Search

Objectives: Knowledge of the correspondence between clinical ICD diagnoses and classification criteria fulfilment is crucial to interpret studies identifying cases via ICD codes. We assessed the degree to which patients registered with ICD-10 diagnoses of psoriatic arthritis (PsA) in the Swedish National Patient Register (NPR) fulfil established PsA classification criteria. Method: Four hundred patients with at least one outpatient visit to one of five rheumatology or internal medicine departments (three university/two county departments across Sweden) in 2013–2015, with a main ICD-10 diagnosis of PsA (L40.5–M07.3), were randomly selected (80 cases/site). Through a structured medical record review, positive predictive values (PPVs) for fulfilment of the following classification criteria were assessed: CASPAR, Moll and Wright, Vasey and Espinoza, and modified ESSG criteria for PsA. A subset analysis regarding CASPAR fulfilment was also performed among cases with available rheumatoid factor and peripheral X-ray status (central CASPAR items; n = 227). Results: Of the 400 patients with a main ICD-10 diagnosis of PsA, 343 (86%) fulfilled at least one of the four PsA classification criteria. PPVs for the different criteria were: CASPAR 69% (82% in the subset analysis), Moll and Wright 51%, Vasey and Espinoza 76%, and modified ESSG 64%. Overall, only 6.5% of the 400 PsA diagnoses were judged as clearly incorrect by the medical record reviewers. Conclusion: The validity of rheumatologist-made, clinical ICD-10 diagnoses for PsA in the Swedish NPR is good, with PPVs of 69–82% for CASPAR fulfilment and 86% for meeting any established PsA classification criteria.

BackgroundDespite the significant improvements in the field of rheumatoid arthritis (RA) treatment, a significant and troubling minority of patients remain refractory to multiple disease modifying antirheumatic drugs (DMARDs). The consequence of this ‘’difficult-to-treat’’ state is irreversible damage, risk of co-morbid conditions, and substantial loss of quality of life. Early, precise, and actionable identification of this challenging group of RA patients is crucial for optimal prevention and management.ObjectivesTo assess the frequency and to identify predictors of switching between multiple biological and targeted synthetic DMARDs (b/tsDMARDs) in RA patients in a large national register.MethodsObservational cohort study including RA patients starting a first-ever b/tsDMARD 2009-2018, based on data from the Swedish Quality Rheumatology register. Comorbidities were identified through linkage to the national Patient Register. Baseline (time of RA diagnosis) characteristics of the population were described. Three groups were investigated: A) Patients starting ≥3 treatment courses; B) Patients starting ≥4 treatment courses; and C) Patients starting ≥5 treatment courses. Predictors of multi-switching were explored using univariate and multivariable logistic regression analyses.Results23,908 RA patients were identified. Proportions of patients starting ≥3, ≥4 or ≥5 b/tsDMARDs treatment courses were 7%, 3.2% and 1.6%, during a mean (95% CI) of 3.6 (3.5-3.7), 4.3 (4.2-2.5) and 4.9 (4.7-5.2) years from RA diagnosis, respectively. In Table 1 baseline characteristics for each multi-switching group are summarized. For definition A, the following baseline univariate predictors were identified: female sex (OR=1.57, 95% CI=1.39-1.76), younger age (OR=0.96, 95% CI=0.95-0.96), positive RF (OR=1.36, 95% CI=1.22-1.53) and ACPA (OR=1.40, 95% CI=1.24-1.58), higher DAS28 (OR=1.21, 95% CI=1.15-1.26), HAQ (OR=1.46, 95%=1.33-1.61), pain (OR=1.014, 95% CI=1.012-1.017) and fatigue (OR=1.017, 95% CI=1.014-1.021). In the multivariable logistic regression model, female sex, younger age, higher HAQ, pain and fatigue at baseline were independent predictors of multiple treatment switching. Similar results were found for all three multi-switch definitions. Several comorbidities (i.e. heart failure, ischemic heart disease, malignancy, renal failure) were associated with a lower risk for multiple treatment switching, suggestive of medical contraindications for b/tsDMARDs.Table 1.Baseline (time of RA diagnosis) characteristicsAll patientsMulti-switching definitionA: ≥3 b/tsDMARDsB: ≥4 b/tsDMARDsC: ≥5 b/tsDMARDsN, %23 908 (100)1677 (7)755 (3.2)385 (1.6)Age (years), mean (SD)59.5 (15.2)50.3 (14.5)50.0 (14.6)47.6 (14.7)Sex (male) %30.7%22.5%22.4%21.6%CRP, mg/L (median, IQR)8.9 (4-22)10 (4-24)10 (4.2-25)10 (4-29)ESR (median, IQR)23 (12-40)23 (25-39)23 (11-37.5)22 (11.8-36.3)Patient global, VAS 0-100 (mean, SD)48.8 (26.8)58.4 (25.3)59.8 (24.5)60.8 (24.0)Patient pain, VAS 0-100 (mean, SD)50.2 (26.8)59.2 (25.4)59.8 (25.2)59.9 (25.2)Fatigue, VAS 0-100 (mean, SD)48.5 (28.8)61.2 (26.5)63.1 (25.9)64.6 (23.6)HAQ (mean, SD)0.97 (0.66)1.1 3(0.64)1.15 (0.64)1.13 (0.63)Swollen joint count (median, IQR)5 (2-9)6 (3-10)6 (3-10)6 (3-10)Tender joint count (median, IQR)5 (2-9)6 (3-12)6 (3-12)7 (3-11.25)Concomitant csDMARD, %52.5%50.4%51.7%51.4%Reumatoid factor positive, %63.1%69.6%69.8%67.8%ACPA positive, %67.0%73.4%74.3%72.7%DAS28-ESR (mean, SD)4.62 (1.51)5.00 (1.41)5.10 (1.37)5.12 (1.33)VAS general health physician (mean, SD)42.28 (23.02)45.30 (22.19)45.68 (20.69)51.40 (25.83)ConclusionIn this large national observational cohort, multiple treatment switching, indicative of difficult to treat RA, was observed in a significant proportion of patients, ranging between around 2 to 7% during the first 5 years from time of diagnosis. Risk factors include female gender, younger age, higher HAQ, pain and fatigue at the time of RA diagnosis, suggesting increased attention to this challenging group of patients.Disclosure of InterestsEmma Birgersson Wettersand: None declared, Daniela Di Giuseppe: None declared, Johan Askling Grant/research support from: Karolinska Institutet has entered into agreements between Karolinska Institutet (JA as principal investigator) with AbbVie, BMS, MSD, Eli Lilly, Pfizer, Roche, Samsung Bioepis, Sanofi and UCB, mainly regarding safety monitoring of anti-rheumatic therapies., Katerina Chatzidionysiou Consultant of: consultancy fees from Eli Lilly, AbbVie and Pfizer.

