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Background The impact of rheumatic and musculoskeletal diseases is significant worldwide. Progress in disease management has put current care models under pressure. Mobile Health solutions may constitute a solution for these changes. However, vulnerable populations groups including people with a migration or ethnic background different from the host country, people with low socio-economic status and people with low (digital) literacy skills seem to be underrepresented in mHealth research and practice. Main body In this editorial, we propose tailored interventions with mobile health applications on three levels including patient-related strategies, healthcare provider-related strategies and healthcare system-related strategies to solve this unmet need for patients from vulnerable populations groups with rheumatic and musculoskeletal diseases. Patient-related mobile health strategies should focus on increasing self-efficacy and enabling peer-education. Gamification could be a solution to motivate patients to use mobile health. On the level of the healthcare provider, we propose strategies including technology-enhanced learning and adaptative communication strategies, to tailor mobile health towards vulnerable populations groups with rheumatic and musculoskeletal diseases. Regarding healthcare system-related strategies, the aim is to increase minority participation in research in a cost-effective manner by remote longitudinal data tracking, using teleconsultation or remote symptom monitoring devices to ensure quality care for all patients with rheumatic and musculoskeletal diseases, even in vulnerable populations groups that are normally hard to reach. Conclusion Vulnerable population groups in rheumatic and musculoskeletal diseases are underrepresented in mobile health research and practice. Evidence is sparce on the scale of the digital divide between patients using or not using mobile health. Interventions that directly attempt to reduce health disparities among vulnerable populations groups are needed to guarantee all patients with rheumatic and musculoskeletal diseases might be engaged in the rheumatology care of the future.

The reliability and clinical usefulness of the different composite disease activity scores and their individual components in Rheumatoid Arthritis (RA) are still debated. This study investigated which measures of disease activity were preferred by rheumatologists. A mixed-method study was performed. First, ten Belgian rheumatologists were invited for individual interviews on their current practice and preferences for measurement of RA disease activity. Results of this qualitative study and evidence from literature served as input for developing a survey. This survey asked rheumatologists to rate preferred standard disease activity score(s), their individual components, ultrasound and related patient-reported outcomes (PROs), by maximum difference scaling. The relative importance score (RIS) for each indicator was calculated using hierarchical Bayes modeling. The qualitative study included 6/10 invited rheumatologists. Composite scores and components were perceived as useful, while PROs were found subjective. Interestingly, ultrasound was used to mediate discrepancies between physician and patient. The survey based on this was sent to 244 Belgian rheumatologists, 83/244 (34%) responded, including 66/83 (80%) complete and 17/83 (20%) incomplete surveys (two missing essential information). Most rheumatologists (75/81, 93%) used a disease activity score and 68/81 (84%) preferred the DAS28-CRP. Swollen joint count obtained the highest mean ± SD RIS (22.54 ± 2.64), followed by DAS28 ESR/CRP (20.61 ± 4.06), ultrasound (16.47 ± 7.97), CRP (13.34 ± 6.11) and physician's global assessment (12.59 ± 7.83). PROs including fatigue, pain, and patient's global assessment, and Health Assessment Questionnaire, obtained the lowest mean RIS (0.34-2.54). Rheumatologists place more faith in self-assessed disease activity components or in laboratory tests. Trust in PROs to evaluate disease activity is low in clinical practice. ispartof: RHEUMATOLOGY INTERNATIONAL vol:42 issue:5 pages:815-823 ispartof: location:Germany status: published

Objective: In patients with rheumatoid arthritis (RA) in sustained remission, tapering of biological disease-modifying anti-rheumatic drugs can be considered. Tapering has already been investigated, but its feasibility remains to be determined. Therefore, we explored the feasibility of tapering etanercept in RA in a setting close to practice. Method: Patients with RA in 28-joint Disease Activity Score (DAS28) remission (>= 6 months) and treated with etanercept 50 mg weekly (>= 1 year) were included in the pragmatic 1 year open-label multicentre randomized controlled TapERA (Tapering Etanercept in Rheumatoid Arthritis) trial. Patients were assigned to continue etanercept weekly or to taper to every other week (EOW). Patients who lost remission [DAS28-C-reactive protein (CRP) >= 2.6] were re-escalated to etanercept weekly. The primary outcome was the proportion of patients maintaining DAS28-CRP remission for 6 months. Results: Sixty-six patients were randomized to etanercept weekly (n = 34) or EOW (n = 32). After 6 months, 26/34 patients (76%) in the weekly and 19/32 (59%) in the EOW group maintained disease control (p = 0.136). In the EOW group, 20/32 patients (63%) remained on their tapered treatment during the trial. Two patients reintroduced weekly etanercept themselves. Ten patients were re-escalated to etanercept weekly by the rheumatologist, after a median (interquartile range) interval of 3.0 (2.0-6.0) months. Among these patients, 7/10 regained remission after re-escalation, four of them at the next study visit. Conclusions: Although non-inferiority could not be demonstrated, tapering of etanercept to EOW appeared feasible in patients in sustained remission.

BackgroundRituximab is an efficacious drug for the treatment of Rheumatoid Arthritis (RA). According to literature, administration of rituximab can be based on a fixed interval or on relapse of disease activity. In some countries, like Belgium, after the first rituximab cycle a flare is required for reimbursement of a subsequent cycle. A better understanding of the perceptions of patients and rheumatologists regarding this retreatment strategy would be informative in view of potential adjustments.ObjectivesThe aim was to investigate patients’ and rheumatologists’ perceptions on the on-flare retreatment strategy of rituximab.MethodsPatients with RA, who were currently or previously treated with rituximab, and rheumatologists were invited to participate in a qualitative study consisting of individual, in depth, face-to-face, semi-structured interviews. Participants were recruited based on purposive sampling to ensure diversity. Interviews were conducted via video or telephone call. Additional participants were interviewed until data saturation was achieved, meaning no new information emerged from the last 3 interviews. Interviews were audiotaped and transcribed verbatim, followed by analysis according to the Qualitative analysis guide of Leuven, which generated themes and subthemes. Patient experts were involved in this research.ResultsIn total, 16 patients with RA and 13 rheumatologists were interviewed. Five overarching themes were generated from the interviews: flare definition, recognition, reaction, balance between benefits and barriers and suggestions (Figure 1). Patients and rheumatologists described how they perceive the on-flare retreatment strategy in daily practice, starting with the FLARE DEFINITION itself. Namely, what patients perceived as a flare and the impact of this flare. The second step was RECOGNITION of the flare. Both rheumatologists and patients indicated that patients are able to recognise a flare. However, the patient’s ability to discriminate between inflammatory and other types of pain was perceived as a difficulty. Moreover, patients indicated that depending on the flare’s intensity, they can cope with it themselves, delaying the need for a rituximab cycle. The next step after correctly recognising a flare, was the REACTION, from both the patient’s and rheumatologist’s side. It was stressed that patients must contact their treating rheumatologists in time. Furthermore, a swift response of the rheumatologists was perceived as important. After confirming eligibility, the shared decision to plan a new rituximab cycle can be made while keeping an eye on the organisation. Remarkably, it seemed that rheumatologists approached the retreatment strategy in different ways, meaning that not everyone adhered to the on-flare principle. Several perceived BENEFITS (e.g. lower safety risk, societal cost savings) and BARRIERS (e.g. disease activity fluctuations, slow working mechanism) were mentioned, making clear that the optimal retreatment strategy should be based on a BALANCE between both. Finally, some SUGGESTIONS (e.g. biomarkers for flare prediction, subcutaneous administration of rituximab) were brought up that could be helpful in applying the optimal retreatment strategy.Figure 1.Conceptual framework of the perceptions of patients and rheumatologists regarding the on-flare retreatment strategy with rituximab. SDM = Shared decision making. (Icons: Iconfinder)ConclusionPatients play an important role in the recognition of flares and their reaction, in shared decision with the rheumatologist, contributes to the effectiveness of the rituximab on-flare retreatment strategy. Rheumatologists handle the on-flare retreatment strategy as pragmatically as possible, resulting in different approaches. Moreover, both benefits and barriers of on-flare retreatment were perceived, making clear that a balance should be found to determine the optimal retreatment strategy.Disclosure of InterestsNone declared

The reliability and clinical usefulness of the different composite disease activity scores and their individual components in Rheumatoid Arthritis (RA) are still debated. This study investigated which measures of disease activity were preferred by rheumatologists. A mixed-method study was performed. First, ten Belgian rheumatologists were invited for individual interviews on their current practice and preferences for measurement of RA disease activity. Results of this qualitative study and evidence from literature served as input for developing a survey. This survey asked rheumatologists to rate preferred standard disease activity score(s), their individual components, ultrasound and related patient-reported outcomes (PROs), by maximum difference scaling. The relative importance score (RIS) for each indicator was calculated using hierarchical Bayes modeling. The qualitative study included 6/10 invited rheumatologists. Composite scores and components were perceived as useful, while PROs were found subjective. Interestingly, ultrasound was used to mediate discrepancies between physician and patient. The survey based on this was sent to 244 Belgian rheumatologists, 83/244 (34%) responded, including 66/83 (80%) complete and 17/83 (20%) incomplete surveys (two missing essential information). Most rheumatologists (75/81, 93%) used a disease activity score and 68/81 (84%) preferred the DAS28-CRP. Swollen joint count obtained the highest mean ± SD RIS (22.54 ± 2.64), followed by DAS28 ESR/CRP (20.61 ± 4.06), ultrasound (16.47 ± 7.97), CRP (13.34 ± 6.11) and physician's global assessment (12.59 ± 7.83). PROs including fatigue, pain, and patient's global assessment, and Health Assessment Questionnaire, obtained the lowest mean RIS (0.34-2.54). Rheumatologists place more faith in self-assessed disease activity components or in laboratory tests. Trust in PROs to evaluate disease activity is low in clinical practice.

BackgroundThe CareRA trial showed that remission induction with methotrexate (MTX) and glucocorticoid (GC) bridging in a treat-to-target setting is cost-effective up to 2 years in early Rheumatoid Arthritis (eRA) patients.ObjectivesTo evaluate the long-term cost-effectiveness of treat-to-target treatments among recently diagnosed (MethodsWe used data from the 2-year RCT CareRA trial and its 3-year observational follow-up, CareRA plus. Patients completing the 2-year visit of CareRA were eligible for participation in CareRA plus, in which patients were evaluated every 6 months till year 5. Healthcare costs considered in this piggyback economic analysis were rheumatology visits, RA-related medication (synthetic and biological DMARDs, GCs, and all recorded analgesics including paracetamol, non-steroidals, tramadol and opioids), hospital admissions, laboratory tests and radiographs occurring during the 5-year trial. All pricing is based on December 2021 rates. Total costs per resource were calculated by multiplying the number of resources by the cost unit price extracted from Belgian national websites. Total costs per patient were obtained by summing costs of all resources. Effectiveness was measured with DAS28-CRP and compared between the originally allocated treatment arms. An incremental cost-effectiveness ratio (ICER) was calculated by dividing the cost difference by the DAS28-CRPResultsOf 322 eligible patients, 252 were included in CareRA plus, of which 203 completed the trial. Rates of disease control (DAS28-CRPConclusionThe combination of MTX with a GC bridging scheme (COBRA Slim) was more cost-effective (less expensive with comparable disease control) than more intensive step-down combination strategies or a conventional step-up approach 5 years after initial treatment. Over 5 years, around one-fifth of all patients, were in need of starting biological treatment and the transition to a bDMARD was later in COBRA Slim. These results point out the possibility of an early “economic” window of opportunity for diminishing costs long-term while still maintaining optimal disease control.Disclosure of InterestsNone declared

BackgroundNon-pharmacological approaches additional to the pharmacological treatment of rheumatoid arthritis (RA) may include meditation, as well as yoga and mindfulness. These mind-body therapies (MBTs) create an interaction between the mind and body to enhance overall health. MBTs are perceived as valuable in RA management, but the extent of this contribution is unclear, as well as patients subgroups who benefit most from these MBTs.ObjectivesTo investigate the effects of meditation, mindfulness, and yoga in patients with RA in a systematic literature review.MethodsA search was performed in 4 databases (PubMed, Embase, Web of Science (core collection, Chinese and Korean collection) and CINAHL). All studies were screened by two independent reviewers, via title/abstract/full text. Studies included any form of meditation, mindfulness and/or yoga as an intervention for patients with RA. Animal studies, case reports, non-English articles, qualitative studies, conference abstracts and articles without full text access were excluded. Each study was assessed for quality.ResultsOut of the 1,527 records, 23 studies were included after screening (Table 1). There was considerable heterogeneity, both in applied interventions and outcome measurements. All MBTs showed limited beneficial effects on psychosocial outcomes, such as vitality, functioning, and mental health, as well as on disease activity markers. Mindfulness-based interventions mainly reduced the subjective disease activity (e.g., joint tenderness/pain), rather than objective disease activity (e.g., swollen joints/CRP). RA patients with recurrent depression seemed to benefit more from these non-pharmacological therapies than patients without recurrent depression.Table 1.Overview of included studiesAuthor (year)InterventionCountryOutcomeAuthor (year)InterventionCountryOutcomeYogaMindfulnessHaslock (1994)YogaUKFunctionalityPradhan (2007)MBSRUSAQoL, Disease activity, depressionDash (2001)YogaIndiaphysiologicalZautra (2008)MERTUSADisease activity, depression, painBadsha (2009)YogaUAEFunctionality, QoL, Disease activityDavis (2015)MAATUSAdepression, anxiety, pain, fatigueBosch. (2009)YogaUSAFunctionality, physiological, depression, painFogarty (2015)MBSRNew ZealandDisease activity, painEvans (2010)Iyengar YogaUSAFunctionality, QoL, depression, anxiety, painDalili (2019)MBCTIranQoL, depression, anxiety, pain, stressSingh (2011)Yogic package (incl. meditation)IndiaDisease activity, painFogarty (2019)MBSRNew ZealandDisease activity, depression, anxietyTelles (2011)YogaIndiaFunctionality, Disease activityRelaxationEvans (2013)Iyengar YogaUSAFunctionality, QoL, depression, anxiety, pain, fatigue, sleep qualityBagheri-Nesami (2006)Benson RelaxationIranDisease activity, depression, anxiety, pain, fatigueWard (2018)YogaNew ZealandFunctionality, QoL, Disease activity, depression, anxiety, pain, fatigue, sleep qualityBarsky (2010)Relaxation Response (PMR)USAQoL, Disease activity, depression, anxiety, pain, fatigue, sleep qualityGreysen (2019)YogaUSAFunctionality, depression, pain, fatigue, sleep qualityGautam (2020)Yoga-based lifestyleIndiaQoL, Disease activity, physiologicalYazdani (2017)PMRIranQoLGanesan (2020)YogaIndiaDisease activity, physiologicalGautam (2021)YogaIndiaFunctionality, Disease activity, physiologicalPuksic (2021)YogaCroatiaQoL, depression, anxiety, pain, fatigue, stressMBCT = Mindfulness-Based Cognitive Therapy; PMR = Progressive muscle relaxation; MBSR = Mindfulness-based stress reduction, MERT = mindfulness-based emotion regulation therapeutic program, MAAT = mindfulness-based emotion regulation therapeutic program QoL= quality of lifeConclusionThis systematic literature review found that MBTs have added value in RA management, especially for patients with depressive symptoms. These non-pharmacological approaches as an addition to treatment can be a way to diminish polypharmacy in specific RA patient populations.Disclosure of InterestsNone declared

