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Background:Recently, the interest and research in artificial intelligence (AI) in healthcare has increased exponentially [1, 2]. AI encompass the development of computer systems or software that can perform tasks that typically require human intelligence [3]. These tasks include learning, reasoning, problem-solving, understanding natural language, speech recognition, and visual perception [3]. But, what is the landscape of AI in Rheumatology? What type of tasks is AI comprising in two of the areas with greater research, namely rheumatoid arthritis (RA) and spondyloarthritis (SpA)? What is the level of validation and adequacy?Objectives:To analyse the uses, type of research and its quality, of AI in RA and SpA.Methods:We performed a systematic review (SR) using a standardised, reproducible approach, following the Cochrane dual-reviewer methodology, and observing the PRISMA statement (PROSPERO CRD42023396462). The protocol was established by a group of rheumatologists experts in digital health tools, who defined the research question (PICO) and the data to be collected. We searched for articles that analysed the characteristics, efficacy, safety or validity of any digital health technology in RA and SpA (including psoriatic arthritis; PsA). Two expert Librarians established a sensitive search strategy in Medline, Embase and the Cochrane databases (up to December 2022), using MeSH and free text terms. By study type, SRs, randomized controlled trials (RCTs) and observational studies were eligible. A hand search was completed by reviewing the references of the included studies, plus publications and other information provided by the experts. Two reviewers selected the studies and collected the data. To grade the quality of included studies, we used the PROBAST (Prediction model Risk Of Bias Assessment Tool) and AMSTAR 2 (A Measurement Tool to Assess Systematic Reviews) tools. The information gathered included country, data source, application of AI, and type of algorithms.Results:The global search included 560 studies of which 84 met the criteria. Two were SRs, 8 RCTs and 74 observational studies. Most of the included studies were carried out in the United States of America. We found a great variability by type of AI, data sources, and studied samples. By type of AI algorithm, 34 studies used multiple models, 10 artificial neural networks, and 10 random forest. By disease, 54 studies were focused on RA, 14 on axSpA/pSpA, of which 6 were on PsA and 10 on rheumatic diseases in general but including patients with RA or SpA. The applications of AI were medical diagnosis in 21 studies, prognosis in 39 and prediction of treatment response in 24. No implementation studies were found.Regarding the quality of the AI-based models, we identified several limitations that hinder reliable assessment of the models including the lack of specific guidelines about an objective methodology for the design and validation of the model, lack of flexibility, the handling of many variables, and the underreporting of results (see Figure 1 for detailed quality according to the PROBAST scale).Figure 1.PROBAST quality scaleConclusion:Numerous AI-based models and applications have been developed for RA and SpA, especially in the areas of diagnosis, prognosis and treatment response; however, they still show deficiencies, highlighting the need for better critical appraisal.REFERENCES:[1] Bergier H, Duron L, Sordet C, Kawka L, Schlencker A, Chasset F, et al. Digital health, big data and smart technologies for the care of patients with systemic autoimmune diseases: Where do we stand? Autoimmun Rev. 2021;20(8):102864.[2] Solomon DH, Rudin RS. Digital health technologies: opportunities and challenges in rheumatology. Nat Rev Rheumatol. 2020;16(9):525-35.[3] Russell S, Norvig P. Artificial Intelligence: A Modern Approach: Prentice Hall Press; 2009.Acknowledgements:NIL.Disclosure of Interests:Diego Benavent: None declared, Loreto Carmona: None declared, Jose Francisco Garcia LLorente: None declared, Maria Montoro Full-time employee of Pfizer, SUSAN RAMIREZ Full-time employee of Pfizer, Teresa Oton: None declared, Estíbaliz Loza: None declared, Antonio Gómez-Centeno: None declared

Background:Immune checkpoints inhibitors (ICI) cancer immunotherapy target specific molecules of the immune system to block the mechanisms that regulate the immune tolerance, enhancing the immune system’s response against tumor cells. Although these treatments have acceptable safety profiles, an increase in the occurrence of immune-related adverse events (irAEs) has been identified. IrAEs can affect any organ and system, with a wide range of manifestations and severity. Regarding rheumatic manifestations (R-irAEs), arthritis, myositis, polymyalgic syndrome, and others are being reported.Objectives:Our aim was to characterize a cohort of patients treated with ICIs that develop R-irAEs.Methods:An observational, descriptive study, including 734 patients treated with ICIs at Parc Taulí and Marqués de Valdecilla University Hospitals, between 2016 and 2022. Medical records were reviewed by a rheumatologist to identify possible manifestations compatible with R-irAEs.Results:734 patients treated with ICIs were analyzed. 