BackgroundThe treatment landscape in psoriatic arthritis (PsA) is changing, including newer biologic and targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) with different modes of action becoming available. However, the most effective treatment strategy in routine care remains to be established.ObjectivesTo explore the uptake and treatment patterns of newer b/tsDMARDs, namely JAK-inhibitors (JAKi; baricitinib, tofacitinib, upadacitinib), IL-17-inhibitors (ixekizumab, secukinumab), abatacept, apremilast, and ustekinumab in PsA patients from the Nordic countries. Furthermore, to describe patient characteristics and extra-musculoskeletal manifestations at treatment start (=baseline).MethodsObservational cohort study, using prospectively collected routine care data from 4 Nordic rheumatology registries. Treatments (newer b/tsDMARDs with tumor-necrosis-factor inhibitors (TNFi) as the reference) initiated from January 2009 until December 2020 and corresponding baseline patient characteristics were identified. Linkage to national patient registries was used to identify previous extra-musculoskeletal manifestations (0-5 years). Country-level data were pooled for analyses. Uptake of each drug was explored as the cumulative number of treatment starts (a) overall, irrespective of previous b/tsDMARD experience, and (b) in b/tsDMARD-naïve patients. Each patient could contribute >1 treatment course.ResultsOverall, 13,364 unique patients contributing 24,325 treatment courses with either a newer b/tsDMARD (4,855, 20%) or a TNFi (19,470, 80%, whereof 10,897 were started year 2015-20) were identified. For the sub-group of 11,892 first b/tsDMARD treatment courses, 1,009 (8%) were a newer b/tsDMARD (10,883 were a TNFi, whereof 5,956 were started year 2015-20).Secukinumab dominated the newer b/tsDMARD uptake (1,848 new-starts, Figure 1). Ustekinumab-uptake increased over time both overall and in b/tsDMARD-naïve patients. In b/tsDMARD-naïve patients, apremilast had the fastest uptake (490 new-starts) (Figure 1). Use of JAKi was limited, especially in b/tsDMARD-naïve patients.Figure 1.Patients starting a newer b/tsDMARD tended to have longer disease duration and slightly higher disease activity at baseline (DAS28, patient-reported outcomes) than TNFi initiators (Table 1). Previous extra-musculoskeletal manifestations (uveitis, IBD) were rare, and with similar distributions across treatments (Table 1).Table 1.Baseline characteristics upon treatment startAbata-ceptApre-milastBari-citinibIxe-kizumabSecuki-numabTofa-citinibUpada-citinibUste-kinumabAny TNFiCumulative uptake, n3629351063421848494669119470Male gender, %334227384033333744Age54 (12)53 (12)55 (13)52 (13)51 (13)54 (13)52 (10)50 (12)49 (13)b/tsDMARD treatment number, %1952911149020562191512262518171925≥3723378746173836219Disease duration, yrs9 (8)8 (8)10 (8)10 (8)9 (9)11 (10)8 (8)8 (9)7 (8)Pain, VAS (0-100)63 (21)61 (23)64 (23)64 (25)63 (24)66 (23)75 (17)64 (23)59 (24)DAS284.73 (1.34)4.04 (1.35)3.95 (1.36)4.24 (1.19)4.13 (1.36)4.49 (1.33)4.74 (0.88)4.19 (1.32)4.07 (1.29)Uveitis, %*323123022IBD, %*113111-31Numbers are mean (SD) unless otherwise statedIBD: inflammatory bowel disease, bDMARD: biologic DMARD, ts: targeted synthetic*0-5 years previously, available all study period for Iceland, Sweden, Finland until 31Dec2018, not available for DenmarkConclusionIn this cross-country collaboration we were able to explore uptake of newer b/tsDMARDs. TNFi still dominates compared to newer b/tsDMARDs in routine care treatment of PsA. Newer b/tsDMARDs are mainly used in patients with several previous treatment failures, i.e. with longer disease duration and higher disease activity, indicating difficult to treat disease. Further studies are planned to explore real-world treatment patterns and outcomes.AcknowledgementsBG and DdiG contributed equally.Partly funded by NordForsk and Foreum grants. On behalf of the Danish DANBIO, Swedish SRQ, Norwegian NOR-DMARD, Finnish ROB-FIN and Icelandic ICEBIO registriesDisclosure of InterestsBente Glintborg Grant/research support from: Pfizer, AbbVie, BMS, Daniela Di Giuseppe: None declared, Johan K Wallman Consultant of: AbbVie, Amgen, Celgene, Eli Lilly, Novartis, Grant/research support from: AbbVie, Amgen, Eli Lilly, Novartis, Pfizer, Dan Nordström: None declared, Björn Gudbjornsson Speakers bureau: Novartis and Amgen, Merete Lund Hetland Grant/research support from: AbbVie, Biogen, BMS, Celltrion, Eli Lilly Denmark A/S, Janssen Biologics B.V, Lundbeck Fonden, MSD, Pfizer, Roche, Samsung Biopis, Sandoz, Novartis., Johan Askling Grant/research support from: Abbvie, Astra-Zeneca, BMS, Eli Lilly, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB., Gerdur Gröndal: None declared, Tuulikki Sokka-Isler Grant/research support from: Abbvie, Amgen, BMS, Celgene, Eli Lilly, GSK, Medac, MSD, Novartis, Orion Pharma, Pfizer, Roche, Sandoz, UCB, Sella Aarrestad Provan: None declared, Ulf Lindström: None declared

BackgroundIn axial spondyloarthritis (axSpA), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) is a key patient-reported outcome. However, one or more of its components may be missing when recorded in clinical practice.ObjectivesTo determine whether an individual patient’s BASDAI at a given timepoint can be reliably calculated with different single imputation techniques and to explore the impact of the number of missing components and/or differences between missingness of individual components.MethodsReal-life data from axSpA patients receiving tumour necrosis factor inhibitors (TNFi) from 13 countries in the European Spondyloarthritis (EuroSpA) Research Collaboration Network were utilized [1]. We studied missingness in BASDAI components based on simulations in a complete dataset, where we applied and expanded the approach of Ramiro et al. [2]. After introducing one or more missing components completely at random, BASDAI was calculated from the available components and with three different single imputation techniques: possible middle value (i.e. 50) of the component and mean and median of the available components. Differences between the observed (original) and calculated scores were assessed and correct classification of patients as having BASDAIResultsA total of 19,894 axSpA patients with at least one complete BASDAI registration at any timepoint were included. 