BackgroundFatigue is a common and impactful symptom of rheumatoid arthritis (RA). Given its heterogeneity and unpredictable nature, studies on contributing factors of RA-related fatigue should include multidimensional measures of fatigue and assess these longitudinally with multivariate methods, starting early in the disease.ObjectivesWe aimed to explore the longitudinal course of fatigue and its predictors among patients with early RA starting DMARD therapy.MethodsData came from the 2-year treat-to-target trial Care in early RA (CareRA) and its 3-year extension. Fatigue was measured based on visual analog scale (VAS), Multidimensional Fatigue Inventory (MFI), and Short-Form 36 (SF-36). Longitudinal fatigue trajectories were identified with multivariable growth mixture modeling. Baseline and early predictors of trajectory membership, including treatment response, were studied with multinomial logistic regression adjusted for age, gender, and treatment type. Patient global assessment (PGA), pain (VAS), and disability (HAQ) were studied in separate models because of collinearity (Spearman r > 0.60). For all models, posterior probabilities of trajectory assignment were included in the regression as weights to account for classification uncertainty. Treatment response was defined, based on whether remission (DAS28-CRP < 2.6) was achieved by week 16 and sustained until year 2, as either early persistent response, secondary failure, or delayed response.ResultsIn total, 356 and 244 patients were included in the 2-year and 5-year analyses, respectively. Mean (SD) fatigue (VAS) at inclusion was 48/100 (24). Four fatigue trajectories were identified: Rapid, Gradual, and Transient Improvement, and Early Deterioration, consisting of 10%, 14%, 56%, and 20% of patients, respectively (Figure 1). Higher PGA, pain and HAQ at baseline were associated with increased probability of Rapid Improvement compared to Transient Improvement or Early Deterioration (Table 2). Secondary treatment failure and delayed treatment response strongly increased the probability of less positive fatigue trajectories when compared to early persistent response.Figure 1.Latent trajectories of fatigue evolution over the first 2 years in CareRA (n = 356).ConclusionThe longitudinal course of fatigue in early RA is dynamic but highly refractory, with less than 25% of patients making lasting improvements and 20% even experiencing worsening fatigue despite intensive DMARD therapy. Remarkably, a higher perceived disease impact at baseline was associated with an increased probability of fatigue improvement, possibly reflecting the fluctuating nature of this complex symptom. However, early inflammatory disease control appears to be the most important contributor to improved long-term fatigue outcomes, illustrating the far-reaching impact of the therapeutic window of opportunity in early RA.References/Table 1.Predictors of fatigue trajectory membershipGradual improvementTransient improvementEarly deteriorationOR (95% CI)pOR (95% CI)pOR (95% CI)pFatigue (0-100)1.01 (0.99; 1.04)0.320.99 (0.97; 1.01)0.160.98 (0.96; 1.00)0.07PGA (0-100)0.98 (0.95; 1.01)0.110.96 (0.94; 0.99)0.0030.95 (0.92; 0.98)Tender joints (0-28)1.00 (0.91; 1.13)0.821.00 (0.91; 1.09)0.970.99 (0.88; 1.11)0.80Swollen joints (0-28)1.01 (0.90; 1.15)0.820.99 (0.89; 1.10)0.830.93 (0.81; 1.06)0.30CRP (mg/dL)1.00 (0.98; 1.01)0.670.99 (0.98; 1.01)0.361.00 (0.97; 1.02)0.66Pain (0-100)0.99 (0.96; 1.02)0.360.96 (0.94; 0.98)0.0020.95 (0.92; 0.98)HAQ (0-3)1.07 (0.52; 2.20)0.850.55 (0.30; 1.01)0.050.24 (0.11; 0.51)SF-36 Mental Component Score (0-100)1.00 (0.96; 1.04)0.971.02 (0.99; 1.06)0.231.02 (0.98; 1.06)0.34Treatment responseSecondary failure2.22 (0.78; 6.32)0.133.87 (1.57; 9.55)0.0037.88 (2.68; 23.13)Delayed response2.93 (0.70; 12.15)0.146.82 (1.91; 24.44)0.00311.14 (2.33; 53.19)0.003Disclosure of InterestsMichaël Doumen: None declared, Sofia Pazmino: None declared, Delphine Bertrand: None declared, Diederik De Cock: None declared, Johan Joly: None declared, Rene Westhovens Speakers bureau: - Celltrion- Galapagos- Gilead, Consultant of: - Celltrion- Galapagos- Gilead, Patrick Verschueren Speakers bureau: - MSD- Eli Lilly- Galapagos, Consultant of: - Sanofi- Galapagos- Gilead- Pfizer, Grant/research support from: Pfizer Chair Management of Early Rheumatoid Arthritis at KU Leuven Belgium

BackgroundChronic inflammatory arthritides require lifelong follow-up and treatment. Electronic health (eHealth) could be used to remotely monitor disease, possibly improving patient self-management and lowering the burden of in-person consultations. For clinical use, it is important to understand adherence rates of patients with chronic arthritis to eHealth tools.ObjectivesTo systematically review the literature on adherence to eHealth tools for remote monitoring of symptoms or disease activity in chronic arthritis.MethodsWe systematically searched the following databases: Embase, PubMed, Cochrane Central, CINAHL, Web of Science, Clinicaltrials.gov, and the International Clinical Trials Registry Platform (ICTRP). Eligible articles reported adherence rates to an eHealth tool in patients with rheumatoid arthritis (RA), juvenile idiopathic arthritis (JIA), spondyloarthritis (SpA), osteoarthritis (OA), or gout. Included texts were screened individually. Finally, quality assessment was done with the Newcastle-Ottawa scale (NOS) and the PEDro scale.ResultsThe literature search resulted in 7027 articles. After deduplication, 4219 articles were screened for eligibility, and 47 articles were included. We found highest adherence rates in studies applying electronic diaries (81.8%), followed by text messages (79.9%), web-based platforms (74.6%), activity trackers (73%), and smartphone applications (65.5%). Highest adherence was reported in studies on patients with OA (79.7%), followed by patients with gout (73.7%), RA (71.3%), ankylosing SpA (67%), and JIA (59%). Demographic characteristics did not seem to affect patient adherence. Based on frequency of data entering, a time interval of once-daily showed highest adherence rates (72.6%), followed by entering data more than once a day (72.3%) and once a week (67.7%), or longer (59.2%). Adherence declined with longer study duration.ConclusionOur literature review identified declining adherence levels with longer study duration, and highest adherence rates for patients with OA, making use of electronic diaries, and requesting once-a-day completion. OA studies had an overall shorter duration than RA studies, which could be an explanation as to why OA patients showed higher adherence. Lower adherence rates were reported in studies in juvenile populations, while older age did not seem to affect reported adherence.Figure 1.Linear regression model of adherence based on study duration per disease. X = study duration (days), Y = adherence (%). Y = -0.0332X + 71.84. Light blue = RA, yellow = OA, dark blue = JIA, red = Gout, green = SpA, white = >1 diseaseTable 1.Included studies. Adh = adherence SA = smartphone app, ED = electronic diary, AT = activity tracker, OP = online platform, TM= text message. JIA= Juvenile Idiopathic Arthritis, PsA = Psoriatic Arthritis, SpA = Spondyloarthritis, OA = osteoarthritis, RA = Rheumatoid arthritisStudyDiseaseEHealthAdh (%)StudyDiseaseEHealthAdh (%)StudyDiseaseEHealthAdh (%)Skrepnik, ‘17OAAT/SA91 AT 36 SABeukenhorst, ‘20OAAT/SA75 AT 62 SAMcKenna, ‘18RAAT43Lee, ‘20JIASA51Nowell, ‘20RAAT/SA82 AT 72 SAYu, ‘20OAAT99Serlachius, ‘19GoutSA67Heiberg, ‘07RAED95Zaslavsky, ‘19OAAT/SA85Pers, ‘21RASA67Connelly, ‘11JIAED71Gossec, ‘18RAOP63Heale, ‘18JIAAT/SA19 ATConnelly, ‘10JIAED88Walter, ‘14RAOP61Reade, ‘17RASA77Bromberg, ‘16JIAED66Christodoulou, ‘14OAOP98Bellamy, ‘10OASA100Bromberg, ‘14JIAED66Renskers, ‘20RA/SpAOP68Seppen, ‘20RASA69Franceschelli, ‘19OAED/Tyrell, ‘16SpAOP67Harbottle, ‘18JIAAT/SA17 SABingham, ‘19RAED94Martin, ‘21RAOP69Pouls, ‘20GoutSA94Connelly, ‘17JIAED87Kai, ‘19OAOP52Colls, ‘21RASA79Stinson, ‘08JIAED72Richter, ‘21RAOP98Brayne, ‘21RASA41Wilson, ‘13OAED83Broderick, ‘13OAOP>95Austin, ‘20RASA91Jacquemin, ‘18RA/SpAAT88Zuidema, ‘19RAOP71Crouthamel, ‘18RASA20Elmagboul, ‘20GoutAT61Barber, ‘18RAOP69Nowell, ‘21AS, OA, SpA, RASA55Östlind, ‘21OAAT/SA88 ATChristie, ‘14RA/SpATM98Lee, ‘12RATM73Disclosure of InterestsNone declared

Introduction Drug therapy could alter fertility in patients with rheumatoid arthritis (RA). We aimed to perform a systematic review to evaluate if Disease-modifying antirheumatic drug (DMARD) therapy influences fertility as this is an important point to consider in shared decision making on RA therapy. Methods A search was conducted at 18/10/2019 in EMBASE, PubMed (including MEDLINE) and the Web of Science Core Collection. Our inclusion criteria were studies involving women or men diagnosed with RA, older than 18 years and on DMARD therapy, with as outcome a fertility parameter. Systematic reviews, meta-analyses, case reports, case series and animal studies were excluded. Studies not in English or Dutch or published before 2004 were excluded. Quality appraisal was performed by the CASP systematic review checklist. Results After duplicate removal, 9030 references were identified. After title/abstract screening, 82 articles remained. After full text screening, 4 articles could be retained. No studies were found through backward snowballing. Only studies involving women could be retained. The included studies investigated the effect of methotrexate, certolizumab pegol, etanercept and sulfasalazine on fertility. No detrimental effects of these DMARDs on time-to-pregnancy, anti-Mullerian hormone serum level or presence of a history of infertility, were reported. Conclusion This systematic review underlines the gap in knowledge regarding the effect of DMARDs on fertility in women and especially men with RA. DMARD treatment, contrary to general belief, seemed to have no harmful effect on fertility, possibly because it resulted in better controlled disease activity. More research is needed to improve guidance for patients with RA with a child wish.

Background:Industry, regulators, and the rheumatology community have recognized the need for observational studies to monitor the safety of new antirheumatic agents. Registries provide a unique opportunity to understand the safety of newer therapies, but pharmacovigilance studies require large number of patients to evaluate rare drug-related adverse-events (AEs). Because JAK-inhibitors (JAKi) have only recently been approved for the treatment of rheumatoid arthritis, it makes sense to combine data from several registries in order to obtain a sufficiently large sample size to promote earlier detection of adverse events.Objectives:The purpose of this analysis was to evaluate how AEs are assessed in the various registries in preparation for a collaborative pharmacovigilance analysis, and present preliminary results.Methods:The “JAK-pot” collaboration includes 19 RA registries. The principal investigators of the participating registries were sent a structured questionnaire on AE assessment and 18 (94%) provided complete responses on the AE assessment procedures of their registries. We present simple descriptive statistics of the AE assessment procedures employed by the participating registries.Results:The 19 registries represent 7186 patients initiating a JAKi (Table 1), who are on average 57 years old, with a mean disease duration 11 years, seropositive (83%), female (82%) and with moderate disease activity at treatment initiation.Table 1.Country, registryN° of patients on JAKi includedAustria, BIOREG87Belgium, TARDIS2113Canada, RHUMADATA363Czech Republic, ATTRA197Denmark, DANBIO506Finland, ROB-FIN229Germany, RABBIT620Italy, GISEA244Israel, I-RECORD96Netherlands, METEOR4Norway, NOR-DMARD97Portugal, REUMA.PT44Romania, RRBR252Russia, ARBITER428Slovenia, biorx.si141Spain, BIOBADASER139Switzerland, SCQM738Turkey, TURKBIO404UK, BSRBR484After ineffectiveness, AEs was the second most common reason for JAKi discontinuation (25.5%), with large differences between registries (Figure 1).Of the participating registries, 2 registries do not collect AEs, while 16 (89%) assess incident AEs, by means of a pre-specified extraction form (3 registries), by free text (5 registries), by a combination of both (6 registries) and/or the use of linkage to external electronic records (3registries). AEs are coded using a predefined coding system by 11 registries (MeDRA (8), other (3)), but nearly all are recording the severity of the AE (15, 94%), AE related-death (15, 94%), or AE-related hospitalisation (15, 94%). AEs of special interest, such as serious infections (15, 94%), thromboembolic events (15, 94%), or shingles (9, 56%), are recorded by most registries. Incident AEs are linked by the treating physician to specific therapies in 11 registries (69%), while the other 5 registries extrapolate potential causal associations based on therapy start and stop dates. A pre-specified adjudication process for AEs is made only by 5 registries (31%).Conclusion:Substantial heterogeneity exists among registries regarding AE assessment within the JAK-pot collaboration. These differences must be taken into account when analysing the safety of JAKi across different countries in collaborative studies. For comparative analyses, stratified analyses by country are required to account for differential AE assessment and varying degrees of potential under-reporting.Disclosure of Interests:Kim Lauper: None declared, Denis Mongin: None declared, Sytske Anne Bergstra: None declared, Denis Choquette: None declared, Catalin Codreanu: None declared, Diederik De Cock: None declared, Lene Dreyer: None declared, Ori Elkayam: None declared, Kimme Hyrich: None declared, Florenzo Iannone: None declared, Nevsun Inanc: None declared, Eirik kristianslund: None declared, Tore K. Kvien: None declared, Burkhard Leeb: None declared, Galina Lukina: None declared, Dan Nordström: None declared, Karel Pavelka: None declared, Manuel Pombo-Suarez: None declared, Ziga Rotar: None declared, Maria Jose Santos: None declared, Anja Strangfeld: None declared, Delphine Courvoisier: None declared, Axel Finckh Speakers bureau: Eli-Lilly, Pfizer, Consultant of: Eli-Lilly, Pfizer, Grant/research support from: BMS, Pfizer.

A survey was conducted to provide a state of the art of online banking authentication and communications security implementations. Between global regions the applied (single or multifactor) authentication schemes differ greatly, as well as the security of SSL/TLS implementations. Three phases for online banking development are identified. It is predicted that mobile banking will enter a third phase, characterized by the use of standard web technologies to develop mobile banking applications for different platforms. This has the potential to make mobile banking a target for attacks in a similar manner that home banking currently is.

