses were used to evaluate impact of BMI on treatment outcomes controlling for baseline covariates of age, sex, disease duration, co-morbidities, baseline disease activity and serostatus. Separate models were run for the TNF and non-TNF groups. Results A total of 997 (78%) pts in the registry had baseline BMI values and were included in the analysis. Around 37% (n=371) had TNF exposure and were included in the TNF cohort; the remainder (63%; n=626) were included in the non-TNF cohort. Proportions of pts in the normal, overweight and obese groups for the TNF cohort were 45.5% (n=169), 27.5% (n=102) and 27.0% (n=100), respectively. For the non-TNF cohort, these were 41.7% (n=261), 33.1% (n=207) and 25.2% (n=158), respectively. In both cohorts, pts with normal BMIs were younger vs the overweight and obese BMI groups. However, obese BMI pts had higher disease activity measures at baseline (mean [SD] CDAI: 22.8 [17.8] for TNF and 24.9 [17.3] for non-TNF) vs the normal BMI pts (17.5 [15.9] for TNF and 19.9 [16.7] for non-TNF) and overweight BMI pts (20.9 [16.5] for TNF and 20.5 [15.0] for non-TNF). Adjusted mean change from baseline in disease activity in the TNF cohort was significantly reduced across all disease activity measures for the normal BMI group (p Conclusions Independent of BMI, non-anti-TNF therapy demonstrated similar outcomes in pts with RA. However, obese and overweight pts with RA (vs normal weight) had less improvement in disease activity (as measured by DAS28 [CRP]) with anti-TNF therapy. References Gremese E, et al. Arthritis Care Res 2013;65:94–100. Klaasen R, et al. Arthritis Rheum 2011;63:359–64. Gardette A, et al. Ann Rheum Dis 2015;74:1041. Disclosure of Interest E. Alemao Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Z. Guo Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, C. Iannaccone: None declared, M. Frits: None declared, M. Weinblatt Grant/research support from: Amgen, Bristol-Myers Squibb, Crescendo Biosciences, UCB, DxTerity, Consultant for: Amgen, Bristol-Myers Squibb, Crescendo Biosciences, UCB, AbbVie, Lilly, Pfizer, Roche, N. Shadick Grant/research support from: Bristol-Myers Squibb, UCB, Mallinckrodt, Amgen, Brescendo Biosciences, Consultant for: Bristol-Myers Squibb

Background Potent anti‐inflammatory rheumatoid arthritis (RA) treatments are associated with reduced cardiovascular risk as well as increases in low‐density lipoprotein ( LDL ) cholesterol. This apparent paradox may be explained by favorable changes in other lipid measurements. The objective of this study was to determine the longitudinal association between changes in inflammation with advanced lipoprotein measurements and high‐density lipoprotein ( HDL ) cholesterol efflux capacity. Methods and Results We conducted this study in a longitudinal RA cohort from a large academic center, including subjects with high‐sensitivity C‐reactive protein (hs‐ CRP ) reduction ≥10 mg/L at 2 time points 1 year apart. Subjects receiving statins during the study period or preceding 6 months were excluded. We compared total cholesterol, LDL cholesterol, HDL cholesterol, apolipoprotein B, and apolipoprotein A1 levels and HDL cholesterol efflux capacity at baseline and 1‐year follow‐up by using the paired t test. We also assessed the correlations between reductions in hs‐ CRP with percentage change in lipid parameters. We studied 90 RA subjects (mean age 57 years, 89% female), all of whom were receiving disease‐modifying antirheumatic drugs. We observed a 7.2% increase in LDL cholesterol levels ( P =0.02) and improvement in efflux capacity by 5.7% ( P =0.002) between baseline and follow‐up, with a median hs‐ CRP reduction of 23.5 mg/L. We observed significant correlations between reductions in hs‐ CRP with increases in apolipoprotein A1 ( r =0.27, P =0.01) and HDL cholesterol efflux capacity ( r =0.24, P =0.02). Conclusion Among RA subjects experiencing reductions in hs‐ CRP , we observed increased LDL cholesterol levels and concomitant improvements in HDL cholesterol efflux capacity. These findings provide further insight into lipid modulation and the beneficial effect of reduction in inflammation on lipids in vivo.