59,126 complete BASDAI registrations were utilized for the analyses with a mean BASDAI of 38.5 (standard deviation 25.9). Calculating BASDAI from the available components and imputing with mean or median showed similar levels of agreement (Table 1). When allowing one missing component, >90% had a difference of ≤6.9 mm between the original and calculated scores and >95% were correctly classified as BASDAI90% (Figure 1, upper panels). As expected, it was observed that regardless of the BASDAI component set to missing and the imputation technique used, correct classification of patients as BASDAITable 1.Level of agreement between the original and calculated BASDAI and correct classification for BASDAILevel of agreement with Dif≤6.9 mm* (%)Correct classification for BASDAI1 missing componentAvailable93.996.9Value 5073.996.3Mean94.296.8Median93.196.82 missing componentsAvailable83.794.8Value 5040.792.8Mean83.594.8Median82.894.73 missing componentsAvailable71.992.6Value 5028.187.3Mean72.292.6Median69.792.2* The levels of agreement with a difference (Dif) of ≤6.9 mm between the original and calculated scores were based on the half of the smallest detectable change. Agreement of >90% was considered as acceptable. ** Correct classification of >95% was considered as acceptable.Figure 1.Level of agreement between the original and calculated BASDAI and correct classification for BASDAIConclusionBASDAI calculation with available components gave similar results to single imputation of missing components with mean or median. Only when missing one of BASDAI components 5 or 6, single imputation techniques can reliably calculate individual BASDAI scores. However, missing any single component value results in misclassification of patients with original BASDAI scores close to 40.References[1]Ørnbjerg et al. (2019). Ann Rheum Dis, 78(11), 1536-1544.[2]Ramiro et al. (2014). Rheumatology, 53(2), 374-376.AcknowledgementsNovartis Pharma AG and IQVIA for supporting the EuroSpA collaboration.Disclosure of InterestsStylianos Georgiadis Grant/research support from: Novartis, Myriam Riek Grant/research support from: Novartis, Christos Polysopoulos Grant/research support from: Novartis, Almut Scherer Grant/research support from: Novartis, Daniela Di Giuseppe: None declared, Gareth T. Jones Speakers bureau: Janssen, Grant/research support from: AbbVie, Pfizer, UCB, Amgen, GSK, Merete Lund Hetland Grant/research support from: Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Medac, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis, Mikkel Østergaard Speakers bureau: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, UCB, Consultant of: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, UCB, Grant/research support from: Abbvie, BMS, Merck, Celgene, Novartis, Simon Horskjær Rasmussen Grant/research support from: Novartis, Johan K Wallman Consultant of: AbbVie, Amgen, Celgene, Eli Lilly, Novartis, Bente Glintborg Grant/research support from: Pfizer, Abbvie, BMS, Anne Gitte Loft Speakers bureau: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Consultant of: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Karel Pavelka Speakers bureau: Pfizer, MSD, BMS, UCB, Amgen, Egis, Roche, AbbVie, Consultant of: Pfizer, MSD, BMS, UCB, Amgen, Egis, Roche, AbbVie, Jakub Zavada Speakers bureau: Abbvie, Elli-Lilly, Sandoz, Novartis, Egis, UCB, Consultant of: Abbvie, Elli-Lilly, Sandoz, Novartis, Egis, UCB, Merih Birlik: None declared, Ayten Yazici Grant/research support from: Roche, Brigitte Michelsen Grant/research support from: Novartis, Eirik kristianslund: None declared, Adrian Ciurea Speakers bureau: AbbVie, Eli Lilly, Merck Sharp & Dohme, Novartis, Pfizer, Consultant of: AbbVie, Eli Lilly, Merck Sharp & Dohme, Novartis, Pfizer, Michael J. Nissen Speakers bureau: AbbVie, Eli Lilly, Janssens, Novartis, Pfizer, Consultant of: AbbVie, Eli Lilly, Janssens, Novartis, Pfizer, Ana Maria Rodrigues Speakers bureau: Abbvie, Amgen, Consultant of: Abbvie, Amgen, Grant/research support from: Novartis, Pfizer, Amgen, Maria Jose Santos Speakers bureau: Abbvie, AstraZeneca, Lilly, Novartis, Pfizer, Gary Macfarlane Grant/research support from: GSK, Anna-Mari Hokkanen Grant/research support from: MSD, Heikki Relas Speakers bureau: Abbvie, Celgene, Pfizer, UCB, Viatris, Consultant of: Abbvie, Celgene, Pfizer, UCB, Viatris, Catalin Codreanu Speakers bureau: AbbVie, Amgen, Boehringer Ingelheim, Ewopharma, Lilly, Novartis, Pfizer, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Ewopharma, Lilly, Novartis, Pfizer, Corina Mogosan: None declared, Ziga Rotar Speakers bureau: Abbvie, Novartis, MSD, Medis, Biogen, Eli Lilly, Pfizer, Sanofi, Lek, Janssen, Consultant of: Abbvie, Novartis, MSD, Medis, Biogen, Eli Lilly, Pfizer, Sanofi, Lek, Janssen, Matija Tomsic Speakers bureau: Abbvie, Amgen, Biogen, Eli Lilly, Janssen, Medis, MSD, Novartis, Pfizer, Sanofi, Sandoz-Lek, Consultant of: Abbvie, Amgen, Biogen, Eli Lilly, Janssen, Medis, MSD, Novartis, Pfizer, Sanofi, Sandoz-Lek, Björn Gudbjornsson Speakers bureau: Amgen, Novartis, Consultant of: Amgen, Novartis, Arni Jon Geirsson: None declared, Pasoon Hellamand Grant/research support from: Novartis, Marleen G.H. van de Sande Speakers bureau: Eli Lilly, Novartis, UCB, Janssen, Abbvie, Consultant of: Eli Lilly, Novartis, UCB, Janssen, Abbvie, Grant/research support from: Eli Lilly, Novartis, UCB, Janssen, Abbvie, Isabel Castrejon: None declared, Manuel Pombo-Suarez Consultant of: Abbvie, MSD, Roche, Bruno Frediani: None declared, Florenzo Iannone Speakers bureau: Abbvie, Amgen, AstraZeneca, BMS, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Consultant of: Abbvie, Amgen, AstraZeneca, BMS, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis

BackgroundLung cancer is a common malignancy in rheumatoid arthritis (RA)1,2. Since smoking is a risk factor for both (seropositive) RA and lung cancer, it remains unclear whether RA, in itself, increases lung cancer risk.ObjectivesThe aim of this study was to examine whether and to what extent the increased risk of lung cancer in RA may (or may not) be attributable to smoking, and to examine this association, both in terms of absolute and relative risks, specifically in relation to RA serostatus.MethodsWe performed a population-based cohort study of RA patients and individually matched general population reference individuals identified in Swedish registers and from the EIRA early RA study, prospectively followed for lung cancer occurrence 1995 through 2018. We calculated incidence rates and performed Cox regression to estimate hazard ratios (HR) including 95% confidence intervals (CI) of lung cancer, taking smoking and sero-status into account.ResultsOverall, we included 44,101 RA patients (590 incident lung cancers, 56 per 100,000), and 216,495 matched general population individuals (1,691 incident lung cancers, 33 per 100,000), corresponding to a crude HR (95% CI) of 1.76 (1.60-1.93). In subset analyses this increased risk remained after adjustment for smoking (HR=1.77, 95% CI 1.06-2.97). Compared to general population subjects who were never smokers, RA patients who were ever smokers had almost 7 times higher risk of lung cancer.Positive autoantibody status was associated with an at least doubled risk of lung cancer in ACPA positive patients (vs. ACPA negative patients) and double seropositive (vs. double seronegative) patients after adjusting for comorbidities and smoking (Table 1).Table 1.Number of events, person-years of follow-up, number of events per 100,000 person-years, and relative risk of lung cancer according to autoantibody status in the EIRA sub-cohort. Five Hazard ratios are presented: a) crude; b) adjusted for age, sex, index year, county of residency (model A); c) age, sex, index year, county of residency and comorbidities (renal failure, heart failure, ischemic heart disease, COPD, respiratory infections, hospitalization) (model B) c) all the above plus smoking (model C) and d) as model C with packet-years instead of smoking ever vs. never.No of events (person years of follow-up; No of events/100 000 person years)Crude Hazard ratio (95% CI)Model A Hazard ratio* (95% CI)Model BHazard ratio** (95% CI)Model CHazard ratio** (95% CI)Model D with smoking as pack-years instead of ever/neverPositiveNegativeRF (N=2060)30(49,440; 60.7)6(49,440; 12.1)2.78 (1.16-6.69)3.01 (1.25-7.26)2.82 (1.17-6.82)2.44 (1.01-5.89)2.16 (0.88-5.28)ACPA (N=2060)30(49,440; 60.7)6(49,440; 12.1)3.13 (1.30-7.51)3.43 (1.42-8.25)3.22 (1.33-7.77)2.88 (1.19-6.95)3.29 (1.26-8.58)RF and/or ACPA (N=2060)34(49,440; 68.8)2(49,440; 4.0)6.38 (1.53-26.56)7.62 (1.83-31.83)7.20 (1.72-30.11)6.29 (1.51-26.30)5.76 (1.37-24.21)RF and ACPA (positive vs. double negative)(N=1608)26(38,592; 67.4)2(38,592; 5.2)6.67 (1.58-28.08)7.92 (1.87-33.50)7.08 (1.67-29.98)6.21 (1.47-26.33)5.86 (1.37-25.01)The average absolute five-year risk of lung cancer counting from RA diagnosis was 1.3% in ever-smoking seropositive RA. At 20 years the risk was almost 3% in RA overall, and over 4% for patients who were ever smokers and had at least one autoantibody.ConclusionRA seropositivity is a strong and at least seemingly independent risk factor for lung cancer in RA. The absolute risks point to the potential for regular lung cancer screening, at least in seropositive RA.References[1]Simon TA, Thompson A, Gandhi KK, et al. Incidence of malignancy in adult patients with rheumatoid arthritis: A meta-analysis. Arthritis Res Ther Published Online First: 2015.[2]Khurana R, Wolf R, Berney S, et al. Risk of development of lung cancer is increased in patients with rheumatoid arthritis: A large case control study in US veterans. J Rheumatol 2008.Disclosure of InterestsKaterina Chatzidionysiou Consultant of: consultancy fees from Eli Lilly, AbbVie and Pfizer, Daniela Di Giuseppe: None declared, Jonas Söderling: None declared, Anca Catrina: None declared, Johan Askling Grant/research support from: Karolinska Institutet has entered into agreements between Karolinska Institutet (JA as principal investigator) with AbbVie, BMS, MSD, Eli Lilly, Pfizer, Roche, Samsung Bioepis, Sanofi and UCB, mainly regarding safety monitoring of anti-rheumatic therapies

BackgroundIn Sweden, methotrexate (MTX) is recommended as first-line DMARD for both psoriatic arthritis (PsA) and rheumatoid arthritis (RA). Whereas in RA the use of MTX monotherapy is supported by efficacy data from randomized trials, in PsA no clear efficacy has been demonstrated in placebo-controlled trials. Therefore, the use of MTX in PsA is mostly based on clinical experience and results from studies not primarily designed to evaluate MTX efficacy.ObjectivesTo compare time from MTX initiation until start of a biological or targeted synthetic DMARD (b/tsDMARD), as marker of insufficient MTX response, in previously DMARD-naïve, incident cases with PsA and matched, corresponding, reference subjects with RA.MethodsPatients with PsA, having collected a prescription of MTX as their first ever DMARD any time between 2011 through 2018, and with a first ever PsA diagnosis in the Swedish National Patient Register within two years prior to this date, were included. Each individual was required to have a visit in rheumatology, but no visit in dermatology, within 6 weeks prior to MTX initiation, to ensure that PsA rather than psoriasis was the main reason for MTX treatment. For each individual with PsA, a corresponding individual with incident RA was identified, matched on sex, age, and year of MTX initiation. Only PsA cases with an identified RA comparator were included. All individuals with a diagnosis indicating axial spondyloarthritis prior to MTX start were excluded. The data were enriched through linkage