Background:The treat-to-target Care in Early Rheumatoid Arthritis (CareRA) trial demonstrated that remission induction with csDMARD combinations and step-down glucocorticoids (GCs) was not superior over methotrexate (MTX) monotherapy with step-down GCs (Cobra Slim) in RA patients with a high-risk profile (1). Moreover, Cobra Slim showed benefit over a tight step-up with MTX in monotherapy (TSU) in RA patients with a low-risk profile.Objectives:To compare the long term outcomes up to 5 years of different initial intensive treatment strategies in participants of the CareRA-plus study.Methods:In the CareRA trial, patients with DMARD naïve early RA were stratified in a high- or low-risk group based upon the presence of serummarkers, disease activity and erosive status. High-risk patients were randomised to Cobra Classic (MTX+sulphasalazine with highly dosed GC remission induction scheme), Cobra Avant-Garde (MTX+leflunomide with moderately dosed GC scheme) or Cobra Slim. Low-risk patients were randomised to Cobra Slim or TSU. Patients completing this trial were eligible for the CareRA-plus observational study. Here, patients were evaluated 6-monthly over 3 years. Therapy adaptation was left to the treating physician. Efficacy was assessed by DAS28-CRP and HAQ and compared between the originally allocated treatment arms. The 5-year evolution from CareRA baseline of DAS28-CRP and HAQ was assessed via linear mixed models. All adverse events (AEs), considered to be clinically relevant by investigators, and DMARD/GCs therapy were registered.Results:Of 322 eligible patients, 252 (78%) were included in CareRA-plus, of which 203 (81%) completed the study. Characteristics and outcomes at the CareRA closing visit (year 2) did not differ between patients entering CareRA-plus or not. DAS28-CRP3 months).Conclusion:All intensive treatment strategies resulted in excellent long-term clinical outcomes. Initial Cobra Slim therapy showed comparable 5-year effectiveness as Cobra Classic and Avant-Garde in high-risk early RA patients and better efficacy and safety than conservative step up treatment in low-risk patients.Figure 1.Mean disease activity by DAS28-CRP or mean functionality by HAQ index scores for high-risk or low-risk patients.References:[1]Stouten, V. et al. Effectiveness of different combinations of DMARDs and glucocorticoid bridging in early rheumatoid arthritis: two-year results of CareRA. Rheumatology (Oxford). (2019)doi:10.1093/rheumatology/kez213.Disclosure of Interests: :Veerle Stouten: None declared, Rene Westhovens Grant/research support from: Celltrion Inc, Galapagos, Gilead, Consultant of: Celltrion Inc, Galapagos, Gilead, Speakers bureau: Celltrion Inc, Galapagos, Gilead, Diederik De Cock: None declared, Sofia Pazmino: None declared, Johan Joly: None declared, Delphine Bertrand: None declared, Kristien Van der Elst: None declared, Patrick Verschueren Grant/research support from: Pfizer unrestricted chair of early RA research, Speakers bureau: various companies

Background:In many countries, JAK-inhibitors (JAKi) have only recently been approved as treatment for patients with rheumatoid arthritis (RA).Objectives:To evaluate the effectiveness of JAKi compared to bDMARDs in RA patients in the real-world population in an international collaboration of registers (the “JAK-pot” collaboration).Methods:Patients initiating either JAKi, TNFi, IL-6i or abatacept (ABA) during a time period when JAKi were available in each country (19 registers, Table) were included. We compared the effectiveness of JAKi and bDMARDs in terms of retention using crude and adjusted survival analysis. Missing covariates were imputed using multiple imputation.Results:Among 25521 included patients, 6063 initiated a JAKi, 13879 a TNFi, 2348 ABA, and 3231 an IL-6i. Patients were on average 55 years old, with a mean disease duration 10 years, mostly seropositive (67%), female (77%) and with moderate disease activity at treatment initiation. The main reason of stopping treatment was ineffectiveness (49%), followed by adverse events (21%). Patients on JAKi were treated more often as monotherapy, had higher CRP and disease activity at baseline and had experienced more previous ts/bDMARDs. Crude median retention was 1.4 (95% CI 1.2-1.5) years for JAKi, 1.6 (1.6-1.7) for TNFi, 1.5 (1.3-1.7) for IL6i and 1.1 (1.0-1.3) for ABA. After adjustment, the hazard ratio (HR) for discontinuation tended to be lower for JAKi (HR 0.86 (0.65-1.13)) compared to TNFi, but comparable for ABA (1.02 (0.94-1.10)) and IL6i (0.99 (0.88-1.10)) (Figure 1). HRs differed notably between countries (Figure 2).Table 1.RegistersCountry, registerNJAKi, n (%)Austria, BIOREG*Belgium, TARDIS62882113 (33.6)Canada, RHUMADATA528114 (21.6)Czech Republic, ATTRA374253 (67.6)Denmark, DANBIO4721506 (10.7)Finland, ROB-FIN807234 (29.0)Germany, RABBIT*Italy, GISEA757250 (33.0)Israel, I-RECORD40094 (23.5)Netherlands, METEOR16424 (0.2)Norway, NOR-DMARD50799 (19.5)Portugal, REUMA.PT79744 (5.5)Romania, RRBR593328 (55.3)Russia, ARBITER526483 (91.8)Slovenia, BIORX.SI583146 (25.0)Spain, BIOBADASER781139 (17.8)Switzerland, SCQM2956796 (26.9)Turkey, TURKBIO2150397 (18.5)UK, BSRBR111163 (5.7)*Registers planning to participate in future studies but not included yetConclusion:The adjusted overall drug retention of JAKi tended to be higher than for TNFi, with large variation between countries. Other measures of effectiveness, such as the evaluation of CDAI remission and low disease activity are planned to shape a more comprehensive picture of JAKi effectiveness in the real world.Disclosure of Interests:Kim Lauper: None declared, Denis Mongin: None declared, Sytske Anne Bergstra: None declared, Denis Choquette Grant/research support from: Rhumadata is supported by grants from Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Consultant of: Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Speakers bureau: Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Catalin Codreanu Consultant of: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Speakers bureau: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Diederik De Cock: None declared, Lene Dreyer: None declared, Ori Elkayam Speakers bureau: AbbVie, BMS, Pfizer, Roche, Sanofi-Aventis, Novartis, Jansen, Kimme Hyrich Grant/research support from: Pfizer, UCB, BMS, Speakers bureau: Abbvie, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Nevsun Inanc: None declared, Eirik kristianslund: None declared, Tore K. Kvien Grant/research support from: Received grants from Abbvie, Hospira/Pfizer, MSD and Roche (not relevant for this abstract)., Consultant of: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Paid instructor for: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Speakers bureau: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Burkhard Leeb Grant/research support from: chairman of BioReg, Consultant of: AbbVie, Pfizer, Roche, Lilly, Grünenthal, Gebro,, Paid instructor for: Lilly, Biogen, Speakers bureau: Biogen, Lilly, Pfizer, Grünenthal, Astropharma,, Galina Lukina Speakers bureau: Novartis, Pfizer, UCB, Abbvie, Biocad, MSD, Roche, Dan Nordström Consultant of: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Speakers bureau: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Karel Pavelka Consultant of: Abbvie, MSD, BMS, Egis, Roche, UCB, Medac, Pfizer, Biogen, Speakers bureau: Abbvie, MSD, BMS, Egis, Roche, UCB, Medac, Pfizer, Biogen, Manuel Pombo-Suarez Consultant of: Janssen, Lilly, MSD and Sanofi., Speakers bureau: Janssen, Lilly, MSD and Sanofi., Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Maria Jose Santos Speakers bureau: Novartis and Pfizer, Anja Strangfeld Speakers bureau: AbbVie, BMS, Pfizer, Roche, Sanofi-Aventis, Delphine Courvoisier: None declared, Axel Finckh Grant/research support from: Pfizer: Unrestricted research grant, Eli-Lilly: Unrestricted research grant, Consultant of: Sanofi, AB2BIO, Abbvie, Pfizer, MSD, Speakers bureau: Sanofi, Pfizer, Roche, Thermo Fisher Scientific

Background:Treatment of Rheumatoid Arthritis (RA) has improved significantly based on early treat-to-target (T2T) strategies. Still, decreased health related quality of life (QoL), restricted ability to work and other unmet needs are reported by RA patients even in the absence of disease activity. We previously identified 3 factors representing the broader impact of RA using exploratory factor analysis: a patient-reported factor (patients global health, pain, fatigue and HAQ), a clinical factor (physician’s global health, tender and swollen joint count), and a laboratory factor (ESR and CRP)1.Objectives:To test whether the discordance between patient-reported (PRF) and clinical(CF)/laboratory(LF) measures can predict QoL, or has a mediating effect in predicting future disease burden based on disease activity (DAS28CRP).Methods:This is a post-hoc analysis of the 2-year CareRA trial. PRF, CF and LF scores were calculated as weighted (by factor loading) sum of their components at week 16, 52 and 104 after treatment initiation. A discordance score (DS) between PRF and the mean of the other two scores was also computed.Mediation analyses were fitted to test the hypothesis (Figure 1) that DS could be a mediator for predicting PRF, CF and LF at a future time point (week 16, 52 and 104) using DAS28CRP at a previous time point (baseline and week 16). Confidence intervals were estimated via 10 000 bootstraps. Finally, a linear regression was fitted for DS to predict future QoL (RAQoL questionnaire; range 0-30; higher values indicating worse QoL).Results:Patients with early RA (n=379) were included with a mean (SD) age of 53.9 (13.0), 77% seropositive and 69% women.The DS was shown to be mediating the effect of DAS28CRP on any future PRF (Table1). On the other hand, there was no mediation effect of the DS in the prediction of the CF and an inconsistent mediation effect when predicting the LF.Moreover, the DS at week 16 significantly predicted (p2 of 0.30 (CI 0.22-0.38). Similarly, it predicted RAQoL (p2 of 0.32 (CI 0.24-0.40).Table 1.Results of mediation analyses for prediction of future burden based on previous DAS28CRP and mediated by discordance.TimepointPredictor variablesDirect Effect95% CIsR2Mediation effect Patient-reported factorW16DAS28CRP at BL-0.0091-0.0240, 0.00580.1450PresentDS at BL0.0246*0.0169, 0.03310.1784W52DAS28CRP at W160.0215*0.0010, 0.04190.3394PartialDS at W160.0580*0.0442, 0.07390.2749W104DAS28CRP at W160.0101-0.0102, 0.03050.2798PresentDS at W160.0528*0.0396, 0.06860.2749Clinical factorW16DAS28CRP at BL0.0153*0.0074, 0.02320.0599AbsentDS at BL0.0019-0.0010, 0.00480.1784W52DAS28CRP at W160.0365*0.0267, 0.04630.1944AbsentDS at W160.0034-0.0031, 0.00950.2749W104DAS28CRP at W160.0115*0.0024, 0.02070.0409AbsentDS at W160.0033-0.0019, 0.00890.2749Laboratory factorW16DAS28CRP at BL0.0063*0.0015, 0.01110.0634PartialDS at BL0.0030*0.0012, 0.00500.1784W52DAS28CRP at W160.0003-0.0063, 0.00680.0305PresentDS at W160.0051*0.0012, 0.00960.2749W104DAS28CRP at W16-0.0007-0.0079, 0.00640.0014AbsentDS at W160.0013-0.0019, 0.00460.2749W: week BL: baseline DS: discordance scoreDAS28CRP: disease activity score in 28 joints with C-reactive protein*pConclusion:Early discordance between patient-reported and biological/clinical factors mediates the effect of disease activity on future patient-reported outcomes, but also predicts QoL. Paying attention to this early discordance might provide opportunities to prevent patient’s unmet needs by additional non-pharmacological interventions, hence broadening the scope of T2T.References:[1]Pazmino S, et al. Does Including Pain, Fatigue, and Physical Function When Assessing Patients with Early Rheumatoid Arthritis Provide a Comprehensive Picture of Disease Burden? J Rheumatol. 2020 Nov 15:jrheum.200758. doi: 10.3899/jrheum.200758. Ahead of print.Disclosure of Interests:None declared

Background:Rheumatic and musculoskeletal diseases (RMDs) diminish psychosocial well-being. Social support (SS) is considered to improve this psychosocial wellbeing. Therefore, SS is an important construct to measure in RMDs.Objectives:To systematically review and summarize the psychometric properties of SS instruments developed or validated in RMDs.Methods:A comprehensive search in Medline, Embase, PsycINFO, CINAHL and Epistemonikos was performed from inception to June 8, 2020, with the aid of an experienced librarian (LF). Two researchers (DDC and DB) independently screened articles on title+abstract and next on full text. Reference lists of included studies were reviewed for additional references. Articles were included if covering psychometric properties (detailed in the Table 1) of SS instruments used in RMDs. Studies on questionnaires lacking an English version, unpublished material, case reports, editorials, letters, or reviews were excluded. Risk of bias of studies and instruments was assessed via the COSMIN checklist.Table 1.psychometric properties per social support instrumentInstrumentFace validityContent ValidityStructural validityCriterion validityInternal consistencyReliabilityMeasurement errorHypothesis testing for construct validityCross-cultural validity/Measurement invarianceResponsivenessAIMS44444 AIMS2444444 AIMS2-SF444Brief Screening Questions444Dyadic Efficacy Scale4444EIS4444Flanagan QOL4444FS4444444IRGL44444ISSI444LISRES444MEPS444444MWA444OAKHQOL4444444 e-OAKHQOL444 Mini-OAKHQOL444444PFSSADI4444RASP4444SIP44SPQ4444SSQT44444Arthritis Impact Measurement Scales (AIMS); Short Form (SF); Emotional Intimacy Scale (EIS); Quality of Life (QOL); Friendship Scale (FS); Impact on Rheumatic diseases and General health and Lifestyle (IRGL); Interview Schedule for Social Interactions (ISSI); Life Stressors and Social Resources Inventory (LISRES); Medical Issues, Exercise, Pain, and Social Support (MEPS); Modified Work APGAR (MWA); Osteoarthritis Knee and Hip Quality of Life (OAKHQOL); preferences for formal social support of autonomy and dependence in pain inventory (PFFSADI); Responses and Attitudes to Support during Pain questionnaire (RASP); Sickness Impact Profile (SIP); Social support and Pain Questionnaire (SPQ); Social Support Questionnaire for Transactions (SSQT).Results:From 4986 articles captured, 30 met the predefined inclusion criteria. These articles included 21 SS instruments used in 8 RMDs, mainly rheumatoid arthritis and osteoarthritis.Table 1 shows the psychometric properties per instrument. Construct validity, structural validity, and internal consistency were assessed for most instruments, while measurement invariance, measurement error, criterion validity and responsiveness in ≤3 instruments each. Development and content validity of the instruments gave consistently high risk of bias by the COSMIN checklist.The most widely validated instruments were the Arthritis Impact Measurement Scales (AIMS) and the Osteoarthritis Knee and Hip Quality of Life (OAKHQOL), with their respective derived instruments (AIMS2, AIMS2-SF, mini-OAKHQOL and e-OAKHQOL). For the AIMS SS scale, internal consistency ranged between 0.33-0.69 (Cronbach’s α) and test-retest reliability was estimated 0.92 (Guttman reproducibility coefficient). For the OAKHQOL SS scale, internal consistency ranged between 0.78-0.81 (Cronbach’s α) and test-retest reliability ranged between 0.5-0.85 (ICC). Responsiveness was only investigated in AIMS and the Sickness Impact Profile (SIP) instrument. Relative efficiency for SS for the SIP was considerably higher than for AIMS (0.74 vs 0.18).Conclusion:This review gives a summary of the psychometric properties of SS instruments in RMDs. Most instruments show sufficient structural validity internal consistency and reliability, but some psychometric properties such as criterion validity, measurement error and invariance, need to be investigated before choosing an optimal SS instruments.Disclosure of Interests:None declared