227 (30.9%) presented irAEs, of which 54 (7.35%) were R-irAEs, (29 male/26 female), with an average age of 64.6±11.5 years at the starting of ICI treatment. Only 4 patients presented previous autoimmune diseases. Underlying cancer types included lung (n=24), melanoma (n=18), colorectal (n=4), renal (n=3), urothelial (n=3), gastric and hepatic (n=1), and oral cavity (n=1). 50 patients received ICIs as monotherapy. Average time from starting ICI treatment to onset of R- irAE was 18.0±35.6 weeks.Clinically, patients presented as PMR-like (n=12), AR-like (n=10), unspecified arthralgia (n=9), unspecified arthritis (n=7), myositis (n=5), sicca syndrome (n=5), psoriatic arthritis (n=3), large vessel vasculitis (n=2), spondylarthritis (n=1). Demographic and clinic characteristics are summarized in Tables 1 and 2.Elevated C-reactive protein (CRP) was detected in 18/21 patients, and altered erythrocyte sedimentation rate (ESR) in 8/10 patients. Autoantibody testing was positive in 11/40 patients, being the most frequent ANA positive (n=5; 3 with homogeneous pattern).38 patients received corticosteroids, of those, 3 also required immunosuppressive (IS) synthetic drugs, 2 required IS biologic drugs and 4 required intravenous immunoglobulins. 27/39 responded favorably, with improvement in symptoms and no relapses. 18 patients had to stop their ICI treatment due to their R-irAEs.Conclusion:The increasing use of ICIs in cancer treatment has led to an increase in irAEs. Moreover, irAEs (30.9%) and R-irAEs (7.35%) are relatively frequent. The most common R-irAEs are PMR-like (21.8%) and AR-like syndromes (18.2%). Analytically R-irAEs are characterized by high CPR (85%) and/or ESR (80%) and negative immunological tests. Although many patients respond favorably to treatment, 18 (33.3%) patients had to stop their ICI due to R-irAEs. Myositis appears as a characteristic disease, with faster onset, higher morbimortality and the need for intensive treatment, as seen in previous studies. More studies are needed to assess the long-term outcomes in these patients and the impact of IS treatment on cancer survival.REFERENCES:NIL.Table 1. Demographic and clinic data of ICI treated patients that develop R-irAEs.Table 2. Clinical characteristics of patients with rheumatologic irAEs.Acknowledgements:NIL.Disclosure of Interests:None declared.

Background:The emergence of immune checkpoint inhibitors (ICI), a type of immunotherapy, has revolutionized the treatment of many malignant neoplasms. However, immune-mediated adverse events have often been reported. Among them, ICI-related myositis is one of the most serious and difficult-to-treat complications.Objectives:To describe the clinical features, management and outcome of patients with ICI-related myositis.Methods:National Observational multicenter study from clinical practice of ICI-related myositis reported between 2016 and 2023. We reviewed demographic, clinical features, treatment and outcomes. In addition, we conductress a literature review in PubMed, Embase and the Cochrane library from their inception up to 31 December 2023.Results:We present 7 patients (2 women, 5 men), mean±SD age 77.1± 7.0 years, with ICI-related myositis. The most common malignancy was melanoma (n=4), followed by renal cell carcinoma (n=1), urothelial carcinoma (n=1) and rectal cancer (n=1). Patients received the following ICI therapy: pembrolizumab (n=3), nivolumab (n=2), atezolizumab (n=1) and durvalumab (n=1). Myocarditis and miastenia gravis (MG) were also present in 28.6% and 42.9% of patients, respectively. Other adverse events included: hepatitis (n=3), pneumonitis (n=1), encephalitis (n=1), thyroiditis (n=2), diarrhea (n=1) and toxicoderma (n=1). A marked elevation of CK was observed in all patients (median[IQR]: 3023[1990-3500] U/L). Treatment consisted of ICI discontinuation and immunosuppressive agents: all received oral glucocorticoids, IVIG (n=4), mycophenolate (MMF) (n=2), rituximab (RTX) (n=1), tocilizumab (TCZ) (n=1). Most of the patients (5/7) improved, two patients died. In the literature review (Table 1), we found 124 patients (31 women/93 men, mean±SD 69.7±5.1 age). The most frequent malignancy was melanoma and the most common ICI pembrolizumab. The prevalence of myocarditis and MG varies widely among the different studies. Therapeutic strategies included glucocorticoids in almost all patients, plasma exchange (n=26), IVIG (n=60), conventional DMARDs [MTX (n=5), MMF (n=5), AZA (n=1)] and biologics [IFX (n=8), RTX (n=8), TCZ (1)]. Most of patients improved, but death related to myositis were reported in 20 (17.7%) of patients.Conclusion:Our study highlights that ICI-related myositis is a severe adverse event of ICI that needs early treatment including ICI discontinuation and immunosuppressive therapy.Table 1.REFERENCES:NIL.Acknowledgements:NIL.Disclosure of Interests:None declared.