Background Autoantibody production, including RF and anti-citrullinated protein antibody (ACPA), may play a role in RA disease pathogenesis. 1 ACPA positivity(+) in patients (pts) with RA is a strong predictor of joint erosions and radiographic progression. 1,2 However, data evaluating the association of seropositive, erosive disease with disease activity and resource use (RU) are limited. Objectives To evaluate the association of ACPA+/RF+ with erosions and disease activity; to compare activity, RU and work productivity (WP) in ACPA+ pts with erosions vs all other RA pts. Methods Pts enrolled in the BRASS Registry were analysed. BRASS comprises mostly pts with established RA who were evaluated annually on clinical measures and semi-annually on clinical pt-reported outcomes and resource utilization parameters. Baseline (BL) visit was the time of enrolment into BRASS. ACPA levels at BL and annual follow-up were measured using a validated ELISA (Inova Diagnostics, San Diego, CA) until its discontinuation in 2011, and the Euro-Diagnostica assay (IBL-America, Minneapolis, MN) thereafter. RF levels at BL and follow-up were measured during the annual rheumatologist visit. RU and WP were measured at 6 months (M) via pt questionnaires. Subgroups at BL were described using Wilcoxon rank-sum test (continuous variables) and Pearson9s chi-square test (categorical variables); multivariate logistic regression models (binary outcome variables) and ordinary least-square regression analysis (continuous outcome variables) were used. Covariates included in the multivariate models were age, sex, race, BMI, RA duration, number of co-morbidities and treatment. Results Among 1309 pts with ACPA data, 82% were female, mean (SD) age was 56.5 (14.1) yrs and DAS28(CRP) was 3.7 (1.6). Pts had mean (SD) TJC of 14.3 (14.0), ACPA levels of 128.3 (151.9) units/mL and RF levels of 127.7 (301.6) units/mL. After controlling for covariates, odds ratio (OR) for erosive disease was 2.72 (95% CI: 1.77, 4.18) for ACPA+ and 1.36 (0.88, 2.08) for RF+ (Fig. 1a). The OR for attaining SDAI LDA ( Conclusions ACPA+ has a stronger association with erosions and disease activity. The presence of ACPA+ and erosions (vs absence) is associated with higher disease activity, lower odds of remission and lower WP, even when treated with standard-of-care bDMARDs. References Aggarwal R, et al. Arthritis Rheum 2009;61:1472–83. Jilani AA and Mackworth-Young CG. Int J Rheumatol 2015;2015:72810. doi: 10.1155/2015/728610. Disclosure of Interest E. Alemao Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Z. Guo Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, C. Iannaccone: None declared, M. Frits: None declared, N. Shadick Grant/research support from: Bristol-Myers Squibb, Crescendo Biosciences, Amgen, UCB, Questcor, M. Weinblatt Grant/research support from: Bristol-Myers Squibb, Crescendo Bioscience, UCB, Amgen, Consultant for: Bristol-Myers Squibb, Crescendo Bioscience, UCB, AbbVie, Roche, Janssen, Pfizer, Lilly, Amgen

Background Adults with Rheumatoid Arthritis (RA) demonstrate low physical activity (PA) levels and excess cardiovascular risk. Most PA studies in RA are cross-sectional and PA interventions are often part of self-management programs of short-term duration (≤1 year). Longitudinal examination of PA in RA may inform PA intervention design. Objectives To identify trends in PA in adults with RA over 3 years and to longitudinally characterize correlates of PA. Methods This 3-yr study included 573 RA registry patients with ≥1 annual visit and complete PA data. Baseline and annual measures were: demographics, medical history/meds, alcohol use, psychosocial support, self-efficacy, disease activity, quality of life, patient/physician global assessment, function, and PA defined as either meeting or not meeting the US Dept Health & Human Services (DHHS) recommendations of 150 min of moderate activity/wk or 90 min vigorous PA/week, at each interval. McNemar χ 2 tests assessed the relationship between disease activity (DAS-CRP3 categories) and PA. A mixed model repeated measures analysis identified factors associated with PA, adjusting for disease activity over time. Results 94% of adults were Caucasian, 83% female with a mean age of 61 yrs (SD=12). Average RA duration was 19.5 yrs (SD=11.8). At baseline, 59.2% had low disease activity, 29.9% moderate and 10.9% highly active disease. 