Background:Rheumatoid arthritis (RA) can cause important bio-psychosocial burden. When exploring disease burden evolution in the 2-year Care in early RA (CareRA) trial, 3 factor scores were extracted via exploratory factor analysis (EFA).1 EFA uncovers the fact that multiple observed variables have similar patterns of responses because they are all associated with a latent, not directly observable, variable.Objectives:To validate in a population with established RA, the 3 factors scores and their individual components originally extracted in CareRA.Methods:Patients with established RA in sustained remission under treatment with etanercept (≥1 year) were enrolled in the TapERA (Tapering Etanercept in RA) trial between 2012 and 2014. Patients completed the Flare Assessment in RA (FLARE-RA) questionnaire.2Components of disease activity scores (swollen/tender joint count, physician and patient global health assessment, CRP and ESR), as well as pain (question 2) and fatigue evaluation (question 8), from the FLARE-RA questionnaire, and HAQ were recorded at every visit (v=5).Missingness on previously mentioned variables was handled with multiple imputation (100 imputations). Pain and fatigue were re-scaled from their original Likert scale of 1-6 to 0-100 to match CareRA data. Next, timepoint clustering was removed with multiple outputation (1000x) and each of the 100 000 datasets was analyzed by EFA with principal component extraction and oblimin rotation. The analyses were combined after re-ordering the factors by maximizing factor congruence.Results:Sixty-six patients with a mean disease duration of 14.8 years (SD 9.03), mean age of 55.21 years (SD12.87), 96% (63/66) positive to RF or ACPA, 77% (51/66) with erosions and 68% (45/66) female were included in this analysis.Table 1 provides the results of the EFAs from CareRA and TapERA. The factor structure and factor components remained the same in both datasets. The factor loadings, indicating how strongly a variable relates to its factor (correlation between observed and latent score), were also comparable. The HAQ, however; did have a stronger factor loading in TapERA (0.57 vs 0.92).Table 1.Results from the exploratory factor analyses in CareRA and TapERAVariableCareRATapERAPRFCFLFPRFCFLFFatigue0.900.80PaGH0.870.81Pain0.860.75HAQ0.570.92SJC280.920.82TJC280.890.84PhGH0.760.60CRP0.870.85ESR0.780.82Factor loadings presented (correlation between the observed score and the latent factor). Cross-loadings were negligible (PRF: patient-reported factor, CF: clinical factor, LF: laboratory factor, PaGH: patient’s global health assessment, HAQ: health assessment questionnaire, SJC28: 28 swollen joint count, TJC28: 28 tender joint count, PhGH: physician’s global health assessment, CRP: C-reactive protein, ESR: erythrocyte sedimentation rateConclusion:The latent factor structure for disease burden originally found in CareRA was successfully validated in the TapERA dataset, underlining the robustness of the PRF, CF and LF scores. HAQ seems to take “greater importance” on established RA. However, deviations in factor loadings (e.g., HAQ) could be attributed to differences between study populations (e.g., early vs. established RA, sample size). Apart from traditional clinical and laboratory factors, patient-reported pain, fatigue, functionality and overall well-being determine disease burden, both in early and established RA. Using these factor scores could facilitate detection and management of patient’s unmet needs.References:[1]Pazmino, et al. Does Including Pain, Fatigue, and Physical Function When Assessing Patients with Early Rheumatoid Arthritis Provide a Comprehensive Picture of Disease Burden? J Rheumatology 2020 Nov.[2]Berthelot JM, et al. A tool to identify recent or present rheumatoid arthritis flare from both patient and physician perspectives: the ‘FLARE’ instrument. Annals Rheumatic Diseases. 2012.Disclosure of Interests:None declared

Background:Current EULAR guidelines recommend treating RA early, intensively and to-target. A data-driven tool for planning the optimal moment for subsequent visits might adapt visit schedules more to the patient’s needs, without losing treatment quality.Objectives:To determine the optimal statistical model and clinical factors to predict the time to a treatment adaptation in early RA patients.Methods:This study included 379 patients from the treat-to-target Care in Rheumatoid Arthritis (CareRA) trial. The CareRA protocol included 2 predefined treatment adaptation steps for patients not reaching low disease activity (DAS28CRPResults:Factors selected to predict the first per protocol change included TJC, SJC, HAQ, CRP, pain and morning stiffness>15min. Factors selected to predict the second per protocol change included TJC, SJC, PGA, PhGA. Uno Concordance indices showed similar scores per different statistical model but higher scores at w4 and w8 compared to baseline indicating a better predictive performance (Table 1. next page).Table 1.Uno Concordance Scores. Format ‘mean (min-max)’.BaselineWeek 4Week 8Cox Proportional HazardsChange 10.63 (0.59-0.69)0.72 (0.68-0.80)0.75 (0.69-0.82)Change 20.58 (0.50-0.66)0.75 (0.65-0.87)0.78 (0.65-0.93)Linear Multi-Task RegressionChange 10.65 (0.62-0.68)0.72 (0.68-0.78)0.75 (0.69-0.79)Change 20.58 (0.51-0.68)0.72 (0.67-0.82)0.77 (0.68-0.89)Random Survival ForestChange 10.64 (0.58-0.67)0.71 (0.66-0.78)0.76 (0.68-0.80)Change 20.56 (0.50-0.68)0.72 (0.60-0.82)0.77 (0.64-0.92)Conclusion:Our data-driven approach identified predictive clinical factors with a high face validity including joint counts, functionality scores and global health indicators. The different model approaches did not seem to increase the predictive capacity performance. However, our results underline that not so much the baseline disease status but rather the early response to initial treatment reflected in the selected predictive factors can be used for prediction of the need for further treatment adaptation. These models will have to be enriched with patient reported outcomes to further improve predictive performance.Disclosure of Interests:None declared

Background:Belgium suffered considerably from the COVID19 pandemic with high hospitalisation rates during 2 periods: a first wave in March and April 2020, and a second starting from October until the end of 2020. Measures of lowering social interaction were taken throughout 2020 and intensified during the first and second wave when needed. This pandemic could have influenced the access to care and advanced therapies for patients with Rheumatoid Arthritis (RA). In the electronic platform “Tool for Administrative Reimbursement Drug Information Sharing” (TARDIS), data from all Belgian RA patients on biologic and targeted therapy are collected during the submission of a request for initiation and prolongation of reimbursement for these drugs.Objectives:to investigate the effect of the COVID19 pandemic on the monthly prescription behaviour of a new advanced therapy in 2020 by comparing it to 2019.Methods:Patients were selected for this analysis if they started a new TNFi, B/T cell therapy, IL6 inhibitors or tsDMARD therapy in the TARDIS registry in 2019 or in 2020. Rheumatologists request reimbursement via the online TARDIS tool, which is considered here as a new drug prescription. Prescription behaviour was compared between 2019 and 2020, between bionaive and bioexperienced patients, and between the different drug classesResults:In 2019, 2949 patients were prescribed any new advanced therapy, including 1153 TNFi, 469 B/T cell therapy, 436 IL6 inhibitors and 891 tsDMARDs. In 2020, 2998 patients were prescribed any new advanced therapy including 1233 TNFi, 382 B/T cell therapy, 496 IL6 inhibitors and 887 tsDMARDs.On a monthly basis, on average 246 and 250 new advanced therapies were prescribed in 2019 and 2020 respectively. Monthly deviations from this average in 2019 ranged from -19% to +16%. Monthly deviations from this average in 2020 ranged from -50% to +30%. Figure 1A shows the monthly prescription of new advanced therapies in 2019 and 2020.For bionaive and bioexperienced patients, the same trend can be noted. Monthly deviations in bionaive patients in 2020 ranged from -60% to +38%, compared to -18% to +21% in 2019. Monthly deviations in bioexperienced patients ranged from -40% to +25%, compared to -19% to +17% in 2019.Comparison per drug class in 2020 show similar trends. IL6 inhibitors show a slightly different timeline than other drugs classes with other periods of less or more prescriptions changes compared to the other drugs classes. See Figure 1B.Conclusion:The COVID19 pandemic did affect reimbursement requests for patients starting new advanced therapies in March and April 2020, especially for bionaive patients. The latter half of 2020 was apparently used to catch up with reimbursement requests for patients in need for advanced therapies resulting in similar total numbers of patients treated with advanced therapy in 2019 and 2020. The choice for a particular drug type was not clearly influenced by the pandemic. IL6 inhibitor use did seem to be affected differently by the pandemic, yet caution is warranted as these relatively large differences in proportional changes parallel small differences in actual drug numbers.In sum, the observed effect of the pandemic on initiating advanced therapy during the first wave corresponds with Belgian governmental measures that restricted non-essential care which was less observed in the latter half of 2020.Disclosure of Interests:None declared.

Background:Flares are common in rheumatoid arthritis (RA). While flares negatively impact clinical and patient-reported outcomes, different aspects of disease activity may constitute a flare to patients. Flare Assessment in RA (FLARE-RA) is a patient-reported questionnaire aiming to detect active or recent RA flares (1). During its validation, arthritis and general health subscales were identified and the instrument was adapted from 13 questions (1-6 Likert scale) to 11 questions (0-10).Objectives:To investigate which patient-perceived aspects of flare are assessed by FLARE-RA in the context of a TNFi-tapering trial, using exploratory factor analysis (EFA).Methods:Patients with RA in DAS28CRP/ESR-remission (≥6 months) and treated with etanercept 50 mg weekly (≥1 year) were included in the 12-month TapERA (Tapering Etanercept in Rheumatoid Arthritis) trial between 2012 and 2014. Participants completed 3-monthly FLARE-RA questionnaires.The first and final follow-up visits (M3 & M12) were analyzed. Missing data were imputed with multiple imputation (n = 10). Sampling adequacy was assessed by Kaiser-Meyer-Olkin (KMO) and correlations between variables were evaluated with Bartlett’s sphericity test. Spearman correlation matrices were constructed in each of the 10 imputed datasets. The pooled matrix was then analyzed by EFA with principal component extraction and promax-rotation. EFA aims to identify clusters of questions that elicit similar responses because of association with the same underlying latent (not observable) constructs/factors.Results:Sixty-six patients (68% female) with a mean age of 55 years (SD 13) and a mean disease duration of 14.8 years (SD 9) completed a total of 330 FLARE-RA questionnaires. Sampling adequacy was acceptable (KMO = 0.94) and correlation between items was sufficient for factor analysis (p < 0.001).Table 1 shows the results of EFA in TapERA compared to the validation study (1). Factor loadings indicate how strongly each item correlates with its underlying factor. EFA of the full 13-item FLARE-RA at M3 revealed 3 factors: Arthritis, General health and a Medication factor relating to management of flare. The Arthritis factor explained the largest proportion of variance (31%). EFA at M12 showed the same underlying factors, but a less robust factor structure (cross-loadings >0.3) and a larger proportion of variance explained by the General health factor (33%).Conclusion:FLARE-RA assessed similar patient-perceived aspects of RA flare within the context of a TNFi-tapering trial when compared to the validation study, including a Medication factor reflecting use of both glucocorticoids and analgesics. This underlines the usefulness of FLARE-RA in providing a multi-faceted view of patients’ conceptions of RA flare. However, these aspects and their relative importance do seem to evolve over time. Further research is needed to assess if this is due to the influence of time or specific to the studied population/tapering setting.References:[1]Fautrel B, et al. Validation of FLARE-RA, a Self-Administered Tool to Detect Recent or Current Rheumatoid Arthritis Flare. Arthritis Rheumatol. 2017;69(2):309–19Table 1.Factor loadings (>0.3) from exploratory factor analysis of the 13-question FLARE-RA collected in TapERA, compared to results from the FLARE-RA validation study (1). Factors presented in descending order of % variance explained. Q5 & Q7 were removed in the final FLARE-RA.ITEMFLARE-RA ValidationTapERA M3TapERA M12GFAFAFGFMFGFAFMFQ1: stiffness0.330.750.930.73Q2: pain0.470.650.911.00Q3: swelling0.350.800.920.93Q4: nocturnal pain0.390.820.670.76Q5: overall0.390.840.860.86Q6: analgesics0.360.810.680.470.51Q7: glucocorticoids0.910.96Q8: fatigue0.680.510.700.87Q9: limitation0.730.480.300.750.74Q10: irritability0.850.390.770.69Q11: mood0.830.440.970.79Q12: withdrawal0.900.891.06Q13: needing help0.810.380.720.600.30Variance explained (%)6610313112333110AF = arthritis factor, GF = general health factor, MF = medication factorDisclosure of Interests:None declared

Background:The literature about the impact of Rheumatoid Arthritis (RA) on mental health is mostly focused on depression and anxiety. Yet, patients can experience stress without depressed mood or anxiety.Objectives:To examine the impact of RA on psychological stress excluding depression and anxiety focusing on 3 questions: 1) What is the stress level of RA patients compared to a control group? 2) Which types of stress do RA patients experience? 3) Which are risk factors to develop stress as an RA patient?Methods:Four scientific databases, EMBASE, PubMed (including MEDLINE), Web of Science Core Collection and Cochrane Library, were systematically searched from inception until 19/04/2020. Eligible studies included psychological stress in RA patients as outcome. Two reviewers (CV&AVB) independently screened titles and abstracts, and later full texts for eligibility. Full-text screening excluded studies without a separate RA population, with a focus on only anxiety and/or depression or not answering at least 1/3 research questions. Quality was appraised by MINORS/AXIS tools.Results:From 11 115 potentially relevant studies, 16 studies met the inclusion criteria (Table 1). Remarkably, 13 different stress measurement instruments were picked-up in this review. Work stress and interpersonal stress seem more prevalent in RA patients compared to healthy controls. Stress at disease onset was more prevalent in RA compared to osteoarthritis. Psychological stress was higher in patients with chronic pain compared to RA. Role stress, social stress and work stress were induced by RA. More disability, more pain, less social support, lower income, younger age and personality factors like excessive worrying, pessimism, and sensitivity to anxiety, seem to increase the risk for increased stress levels.Table 1.Included StudiesFirst AuthorYearCountryPopulationAgeMean ±SDStress InstrumentQuality AssessmentBugajska2010PolandN=437 PolishN=137 German>50y (71%)>50y (38%)SF36v2AXIS: 16/20Coty2017USAN=8054y ±12yRCQWAXIS: 17/20Cunha2016PortugalN=8058yDASS-21AXIS: 10/20Goulia2015GreeceN=16855y ±13ySCL-90RMINORS: 11/16Latman1996USARA, N=128OA, N=7956y63ySRRSAXIS: 20/20Mancuso2006USARA, N=122HC, N=12249y ±12y49y ±12yDUSOCSMINORS: 20/24Nyklicek2015The NetherlandsN=20157y ±12yPSSMINORS: 13/16Persson2005SwedenN=15852ySCL-90RMINORS: 12/16Rahim2018MalaysiaN=18952y ±11yDASS-21AXIS: 17/20Rice2017CanadaRA, N=226CP, N=22958y ±15y45y ±12yDASS-21AXIS: 17/20Rice2016CanadaRA, N=163CP, N=16756y ±13y45y ±11yDASS-21AXIS: 18/20Richter2018GermanyRA, N=163HC, N=16748y ±10y43y ±10yERIAXIS: 17/20Smith2002USARA, N=93OA, N=82HC, N=80RA, 62yOA, 65yHC, 62y1 question probing stressMINORS: 17/24Treharne2007UKN=13455yPSSMINORS: 11/16Turner-Cobb1998UKRA, N=13CP, N=2442y ±8y39y ±4yLEI/HUSMINORS: 17/24Zautra1997USAN=4155y ±10yISLEMINORS: 12/16Conclusion:This scoping review is to our knowledge the first to address the heterogeneity of measurement tools and definitions of stress in RA research. It provides the basis for further research, which is needed to predict different stress trajectories and respond to these with patient-centered interventions.Disclosure of Interests:None declared