Background:Immune-related adverse events (irAEs), including inflammatory arthritis (IA), have become a subject of increasing interest within the rheumatology community. Unraveling the prognosis and treatment needs for individuals experiencing ICI-induced arthritis remains a complex task, as outcomes can vary widely among patients.Objectives:To analyse the clinical presentation, treatment response, and outcomes of IA induced by immune checkpoint inhibitors (ICIs) in patients with cancer.Methods:Retrospective observational study conducted from January 2015 to December 2023 at four tertiary university hospitals.Results:We included 119 patients (63% male) with a mean age at diagnosis of 66 ± 11 years. The primary underlying cancers were lung (41%), melanoma (18.5%), renal-urothelial (12.6%), hematologic (6%), and other neoplasms (6%). ICIs comprised monotherapy (91%) and combined regimens (9%). In the monotherapy group, most patients received PD-1/PD-L1 inhibitors, with only one case receiving a CTLA-4 inhibitor. Thirteen patients (11%) underwent additional oncologic treatments.Nine patients (7.5%) developed other rheumatic irAEs, including sicca syndrome (9 cases), myositis (1 case), and sarcoidosis (1 case), while 41 (34.4%) experienced one or more non-rheumatic irAEs, usually before or simultaneously with rheumatic syndromes.Of the 119 patients, 83 (70%) developed peripheral arthritis, and 36 (30%) exhibited a polymyalgia rheumatica (PMR)-like syndrome.Among patients with peripheral arthritis, the median time from cancer diagnosis to ICI initiation was 6 months (IQR 25th–75th percentile: 1.8–14.0 months), and from ICI initiation to joint involvement was 127 days (IQR 51–242 days). Patients receiving combined therapy tended to develop symptoms earlier than those on monotherapy. IA manifestations included polyarthritis (53 cases), oligoarthritis (24 cases), and monoarthritis (6 cases). The final diagnoses were undifferentiated arthritis in 53 (44.5%) patients, rheumatoid arthritis (RA)-like in 19 (16%), psoriatic arthritis-like in 8 (7%) and reactive arthritis-like in 3 (2.5%). Immunological markers showed positive ANA in 23.7% (14/59) and positive RF and ACPA in 3.3% (3/59).IA treatments included the use of NSAIDs in 58% (48/83) of cases, GCs in 96% (80/83), HCQ in 44.5% (37/83), MTX in 12% (10/83), SSZ in 1.2% (1/83) and anti-TNF in 1.2% (1/83).The median follow-up time for patients with arthritis was 9 months (IQR 3.4–16). At the last visit, ICIs had been discontinued in 55.4% (46/83) of patients. Thirty-six percent (30/83) achieved sustained drug-free remission (SDFR), while the rest (64%, 53/83) continued treatment.Among the 36 patients with PMR-like syndrome, the median time from cancer diagnosis to ICI initiation was 2 months (IQR 0.5–5.5 months), and from ICI initiation to PMR onset was 118 days (IQR 59–219 days). Besides GCs, 17% (6/36) were on steroid-sparing agents (MTX, leflunomide, or HCQ). The median follow-up was 12.4 months (IQR 5.2–21). ICIs were discontinued in 33.3% (12/36) of these patients, with 35% (11/36) achieving SDFR, while 69.5% (25/36) remained on treatment.Conclusion:The most frequent patterns of IA induced by ICIs are undifferentiated arthritis (44.5%), PMR-like syndrome (30%), and RA-like (16%). Forty-five percent of patients required a csDMARD/bDMARD. At the last follow-up, 65% of cases remained with active arthritis, either persistent or presenting intermittent flares.REFERENCES:NIL.Acknowledgements:NIL.Disclosure of Interests:José A Gómez-Puerta Astra-Zeneca, GSK, Galápagos, Lilly, Pfizer, Otsuka, Sanofi, Arturo Llobell: None declared, Andrés Ponce: None declared, Antonio Gómez-Centeno Abbvie, Galápagos, Lilly, Pfizer, Ana Milena Millán Arciniegas: None declared, Héctor Corominas Abbvie, Amgen, Galápagos, Lilly, Pfizer, Sanofi, Joan Miquel Nolla: None declared, Javier Narváez Boehringer Ingelheim, GSK, Pfizer.