36% of subjects were sedentary and 29% met the PA recommendations. Over 3 years, PA was significantly negatively associated with disease activity (χ 2 , p 53–62 OR=0.62; 95%CI 0.40,0.94; age >62–69 OR=0.64; 95%CI 0.42,0.96; age >69 OR=0.53; 95%CI 0.33,0.83) poor mental health (OR =0.58; 95%CI 0.38,0.87) and higher patient global assessment scores [10–20] OR=0.59; 95%CI 0.41,0.85; [>20–50] OR=0.61; 95%CI 0.39,0.96; [>50] OR=0.51; 95%CI 0.29,0.89) were associated with not meeting the PA threshold. Conclusions A small proportion of adults with RA met PA recommendations, despite well-controlled disease, and the proportion decreased over time. After controlling for disease activity, modifiable correlates of PA were linked to lifestyle, mental health and patient perceptions of disease, suggesting PA interventions target patient perspectives and lifestyles. References del Rincon ID, Williams K, Stern MP, Freeman GL, Escalante A. High incidence of cardiovascular events in a rheumatoid arthritis cohort not explained by traditional cardiac risk factors. Arthritis Rheum. 2001;44(12):2737–45. Veldhuijzen van Zanten JJ, Rouse PC, Hale ED, Ntoumanis N, Metsios GS, Duda JL, et al. Perceived Barriers, Facilitators and Benefits for Regular Physical Activity and Exercise in Patients with Rheumatoid Arthritis: A Review of the Literature. Sports Med. 2015;45(10):1401–12 US Department of Health and Human Services. Physical Activity Guidelines for Americans Committee. Physical Activity Guidelines Advisory Committee report, 2008 Washington, D.C: 2008. Acknowledgement Financial support by NIH grant # R03 AR057133–0 (M Iversen: PI) Disclosure of Interest None declared

Background The advent and use of biologic DMARDs (bDMARDs) have advanced the standard of care in RA, reducing unmet needs and increasing remission rates. Abatacept (ABA), a selective T-cell co-stimulatory modulator, is approved for the management of moderate-to-severe RA. In clinical trial settings, ABA showed efficacy similar to TNFi.1 In clinical practice, TNFi are the predominantly used bDMARDs in the management of RA; however, there are limited data comparing ABA to bDMARDs in clinical practice. Objectives The primary objective was to assess baseline characteristics of RA patients receiving ABA or other bDMARDs in clinical practice. The secondary objective was to evaluate changes from baseline to 12 months in RA disease activity measures (DAS28 [CRP], CDAI and SDAI), as well as patient-reported outcomes (PROs; physical functioning [modified Health Assessment Questionnaire (mHAQ)], quality of life [EQ-5D] and arthritis active/pain today) in RA patients receiving ABA or other bDMARDs in clinical practice. Methods Data from patients enrolled in the Brigham and Women's Hospital Rheumatoid Arthritis Sequential Study (BRASS) registry, established in 2003, were analysed to address the study objectives. The registry comprises mostly patients with established RA who were evaluated annually on clinical measures and semi-annually on multiple clinical PROs and resource utilization parameters. The current analysis is based on patients who had exposure to bDMARDs and had data on at least one disease activity measure available during 12-month follow-up in the registry. Descriptive statistics were used to summarize the baseline differences in demographics, disease activity measures and laboratory measurements between RA-patients prescribed ABA vs other bDMARDs. Mean change from baseline to 12 months in disease activity measures and PROs were assessed using univariate and multivariate regression analyses that controlled for baseline covariates, including baseline ABA vs bDMARD treatments. Results A total of 748 patients were included in the analysis; of