to other national registers.Follow-up was defined as the time from MTX initiation until start of any b/tsDMARD. Censoring was performed at the first of death, migration or 31 Dec 2020. Time until start of a b/tsDMARD was compared for PsA and RA through crude survival curves and conditional Cox-regression, crude and adjusted for comorbidity, level of education and patient global health.Results3098 patients with PsA, and their individually matched RA comparators were included. At initiation of MTX, PsA cases had a mean 28-joint disease activity score (DAS28) of 4.0 and RA-controls of 4.6, while patient-reported global health was 51 (of 100) for both groups and number of swollen joints (28-joint count) 4.0 for PsA and 6.8 for RA, Table 1. The comorbidity burden was similar at baseline.Table 1.Characteristics of PsA cases and matched RA controls at start of MTX.Psoriatic arthritis N=3098Rheumatoid arthritis N=3098Age, mean (sd)55 (14)55 (14)Sex, male49%49%Length of education, yrs 20%24% 10-1251%49% >1228%26%Diabetes1, 27.4%6.7%Myocardial infarction11.3%1.8%Malignancy14.7%5.0%Congestive heart disease10.2%0.2%Chronic lung disease11.6%2.2%Use of anti-depressive drugs1, 315.4%11.4%DAS28-CRP, mean (sd)44.0 (1.1)4.6 (1.2)Patient global, mean (sd) 451 (23)51 (23)CRP, median (IQR) 47 (14)10 (21)Tender joint count (28), mean (sd) 45.2 (4.9)7.0 (5.7)Swollen joint count (28), mean (sd) 44.0 (4.1)6.8 (5.2)1) Diagnosis within 5 years. 2) Also identified by collecting ≥1 prescription of anti-diabetics in 1 year. 3) Identified by collecting ≥1 prescription within 1 year before methotrexate start. 4) Data on disease activity variables available for 28-36% of PsA and 56-62% of RA.During a mean follow-up of 4.5 and 4.4 years, 34% and 33% of PsA and RA patients, respectively, started a b/tsDMARD, of whom 63% and 84% had also used ≥1 non-MTX conventional synthetic DMARD before the b/tsDMARD initiation. The crude survival curves for time from MTX initiation until start of a b/tsDMARD were identical for PsA and RA, Figure 1A. The adjusted HR for starting a b/tsDMARD in PsA compared with RA was 0.99 (95% CI 0.90-1.09). No calendar time trends were observed (Figure 1B and C).ConclusionIn this study, the risk of escalating treatment from MTX, by adding or switching to a b/tsDMARD, was identical in PsA cases and matched RA controls. This supports a good response to MTX in PsA, similar to that in RA. Due to the matching, neither the results from the PsA nor the RA populations may be fully generalizable.Disclosure of InterestsUlf Lindström: None declared, Daniela Di Giuseppe: None declared, Sofia Exarchou Consultant of: AbbVie, Amgen, Janssen, Novartis, Grant/research support from: AbbVie, Amgen, Eli Lilly, Novartis, Pfizer, Gerd-Marie Alenius: None declared, Tor Olofsson Consultant of: Merck Sharp & Dohme, Eva Klingberg: None declared, Lennart T.H. Jacobsson Speakers bureau: Janssen, Eli Lilly, Novartis, Consultant of: Janssen, Eli Lilly, Novartis, Johan Askling Grant/research support from: Abbvie, Astra-Zeneca, BMS, Eli Lilly, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB., Johan K Wallman Consultant of: AbbVie, Amgen, Celgene, Eli Lilly, Novartis, Grant/research support from: AbbVie, Amgen, Eli Lilly, Novartis, Pfizer

BackgroundIn a national context, the Swedish Rheumatology Quality register (SRQ) is a major source of information on clinical data for patients treated with biological and targeted synthetic disease-modifying anti-rheumatic drug (b/tsDMARD) for rheumatic diseases. Data from SRQ are fundamental for research on drug effectiveness and safety.ObjectivesTo understand to what degree patients with psoriatic arthritis (PsA) and their dispensed b/tsDMARD treatments are recorded in the SRQ.MethodsWe identified all dispensed oral or subcutaneously administered b/tsDMARDs, approved for use in PsA, from the Swedish Prescribed Drug register (PDR, with 100% coverage) in 2018-2019. We required the patients who received the dispensation to have at least one ICD code for PsA (L405, M070, M071, M072, M073) as main diagnosis from a visit to a rheumatology or internal medicine (IM) unit in the National Patient Register (NPR) before dispensation, but no main diagnosis of rheumatoid arthritis (ICD code: M05, M06 (excluding M06.1 and M06.4), M12.3). Furthermore, to limit the assessment to patients with contemporary contact with the specialized rheumatology care, we also required at least one visit with a PsA main diagnosis from rheumatology/IM during 2017-2019. We then checked if the patients and their treatments were registered in SRQ. In a sensitivity analysis, we excluded patients with a visit in dermatology within 6 weeks prior to the first prescription of each b/tsDMARD, in order to exclude patients being prescribed the drug for cutaneous psoriasis.ResultsIn 2018-2019, a total of 7922 unique b/tsDMARD prescriptions had been dispensed to 6311 patients with PsA, having contemporary contact with the specialized rheumatology care. Of them, 5687 patients were registered in SRQ (90.1%), of which 94.4% with a PsA diagnosis and 95.5% with at least one registration of a b/tsDMARD. The coverage of the single drugs in SRQ, as compared to dispensations in PDR, ranged between 53.5% to 93.3% (69.3% to 95.8% considering only patients also in SRQ), with the tumor necrosis factor inhibitors (TNFi) having the best coverage (79.4-93.3%) (Table 1). In a sensitivity analysis, among the 5290 patients without a main diagnosis of psoriasis before start of treatment, 4919 (93%) were registered in SRQ, of which 94% with a PsA diagnosis and 96% with at least one registration of a b/tsDMARD.Table 1.coverage of the single b/tsDMARD approved for use in PsA patients in the SRQ as compared to the prescribed drug register, 2018-2019ATCDrug*Total patients in PDRPatients with the same drug in SRQPercentagePercentage only considering patients included in SRQL04AB01Etanercept2753234885.3%92.5%L04AB04Adalimumab2436193379.4%88.8%L04AB05Certolizumab