Background:Baricitinib (BARI) and tofacitinib (TOFA) are Janus kinase inhibitors (JAKi) approved for treating rheumatoid arthritis (RA). Phase II clinical trials have shown a significant dose-response relationship for JAKi. However, there’s a lack of studies analyzing the correlation between blood drug levels and clinical response in RA [1].Objectives:To evaluate the precision of drug plasma levels in discerning the clinical disease status of RA patients receiving BARI and TOFA.Methods:Multicenter, non-interventional prospective study involving RA patients receiving BARI or TOFA, according to clinical judgment. Patients were enrolled during their first follow-up visit after initiating JAKi treatment (at 12-16 weeks). The primary endpoints was to determine the accuracy of drug plasma levels in discerning clinical disease status based on the Clinical Disease Activity Index (CDAI). BARI and TOFA levels were determined simultaneously by liquid chromatography tandem mass spectrometry (LC-MS/MS)[2]. C max (after 45min of drug administration) and C min (just before drug intake) was analysed in each patient.Results:Fourty-nine patients (84% female, 86% seropositive (RF and/or ACPA), mean age 54 ± 12.9 years and mean RA duration 10±8.4 years) were included: 44 received BARI and 5 TOFA. The mean number of previously administered biological DMARDs was 1.1±1.5. Three patients had received previous treatment with another JAKi. The mean DAS28 and CDAI at JAKi initiation were 4.63±1.25 and 21.6±9.0, respectively. At the 12–16-week visit, 37 patients (75.5%) achieved remission or low disease activity according to CDAI, with a mean DAS28 and CDAI of 2.62±1.25 and 8.0±7.2, respectively (Table 1). Table 2 summarizes the mean drug plasma levels according to CDAI score. Drug plasma levels (both Cmax and Cmin) showed similar results in patients with different disease activity statuts according to CDAI, without significant differences. However, the two patients treated with BARI and high disease activity showed the lower drug levels, although the difference was not significant.Conclusion:In this preliminary study, no clear dose-response relationship was found between plasma JAKi levels and disease activity in RA. However further studies including patients with moderate/high disease activity are needed to assess the potential usefulness of evaluating plasma drug levels as indicator of the clinical status of RA patients undergoing treatment with BARI and TOFA.REFERENCES:[1] Kremer JM, Cohen S, Wilkinson BE, Connell CA, French JL, Gomez-Reino J, et al. A phase IIb dose-ranging study of the oral JAK inhibitor tofacitinib (CP-690,550) versus placebo in combination with background methotrexate in patients with active rheumatoid arthritis and an inadequate response to methotrexate alone. Arthritis Rheum 2012;64:970-81.[2] Koller D, Vaitsekhovich V, Mba C, Steegmann JL, Zubiaur P, Abad-Santos F, et al. Effective quantification of 11 tyrosine kinase inhibitors and caffeine in human plasma by validated LC-MS/MS method with potent phospholipids clean-up procedure. Application to therapeutic drug monitoring. Talanta 2020;208:120450.Acknowledgements:NIL.Disclosure of Interests:Beatriz Frade-Sosa received support for attending meetings and/or speaker honoraria from Pfizer, AbbVie, Lilly, BMS, Galápagos, Sandoz and GSK., Chafik Alejandro Chacur: None declared, Jose Inciarte-Mundo Current employee at Astrazeneca., Cristina Valero: None declared, Marta Novella-Navarro: None declared, Helena Borrell Paños: None declared, Águeda Prior-Español: None declared, Eduard Graell: None declared, Pablo Zubiaur: None declared, Gonzalo Villapalos: None declared, Nuria Sapena: None declared, Lola Tobalina: None declared, Antonio Gómez-Centeno: None declared, Lourdes Mateo: None declared, Alejandro Balsa: None declared, Sara Marsal Barril: None declared, Rosario Garcia-Vicuña: None declared, Raimon Sanmarti: None declared.