these, 102 (13.6%) received ABA and 646 (86.4%) received other bDMARDs; the majority (83%) of ABA patients had prior exposure to bDMARDs. At baseline, ABA patients (vs other bDMARD patients) were older (mean [SD] age: 59.5 [10.7] vs 54.8 [14.2] yrs; p=0.0015), with higher CRP levels (17.09 [41.5] vs 8.1 [19.2] mg/L; p=0.0004), higher DAS28 (CRP) (4.42 [1.58] vs 3.68 [1.65]; p≤0.001), higher mHAQ (0.59 [0.52] vs 0.37 [0.47]; p≤0.001) and lower EQ-5D (0.71 [0.15] vs 0.80 [0.17]; p≤0.001). After controlling for baseline covariates, the mean changes from baseline to 12 months in disease activity measures and PROs were comparable in ABA and other bDMARD patients ([Table][1]). ![Figure][2] Conclusions RA patients prescribed abatacept (vs other bDMARDs) in clinical practice tend to be older, with longer disease duration, higher disease activity scores, higher acute-phase reactant and the majority had prior bDMARD exposure. Despite this, mean changes from baseline to 12 months in disease activity measures and PROs in patients on abatacept and other biologic therapies were comparable. References 1. Schiff M, et al. Ann Rheum Dis 2014;73:86–94. Disclosure of Interest E. Alemao Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, S. Joo Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, M. Frits: None declared, C. Iannaccone: None declared, N. Shadick Grant/research support from: Bristol-Myers Squibb, Crescendo Bioscience, Amgen, UCB, AbbVie, M. Weinblatt Grant/research support from: Bristol-Myers Squibb, Crescendo Bioscience, UCB, Consultant for: Bristol-Myers Squibb, Crescendo Bioscience, UCB, Abbvie, Roche, Janssen, Pfizer, Lilly, Amgen [1]: #F1 [2]: pending:yes

Background Patients (pts) treated for RA have higher incidence rates of infections compared with the general population, which can complicate the clinical management of RA.1 However, there is a paucity of data in the literature on medical resource utilization associated with infection in RA pts in clinical practice. Objectives The primary objective of this analysis was to compare resource use (proportion of pts with durable medical equipment [DME] use, hospitalization and emergency room [ER] visits) in RA pts with vs without infections in clinical practice. The secondary objective was to compare the pt-reported outcomes (PROs) of physical functioning (mHAQ) and quality of life (EQ-5D) in RA pts with vs without infections in clinical practice. Methods Pts enrolled in the Brigham and Women9s Hospital Rheumatoid Arthritis Sequential Study (BRASS) registry, established in 2003, were analysed. BRASS mostly comprises pts with established RA who were evaluated semi-annually for multiple clinical PROs and resource utilization parameters. Infections/opportunistic infections were recorded annually by a rheumatologist. The current analysis is based on the first 5 years of pt follow-up in BRASS. Pts with any infections at baseline or follow-up were categorized as Infection=Yes; those without were categorized as Infection=No. To control for any intra-class correlation of the panel data in BRASS, the generalized estimating equation method was utilized for bivariate outcomes of hospitalizations, ER visits and use of DME; mixed models were used for continuous outcomes of mHAQ and EQ-5D. Variables for the fixed effects included baseline age, sex, disease duration, DAS28 (CRP), BMI, osteoporosis, renal disease, diabetes, infection and corticosteroid use. Results Overall, 1137 (84.9%) BRASS pts were included in the current analysis. Of these, 462 (40.6%) had at least one infection during follow-up. In general, the two groups were comparable, although pts with infections were older (mean [SD] age 57.4 [13.2] yrs vs 55.2 [14.4] yrs for Infection=Yes and No, respectively), had a higher number of comorbidities (mean [SD] 1.3 [1.2] vs 0.9 [0.8]), and lower physical functioning (mean [SD] mHAQ 0.49 [0.51] vs 0.39 [0.43]). After controlling for baseline covariates, RA pts with infections (vs those without) had higher odds for hospitalizations (odds ratio [OR]=2.27; 95% CI 