pegol24321387.7%89.9%L04AB06Golimumab41839093.3%95.8%L04AA24Abatacept947377.7%83.9%L04AA32Apremilast54729453.7%69.3%L04AC10Secukinumab83365678.8%84.8%L04AC13Ixekizumab1187160.2%74%L04AC05Ustekinumab21913863%76.2%L04AA29Tofacitinib26119474.3%77%* In Sweden intravenously administered drugs are not prescribed and therefore not included in the PDR. Also, some hospitals administer ustekinumab in hospital, due to its high cost. However, all b/tsDMARDs, irrespectively of administration route, can be registered in SRQ.ConclusionThe coverage of b/tsDMARD-treated PsA patients in SRQ as compared to the PDR in Sweden is ranging between 90 and 93%, and SRQ is performing well in the registration of the single drugs, especially for TNFi. These results suggest that research studies based on data from the SRQ are representative of the Swedish b/tsDMARD-treated PsA population.Disclosure of InterestsDaniela Di Giuseppe: None declared, Ulf Lindström: None declared, Johan K Wallman Consultant of: AbbVie, Amgen, Celgene, Eli Lilly, Novartis, Grant/research support from: AbbVie, Amgen, Eli Lilly, Novartis, Pfizer, Lotta Ljung: None declared, Johan Askling Grant/research support from: Abbvie, Astra-Zeneca, BMS, Eli Lilly, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB

BackgroundWhile the relative efficacy of treatments can be demonstrated in relatively small studies with limited follow-up, most safety concerns are infrequent, requiring longer follow-up and larger populations. This is recognized by the regulatory framework, where data from pivotal randomized controlled trials are usually considered sufficient for demonstrating efficacy and non-toxicity, but post-approval safety studies are required for many years to fully evaluate drug-associated risks. Though such regulatory safety-studies often focus on one drug (vs. all others), clinical decision-making requires data across all available treatment options. Long-standing longitudinal clinical registries, like the Anti-Rheumatic Therapies in Sweden (ARTIS) database, thus have a key role in assessing the relative safety of b/tsDMARDs, allowing simultaneous comparison of all drugs used in clinical practice, with consistent definitions of treatment cohorts, follow-up, and outcomes.ObjectivesTo assess incidence rates of critical safety endpoints for individual b/tsDMARDs used to treat RA, updating previously published reports and including more recently introduced treatments.MethodsNationwide register-based cohort study including all RA patients in Sweden registered as starting any b/tsDMARD between Jan 1st 2010 and Dec 31st 2019, and followed until Dec 31st 2020. The incidence rates of selected outcomes, identified through national healthcare registers, were compared between individual b/tsDMARDs while adjusting for a range of potential confounders (covering demographics, RA-related characteristics and disease activity, and comorbidity) using Inverse Probability of Treatment Weighting. Probabilities were predicted by multinomial logistic regression, regressing all covariates on treatment status. Exposure time was counted from treatment start until stop (+90 days’ lag time), censored at emigration and death.ResultsThere were clear differences between patients starting individual b/tsDMARDs, in particular with TNF inhibitors more often used as a first line b/tsDMARD; sarilumab, baricitinib, and tofacitinib predominantly used later in the treatment course; rituximab used more often for older patients, and non-TNFi generally used more frequently for patients with higher disease activity or comorbidity. Expectedly, these differences translated into differences in the crude rate of safety endpoints.Several differences remained after confounder-adjustment (Table 1), including a higher rate of treatment discontinuation due to adverse events on baricitinib, tofacitinib, and sarilumab. Rituximab was associated with higher rates of several outcomes, but the confounder-adjustment markedly reduced risks and residual confounding likely explain part of the remaining increase. Baricitinib and tofacitinib were associated with higher rates of hospitalised herpes zoster, but not with similarly elevated rates of other serious infections. There were no clear differences in the rate of cardiovascular events or severe depression. Low number of events limit the comparison, in particular for sarilumab and tofacitinib.Table 1.Weighted incidence rate per 1,000 person-years of selected safety outcomes.DMARDNDiscont. due to. adverse eventACSStrokeLiver diseaseHosp. infectionHosp. Herpes zosterHosp. depressionAny hosp.All-cause mortalityETA8244456.24.51.4322.92.315610.8ADA5069465.95.61.1363.51.51669.5INF2832508.25.83.1433.22.019712.7CER2072546.47.02.5343.61.717211.0GOL1796515.96.8-322.8-15411.5ABA3254567.34.71.9362.31.617213.9RTX3990318.46.22.2413.32.419415.1TCZ2619305.75.02.1312.91.616315.7SAR271100---18--298-BARI1665693.04.21.4378.82.617316.7TOFA39282---3212.9-129-Note: Rates based on ConclusionWe found large differences in the rate of treatment discontinuations due to adverse events across b/tsDMARDs, which were not generally mirrored by corresponding differences in the rates for specific serious adverse events.ReferencesN/AAcknowledgementsARTIS has been or is currently supported by agreements with Abbvie, BMS, Eli Lilly, MSD, Pfizer, Roche, Samsung Bioepis, and Sanofi.Disclosure of InterestsThomas Frisell: None declared, Hannah Bower: None declared, Eva Baecklund: None declared, Daniela Di Giuseppe: None declared, Bénédicte Delcoigne: None declared, Nils Feltelius Employee of: NF is employed by the Medical Products Agency (MPA), which is a governmental body. The views in this abstract may not represent the views of the MPA, Helena Forsblad-d’Elia: None declared, Elisabet Lindqvist: None declared, Ulf Lindström: None declared, Johan Askling Grant/research support from: Karolinska Institutet has entered into agreements with the following companies, with JA as PI: Abbvie,BMS, Eli Lilly, Galapagos, Janssen, Pfizer, Roche, Samsung Bioepis and Sanofi.