The objective of the study was to analyze the prognostic factors of radiographic progression in a series of patients with early rheumatoid arthritis (RA) after 2 years of therapy with a structured algorithm using disease-modifying antirheumatic drugs (DMARDs) and very low doses of oral glucocorticoids. One hundred and five patients (81% female) with early RA (disease duration <2 years) treated with the same therapeutic protocol using gold salts and methotrexate in a step-up strategy, together with methylprednisolone (4 mg/day), were followed up for 2 years. The outcome variable was radiographic progression after 2 years of DMARD therapy using the modified Larsen method. Clinical, biological, immunogenetic, and radiographic data were analyzed at study entry and after 1 and 2 years of follow-up. Radiographic progression (increase of four or more units in the Larsen score) was observed in 32% of patients after 2 years of follow-up. The percentage of erosive disease increased from 18.3% at baseline to 28.9% at 12 months and 44.6% at 24 months, in spite of a significant improvement in disease activity. New erosions appeared in 33% of patients after 2 years. Several baseline parameters were associated with radiographic progression in the univariate analysis: shared epitope (SE) homozygozity, HLA-DRB*04 alleles, female gender, hemoglobin, erythrocyte sedimentation rate, and anticyclic citrullinated peptide antibodies (anti-CCP). In the multivariate analysis, female gender [odds ratio (OR) 5.5, 95% confidence interval (CI): 1.1-28.2, p = 0.04], DRB1*04 alleles (OR 3.1, 95% CI 1.1-9, p = 0.03) and, marginally, anti-CCP antibodies (OR 3.6, 95% CI 0.9-14.5, p = 0.06), were associated with progression. Female patients with both DRB1*04 alleles and anti-CCP antibodies showed the highest scores in radiographic progression. The presence, but not the titer, of anti-CCP antibodies predicted progression. The positive predictive value of the multivariate model for progression was only 53.9% whereas the negative predictive value was 80.3%. In a series of early RA patients treated with a structured algorithm using DMARDs and very low doses of glucocorticoids, radiographic progression was observed in one third of patients after 2 years. Female gender, DRB1*04 alleles (rather than the SE), and the presence of anti-CCP antibodies at baseline (independently of the titer) were the most important predictors of progression. The utility of these parameters in clinical practice is limited by their relatively low positive predictive value.

The Janus kinase-1 preferential inhibitor filgotinib (FIL) improved signs and symptoms of rheumatoid arthritis (RA) in the FIL clinical program.1–3 To assess FIL safety across regions. This was an analysis of patients (pts) meeting 2010 ACR/EULAR RA criteria in pooled phase (P)2 DARWIN 1–2 (D1–2), P3 FINCH 1–3 (F1–3), and long-term extension studies (DARWIN 3, FINCH 4). Data were analyzed by region: North America, South and Central America, Western Europe, Eastern Europe, Asia, South East (SE) Asia, and Other. Week (W)12 placebo (PBO)-controlled analysis included data from pts receiving once-daily FIL 100 mg (FIL100), FIL 200 mg (FIL200), or PBO for ≤12W (D1–2, F1–2); long-term as-treated data included pts from all 7 studies receiving FIL100 or FIL200; data after rerandomization were included and contributed to treatment received. Data presented as exposure-adjusted incidence rates (EAIRs)/100 patient-years of exposure (PYE) of treatment-emergent (TE) adverse events (TEAEs). Table 1 shows EAIRs of TEAEs in PBO-controlled analysis. EAIRs/100 PYE of all TEAEs in Western Europe, Asia, and Other were higher than in remaining regions and for PBO vs FIL arms; EAIRs for FIL200/FIL100 in North America and SE Asia were higher vs PBO. EAIRs/100 PYE of TE serious AEs were higher in SE Asia for FIL100 and for FIL200/FIL100 in Other, with high PBO EAIRs in Western Europe. EAIRs/100 PYE of TEAEs leading to study discontinuation were higher in FIL arms vs PBO in Western Europe and Other (FIL200); in Asia and SE Asia, EAIRs were higher for PBO vs FIL200/FIL100. [Display omitted] EAIRs