Background:Advances in therapeutics and treatment strategies for Rheumatoid Arthritis (RA) have improved clinical outcomes. Although these advances also impact the well-being as shown in many patient-reported outcomes, still a sizeable number of patients in clinical remission report a reduced well-being.Objectives:To explore factors that contribute to well-being in patients with early RA.Methods:Patients from the 2-year pragmatic treat-to-target Care in Early Rheumatoid Arthritis (CareRA) trial were included. Patients were treated intensively, with a combination of csDMARDs and glucocorticoid remission induction schemes, except one group treated with MTX monotherapy.Eight different validated questionnaires including the Arthritis Self-Efficacy Scale (ASES), the multidimensional Fatigue Inventory (MFI), the Pittsburgh Sleep Quality Index (PSQI) the Revised Illness Perception Questionnaire (IPQ-R), the Utrecht Coping List (UCL), the Short Form 36 (SF-36), RA Quality of Life questionnaire (RA-QOL) and the Social Support List (SSL) were taken. Questionnaires were obtained at baseline, at week 16, 52 and 104 except for the IPQ and UCL, which were only taken at baseline and week 16.Three patients` groups were created including all patients, patients in remission (DAS28crp < 2.6) and not in remission. Regression models were constructed to define well-being at week 16, 52 and 104. The Patient Global Assessment (PGA) on a Visual Analogue Scale 0-100 (VAS) was chosen as a proxy for well-being (score 0-100). As predictors, all subscales of the 8 validated questionnaires, summing to 84 variables, with and without the VAS for Pain (VAS-Pain) were used in 18 models (3 patient groups, 3 time points, with/without VAS-Pain) in total. Data reduction used forward, backward and stepwise selection based on the Aikake information criteria. Data was checked for influential observations by Cook’s distance and for multicollinearity by variance inflation factors (threshold = 5). Influential observations were removed one observation every time. Highly correlated variables were deleted by backward selection (α=5%). Missing data was handled by multiple imputation using CART with 15 iterations.Results:In total, 379 patients were included. Table 1 gives the number of variables and the associated R2. In the 9 models defining well-being without VAS-Pain, 53 variables were used at least once. Most common variables were bodily pain (n=8) and social function (n=5) of the SF-36, and positive emotions (n=4) of the SSL. In the 9 models with VAS-Pain, 31 variables were used at least once. Most common variables were vitality (n=3) and social function (n=3) of the SF-36, and identity (n=3) of the IPQ-R. Model content was heterogenous regarding patient population and time.R2and number of variables in each model of well-beingAll patientsPatients in remissionPatients not in remissionR2#R2#R2#week 1652%1339%753%6week 16 with VAS-Pain78%469%680%5week 5244%844%757%12week 52 with VAS-Pain84%584%692%2week 10440%1339%862%10week 104 with VAS-Pain81%782%486%11R2= coefficient of determination, the proportion of the variance in the dependent variable that is predictable from the independent variable(s). # = number of variables selected in regression modelConclusion:Well-being is apparently difficult to define uniformly as many factors contribute to it. As already known, well-being, defined by PGA, and VAS-Pain are highly associated, even in patients in remission where pain levels should be theoretically lower. Other well-being definitions could lead to different results and should be further explored.Disclosure of Interests:Diederik De Cock: None declared, Tianna Poffe: None declared, Geert Verbeke: None declared, Veerle Stouten: None declared, Sofia Pazmino: None declared, Delphine Bertrand: None declared, Johan Joly: None declared, Rene Westhovens Grant/research support from: Celltrion Inc, Galapagos, Gilead, Consultant of: Celltrion Inc, Galapagos, Gilead, Speakers bureau: Celltrion Inc, Galapagos, Gilead, Patrick Verschueren Grant/research support from: Pfizer unrestricted chair of early RA research, Speakers bureau: various companies

Background:Fatigue is reported in up to 90% of patients with established Rheumatoid Arthritis (RA). Fatigue has a large impact on patient`s life and is perceived difficult to manage in many patients. The early disease course could constitute a window of opportunity to tackle fatigue.Objectives:To explore that, if RA can be controlled rapidly, complaints of fatigue could be less in the long run, even in patients considered at low risk to develop a severe disease course.Methods:Patients with a low risk profile recruited in the 2-year pragmatic Care in Early Rheumatoid Arthritis (CareRA) trial were used in this analysis. This low risk profile was based on the absence of erosions, rheumatoid factor, anti-citrullinated protein bodies or low disease activity status. The low-risk group was randomised to either a tight step-up starting with 15mg MTX weekly in monotherapy (MTX-TSU) or COBRA Slim, consisting of 15 mg MTX weekly and a prednisone step-down scheme starting at 30 mg. Fatigue was measured by the multi-dimensional fatigue inventory (MFI), a self-report instrument consisting of 20 questions with a Likert scale from 1-5 as answer. These 20 questions can be subdivided in five subscales (0-20) of four questions (higher scores indicating higher fatigue levels): general fatigue, mental fatigue, physical fatigue, reduced activity and reduced motivation. General fatigue means the general feeling of being tired. Mental fatigue implicates concentration and memory problems. Physical fatigue implicates a lack of energy and strength. Reduced activity means that patients can do less activities for example on one day. Reduced motivation means that patients don’t want to plan or do things due to lack of motivation. MFI was obtained at baseline, at week 16, week 52 and week 104. Cobra Slim was compared with MTX-TSU by Mann-Whitney-U test. The 5 domains of the MFI of the two groups were compared by a generalized estimating equation (GEE) over 2 years adjusting for baseline MFI domain score and DAS28.Results:Of the 90 patients recruited in the low-risk group, 80 (89%) patients completed the MFI at baseline. Randomisation was successful resulting in similar baseline characteristics and MFI levels between Cobra Slim (n=38) and MTX-TSU (n=42). After 2 years of treatment, DAS28CRP levels (Slim 1.9 ±0.8 - MTX-TSU 2.2 ±1.0, p=0.253) and DAS28CRP remission (Slim 81.5% - MTX-TSU 77.1%, p=0.677) did not differ between patients. However, general (Slim 9.8 ±4.1 – MTX-TSU 13.1 ±4.0, p=0.005) and mental (Slim 6.8 ±2.7 - MTX-TSU 10.0 ±4.9, p=0.022) fatigue levels on the MFI were lower in the Cobra Slim group at week 104. GEE analysis confirmed that groups differed in the general (p=0.026) and mental (p=0.013) fatigue scale over 2 years (Figure 1).Figure 1.DAS28CRP and MFI General Fatigue score over 2 years between groupsConclusion:Patients treated intensively have lower fatigue levels over 2 years compared to patients treated more conservatively, even if disease activity became similar in the two groups over time. This underlines the importance of initiating an optimal intensive treatment even in so called low-risk patients. Moreover, our results show that fatigue is a heterogeneous concept, with different interactions between treatment and type of fatigue. Although our study was limited by a small sample size, the data clearly shows how to improve fatigue levels significantly in early RA.Disclosure of Interests:Diederik De Cock: None declared, Amber Nooyens: None declared, Sofia Pazmino: None declared, Delphine Bertrand: None declared, Veerle Stouten: None declared, Johan Joly: None declared, Rene Westhovens Grant/research support from: Celltrion Inc, Galapagos, Gilead, Consultant of: Celltrion Inc, Galapagos, Gilead, Speakers bureau: Celltrion Inc, Galapagos, Gilead, Patrick Verschueren Grant/research support from: Pfizer unrestricted chair of early RA research, Speakers bureau: various companies

Background:The Flare assessment in rheumatoid arthritis (FLARE-RA) questionnaire has been developed to identify flares in patients with rheumatoid arthritis (RA). The first version was published by Berthelot et al. (2012) and consisted of 13 questions on a Likert-scale of 1-6 ranging from ‘completely untrue’ to ‘completely true’. When the FLARE-RA questionnaire was validated by Fautrel et al., 2 questions were removed, and it was rescaled to 0–10. The questionnaires’ usefulness has been tested in few studies. Further external validation in a well-defined cohort of patients with RA is needed.Objectives:To externally validate the FLARE-RA questionnaire and determine cut-offs for identifying a flare in an established RA population in which biologicals are tapered.Methods:Patients who were in remission according to the DAS28CRP or ESR (≥6 months) and treated with etanercept 50 mg weekly (≥1 year), were enrolled between 2012 – 2014 in the pragmatic 1-year open-label randomised controlled TapERA (Tapering Etanercept in RA) trial. Patients were randomised to continue etanercept 50 mg weekly or taper to 50 mg every other week. The FLARE-RA questionnaire (version of 2012) was completed every 3 months. Outcomes were based on 3 versions of the questionnaire (13 questions (13q), 11 questions (11q) and 11 questions rescaled (r11q)). Per time point, the average of the answers was calculated to obtain a total score of the FLARE-RA questionnaire. The total scores were compared between patients in remission (DAS28CRP 3.2 - ≤5.1) and high disease activity (DAS28CRP >5.1) using the Kruskal-Wallis test and between patients with and without a flare according to the OMERACT definition (increase in DAS28 >1.2 compared to baseline or increase in DAS28 >0.6 and current DAS28 ≥3.2) using the Mann-Whitney U test. The total FLARE-RA scores of the different time points were combined to determine the receiver operating characteristics (ROC) curves, the corresponding cut-off values and the area under the curve (AUC) for identifying an OMERACT flare. An AUC of 0.7 stands for having no, moderate and a good predictive value, respectively.Results:FLARE-RA questionnaires of 66 patients (68% female, mean ± standard deviation (SD) age of 55 ± 11 years) were collected. The FLARE-RA score (13q) did increase when disease activity increased at month (M) 3 and M12 (pTable 1.Comparison of the total FLARE-RA scores (13q) between the disease activity groups (DAS28CRP)RemissionLDAMDAHDAP-valueBLPatients (n)62310FLARE Q1.8 ± 0.81.5 ± 0.31.30.800M3Patients (n)501150FLARE Q2.1 ± 1.03.0 ± 0.93.5 ± 1.40.004M6Patients (n)52590FLARE Q2.1 ± 0.83.1 ± 1.33.1 ± 1.90.057M9Patients (n)481071FLARE Q2.1 ± 0.92.8 ± 1.13.3 ± 1.62.40.079M12Patients (n)52860FLARE Q2.1 ± 1.03.1 ± 0.83.2 ± 1.00.002Figure 1.ROC curves of the total FLARE-RA scores (13q, 11q and r11q version) for identifying a flare according to the OMERACT definition. FLARE Q is expressed in mean ± SD. M month, FLARE Q FLARE-RA questionnaire 13q, n number, LDA low disease activity, MDA moderate disease activity, HDA high disease activityConclusion:The FLARE-RA scores seem to reliably discern between patients with and without an OMERACT flare. A cut-off of 2.7 on the current questionnaire (r11q) had the optimal sensitivity and specificity to identify an OMERACT flare.Disclosure of Interests:Delphine Bertrand: None declared, Veerle Stouten: None declared, Sofia Pazmino: None declared, Diederik De Cock: None declared, Anneleen Moeyersoons: None declared, Rene Westhovens Grant/research support from: Celltrion Inc, Galapagos, Gilead, Consultant of: Celltrion Inc, Galapagos, Gilead, Speakers bureau: Celltrion Inc, Galapagos, Gilead, Johan Joly: None declared, Patrick Verschueren Grant/research support from: Pfizer unrestricted chair of early RA research, Speakers bureau: various companies

Background:Fatigue is mentioned as a symptom with high impact in many patients with Rheumatoid Arthritis (RA) and this symptom remains difficult to be managed by both the patient and the physician.Objectives:To investigate if rapid suppression of disease activity in early RA could impact fatigue complaints in the long run.Methods:For this study, we included patients from the 2-year pragmatic investigator-initiated Care in Early Rheumatoid Arthritis (CareRA) trial. Most patients were treated intensively, with different combinations of csDMARDs and glucocorticoid remission induction schemes, except one group without classic markers of poor prognosis that was treated with MTX weekly in monotherapy. Patients were followed up at least every 3 months, with more mandatory visits in the first 6 months of treatment. Clinical parameters including DAS28 components were registered at every visit. Fatigue was measured by the multi-dimensional fatigue inventory (MFI), a self-reported instrument consisting of 20 questions with a Likert scale from 1-5 as answer. These 20 questions can be subdivided in five subscales (0-20) of four questions (higher scores indicating higher fatigue levels): general fatigue, mental fatigue, physical fatigue, reduced activity and reduced motivation. General fatigue means the general feeling of being tired. Mental fatigue implicates concentration and memory problems. Physical fatigue implicates a lack of energy and strength. Reduced activity means that patients can do less activities for example on one day. Reduced motivation means that patients don’t want to plan or do things due to no motivation. MFI was obtained at baseline, at week 16, week 52 and week 104. Only patients with a filled-out MFI at baseline and available DAS28CRP at week 16 were included in this study.Patients were divided in 2 groups based on their response, defined as achieving or not achieving DAS28CRP remission (Results:Of the 379 patients recruited in the CareRA trial, 343 (90.5%) had a MFI score available at baseline and a DAS28CRP available at week 16 with 236 (68.8%) patients achieving remission, and 107 (31.2%) patients not achieving remission at week 16. After 2 years of treatment, the proportion of patients in DAS28CRP remission was still higher in the early responders versus controls (82.3% versus 63.5%, p=0.001). Every MFI domain after 2 years of treatment showed lower scores for early responders including general fatigue (p=0.017), physical fatigue (p=0.011), reduced activity (p=0.040) and mental fatigue (p=0.042) except reduced motivation (p=0.062) (see figure 1). GEE analysis demonstrated that all MFI domains differed over 2 years between patients in remission or not at week 16, including general fatigue (pFigure 1.MFI domain scores at baseline and at week 104 per groupConclusion:Patients reaching remission after 16 weeks of treatment achieve lower fatigue levels over 2 years compared to patients not reaching this early remission. This study underlines the importance of early disease control. Successful early intensive treatment improves in the long run not only clinical outcomes but also an important patient preferred outcome such as fatigue.Disclosure of Interests:Diederik De Cock: None declared, Amber Nooyens: None declared, Delphine Bertrand: None declared, Veerle Stouten: None declared, Sofia Pazmino: None declared, Johan Joly: None declared, Rene Westhovens Grant/research support from: Celltrion Inc, Galapagos, Gilead, Consultant of: Celltrion Inc, Galapagos, Gilead, Speakers bureau: Celltrion Inc, Galapagos, Gilead, Patrick Verschueren Grant/research support from: Pfizer unrestricted chair of early RA research, Speakers bureau: various companies

