Functional capacity is strongly influenced by disease activity throughout the course of RA. Even in longstanding RA, disease activity proves to be the main determinant of the HAQ score for functional capacity.

ObjectivesTo study whether there is an association between body mass index (BMI) category and survival of various tumour necrosis factor inhibitors (TNFi) in rheumatoid arthritis (RA) patients in a real-life longitudinal international registry.MethodsData from 5230 patients with RA starting treatment with any TNFi were selected from the METEOR registry. Patients were divided into six BMI categories: 3.7% underweight, BMI<18.5 kg/m2; 46% normal weight, BMI 18.5–25 kg/m2; 32% pre-obesity, BMI 25–30 kg/m2; 13% obesity class I, BMI 30–35 kg/m2; 3.4% obesity class II, BMI 35–40 kg/m2; and 1.6% obesity class III, BMI >40 kg/m2. Time on treatment in the different BMI categories was compared for all TNFi combined and for the infliximab, adalimumab and etanercept separately, using Kaplan–Meier curves and Cox regression analyses. Cox regression analyses were adjusted for potential confounders, with follow-up censored at 5000 days.ResultsPatients in obesity class II (HR 1.28, 95% CI 1.06 to 1.54) and III (HR 1.67, 95% CI 1.29 to 2.18) and underweight patients (HR 1.30, 95% CI 1.07 to 1.58) showed statistically significantly shorter TNFi survival than normal weight patients. The effect in underweight patients was strongest for infliximab (HR 1.82, 95% CI 1.20 to 2.76), the effect in overweight patients was strongest for infliximab (category II (HR 1.49, 95% CI 0.98 to 2.26); category III (HR 1.46, 95% CI 0.79 to 2.71)) and etanercept (category II (HR 1.27 95% CI 0.98 to 1.65); category III (HR 1.79, 95% CI 1.25 to 2.55)). No significant effect modification from reported pain was found.ConclusionBoth underweight and overweight patients discontinued TNFi treatment earlier than normal weight patients, without evidence of reported pain as the main determinant. It remains uncertain what determines TNFi survival in individual patients.

Background In 2010 we presented a prevalence of 21% fulfilling the ASAS classification criteria for axial spondyloarthritis (aSpA) in primary care patients with chronic low back pain (CLBP) (CaFaSpA 1 study)1. In addition, a referral model was developed to help general practitioners (GP) to pick up patients at risk for aSpA. If valid, these data might have a considerable impact for GPs, since CLBP is one of the most frequent musculoskeletal complaints in primary care. We therefore replicated the study in different primary care practices to assess whether our initial findings were valid. Objectives First to estimate the prevalence of aSpA in primary care patients with CLBP classified by the ASAS criteria. Secondly to externally validate the CaFaSpA 1 referral model which was develop for GPs to identify CLBP patients at risk for aSpA. Methods We conducted the CaFaSpA 2 study; a stratified, cross-sectional study in primary care patients with CLBP, aged 18-45 years. Patients were identified from GP records by the ICPC code L03 and recruited by two strata of symptom duration. Assessments included inflammatory back pain (IBP) questionnaires (ASAS, Calin and Berlin), a standardized history and physical examination, HLA-B27 and CRP. Conventional radiography and MRI of the sacroiliac joints (SIJ) were scored by one out of two experienced MSD radiologist without having any clinical information. Sacroiliitis was defined by mNY criteria and MRI evaluation followed ASAS recommendations2. Definite aSpA was defined by the ASAS criteria of aSpA2. Descriptive statistics, logistic regression and validation methods in R (version 2.15.2) were used to validate the CaFaSpA 1 referral model. Results 579 patients participated and were stratified in two groups, symptom duration shorter than 5 years (n= 270, 42% male, age 33.8 (sd 7.4)) and longer than 5 years (n=309, 40% male, age 37.6 (sd 6.1). The overall point prevalence was 17.3% (n=100). No difference was seen related to symptom duration: 17.0% (< 5 yrs) vs 17.5%(≥5 yrs). The CaFaSpA 1 referral model consists of three variables, a positive ASAS IBP questionnaire, a positive family history of aSpA and a good response to NSAIDs (AUC 0.74, sensitivity 0.70, specificity 0.65, at the cut of 2.28). The performance of the model declined in CaFaSpA 2 with an AUC of 0.67, se of 0.60 and sp of 0.62. No difference was seen between the two groups of symptom duration. Conclusions In the CaFaSpA 2 validation study the high prevalence of aSpA was confirmed among primary care patients with CLBP. The CAFASPA-1 referral model performed moderately in CAFASPA-2 and analyses for updating with other variables to be truly discriminative in primary care are under construction. References Hoeven van L, Luime J, Han H, Weel AEAM. Striking prevalence of axial spondyloarthritis in primary care patients with chronic low back pain; a cross sectional study. Arthritis and rheumatism 2010;62:2180. Sieper J, Rudwaleit M, Baraliakos X, et al. The Assessment of SpondyloArthritis international Society (ASA...