1.802, 2.868), ER visits (OR=2.27; 95% CI 1.802, 2.868) and DME use (OR=1.29; 95% CI 1.078, 1.546). The multivariate models for mHAQ and EQ-5D indicated no significant difference in physical functioning between pts with vs without infections (mean difference in mHAQ=0.0157; p=0.153) and marginal decrease in quality of life for pts with vs without infections (mean difference in EQ-5D= –0.009; p=0.053). Conclusions Both univariate and multivariate results indicate that RA pts with infections tend to have higher healthcare utilization than those without infections. Use of DME was 29% more likely, while hospitalizations and ER visits were twice as likely in pts with infections. Reducing infections in RA patients through implementation of new ACR draft guidelines could reduce healthcare utilization. References Doran MF, Gabriel SE. J Rheumatol 2001;28:1942–3 Disclosure of Interest E. Alemao Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, S. Joo Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, M. Frits: None declared, C. Iannaccone: None declared, N. Shadick Grant/research support from: Bristol-Myers Squibb, Crescendo Biosciences, Amgen UCB, AbbVie, M. Weinblatt Grant/research support from: Bristol-Myers Squibb, Crescendo Bioscience, UCB, Consultant for: Bristol-Myers Squibb, Crescendo Bioscience, UCB, AbbVie, Roche, Janssen, Pfizer, Lilly, Amgen

Background Multiple composite measures of disease activity, such as Disease Activity Score (DAS), Clinical Disease Activity Index (CDAI) and Simplified Disease Activity Index (SDAI), are currently recommended and used to evaluate treatment benefits in RA. However, limited data exist on how key clinical outcomes, such as physical functioning, differ by levels of disease activity in a clinical practice setting. Objectives Evaluate the association between disease activity levels, as defined by DAS28 (C-reactive protein; CRP), CDAI and SDAI, and physical functioning, as measured by the modified Health Assessment Questionnaire (MHAQ), in clinical practice. Methods Data from the Brigham and Women9s Hospital Rheumatoid Arthritis Sequential Study (BRASS) Registry, established in 2003, were used. 1 The current analysis is based on the first 5 years of patient follow-up in BRASS. Disease activity levels of severe disease activity (SDA), moderate disease activity (MDA), low disease activity (LDA) and remission were based on DAS28 (CRP) (SDA: >5.1; MDA: ≤5.1; LDA: ≤3.2), SDAI (SDA: >26; MDA: ≤26; LDA: ≤11; remission: ≤3.3) and CDAI (SDA: >22; MDA: ≤22; LDA: ≤10; remission: ≤2.8). All independent variables including disease activity (SDAI, CDAI, DAS28-CRP) were measured prior to the outcome (MHAQ). To control for intra-class correlation of the panel data in BRASS, mixed models were used to estimate the fixed and random effects on MHAQ. Variables for the fixed effects include baseline demographics, comorbidities, family history of disease, duration of RA disease, joint replacement, disease activity and seropositivity. Results A total of 1297 (82.3% female) BRASS patients are included in the current analysis, with a mean (standard deviation [SD]) age of 56.6 (14.1) years and a mean (SD) duration of symptoms of 15.3 (13) years. At baseline, 71% of patients were seropositive; 10.3% (n=134) and 7% (n=91) were in remission based on CDAI and SDAI, respectively. The majority (95%) of patients were exposed to DMARDs and 45% of these were exposed to biologic DMARDs at baseline. Based on univariate analyses, patients in remission/LDA (vs patients in MDA/SDA) tended to have lower mean MHAQ scores (Figure). After controlling for covariates in mixed models, patients who were in remission (vs LDA) had significantly lower MHAQ scores during follow-up based on SDAI (–0.047; p=0.010) and CDAI (–0.073; p=0.0003) criteria. There was no significant difference in MHAQ between DAS ≤2.6 and ≤3.2 (–0.022; p=0.173). Patients who attained remission/LDA (vs MDA and SDA) had significantly lower MHAQ scores across all composite measures. Conclusions There was no difference in physical functioning