for SI were highest in Other for FIL200 and SE Asia for FIL100. While VTE EAIRs were low, pts in 5/7 regions had VTE. HZ EAIRs were highest in Asia. Although EAIR of TEAEs varied between regions, no consistent trend was reflected in any particular region. [1]Genovese et al. JAMA. 2019;322:315–25. [2]Westhovens et al. Ann Rheum Dis. 2021; online first. [3]Combe et al. Ann Rheum Dis. 2021; online first. Bernard Combe Speakers bureau: BMS; Eli Lilly & Co.; Gilead Sciences, Inc.; MSD; Pfizer; Roche-Chugai; and UCB, Consultant of: AbbVie; Eli Lilly & Co.; Gilead Sciences, Inc.; Janssen; Pfizer; Roche-Chugai; and Sanofi, Grant/research support from: Novartis, Pfizer, and Roche-Chugai, Tsukasa Matsubara Speakers bureau: Pfizer Japan, Nichi-Iko, Astellas, Meiji Seika, Bristol-Myers Squibb, AbbVie GK, Janssen, Chugai, Eisai, AYUMI, Alena Pechonkina Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., YingMeei Tan Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Zhaoyu Yin Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Jaehyung Hong Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Robin Besuyen Shareholder of: Galapagos, BV, Employee of: Galapagos, BV, Antonio Gomez-Centeno Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly & Co., Gebro, Janssen, Menarini, Merck Sharp & Dohme, Pfizer, Roche, Rubio, Sanofi, and UC, Consultant of: AbbVie, Biogen, Bristol-Myers Squibb, Celgene, Eli Lilly & Co., Gebro, Gilead Sciences, Inc., Hospira, Merck Sharp & Dohme, Pfizer, Roche, Rubio, Sandoz, Sanofi, Grant/research support from: Boehringer Ingelheim, Celltrion, Eli Lilly & Co., Galapagos NV, Gilead Sciences, Inc., Novartis, Pfizer, Roche, Sanofi, UCB, YL Biologics, Maya H Buch Speakers bureau: AbbVie; Eli Lilly and Company; Gilead Sciences, Inc.; Merck-Serono; Pfizer; Roche; Sandoz; Sanofi; and UCB, Consultant of: AbbVie; Eli Lilly and Company; Gilead Sciences, Inc.; Merck-Serono; Pfizer; Roche; Sandoz; Sanofi; and UCB, Grant/research support from: AbbVie; Eli Lilly and Company; Gilead Sciences, Inc.; Merck-Serono; Pfizer; Roche; Sandoz; Sanofi; and UCB Table 1EAIR of TEAEs (placebo-controlled)North AmericaN = 481South and Central AmericaN = 350Western EuropeN = 141Eastern EuropeN = 933AsiaN = 236South East AsiaN= 135OtherN = 70TEAEFIL200a216.9 (162.5, 289.5)205.6 (155.1, 272.6)285.0 (188.6, 430.8)150.3 (119.3, 189.4)248.9 (180.6, 343.1)165.1 (104.0, 262.1)298.4 (150.3, 592.5)FIL100b182.2 (136.8, 242.7)159.2 (117.3, 216.1)285.7 (183.7, 444.3)146.4 (115.9, 185.0)246.9 (180.3, 338.1)153.7 (94.2, 251.0)263.5 (113.9, 609.2)PBOC174.5 (130.3, 233.7)162.1 (118.8, 221.2)314.9 (200.7, 493.9)148.4 (117.6, 187.4)259.0 (188.0, 356.8)81.6 (40.8, 163.3)306.0 (142.8, 655.7)TE serious AEFIL200a14.3 (6.0, 34.4)11.4 (3.7, 35.5)8.3 (1.2, 59.0)12.2 (5.2, 28.7)5.5 (0.8, 38.9)0.0 (0.0, ∞)49.6 (10.2, 144.9)FIL100b10.6 (4.0, 28.3)7.2 (1.8, 28.7)19.9 (5.0, 79.7)15.1 (6.8, 33.7)16.2 (5.2, 50.2)28.8 (9.3, 89.4)20.5 (0.5, 114.0)PBOC16.1 (7.2, 35.9)7.5 (1.9, 30.0)29.6 (9.5, 91.7)4.6 (1.3, 15.8)11.4 (2.8, 45.5)10.2 (1.4, 72.4)0.0 (0.0, 69.2)TEAE leading to discontinuationFIL200a8.6 (2.8, 26.6)3.8 (0.1, 21.2)16.6 (4.2, 66.5)12.9 (5.5, 30.5)0.0 (0.0, 20.2)9.2 (1.3, 65.1)16.5 (0.4, 92.1)FIL100b10.6 (4.0, 28.3)7.2 (0.9, 26.0)19.9 (5.0, 79.7)1.9 (0.2, 13.8)5.4 (0.1, 30.1)9.6 (1.4, 68.2)0.0 (0.0, 75.5)PBOC5.4 (1.3, 21.5)0.0 (0.0, 13.8)9.9 (1.4, 70.0)12.9 (5.4, 30.7)17.1 (3.5, 49.9)20.4 (5.1, 81.6)0.0 (0.0, 69.2)Data presented as EAIR (95% CI)/100 patient-yearsaN = 777, 179.8 PYE bN = 788, 181.6 PYE cN = 781, 178.4 PYEA subject may contribute to more than one treatment group if they received more than one treatment of interest.EAIR and corresponding 95% CI were estimated using Poisson regression model by treatment, including study and treatment with an offset of natural log of exposure time, except when 0 events occurred; Poisson model was not adjusted by study.AE, adverse event; CI, confidence interval; EAIR, exposure-adjusted incidence rate; FIL, filgotinib; PBO, placebo; PYE, patient-years of exposure; TE, treatment-emergentFigure shows serious infections (SI), venous thromboembolism (VTE) and herpes zoster (HZ) EAIRs.