Background:Rheumatoid arthritis (RA), psoriatic arthritis (PSA) and spondyloarthritis (SPA) are the most common inflammatory rheumatic diseases. Pain is the hallmark symptom in these conditions and pain relief is ranked first amongst preferred outcomes by patients. Level of analgesic and anti-inflammatory drug use is unknown in these populations in Belgium.Objectives:To compare analgesic and anti-inflammatory drug use in patient populations of RA, PSA and SPA versus controls in a General Practitioners (GP) setting in an era of expanding treatment possibilities in rheumatology.Methods:Data were obtained from Intego over a 13-year time interval from 1999 to 2012. Intego is a Flemish GP-based morbidity registration network hosted at the Academic Center for General Practice of the KU Leuven, covering 2% of the Flemish general population. Patients classified under the International Classification of Primary Care codes L88 (rheumatoid/seropositive arthritis) and L99 (musculoskeletal disease other) were selected for this study. Experienced rheumatologists verified if the keywords mapped to these codes corresponded to a diagnosis of RA/SPA/PSA. The date of these diagnoses in Intego was considered “baseline”. Controls were matched on age, gender, baseline date and GP practice in a 4:1 case ratio. Intego registers all electronic drug prescriptions by the GP. Anytime use of glucocorticoids, NSAIDs, opioids except tramadol, tramadol and paracetamol in the first 3 years after diagnosis is presented. Proportions of patients and controls on analgesic and anti-inflammatory drugs were compared by Chi-Square analyses.Results:Over a 13-year period, 738, 229 and 167 patients were included with a diagnosis of RA, SPA or PSA, respectively. Table 1 presents the medication use of these populations. The three conditions had statistically significantly more prescriptions for all types of analgesic and anti-inflammatory drugs compared to controls. Approximately 70% of patients with an inflammatory rheumatic condition received mild pain medication (NSAIDs, Tramadol and Paracetamol) in the first three years after diagnosis. To note is the high use of opioids, even excluding tramadol, in these populations ranging up to 15%.Table 1.3-year analgesic and anti-inflammatory drug use in RA, SPA and PSA patients versus controlsMedicationRARA ControlSPASPA ControlPSAPSA ControlNumber of patients7382952229916167668Glucocorticoids241(33%)348(12%)29(13%)70(8%)47(28%)67(10%)NSAIDs455(62%)1156(39%)161(70%)340(37%)114(68%)267(40%)Opioids109(15%)263(9%)31(14%)53(6%)24(14%)45(7%)Tramadol87(12%)150(5%)22(10%)28(3%)16(10%)26(4%)Paracetamol233(32%)598(20%)63(28%)165(18%)51(31%)141(21%)Total analgesic and anti-inflammatory drug use506(69%)1409(48%)172(75%)407(44%)121(72%)309(46%)RA= Rheumatoid arthritis, PSA= psoriatic arthritis, SPA= spondyloarthritis. Total analgesic and anti-inflammatory drug is the sum of NSAIDs, Tramadol and Paracetamol. Anytime use of drugs are presented.Conclusion:Frequent analgesic and anti-inflammatory drug use in patients with a chronic inflammatory joint condition is to be expected, and underlined by the results of our study. Remarkably is the high use of opioids, even excluding tramadol, in patients with RA, PSA and SPA in an era of effective disease modifiers, as well in the control population. Our data shows that around 9% of the Belgian population receives at least once over a 3-year period an opioid prescription. As our data only registers electronic GP prescriptions, this is likely to be an underestimation of the true prescription proportion. Detailed analyses on dose and duration of analgesic and anti-inflammatory drugs will follow.Disclosure of Interests:Sofia Pazmino: None declared, Veerle Stouten: None declared, Patrick Verschueren Grant/research support from: Pfizer unrestricted chair of early RA research, Speakers bureau: various companies, Pavlos Mamouris: None declared, Rene Westhovens Grant/research support from: Celltrion Inc, Galapagos, Gilead, Consultant of: Celltrion Inc, Galapagos, Gilead, Speakers bureau: Celltrion Inc, Galapagos, Gilead, Kurt de Vlam Grant/research support from: Celgene, Eli Lilly, Pfizer Inc, Consultant of: AbbVie, Eli Lilly, Galapagos, Johnson & Johnson, Novartis, Pfizer Inc, UCB, Delphine Bertrand: None declared, Kristien Van der Elst: None declared, Bert Vaes: None declared, Diederik De Cock: None declared

Background:Patients with rheumatoid arthritis (RA) seem to experience a diminished fertility. Reasons for this lowered fertility are insufficiently defined and probably multifactorial. Although the effect of DMARDs on pregnancy outcomes have been studied, there is a lack of data on the effect of DMARDs on the fertility of patients with RA.Objectives:To evaluate all studies that concern an effect of DMARDs on the fertility of men and women with RA in a systematic review.Methods:A search was conducted at 18/10/2019 in three databases including Embase, Pubmed (Medline) and Web Of Science with specific search strings for each database, constructed with the help from a health sciences librarian. We included studies involving women or men diagnosed with RA, of fertile age (18-45years) and on a DMARD therapy, with as outcome a fertility parameter. Systematic reviews, meta-analyses, case reports, case series and animal studies were excluded. Studies not in English or Dutch or written more than 15 years ago were excluded. Article selection was firstly based on title/abstract (double blind, two researchers, LB and IS) and then full text (two researchers, LB and IS). In case consensus could not be reached, a third researcher (DDC) was consulted. The references of included articles were reviewed (“snowballing”) to include and minimize the missing articles. A quality check of the included full text papers was performed using the CASP Appraisal Checklists. A chart was made based on outcomes of interest.Results:After duplicate removal, 9030 articles were found. After title/abstract screening, 82 articles remained. After full text screening, 4 articles could be retained. No additional studies were found through snowballing. Only studies about women could be included, as the evidence found for men was all in papers with exclusion criteria for our systematic review (e.g. case reports). Table 1 summarizes these papers. The included studies investigated the following DMARDs: methotrexate (MTX), certolizumab pegol (CZP), etanercept (ETN) and sulfasalazine (SSZ). No detrimental effects of these DMARDs on fertility, defined as time-to-pregnancy (TTP), anti-Müllerian hormone serum level or presence of a history of infertility, were reported.Table 1.Characteristics of studies included in the systematic reviewAuthorsLocationSampleDMARDOutcomeMethodDesignResultAkintayo et al.2018Nigeria50 women with RA and 50 women without RAMTXInfertility or history of infertilityInterviewer-administered questionnaireRetrospective studyMTX was associated with a negative history of infertilityShimada et al.2019Japan25 pregnancies in 19 patients with RACZP and ETNTTP (time to pregnancy)medical recordsRetrospective studybDMARD treatment shortened the TTPBrouwer et al.2013The Netherlands72 women with recent-onset RA compared to 509 healthy womenMTXLevel of serum AMHmedical records, serum samples (2 time points)Retrospective studyAMH levels were not lower with MTX.Brouwer et al.2014The Netherlands245 women with RAMTX and SSZTTPQuestionnaires and interviewsProspective cohort studyMTX and SSZ did not prolong TTPRA = Rheumatoid Arthritis; MTX = Methotrexate; TNFi = Tumor Necrosis Factor inhibitor; CZP = Certolizumab pegol; ETN = Etanercept; SSZ = Sulfasalazine; TTP = Time to Pregnancy; DMARD = Disease Modifying Antirheumatic Drug; AMH = Anti-Müllerian hormoneConclusion:This systematic review underlines the knowledge gap on the effect of DMARDs on fertility in human studies. Only 4 studies on women, and no studies on men were found. In the 4 included studies, DMARD treatment, even with MTX in contrast to general belief, had no harmful effect on fertility, probably because disease activity was better controlled with DMARD therapy. However, effects of other RA medication such as NSAIDs were excluded. More research is needed to improve guidance for patients with RA with a child wish.Disclosure of Interests:Liesbeth Brants: None declared, Isaline Soenen: None declared, Sofia Pazmino: None declared, Rene Westhovens Grant/research support from: Celltrion Inc, Galapagos, Gilead, Consultant of: Celltrion Inc, Galapagos, Gilead, Speakers bureau: Celltrion Inc, Galapagos, Gilead, Patrick Verschueren Grant/research support from: Pfizer unrestricted chair of early RA research, Speakers bureau: various companies, Diederik De Cock: None declared

Background:Commonly used disease activity scores in rheumatoid arthritis (RA) include one patient reported outcome (PRO) -the patient’s global health assessment (PGA). Exploratory factor analysis (EFA) was performed on data from the 2 year Care in early Rheumatoid Arthritis (CareRA) trial to explain the evolution of disease burden extracting 3 factors.1Objectives:To assess the evolution and relative responsiveness over time of clinical, laboratory and patient assessments included in composite scores, together with other PROs like pain, fatigue and functionality in patients with early RA (≤1 year) treated to target (T2T) within the CareRA trial.Methods:DMARD naïve patients with early RA (n=379) were included, randomized to remission induction with COBRA-like treatment schemes (n=332) or MTX monotherapy (n=47) and T2T.Components of disease activity scores (swollen/tender joint count (S/TJC), C-reactive protein (CRP) or erythrocyte sedimentation rate (ESR), and physician (PhGH) or patient (PGA) global health assessment), pain and fatigue (both on 0-100 scale) and HAQ were recorded at every visit.Missing data was handled with multiple imputation (n=15). Clustering was removed with multiple outputation (n=1000), then each of the 15 000 datasets was analyzed by EFA with principal component extraction and oblimin rotation. The analyses were combined after re-ordering the factors by maximizing factor congruence. The 3 extracted factors and their individual components (with their loadings) were: 1. Patient containing PGA (0.87), pain (0.86), fatigue (0.90) and HAQ (0.5) 2.Clinical with SJC (0.92), TJC (0.89) and PhGH (0.76) and 3.Laboratory with CRP(0.87) and ESR (0.78).1(Pazmino, ACR 2019 abstract, Table 3)Afterwards, variables were first normalized to a 0-1 scale, then multiplied -weighted- by the factor loadings previously obtained.1For each Patient, Clinical and Laboratory severity score, the weighted variables belonging to each score were summed together and then re-scaled to 0-1 (higher values suggest more burden).The percentage (%) improvement from baseline to week 104 and the area under the curve (AUC) across time points were calculated per factor.Differences in % improvement and AUC were compared between patients not achieving and achieving early and sustained (week 16 to 104) disease activity score remission (DAS28CRP Results:Severity scores of Patient, Clinical and Laboratory factors improved rapidly over time (Figure 1). In patients achieving sustained remission (n=122), Patient, Clinical and Laboratory scores improved 56%, 90% and 27% respectively. In patients not achieving sustained remission (n=257) the improvement was 32%, 78% and 9% respectively (pPatients in CareRA who achieved sustained remission had an AUC of 15.1, 3.4 and 4.7 in Patient, Clinical and Laboratory scores respectively, compared to 32.3, 10.0, and 7.2 in participants not achieving sustained remission (pConclusion:Patient, Clinical and Laboratory severity scores improved rapidly over time in patients achieving rapid and sustained disease control. However, overall, Patient burden seemed not to improve to the same extent as Clinical burden. Patient’s unmet needs in terms of pain, fatigue, functionality and overall well-being should thus be given more attention, even in patients in sustained remission.References:[1]Pazmino S,et al.Including Pain, Fatigue and Functionality Regularly in the Assessment of Patients with Early Rheumatoid Arthritis Separately Adds to the Evaluation of Disease Status [abstract]. ACR. 2019.Disclosure of Interests:Sofia Pazmino: None declared, Anikó Lovik: None declared, Annelies Boonen Grant/research support from: AbbVie, Consultant of: Galapagos, Lilly (all paid to the department), Diederik De Cock: None declared, Veerle Stouten: None declared, Johan Joly: None declared, Delphine Bertrand: None declared, Rene Westhovens Grant/research support from: Celltrion Inc, Galapagos, Gilead, Consultant of: Celltrion Inc, Galapagos, Gilead, Speakers bureau: Celltrion Inc, Galapagos, Gilead, Patrick Verschueren Grant/research support from: Pfizer unrestricted chair of early RA research, Speakers bureau: various companies

Background:The Flare assessment in Rheumatoid Arthritis (FLARE-RA) questionnaire was developed to identify Rheumatoid Arthritis (RA) flares, but it is unknown if this questionnaire can also predict flares.Objectives:To identify if the FLARE-RA questionnaire has a predictive capacity for OMERACT flares in patients with established RA participating in a tapering trial.Methods:Patients, participating in the 1-year open-label pragmatic randomised controlled TapERA (Tapering Etanercept in RA) trial, were included in the analysis. Patients had to be in DAS28CRP or ESR remission (≥6 months) and treated with etanercept 50 mg weekly (≥1 year). Participants were randomised to continue etanercept 50 mg weekly or to taper to 50 mg every other week.The FLARE-RA questionnaire was completed every 3 months in the trial. This questionnaire consists of 13 questions on a Likert-scale from 1 to 6 reflecting ‘completely untrue’ to ‘completely true’. Validation by Fautrel et al. leaded to elimination of 2 questions (‘steroid intake’ and ‘overall worsening of RA’) and rescaling to 0-10. Our outcomes were based on these 3 versions of the questionnaire, namely 13 questions (13q), 11 questions (11q) and rescaled 11 questions (r11q). The FLARE-RA questionnaire can be divided in 2 subscales: the FLARE-RA arthritis subscale (questions regarding morning stiffness, night disturbances, joint swelling, joint pain, analgesics) and FLARE-RA general symptoms subscale (questions regarding fatigue, functional limitation, irritability, mood disturbances, withdrawal, need for help).The total FLARE-RA score was calculated by taking the average of all the questions per time point. A flare was defined according to the OMERACT definition, namely an increase in DAS28CRP > 1.2 compared to baseline or increase in DAS28CRP > 0.6 and current DAS28CRP ≥ 3.2. All the total FLARE-RA scores of the baseline, month 3, 6 and 9 visit were grouped and the mean ± standard deviation (SD) FLARE-RA score was compared between patients with or without an OMERACT flare on the next study visit using the Mann-Whitney U test. Logistic regressions using the total FLARE-RA score to predict an OMERACT flare 3 months later were carried out for the 13q, 11q and r11q versions and the FLARE-RA subscales. Missing data were imputed using expectation maximisation.Results:Sixty-six patients (68% female, mean ± SD age of 55 ± 11 years) completed the FLARE-RA questionnaire. This yielded 264 FLARE-RA scores, of which the total mean ± SD FLARE-RA score was 2.1 ± 1.0 and 2.7 ± 1.1 for patients without and with an OMERACT flare on the next study visit, respectively (pTable 1.Comparison of overall total FLARE-RA scores between patients with or without an OMERACT flare on the next visitQuestionnaire versionNo OMERACT flare on next visitOMERACT flare on next visitP-valueOverall total FLARE-RA score(mean ± SD)13q2.1 ± 1.02.7 ± 1.10.00211q2.2 ± 1.12.7 ± 1.10.004r11q2.3 ± 2.13.4 ± 2.20.004Overall total FLARE-RA score was derived by grouping the total FLARE-RA scores of the baseline, month 3, 6 and 9 visit.Conclusion:Higher total FLARE-RA questionnaire scores seem to indicate a higher risk of an OMERACT flare 3 months later, regardless of which versions or subscales of the FLARE-RA questionnaire were used. Hence, our findings suggest that the FLARE-RA questionnaire could be used as a predictive tool for flares.Disclosure of Interests:Delphine Bertrand: None declared, Diederik De Cock: None declared, Veerle Stouten: None declared, Sofia Pazmino: None declared, Anneleen Moeyersoons: None declared, Johan Joly: None declared, Rene Westhovens Grant/research support from: Celltrion Inc, Galapagos, Gilead, Consultant of: Celltrion Inc, Galapagos, Gilead, Speakers bureau: Celltrion Inc, Galapagos, Gilead, Patrick Verschueren Grant/research support from: Pfizer unrestricted chair of early RA research, Speakers bureau: various companies