between DAS28 (CRP) ≤2.6 vs ≤3.2. However, being in remission (vs LDA), as per CDAI and SDAI, provided additional improvement in the physical function of the patient. Attainment of remission/LDA in clinical practice was associated with improvements in physical functioning. References Iannaccone CK, et al. Arthritis Care Res (Hoboken) 2013;65:1183–9. Disclosure of Interest : E. Alemao Shareholder of: BMS, Employee of: BMS, S. Joo Shareholder of: BMS, Employee of: BMS, H. Kawabata: None declared, M. Al: None declared, P. Allison: None declared, M. Rutten-van Molken: None declared, M. Frits: None declared, C. Iannaccone: None declared, N. Shadick Grant/research support: ABBVIE, AMGEN, Genentech, M. Weinblatt Grant/research support: BMS, Crescendo Bioscience, UCB, Consultant for: BMS, Crescendo Bioscience, UCB, Abbvie, Roche, Janssen DOI 10.1136/annrheumdis-2014-eular.1519

Background Multimorbidity is an important patient-centered concept that needs to be considered when deciding on diagnostic or therapeutic strategies for typical rheumatoid arthritis (RA) patients. In chronic diseases like RA, health related quality of life (HRQol) is the main outcome. An index reflecting multimorbidity (MMI) that is based on HRQoL would be novel, as existing indices are commonly comorbidity indices based on more unidimensional outcomes, such as mortality, costs or function. A MMI would be helpful to better address the disease-related aspect of patients9 overall well-being. Objectives To develop a multimorbidity index (MMI) based on HRQoL. Methods The index was developed in an RA cohort, the Brigham and Women9s Hospital Rheumatoid Arthritis Sequential Study (BRASS). 40 specific morbidities recommended as core by a systematic literature review were identified using ICD-9 codes; the primary outcome was EQ-5D. Two types of MMI were calculated, one by simply enumerating concomitant morbidities (MMIc), and another one by weighing mobid conditions based on their association with HRQoL (using EQ5D) in a multiple linear regression analysis (weights derived from β-coefficients of the regression model) (MMIw). Performance of both MMI was compared to the Charlson comorbidity index (CCI). Results In total 544 out of 876 patients were multimorbid, defined as ≥2 morbid conditions. MMIc ranged from 1-16 (median 2; 25th/75th percentile 1/3); MMIw ranged from 0 – 38 (mean±SD 3.8±6.1). Both indices were similarly associated with EQ-5D, and significantly more strongly than the established CCI (Correlation coefficient r (95CI)%: MMIc -0.21 (-0.15 to -0.28); MMIw -0.32 (-0.26 to -0.38), CCI -0.10 (-0.03 to -0.15); p 2 obtained by linear regression models using EQ-5D as dependent variable and the two Indices as independent variable, adjusted for age and gender was highest for MMI (R 2 : MMIc 0.05, MMIw 0.11, CCI 0.01). When accounting for RA disease activity (using Clinical disease activity index CDAI) R 2 increased (R 2 MMIc 0.18; MMIw 0.22; CCI 0.17), still showing highest values of MMI compared to CCI. The predictive validity of the MMI was robust as demonstrated by the agreement of predicted values of EQ5D after one year with observed values of EQ5D after one year (Spearman r: MMIc 0.34, MMIw 0.37; both p Conclusions In our cohort, the novel MMI showed a better relationship with HRQol than the well known CCI. A simple enuneration of morbid conditions is similarly effective as a HRQoL weighted index, and could therefore be useful to control for the effect of multimorbidity on patient9s overall well being. Disclosure of Interest None declared DOI 10.1136/annrheumdis-2014-eular.3405