Evolving the management of rheumatoid arthritis (eRA) is a European-wide educational initiative aiming to support improved patient care through practical and educational tools addressing specific unmet needs. The aims of the eRA program were: (1) To identify priority unmet needs with the greatest impact on disease outcomes; (2) To develop practical, educational and guidance tools in line with EULAR recommendations to address identified unmet needs; and (3) To improve RA management and patient care. To describe the process by which local adaptations were made of materials derived from evidence-based recommendations in a training programme in rheumatoid arthritis (RA). A multidisciplinary Steering Committee (17 members, 12 countries) identified unmet needs within the management of RA and prioritised those with the greatest impact on patient outcomes. Practical educational tools addressing priority needs were then developed for dissemination and implementation by the rheumatology community across Europe, including shared decision making practises and a checklist for managing comorbidity in RA, among others. These materials were evaluated in detailed and discussed in small regional groups by practicing rheumatologists. Voting, open discussions and recommendations were extracted from the meetings. Thirty-five Spanish rheumatologists from diverse geographic regions discussed a comorbidity checklist and a shared decision making tool. The results of the local meetings were synthesised as (1) a judicious commitment to check agreed comorbidities, and (2) a list of barriers and facilitators for the implementation of shared decision making at the local settings. With regards to ways to implement the agreed list and periodicity, two issues standed-out: (1) patient education and (2) the need of easy access to information and the use of local organisational systems in place. With respect to shared decision-making, issues raised included messages for self-awareness, challenges, and practical facilitators. Discussion, adaptation, and planning are needed before implementing any evidence-based recommendation and materials if we want to achieve a successful implementation. Further studies should demonstrate whether this initiative was successful in achieving the goals of improved patient care. Our experience could be used as a guidance or example for implementation elsewhere. None declared

I am a rheumatologist working in public and private practice without formal background in computer science but with a special interest in software applications (apps) with the potential to streamline my work while preserving quality of care. I will present an overview of some of problems that i faced and some apps that have helped me to address these problems. File organization and access:Most of us use more than one computer each day, and probably a smartphone and lately a tablet. Inevitably, this results in the creation of multiple versions of the same file on more than one device. Despite that many choose to juggle with pen drives to try and keep files in synch there are apps like “Dropbox”, “Skydrive” or “Google Drive” that may help us to access from wherever and keep synch our files. Information overload: It is almost impossible to keep up with the volume of available news and information. One possible solution to help with this information overload issue is to use Feed/RSS readers. Feeds or RSS (Really Simple Syndication) are essentially Website broadcasts in which users can retrieve information and articles from sites of interest all in one place. To access my subscribed Feeds/RSS, I use Google Reader™, a Web-based service accessible from any computer browser. Every user can subscribe to any number of Feeds/RSS and organize them according to context (ie, internal medicine journals, rheumatology journals, other medical journals, and also general news, sports, etc.). Information capture: Ideas pop up at the most inconvenient and unexpected times, especially when you don’t have a means of jotting them down. Being able to capture them at any time or when you are browsing may be very useful. Another need faced by clinicians is archiving online content for future reference, which can be a cumbersome process. To address both of these issues, is very useful a service called Evernote®. Evernote® allows users to capture almost all information either with your computer, smartphone or tablet. After installing this app on a mobile device and computer, users can immediately archive anything they see, hear or think and keep access to this information in all their devices. Indices calculation and aid to fill in electronic medical records: Often, in rheumatologic clinical practice is required calculations of activity indices (like DAS, SDAI, SLEDAI etc), and of course, electronic medical records should be filled. Several applications may be useful for these purposes. I will highlight calculators for rheumatoid arthritis as RAcalculator, APs Smart calculator for psoriatic arthritis, available in both iOS and Android version. Another interessant application is Rhediant (available for free), which allows the indices calculation and fill in EMR. These are only some needs I face in my daily clinical practice, along with some of solutions that I use. Apps for computers, tablets and smartphones may help us to find solutions for our needs. There is apps almost for everything. Just have to look for. Disclosure of Interest None Declared