Background In patients with established RA, radiological progression is preceded by metacarpal bone mineral density (mBMD) loss. Objectives To assess whether in early (rheumatoid) arthritis patients, mBMD loss after 4 months is an independent predictor for radiological progression after 1 year of antirheumatic treatment. Methods mBMD was measured in metacarpals 2-4 by digital X-ray radiogrammetry (DXR) in patients participating in the IMPROVED study, a single blind multicenter study in 479(79%) RA (2010 ACR/EULAR criteria, symptom duration < 2 years) and 122(20%) UA (arthritis >1 joint, at risk for developing RA by rheumatologists estimation but not fulfilling the 2010 criteria) patients. All patients started treatment with 4 months of methotrexate (MTX) and a tapered high dose of prednisone, followed by tapering or adjusting treatment aiming at DAS <1.6. We performed univariable logistic regression with radiologic progression (increase in total Sharp-van der Heijde Score (tSHS) ≥0.5 after 1 year) as dependent variable and mBMD loss after 4 months and other known predictors as covariates. For power reasons, we selected those two univariable predictive variables (p-value ≤0.10) with the lowest p-value for multivariate regression. Results Of 237 patients (43(18%) UA, 192(81%) RA, 2 missing classification) mBMD measurements at baseline and 4 months and radiological progression data after 1 year were available. Median mBMD loss after 4 months (4mo-mBMD loss, mg/cm2 unless indicated otherwise) was 2.3(-1.7 to 6.8) (corresponding to 0.6(-0.4 to 1.7) mg/cm2/month). Seventeen (7%) patients had radiological progression after 1 year and 220(93%) had not. Patients with radiological progression had a median (IQR) 4mo-mBMD loss of 5.5(2.7 to 13.6) compared to 2.0(-2.0 to 6.6) in patients without progression (corresponding to 1.4(0.7 to 3.4) and 0.5(-0.5 to 1.6) mg/cm2/month), (p=0.002). Univariable predictors for progression (OR (95%CI) were age (1.0(1.0-1.1)), fulfilling the 2010 criteria for RA (6.4(0.9-48)), postmenopausal status (6.2(1.4-27)), ESR (1.0(0.999-1.0)), tSHS (1.1(0.996-1.1)), presence of erosions (4.4(2.0-10.0)) and presence of ACPA (3.5(1.3-9.4)), all at baseline, and 4mo-mBMD loss (mg/cm2/months) (1.5(1.2-1.9)). Female gender, RF positivity, symptom duration, baseline swollen and tender joint counts were not predictive. Independent predictors for progression after 1 year were presence of baseline erosions (5.2(1.7-16)) and 4mo-mBMD loss (mg/cm2/month) (1.5(1.1-2.0)). In 203(86%) patients who had no erosions at baseline, 4mo-mBMD loss (mg/cm2/month) was the only independent predictor for progression after 1 year (1.8(1.3-2.7), adjusted for age). Conclusions In early (rheumatoid) arthritis patients, mBMD loss after 4 months of MTX and prednisone is an independent predictor for radiological joint damage progression, despite the fact that radiological progression was only present in 7% of patients after 1 year of a remission steered treatment strategy. In particular in patients who are non-erosive at baselin...