Background:The Tool for Administrative Reimbursement Drug Information Sharing (TARDIS) is an electronic platform combining data collection from all Belgian patients with Rheumatoid Arthritis (RA) on advanced therapy, together with a drug reimbursement request. Therapy choice after initial 2 classical synthetic DMARD failure is left to the treating rheumatologist in Belgium.Objectives:To investigate first-line therapy choices for tumor necrosis factor inhibitor (TNFi) biologic (b) DMARDs, non-TNFi bDMARDs or targeted synthetic (ts) DMARDs via patient characteristics and initial treatment response in the TARDIS-RA registry.Methods:All Belgian rheumatologist inserted patient data online when prescribing a b/tsDMARD. When data was entered for the first time, previous and current use of DMARD therapies was registered. Every next bDMARD or tsDMARD initiation, prolongation and discontinuation was registered electronically. First prolongation is 6 months for bDMARDs and 12 weeks for tsDMARDs, and yearly thereafter. Patients were selected for this analysis if they started a TNFi, non-TNFi or tsDMARD therapy between Jan 2018 and Jan 2019. Rituximab was excluded. Baseline characteristics of bionaive patients per therapy were compared with Mann-Whitney U or Chi2tests were appropriate. Regression analyses, adjusted for age, DAS28 baseline and disease duration, evaluated DAS28 change, remission (DAS28Results:In 2018, 1263 bionaive RA patients were included. Table 1 describes this population. Time until 1stfollow-up differed between groups with 183 (181-184) days for bDMARD versus 84 (84-84) days for tsDMARD patients. Lineair regression showed an effect of therapy type on DAS28 change in bionaive patients (p=0.017). Logistic regression showed no difference per therapy for remission (p=0.090) nor low disease activity (p=0.123). Proportions of therapy prolongations at 1stfollow up visit did not differ per therapy type.Table 1.Baseline characteristics and treatment response of first-line TNFi, Non-TNFi or tsDMARDsTNFiNon-TNFitsDMARDp-valueNumber patients696 (57%)293 (25%)215 (18%)Age (years)55, (45-64)58, (51-68)58, (49-66)Disease duration (years)3, (1-7)3, (1-9)5, (2-13)DAS28 Baseline4.8, (4.3-5.5)5.1, (4.4-5.7)4.7, (4.2-5.4)0.010DAS28 Change2.2 (1.0-3.0)2.2 (1.1-3.2)1.9 (0.9-2.7)0.014Remission296 (50%)123 (49%)78 (42%)0.143LDA377 (64%)153 (61%)105 (56%)0.196Prolongation therapy492 (82%)219 (87%)161 (86%)0.158Number given are median, (IQR) or number (proportion). TNFi = tumour necrosis factor inhibitor, ts= targeted synthetic, DAS = disease activity score, DAS28 change = DAS28 at 1st follow up visit minus DAS28 at baseline, remission = DAS28Conclusion:Initial therapy choices are partially driven by patient profile, although other factors such as patient preferences could not be verified. DAS28 change for tsDMARDs seemed less important versus bDMARDs, but can possibly be attributed to the preset evaluation moment being sooner for tsDMARDs versus bDMARDs aside of patient profile differences in age and disease duration. In contrast, proportion of remission, low disease activity and therapy prolongation did not differ by therapy.Disclosure of Interests:Diederik De Cock: None declared, Patrick Durez Speakers bureau: AbbVie, Bristol-Myers Squibb, Celltrion, Eli Lilly, Pfizer, Sanofi, Dirk Elewaut: None declared, Bernard Lauwerys: None declared, Rene Westhovens Grant/research support from: Celltrion Inc, Galapagos, Gilead, Consultant of: Celltrion Inc, Galapagos, Gilead, Speakers bureau: Celltrion Inc, Galapagos, Gilead, Patrick Verschueren Grant/research support from: Pfizer unrestricted chair of early RA research, Speakers bureau: various companies

Background Biosimilars and their reference agents have been shown to be equivalent in clinical trials. In the United Kingdom, etanercept biosimilars (ETA-B) are, since 2016, a first-line treatment option for the management of severe rheumatoid arthritis (RA) defined as no response to 2 or more csDMARDs. However, real world data, including how it compares to the etanercept originator (ETA-O) are lacking. Objectives This study aims to compare the short-term effectiveness of etanercept originator with its biosimilar in patients with RA when used as a first biologic following csDMARDs. Methods This study included patients with RA registered with the British Society for Rheumatology Biologics Registers for RA (BSRBR-RA) at the point of starting either ETA-O or an ETA-B since 2011 as their first biologic. Baseline information is collected at drug start and includes demographic and clinical data. Follow-up (FU) data are captured every 6 months and include details on therapy changes, current disease activity, and development of any adverse events. The primary outcome of this study is effectiveness as calculated by change in the 28 joint count disease activity score (DAS28). Only patients with a complete DAS28 at baseline and their 1st FU were included in the final analysis of this study. Hazard ratios (HR) comparing drug survival and risk of first serious adverse event (SAE) between ETA-O and ETA-B patients were calculated using Cox regression. Results Between January 2010 and 11 December 2017, 1217 and 412 patients starting ETA-O or ETA-B respectively were recruited and had ≥1 FU available. Complete DAS28 data at baseline and 1st FU were available for 740 ETA-O patients and 177 ETA-B patients. Patient characteristics were similar between the 2 cohorts (Table). After adjusting for baseline differences, no difference between groups was seen in DAS28 (p=0.1) or remission status (p=0.1) at 1st FU. Nine (5%) and 48 (6%) of ETA-B and ETA-O patients had stopped their respective treatments by the 1st FU. The adjusted hazard ratio for stopping ETA-O versus ETA-B over this time period was similar (HR=0.8 (0.4-1.6); p=0.5). Risk of SAEs over the first 6 months was also similar between groups (HR (ETA-B versus ETA-O) =0.6 (0.3-1.1); p=0.1), with 10 (6%) and 73 (10%) SAEs reported in ETA-B and ETA-O patients respectively until 1st FU. Conclusions In the UK, etanercept biosimilars are now frequently used as first-line biologics in RA patients. These short-term follow-up data demonstrate in routine clinical care that ETA-B appears to be equivalent to ETA-O in terms of short term effectiveness, drug survival and safety. Disclosure of Interest None declared

Background Although biosimilars are routinely used in adults with musculoskeletal diseases, there are limited data regarding the use of biosimilars in patients with juvenile idiopathic arthritis(JIA). Objectives To describe the characteristics of patients with JIA starting biosimilars in the United Kingdom (UK) following their approval in the UK with musculoskeletal diseases. Methods Patients were selected from the Biologics for Children with Rheumatic Diseases (BCRD) study, launched in 2010, an ongoing prospective UK study of biologic therapies other than the etanercept originator (followed in a separate parallel study) in JIA. Baseline information is collected via questionnaires completed by the treating physician or affiliated clinical research nurse. Follow-up data including disease activity measures and changes in drug therapy are collected at 6 months, 1 year and annually thereafter. From 30-Sept-2015, data has been captured on 3 biosimilars available in the UK: 2 infliximab and 1 etanercept biosimilar. Results To 12-Dec-2017, 58 patients were identified in the BCRD study starting a biosimilar; 48 (84%) infliximab and 10(17%) etanercept biosimilars (table 1). Of these, 36 (62%) started a biosimilaras their first biologic therapy. Seventeen (29%) switched to a biosimilar from a non-originator biologic. Five patients switched from their originator. Follow-up data ranging from 6 months to 2 years were available in 14 patients. Four patients switched to another biologic in this period, 3 switching from an infliximab biosimilar to tocilizumab, and 1 etanercept biosimilar patient to adalimumab. Two serious adverse events in a 90 day exposure window were reported, both cases of recurrent uveitis in patients on an infliximab biosimilar switching from a non-originator biologic. Conclusions Biosimilars in children and young people are used as both first-line and subsequent-line biologic therapy, although currently few UK children have been switched directly from an originator product. Whether a move towards switching all children receiving originator products to biosimilar products, as has been seen in rheumatoid arthritis, will occur is currently unknown but it is imperative that the safety of these treatment decisions are captured in patient registers. Disclosure of Interest None declared

Background EULAR guidelines recommend to treat all patients with early Rheumatoid Arthritis (eRA) with a combination of methotrexate (MTX) and a short-term course of Glucocorticoids (GC). The COBRA Slim strategy with MTX and a moderately dosed tapering down scheme of GC was effective, also in patients without classical markers of poor prognosis during the first year. Objectives To compare the outcomes of MTX with or without initial step-down GC in Low-Risk patients during the second year of the CareRA trial, in terms of disease control, safety and DMARD use. Methods CareRA is a two-year prospective investigator-initiated pragmatic multicentre RCT. DMARD naive eRA patients were stratified into a High- or Low-Risk group based on classical prognostic markers (presence of erosions, RF, anti-CCP and DAS28-CRP). Low-Risk patients (n=90) were randomised to either Tight-Step Up (TSU) with MTX 15 mg weekly without GC or to COBRA Slim, a combination of MTX 15 mg weekly and prednisone tapering down scheme starting at 30 mg, tapered to 5 mg daily from w6 and stopped at w34. A treat-to-target approach was applied until year 1 and afterwards treatment was at the discretion of the rheumatologist. Proportions of DAS28-CRP remission at year 2 was a co-primary CareRA endpoint. Secondary outcomes were efficacy according to other remission criteria, EULAR/ACR response rates and functionality measured by HAQ (ITT analysis, last observation carried forward). Adverse events (AEs) and concomitant medication were registered. Results At year 2, 67.4% of Slim and 70.2% of TSU patients were in remission according to DAS28CRP (p=0.777). Out of patients in DAS28CRP remission at year 1, 80.0% (24/30) in the Slim group, versus 69.0% (20/29) in the TSU group remained in remission at every three-monthly evaluation until year 2. Remission rates defined by Boolean criteria were higher in patients of the Slim (39.5%) versus TSU group (19.1%) (p=0.033). Functionality measured by mean area under the HAQ curve over 2 years was better in Slim patients (38.3±47.2) than in TSU patients (56.4±48.7) (p=0.025). Other secondary efficacy outcomes did not differ between the treatment arms. The total numbers of AEs reported as related to study therapy, were 69 in 34 TSU patients and 63 in 28 Slim patients. Biologicals were started in 14 Low-Risk patients (15.6%), more specifically in 8 Slim and 6 TSU patients during the CareRA trial. At the year 2 visit 62.5% of Slim patients were on MTX monotherapy and 12.5% on a combination of csDMARDs. In the TSU group 58.5% was taking MTX as only DMARD, and 19.5% took a combination of csDMARDs. Out of all Low-Risk patients 11.0% (8/73) was taking oral GC at the year 2 visit, 5 patients in the TSU group and 3 patients in Slim group, all at a low dosages. Conclusions In eRA patients lacking classical markers of poor prognosis COBRA Slim showed persistently high remission rates and good disease control 2 years after initiating therapy in a treat to target setting. COBRA slim seems to be slightly more effective than TSU according to the year 2 Boolean remission criteria and the 2 year functionality AUC but the CareRA study was not powered for this analysis. Disclosure of Interest V. Stouten: None declared, J. Joly: None declared, S. Pazmino: None declared, K. Van der Elst: None declared, D. De Cock: None declared, R. Westhovens: None declared, P. Verschueren Grant/research support from: unrestricted Pfizer chair for management of early RA

Background The goal of early rheumatoid arthritis (RA) treatment is to reach remission as soon as possible, as this initial treatment response is a strong predictor of long-term clinical outcomes. Rapidly reaching remission is not only clinically meaningful, it also matters from the patient’s perspective.1 Yet, the influence of an initial response on patients’ future psychosocial functioning remains understudied in early RA. Objectives To explore the association between the initial clinical response of patients with early RA and their psychosocial functioning after 1 year of treatment. Methods We included patients with early RA (disease duration ≤1 year) who started first-time treatment within the Care in early RA (CareRA) trial.2 Based on the speed of response defined as the response at week 16, and the stability of response evaluated from week 16 onwards until week 52 of treatment, we created 4 profiles of initial clinical response relevant to patients: persistent responders, secondary failures, delayed responders and non-responders (table 1). Having a response was defined as a disease activity score (DAS28CRP) 23.1%) only at week 52. Results The 333 included patients shared typical characteristics of an early RA population (69.5% being woman, mean(SD) age of 52.3 (13.0) years), with no differences in demographics between patients for the different response profiles. In almost all regression models, the initial clinical response profiles were identified as significant predictors for each psychosocial outcome at week 52 (table 2). A rapid and sustained response, when compared to having a relapse after initial response or a delayed response or no response at all, resulted in higher vitality, less interference with normal social activities, less problems with work or other daily activities because of emotional problems, an improved mental health, more positive beliefs about disease consequences, a higher belief in the effect of treatment, and a more coherent illness understanding. References [1] Van der Elst K, et al. Arthritis Care Res (Hoboken)2016;68(9):1278–87. [2] Verschueren P, et al. Ann Rheum Dis. 2017;76(3):511–520. Disclosure of Interest None declared

Background The CareRA trial showed that remission induction with MTX and a moderate-dose of Glucocorticoids (GC) (COBRA Slim) in a treat-to-target setting is effective and safe in early Rheumatoid Arthritis (eRA) patients. This strategy showed equally high remission rates at 52 weeks (W), a favourable safety profile compared to DMARD combinations and GC and very few patients had to start biologicals. Objectives To compare the outcome of different intensive combination treatment strategies in high-risk patients of the CareRA trial at W104, focussing on persistent disease control. Methods CareRA is a two-year prospective investigator-initiated pragmatic multicentre RCT; csDMARD naive eRA patients were stratified into a high- or low-risk group based on classical prognostic markers (presence of erosions, RF, anti-CCP and DAS28-CRP). High-risk patients (n=289) were randomized to 1/3 arms: 1) COBRA Classic (n=98): Methotrexate (MTX)+Sulphasalazine+60mg prednisone tapered weekly to 7.5mg daily from W7; 2) COBRA Slim (n=98): MTX+30mg prednisone tapered to 5 mg daily from W6; 3) COBRA Avant-Garde (n=93): MTX+Leflunomide+30mg prednisone tapered to 5 mg daily from W6. From W28, GCs were tapered in all patients and stopped at W34. A predefined treat-to-target approach was applied until W52 and afterwards treatment was at the discretion of the rheumatologist. From W40, DMARD monotherapy was aimed for. From W28 onwards patients were evaluated every 3 months till W104. Efficacy measures were proportions of DAS28-CRP remission, good EULAR response, clinically meaningful HAQ response, HAQ=0 (ITT analysis). Adverse events related to therapy (AEs) were registered. Missing data were imputed by last observation carried forward. Results Remission rates at W104 in high-risk patients were 65.3%, 73.5% and 73.1% in the Classic, Slim and Avant-Garde group respectively (p=0.369). Also, other efficacy outcomes did not differ between groups (see table). From the high-risk patients that were in remission at year 1, 54.7%, 67.8% and 70.2% in the Classic, Slim and Avant-Garde group respectively, stayed in remission at every three-monthly evaluation until w104. Also DAS28-CRP scores remained relatively stable during the second year in these groups. In high-risk patients, the total numbers of AEs reported as related to study therapy, were 209 in 72 Classic patients, 164 in 69 Slim patients and 208 in 74 Avant-Garde patients (p=0.029). Serious AEs were reported in 3 Classic, 4 Slim and 3 Avant-Garde patients. Biologicals were started in 44 high-risk patients (15.2%), of which 7 receiving 2 different biologicals and 2 receiving 3 different ones. Biologicals were administered in 18 Classic, 11 Slim and 15 Avant-Garde patients. Conclusions All groups showed persistently high remission rates 2 years after remission induction with csDMARDs and GCs in a treat to target setting. COBRA Slim showed comparable efficacy with less adverse events compared to DMARD combinations with moderate or high GC induction dosages. In almost 70% of COBRA Slim patients achieving remission at year 1, this was maintained throughout the second year. Disclosure of Interest None declared