Background:Sarilumab is a human mAb blocking IL-6Rα. In Phase 3 MONARCH (NCT02332590), sarilumab (200 mg subcutaneously [SC] every 2 wks [q2w] for 24 wks) was superior to adalimumab monotherapy (40 mg SC q2w) in reducing disease activity and improving physical function in RA patients (pts) with an inadequate response or intolerance to methotrexate.Objectives:To assess whether pts who achieved clinical response on sarilumab during MONARCH sustained this response in the OLE and to evaluate efficacy and safety of switching from adalimumab to sarilumab vs continuous sarilumab treatment.Methods:Pts completing the double-blind phase of MONARCH were eligible for the ongoing OLE, in which all pts receive sarilumab (200 mg SC q2w) for a maximum duration of 276 wks. Disease activity, physical function, and safety were assessed regularly.Results:320/369 Pts enrolled in MONARCH entered the OLE; pts either switched from adalimumab to sarilumab (n=155) or continued on sarilumab (n=165). At OLE entry (Wk 24 of the double-blind phase), the mean from baseline DAS28-ESR was –2.28 in the switch group vs -3.36 in the continuation group, and by Wk 48 was -4.06 vs -4.18, respectively. By Wk 48 of the OLE, the proportion of pts in the switch and continuation groups who achieved DAS28–ESR≤3.2 was 61.3% vs 61.2%, DAS28–ESR<2.6 was 43.9% vs 49.7%, and DAS28-CRP<2.6 was 52.9% vs 52.1%, respectively. From OLE entry to Wk 48, mean HAQ–DI improved in the switch group from 1.21 to 0.91, but did not reach the level of improvements in the continuation group (1.01 to 0.84). See table 1 for ACR responses. After 166 vs 182 cumulative patient-years exposure in the switch vs continuation groups, treatment-emergent adverse events (TEAEs) were observed in 76.1% vs 70.9%, serious TEAEs in 11.0% vs 3.6%, and infections in 41.9% vs 35.8%, respectively, with 2 deaths in the switch group (malignancy; cerebrovascular accident) and 1 death (subarachnoid hemorrhage) in the continuation group. No GI related AEs (ulcerations, perforations or diverticulitis) were observed in either group.ACR responses & mean HAQ-DI in the OLE of MONARCH (OLE ITT Popn) Wk 0 OLEWk 48 OLE Switch group:Adalimumab 40 mg q2w → Sarilumab 200 mg q2w(N=155)Continuation group:Sarilumab 200 mg q2w(N=165)Switch group:Adalimumab 40 mg q2w → Sarilumab 200 mg q2w(N=155)Continuation group:Sarilumab 200 mg q2w(N=165)ACR20/50/70, % responders68.4/35.5/14.279.4/50.9/26.177.4/59.4/38.181.2/63.0/41.8HAQ-DI, mean1.211.010.910.84Figure 1 Mean V from baseline in DAS28-ESR (OLE population; as observed).Conclusions:Switching from adalimumab (40 mg q2w) to sarilumab monotherapy (200 mg q2w) improved the signs and symptoms of RA to a similar level as continuous sarilumab treatment, and was associated with a lower HAQ-DI score, which may have resulted in numerical differences in ACR responses between the two groups.Acknowledgements:Study funding and medical writing support (Vicki Cronin, Adelphi) provided by Sanofi and Regeneron Pharmaceuticals, Inc.Disclosure of Interest:G. R. Burmester Grant/research support from: AbbVie, Pfizer, UCB, Roche, Consultant for: AbbVie, Lilly, Merck Sharpe & Dohme, Pfizer, Sanofi, Roche, UCB, Speakers bureau: AbbVie, Lilly, Merck Sharpe & Dohme, Pfizer, Sanofi, Roche, UCB, G. St John Shareholder of: Regeneron, Employee of: Regeneron, M. Iglesias-Rodriguez Employee of: Sanofi, C.-C. Hu Shareholder of: Sanofi, Consultant for: Astellas, Employee of: Sanofi, Quintiles, T. Raskina: None declared, H. Amital Grant/research support from: Pfizer, Abbvie, Yansen, Consultant for: Pfizer, Merck Sharpe & Dohme, Speakers bureau: Pfizer, Merck Sharpe & Dohme, Yansen, Sanofi, Bristol-Myers Squibb, A. Gomez Centeno Grant/research support from: Boehringer Ingelheim, Celltrion, Galapagos-Gilead, Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, YL Biologics, Consultant for: Abbvie, Biogen, Bristol-Myers Squibb, Celgene, Gebro, Hospira, Lilly, Merck Sharpe & Dohme, Pfizer, Roche, Rubio, Sandoz, Sanofi, Speakers bureau: Abbvie, Bristol-Myers Squibb, Gebro, Janssen, Lilly, Menarini, Merck Sharpe & Dohme, Pfizer, Roche, Rubio, UCB, Sanofi, A. Rubbert-Roth Consultant for: Abbvie, Bristol-Myers Squibb, Chugai, Roche, Merck Sharpe & Dohme, Pfizer, Lilly, Hexal/Novartis, Janssen, Sanofi, Speakers bureau: Roche, Chugai, Sanofi, Lilly