Comparison of agreement between internet-based registration of patient-reported outcomes and clinical-based paper forms within the Swedish Rheumatology Quality Register: comment on the article by Hofstedt et al : Reply

Background:Studies from COVID-19 case-repositories among patients with rheumatic diseases have assessed associations (relative risks) between characteristics of the disease and adverse COVID-19 outcomes. Such designs are susceptible to bias from selection of cases reported. Few studies have assessed absolute and relative risks for COVID-19 outcomes in population-based cohorts of patients with inflammatory joint diseases, nor compared these risks to those in the general population.Objectives:To estimate all-cause mortality, absolute and relative risks for severe COVID-19 in patients with chronic inflammatory joint diseases, compared over time and to the general population.Methods:We updated a multi-register nationwide linkage (“ARTIS”) on adults with RA, PsA, AS, SpA or JIA and population referents (matched on sex, age, and region), with data on hospitalizations, admission to intensive care (ICU), and deaths due to COVID-19. We calculated all-cause mortality March-September 2015-2020, and absolute and relative risks for COVID-19 outcomes March-September 2020. Patients were compared to population referents using hazard ratios (HR) from Cox models adjusted for comorbidities and socio-economy.Results:We identified 110567 individuals with inflammatory joint disease (53455 with RA) in Sweden on March 1st 2020, and 484277 matched general population subjects. In all cohorts, the absolute risk of death from any cause in 2020 was higher than 2015-2019 (Figure 1), with a peak in mid-April, but the relative risks of death (vs. the general population) 2020 remained similar to HRs for 2015-2019 (HR for 2020 in Table 1).Among all individuals with inflammatory joint disease in 2020, the risk for hospitalization, admission to ICU, and death due to COVID-19 was 0.5%, 0.04% and 0.1%, respectively (Table 1). HRs (vs. the general population) were elevated for almost all outcomes. HRs for COVID-19 related outcomes (Table 1) were higher than for non-COVID-19 outcomes; adjustment for co-morbidities and socio-economy explained much of these increases, somewhat less so for the former.Figure 1.All-cause mortality in Swedish individuals with inflammatory joint disease and general population, March-September 2020 and the average 2015-2019Table 1.Absolute and relative risks for COVID-19 outcomes in Swedish individuals with inflammatory joint disease compared to general population comparators March-September 2020OutcomeEvents(risk, %)Events (risk, %), general populationHR1*HR2**AllHospitalization, all causes8971 (8.1%)24273 (5.0%)1.65(1.61, 1.69)1.18 (1.15, 1.21)Hospitalization, COVID-19581 (0.5%)1443 (0.3%)1.77 (1.61, 1.95)1.32 (1.19, 1.46)ICU, COVID-1945 (0.04%)162 (0.03%)1.22 (0.88, 1.70)1.17 (0.82, 1.66)Death, all causes1310 (1.2%)3036 (0.6%)1.90 (1.78, 2.02)1.13 (1.05, 1.21)Death, COVID-19161 (0.1%)338 (0.07%)2.09 (1.73, 2.52)1.18 (0.97, 1.44)RAHospitalization, all causes5275 (9.9%)13072 (5.9%)1.71 (1.66, 1.77)1.21 (1.17, 1.25)Hospitalization, COVID-19379 (0.7%)784 (0.4%)2.02 (1.78, 2.28)1.40 (1.23, 1.60)ICU, COVID-1931 (0.06%)79 (0.04%)1.63 (1.08, 2.48)1.53 (0.98, 2.40)Death, all causes968 (1.8%)2026 (0.9%)1.99 (1.85, 2.15)1.18 (1.09, 1.28)Death, COVID-19134 (0.3%)245 (0.11%)2.28 (1.85, 2.81)1.27 (1.02, 1.59)PsA AS SpA JIAHospitalization, all causes3696 (6.5%)11201 (4.3%)1.54 (1.48, 1.59)1.16 (1.11, 1.20)Hospitalization, COVID-19202 (0.4%)659 (0.3%)1.41 (1.20, 1.65)1.20 (1.02, 1.41)ICU, COVID-1914 (0.02%)83 (0.03%)0.78 (0.44, 1.37)0.76 (0.43, 1.37)Death, all causes342 (0.6%)1010 (0.4%)1.56 (1.38, 1.76)0.98 (0.86, 1.12)Death, COVID-1927 (0.05%)93 (0.04%)1.34 (0.87, 2.05)0.83 (0.54, 1.28)*HR1 unadjusted, matched (age, sex, and region)**HR2, as HR1 but adjusted for comorbidities and socio-economyConclusion:Risks of severe COVID-19 were increased among patients with inflammatory joint diseases, but similar increases were seen for non-COVID-19 morbidity. Co-morbidities and socio-economy explain much of this increase.Disclosure of Interests:Hannah Bower: None declared, Thomas Frisell: None declared, Daniela Di Giuseppe: None declared, Bénédicte Delcoigne: None declared, Gerd-Marie Alenius: None declared, Eva Baecklund: None declared, Katerina Chatzidionysiou Speakers bureau: Eli Lilly, AbbVie and Pfizer, Consultant of: Eli Lilly, AbbVie and Pfizer, Nils Feltelius Employee of: Nils Feltelius is employed by the Medical Products Agency (MPA), which is a governmental body. The views in this abstract may not represent the views of the MPA, Helena Forsblad-d’Elia: None declared, Alf Kastbom Employee of: Former employee of Sanofi, Lars Klareskog: None declared, Elisabet Lindqvist: None declared, Ulf Lindström: None declared, Carl Turesson Speakers bureau: Roche, AbbVie and Pfizer, Consultant of: Roche, Grant/research support from: Research grant from Bristol-Myers Squibb, Christopher Sjowall: None declared, Johan Askling Grant/research support from: PI for agreements between Karolinska Institutet and Abbvie, BMS, Eli Lilly, Pfizer, Roche, Samsung Bioepis, and Sanofi for safety monitoring of anti-rheumatic therapies (ARTIS).