© Springer International Publishing AG 2017. Business Process Outsourcing (BPO) enables the delegation of entire business processes to third party providers. Such scenarios involve communication between federated and heterogeneous workflow engines. However, state-of-the-art workflow engines fall short of a distributed authorisation mechanism for this heterogeneous, federated BPO setting. In a cross-organisational context, the security requirements involve (i) delegation and verification of privileges in a confidential manner, (ii) secure asynchronous operations during the long-term workflows even when the users are logged-off, and (iii) controlling access to interfaces of the different workflow engines involved. To address these challenges, we present a voucher-based authorisation architecture and middleware. We extended the WF-Interop [2] middleware with a security module to support this authorisation architecture. We further validated our contributions by prototyping a billing workflow case study on top of the extended WF-Interop middleware and evaluated the performance overhead of the security extensions to the middleware. ispartof: pages:19-35 ispartof: Lecture Notes in Computer Science vol:10379 pages:19-35 ispartof: ESSoS 2017 location:GERMANY, Bonn date:3 Jul - 5 Jul 2017 status: published

Objectives: Persons who are later diagnosed with early rheumatoid arthritis (ERA) often delay their first contact with a health professional after symptom onset. Besides initial symptoms, psychosocial characteristics of individuals may influence their help-seeking behaviour. We explored the role of disease characteristics, illness perception, and coping in patient-related delay before treatment initiation in recently diagnosed patients with ERA. Method: This exploratory, cross-sectional study included 112 patients with ERA from the Care for early RA (CareRA) trial for whom complete data on patient-related delay, coping, and illness perception were available. In addition to baseline sociodemographic and clinical data, the patients’ psychosocial profiles were assessed with the Utrecht Coping List (UCL) and the revised Illness Perception Questionnaire (IPQ-R). Correlations were measured by Spearman’s rho. Using regression analyses, we weighted the association of variables with patient-related delay. Results: Patient-related delay was positively correlated with perceptions of causality including psychological attributions (r = 0.301, p = 0.001), risk factors (r = 0.189, p = 0.045), immunity (r = 0.261, p = 0.005), and passive coping (r = 0.222, p = 0.018). It was negatively correlated with the 28 swollen joint count (SJC28; r = −0.194, p = 0.040), perceptions of treatment control (r = −0.271, p = 0.004), and illness coherence (r = −0.208, p = 0.028). Clinical and psychosocial variables explained 15% and 18%, respectively, of the variability in patient-related delay. Conclusions: Aside from a lower SJC, a longer patient-related delay was correlated with a passive coping style, a strong conviction of symptom causality, poor expected treatment control, and a feeling of limited illness coherence. Psychosocial aspects influence individuals’ help-seeking behaviour and are worth considering when aiming for a reduction in ERA treatment delay.

Now that more and more legal transactions are being performed online, it is increasingly necessary to enable integration of legal mandates within identity and information management systems. The purpose of this article is to outline the legal framework surrounding delegation and to identify basic requirements for any technical application which seeks to provide recognition to legal mandates and delegation processes. Special consideration is also given to the legal implications in situations where a (presumed) mandate holder acts without or outside his authority. Based on these considerations, this article attempts to outline an approach which can significantly reduce the potential risks for both mandate issuers and relying service providers.

PurposeModern e‐health systems incorporate different healthcare providers in one system and provide an electronic platform to share medical information efficiently. In cross‐context communications between healthcare providers, the same information can be interpreted as different types or values, so that one patient will be issued different identifiers by different healthcare providers. This paper aims to provide a solution to ensure interoperability so that multiple healthcare providers will be able to collaborate in one e‐health system.Design/methodology/approachThis paper primarily focuses on how different healthcare providers, instead of the patients, are able to interact and share information on a common e‐health platform.FindingsIn the course of the work, it was found that previous e‐health solutions mainly have a limited view of patient information, where a user‐centric approach for identity management is usually restricted to a single healthcare provider. Interoperability in an e‐health system becomes more problematic when more actors collaborate, and hence linkability from one context to another should not be straightforward. However, some form of linkability, such as the possibility to follow up a patient's medical treatment, is desirable in the e‐health sector, even when it needs to cross different contexts. Therefore, the authors have designed an identity management mechanism to ensure semantic interoperability when data is exchanged among different authorized healthcare providers.Research limitations/implicationsThe paper points out that the next generation of e‐health will move towards federated e‐health and will require user‐centricity and transparency properties so that patients are able to specify and verify the disclosure of their medical information.Originality/valueThis paper proposes a new service for cross‐context identity management in e‐health systems, improving interoperability between agencies when context‐specific information is transferred from one healthcare provider to another. How the proposed cross‐context identity management service can be integrated in an e‐health system is explained with a use case scenario.

Efficient eGovernment and eCommerce require the ability to authenticate citizens and transactions online, whereas the increasing mobility of citizens demands reliable identification. Identity documents tend to become the most popular form of identity tokens used for these purposes. An important problem, however, is that they can easily be passed on or used by a fraudster. We discuss the use of identity documents and the problem of linking these documents with their genuine holder. We discuss ePassports and eID cards in general using the Belgian identity documents as a reference.

In this article, the authors are evaluating the current authentication mechanisms for eGovernment employed in Belgium. Particular focus is placed on the Belgian electronic identity card (eID) and the use of national identification numbers. After evaluating the current situation the authors proceed to highlight possible alternative.

A wide spectrum of certificate revocation mechanisms is currently in use. A number of them have been proposed by standardisation bodies, while some others have originated from academic or private institutions. What is still missing is a systematic and robust framework for the sound evaluation of these mechanisms. We present a mechanism-neutral framework for the evaluation of certificate status information (CSI) mechanisms. These mechanisms collect, process and distribute CSI. A detailed demonstration of its exploitation is also provided. The demonstration is mainly based on the evaluation of Certificate Revocation Lists, as well as of the Online Certificate Status Protocol. Other well-known CSI mechanisms are also mentioned for completeness.

Current technology is evolving fast and is constantly bringing new dimensions to our daily life. Electronic banking systems provide us with easy access to banking services. The interaction between user and bank has been substantially improved by deploying ATMs, phone banking, Internet banking, and more recently, mobile banking. This paper discusses the security of today's electronic banking systems. We focus on Internet and mobile banking and present an overview and evaluation of the techniques that are used in the current systems. The best practice is indicated, together with improvements for the future. The issues discussed in this paper are generally applicable in other electronic services such as E-commerce and E-government.

Item does not contain fulltext OBJECTIVES: Despite the availability and demonstrated effectiveness of intensive combination treatment strategies (ICTS) for early rheumatoid arthritis (RA), a discrepancy seems to exist between theoretical evidence and actual prescription in daily practice. The purpose of this study was to explore and identify the factors influencing the prescription of ICTS. METHOD: This study involved rheumatologists and nurses participating in the Care for Rheumatoid Arthritis (CareRA) trial, a multicentre randomized controlled trial (RCT) comparing different ICTS for early RA with conventional disease-modifying anti-rheumatic drugs (DMARDs) plus step-down glucocorticoids (GCs). A qualitative study was carried out using individual semi-structured interviews. Each interview was recorded, transcribed literally, and analysed thematically. In addition, observations at outpatient clinics were used to clarify the interpretation of the results. RESULTS: We interviewed 26 rheumatologists and six nurses and observed five outpatient visits. Identified facilitators included available scientific evidence, personal faith in treatment strategy, staff support, and low treatment costs. Rheumatologists had no doubts about the value of methotrexate (MTX) but some questioned the value of combination strategy, others the effectiveness and/or the dosage of individual compounds. Additional barriers for prescribing ICTS included need for patient education, fear for patients' preconceptions, concerns about applicability to the individual patient, difficulties with breaking routine, interference with organizational structures and processes, time constraints, and lack of financial support. CONCLUSIONS: A heterogeneous set of factors highlights the complexity of prescribing ICTS for early RA in daily clinical practice. Future improvement strategies should stimulate the facilitators while at the same time addressing the barriers. The generalizability of these findings to other health care systems needs further examination.

Objectives: A treatment delay of more than 12 weeks can negatively affect treatment response in rheumatoid arthritis (RA). Our aim was to quantify the different stages of delay before RA treatment in different rheumatology centres and to explore influencing factors. Method: A total of 156 disease-modifying anti-rheumatic drug (DMARD)-naive early RA patients were included from eight practices: one academic hospital, five general hospitals, and two private practices. Eight different types of delay were defined from symptom onset until treatment initiation. Information on the duration of each stage of delay was collected from the patient, their general practitioner (GP), and patient files at the rheumatology practice. Patient/GP demographics and disease activity/severity parameters were recorded. Results: The median total delay from symptom onset until treatment initiation was 23 weeks whereas patient-, GP- and rheumatologist-related median delay was 10, 4, and 7 weeks, respectively. Only 21.6% of the patients had a total delay of less than 12 weeks. The total median delay in private rheumatology practices was less than in academic and general hospitals (p < 0.001). Furthermore, RA patients treated within 12 weeks of symptom onset showed a higher level of disease activity. The duration of rheumatologist-related delay was inversely correlated with disease activity parameters. Patients with morning stiffness were treated, on average, 3 weeks sooner than those without morning stiffness (p < 0.006). Conclusions: In only one out of five early RA patients was treatment initiated within 12 weeks of symptom onset, as recommended. Patient-related delay contributed most to overall delay. Disease activity and type of rheumatology centre are pivotal determinants of delay.

Background The (Care in Early RA) CareRA trial compared different treatment strategies in patients with early Rheumatoid Arthritis (ERA) with or without markers of poor prognosis. No significant differences were shown between the treatment arms in terms of remission rate and functionality at 16 and 52 weeks. The differential cost-effectiveness of these therapeutic strategies could aid in determining the optimal approach for ERA. Objectives To compare the cost-effectiveness of different therapeutic strategies used in the CareRA trial during the first treatment year in patients with early Rheumatoid Arthritis. Methods The CareRA trial is a 2-year investigator-initiated randomized pragmatic superiority trial comparing remission induction regimens in a treat-to-target approach. DMARD naive ERA patients were stratified into a high- or low-risk group based on prognostic markers. High-risk patients were randomized to a COBRA Classic (Methotrexate (MTX) + Sulphasalazine + prednisone step-down from 60mg), COBRA Slim (MTX + prednisone step-down from 30mg) or COBRA Avant-Garde (MTX + Leflunomide + prednisone step-down from 30mg) scheme. Low-risk patients were randomized to MTX tight step-up (MTX-TSU) or COBRA-Slim. The direct costs for each patient in the trial were calculated by summing the cost of a rheumatology consultation, per protocol CareRA study medication and RA-related medication such as biologicals and extra glucocorticoids not stipulated in the protocol. The incremental cost-effectiveness ratio (ICER) was calculated using these costs and the treatment efficacy as observed in CareRA. Efficacy parameters investigated were the proportion of patients in remission (DAS28(CRP) 0.22) at week 52. Results 349 out of 379 patients had sufficient cost information to be evaluated at week 52. Remission was achieved in 65,6% Classic, 61.7% Slim (high-risk) and 64.1% Avant-Garde patients; and in 56.8% MTX-TSU and 70.0% Slim (low-risk) patients. A clinically meaningful HAQ response was reached in 66.7% Classic, 70.2% Slim (high-risk) and 75.6% Avant-Garde patients; and in 58.3% MTX-TSU and 60.0% Slim (low-risk) patients. Mean ±SD total costs during year one were €1044.3 ± €871.0 €859.7 ±€431.3 and €1267.7 ±€632.7 for the Classic, Slim (high-risk) and Avant-Garde respectively; and €880.6 ±€917.4 and €867.5 ±€364.0 for MTX-TSU and Slim (low-risk) patients. In MTX-TSU patients, the high average cost ±SD of €268.6 ±€876.5 was remarkable. Cost-effectiveness analysis in the high-risk arm showed a higher ICER for Classic (€47.3/1% remission) and Avant-Garde (€170.0/1% remission) compared to Slim (high-risk); In the low-risk arm, the cost-effectiveness of MTX-TSU was shown to be comparable to Slim (low-risk), with an ICER of €-0.99/1% remission. Conclusions Cobra Slim, a combination of MTX with a moderately dosed glucocorticoid remission induction showed favorable cost-effectiveness in both ERA patients with or without poor prognosis. Disclosure of Interest None declared

Background Glucocorticoids (GCs) can rapidly reduce disease activity in many chronic inflammatory diseases. Numerous adverse events have been attributed to GCs. One of the most commonly mentioned and feared side effects is an increase in weight and BMI, especially with chronic GC use. However, data remains scarce about the impact of short term glucocorticoid remission induction schemes on BMI in patients with Early RA (ERA). Objectives To explore the BMI evolution of patients with ERA treated with short term glucocorticoid remission induction schemes in the (Care in Early RA) CareRA trial. Methods The CareRA trial is a RCT comparing remission induction regimens in a treat-to-target approach. DMARD naive ERA patients were stratified into a high- or low-risk arm based on classical prognostic markers. High-risk patients were randomized to COBRA Classic (Methotrexate (MTX) + Sulphasalazine + prednisone step-down from 60mg), COBRA Slim (MTX + prednisone step-down from 30mg) or COBRA Avant-Garde (MTX + Leflunomide + prednisone step-down from 30mg) scheme. Low-risk patients were randomized to MTX tight step-up (MTX-TSU) without oral GCs or COBRA Slim. Prednisone was tapered down over 6 weeks to 7.5mg in Classic and 5mg in the other COBRA arms. Oral GCs were discontinued from Week 28 and stopped at week 34. Demographics including BMI and disease parameters were routinely registered. For this analysis, only patients with all BMI parameters on all study visits during the first 52 treatment weeks were included. BMI change per group was tested with a paired t-test. Differences in BMI change between groups were tested with a student9s t-test, Spearman9s rho was used for correlation between variables of interest and BMI change. Finally, an adjusted linear regression model further explored the effect of treatment choice on BMI change. Results 281 Of 379 patients were included. Figure 1 describes the evolution of BMI over 52 weeks for the different treatment strategies. Only patients on Cobra Classic had an increase in BMI after 52 weeks (p=0.003). In the High-Risk arm, change in BMI over 52 treatment weeks was larger in Classic versus Slim (High-Risk) (p Conclusions In general, BMI changes were small with any treatment strategy. A statistically significant increase in BMI over 52 weeks was only seen with a remission induction scheme starting at a high GC dose in patients with poor prognosis ERA. No difference in BMI change over 52 weeks was seen between a remission induction scheme starting at a moderate GC dose and a treatment strategy without oral GCs in patients with good prognosis ERA. Disclosure of Interest None declared