Background Identification of factors predictive of rapid radiographic progression (RRP) in RA pts will enable clinicians and policymakers to target appropriate treatment strategies to at-risk pts. Objectives To evaluate baseline (BL) factors associated with RRP in a longitudinal RA cohort study and to develop and validate a prognostic model for RRP in RA pts. Methods Data from the Brigham and Women9s Hospital Rheumatoid Arthritis Sequential Study (BRASS) registry were used to develop the model for RRP. Pts in the BRASS registry underwent physical and laboratory assessments at BL and annually thereafter. Joint X-rays were conducted at BL and Yr 2 and scored by the van der Heijde modified Sharp score (TSS). Pts with both BL and Yr 2 X-ray data were included in the analysis. Annualized change in TSS was calculated and pts having a 5+ unit change were considered rapid progressors. Univariate association of BL factors with RRP was conducted using either a chi-square (χ 2 ) or a Fisher9s exact test. Baseline factors with p 2 . Results Of 1297 pts in the BRASS registry, 644 had BL and Yr 2 TSS. There were no significant differences seen between pts with and without available TSS. Overall, 82% of pts were female; mean (SD) age was 57 (14) yrs and mean symptom duration was 15 yrs. Baseline mean (SD) DAS28 (CRP) was 3.9 (1.6), total swollen tender joints was 16.1 (14.1), TSS was 48.6 (61.1) and 71% of pts were seropositive (RF or ACPA positive). RRP was experienced by 67 (10%) pts in the sample and 302 (46.9%) did not experience radiographic progression. Most (95%) patients were exposed to DMARDs, with 45% of these exposed to biologic DMARDs. BL factors associated with RRP in logistic regression were seropositivity (OR=3.35; 95% CI 1.41, 7.99), duration of RA 2 of 10.47 with 8 DF (p=0.233). The AMPLE validation dataset comprised 579 RA pts with 36 (6.2%) pts experiencing RRP. In this dataset, the model had good external discrimination (ROC=0.73; 95% CI 0.63, 0.82); however, the model overestimated RRP in AMPLE (χ 2 of 164.9 with 8 DF; p 2 of 18.4 with 8 DF; p=0.02). Conclusions RRP in RA can be predicted based on BL seropositivity, body weight, disease duration, DAS28 (CRP) and TSS. Further validation of the model with other datasets is required to confirm the findings. Disclosure of Interest E. Alemao Shareholder of: BMS, Employee of: BMS, S. Joo Shareholder of: BMS, Employee of: BMS, P. Allison: None declared, M. Al: None declared, M. Rutten-van Molken: None declared, G. L9Italien Shareholder of: BMS, Employee of: BMS, C. Iannaccone: None declared, M. Frits: None declared, N. Shadick Grant/research support: AbbVie, AMGEN, BMS, Crescendo Bioscience, Genentech, UCB, M. Weinblatt Grant/research support: BMS, Crescendo Bioscience, UCB, Consultant for: BMS, Crescendo Bioscience, UCB, AbbVie, Roche, Janssen, K. Liao: None declared DOI 10.1136/annrheumdis-2014-eular.2233

To determine the frequency of weight loss in patients treated with leflunomide for rheumatoid arthritis at an arthritis referral center.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.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.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.

Complement-derived peptides capable of activating neutrophils appear in plasma during flares of systemic lupus erythematosus (SLE). One possible consequence of such activation is an increased expression of the surface adhesion promoting heterodimer gp165/95 (the complement receptor CR3). The quantity of gp165/95 was measured by indirect immunofluorescence using a monoclonal antibody of the CD11b group, Mol, directed to the α chain. Eighty-three percent of 26 patients with SLE expressed gp165/95 on their neutrophil surface to a greater extent than normals. The highest levels of surface gp165/95 were found in patients with the most severe disease, who also had the highest levels of the circulating anaphylatoxin C3a (mean = 560 ng/ml versus 147 ng/ml in controls). There was a negative correlation between expression of gp165/95 and absolute neutrophil count. Five individuals followed serially demonstrated an increase in surface gp165/95 during disease flares which returned to normal with clinical improvement. These data support the hypothesis that the neutrophils of patients with active SLE recruit increased numbers of gp165/95 molecules to their surface in response to complement activation; these activated neutrophils bearing increased numbers of adhesion promoting gp165/95 may contribute to endothelial injury in SLE.