Background:BMI appears to be associated with treatment response on TNFi(nhibitors) in rheumatoid arthritis (RA), but large heterogeneity between studies exists. More extreme BMI categories are rarely studied and it is unclear if differences exist between various TNFi.1Table 1Characteristics of RA patientsFemale, n (%)935 (79.8)Age, years*51.0 ±13.7Current smokers, n (%)256 (23.2)RF Positivity, n (%)404 (55.6)Anti-CCP Positivity, n (%)430 (58.2)X-ray Erosion, n (%)317 (61.9)ESR, mm/h*31.2±21.9CRP, mg/L*17.2±3.9DAS 28-CRP*3.8±1.6VAS global*46.6±28.6HAQ*0.9±0.7First TNFi Etanercept, n (%)525 (38.7) Adalimumab, n (%)379 (27.9) Infliximab, n (%)118 (8.7) Certolizumab, n (%)188 (13.8) Golimumab, n (%)147 (10.9)* mean ±S.DRF, Rheumatoid factor; Anti-CCP, Anti- cyclic citrullinated peptid; ESR, erythrocyte sedimentation rate; CRP, C-reactive protein; DAS28–CRP, Disease Activity Score using 28 joints–CRP; VAS, Visual analog scale; HAQ, Health Assessment QuestionnaireObjectives:To study whether there is an association between BMI category and drug survival in RA patients starting treatment with various TNFi in a real life longitudinal international registry.Methods:Data from 5230 RA patients starting a TNFi were included from the METEOR registry. Timing of follow-up visits was daily practice based. Follow-up was censored at 5000 days (±13.5 years). Patients were divided into 6 BMI categories (WHO definition): underweight BMI <18.5, normal weight BMI 18.5-25, pre-obesity BMI 25-30, obesity class I BMI 30-35, class II BMI 35-40, and class III BMI >40. Missing data were imputed using chained equations. The association between BMI category and time on treatment was investigated using Kaplan-Meier (KM) curves and Cox regression analyses, for time on first TNFi and for the first prescribed course of adalimumab (ADA), etanercept (ETA) and infliximab (IFX) separately. All analyses were adjusted for the potential confounders age, gender, smoking, baseline DAS28, concomitant glucocorticoid use and country. Potential effect modification by reported pain was tested by adding an interaction term between BMI category and baseline pain category (VAS pain 0-25, 25-50, 50-75 and 75-100).Results:Most patients had a normal weight (46%) or pre-obesity (32%). 4% of patients were underweight, 10% had obesity class I, 3% obesity class II and 1% obesity class III. N=2936 patients ever started ETA, n=2069 ADA, n=1390 IFX, n=263 certolizumab and n=84 golimumab. The KM curve in fig 1A shows TNFi survival in patient starting their first TNFi per BMI category. Patients with normal weight and pre-obesity had longest drug survival and patients with obesity class II and especially patients with obesity class III had shortest drug survival. The adjusted Cox regression support these findings, with statistically significantly shorter drug survival for patients with obesity class III [HR (95% CI) 1.67 (1.29; 2.18)] and class II [1.28 (1.06; 1.54)], but also for underweight patients [1.3 (1.07; 1.58)], compared to normal weight patients. KM curves for individual TNFi showed shorter drug survival on ADA for patients with obesity class II and III (fig 1B), on ETA for patients with obesity, especially in class III (fig 1C) and on IFX, for patients with obesity class II and III and underweight patients (fig 1D). After adjustment in Cox regression, statistical significant BMI-drug survival associations remained for patients with pre-obesity starting ADA [HR (95% CI) 0.86 (0.75; 0.99)], for patients starting ETA with obesity class II [HR (95% CI) 1.27 (0.98; 1.65) or class III [1.79 (1.25; 2.55)] and for patients on IFX who were underweight [HR (95% CI) 1.82 (1.20; 2.76)] or in obesity class II [1.49 (0.98; 2.26)]. No effect modification was found for reported pain.Conclusion:Both underweight (as identified in IFX treated patients) and overweight patients (in ADA, ETA and IFX treated patients) discontinued a first TNFi treatment earlier than normal weight patients. Reported pain was not the main determinant. It remains uncertain what determines TNFi survival in individual patients.References:[1] Singh, et al.PloS One2018; 13:e0195123Disclosure of Interests:Sytske Anne Bergstra: None declared, David Vega-Morales: None declared, Elizabeth Murphy: None declared, Marieke de Buck: None declared, Karen Solomon-Escoto: None declared, Thomas Huizinga Grant/research support from: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Consultant of: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Cornelia Allaart: None declared