Background:Interstitial lung disease (ILD) is an established extra-articular manifestation of rheumatoid arthritis (RA). Few studies have investigated the prevalence of ILD in patients with psoriatic arthritis (PsA). Methotrexate (MTX) is frequently used in the treatment of both RA and PsA and has been suggested to be a risk factor for the development of ILD. It is of interest to understand the interaction between disease and treatment in the development of ILD.Objectives:To compare the incidence of ILD between patient with PsA and RA treated with biologic disease modifying antirheumatic drugs (bDMARDS), with or without MTX as a co-medication.Methods:Cohorts of patients with RA and PsA starting bDMARD were identified in Nordic registers (Danish nationwide clinical register for patients with RA (DANBIO), Register on antirheumatic and biological therapy in Finland (ROB-FIN), Icelandic nationwide database of biologic therapy (ICEBIO), Norwegian Antirheumatic Drug Register (NOR-DMARD), and the Swedish Rheumatology Quality Register (SRQ)). Linkages to the National Patient Registers and to the Cause of Death Registers were performed in each country to identify cases of ILD. Each individual patient could contribute several treatment courses. ILD was identified as hospital or death certificate ICD10 codes of ILD (J84.1, J84.8, J84.9, J70.2, J70.3, J70.4, J99.0, J99.1, J99.8) given during the follow-up period which was defined as the treatment course duration, plus a 30-day wash-out period added to the end of treatment course period. MTX co-medication was specified as use of MTX at the start of bDMARD. Incidence rates (IR) for any ILD were calculated per 1000 person years at risk (PYR) for each country. The five cohorts were pooled and incidence rate ratios (IRR) for PsA vs. RA were calculated. Hazard ratios (HR) for any ILD in PsA vs. RA were estimated in Cox regression models adjusted for age, gender and repeated observations, and stratified for the use of MTX co-medication.Results:Overall 47 987 individual patients representing 89 239 bDMARD treatment courses and contributing 201 279 PYR were included in the study (Table 1). Methotrexate was reported as comedication in 29 916 (33.5 %) of the treatment courses (PsA vs. RA, 30.4 % vs 34.5 %). 970 cases of ILD were identified during the follow-up period. The risk of ILD was consistently lower in patients with PsA compared to patients with RA in all countries. In models stratified for co-medication the HR for ILD in PsA vs. RA was 0.34 (0.21-0.57) in patients treated with MTX and 0.26 (0.18-0.36) in patients not treated with MTX.Table 1.Interstitial lung disease in PsA vs. RA in five Nordic biologic registersDENMARKFINLANDICELANDNORWAYSWEDENRAPsARAPsARAPsARAPsARAPsANumber of individuals78293386494610916754701590999205966393Number of treatment courses17 07266408634184512808592379142738 27910 824Age baseline (SD)57.3 (13.1)49.0 (12.6)53.8 (13.4)48.8 (11.4)53.9 (14.2)50.1 (13.3)53.8 (13.7)48.7 (12.0)57.1 (13.7)50.6 (12.8)Female n (%)12 963 (76)3929 (59)6571 (76)933 (51)969 (76)551 (65)1815 (77)818 (57)29 635 (77)6162 (57)Number of PYR4023513986217984910451727994556265312033427412ILD-events within PYR2182213287232668028IR pr 1000 PYR5.41.66.11.61.50.77.02.35.71.0IRR PsA vs RA crude0.29 (0.18-0.45)0.27 (0.11-0.55)0.46 (0.05-2.42)0.32(0.11-0.78)0.18 (0.12-0.26)HR PsA vs RA0.31 (0.17-0.56)0.46 (0.22-0.96)0.62 (0.12-3.14)0.19 (0.06-0.54)0.25 (0.17-0.37)PYR: Patient years at risk, IR: Incidence rates, IRR: Incidence rate ratios, HR: Hazard RatiosConclusion:In these preliminary analyses, the incidence of ILD is lower in bDMARD treated PsA vs. RA patients, irrespective of co-medication with MTX. This indicates that the clinician should consider the rheumatological diagnosis when assessing the risk for future ILD in patients treated with bDMARDs and MTX.Acknowledgements:Partly funded by NordForsk and FOREUMDisclosure of Interests:Sella Aarrestad Provan Consultant of: Novartis, Grant/research support from: Boehringer-Ingelheim, Brigitte Michelsen: None declared, Lotta Ljung: None declared, Thorarinn Jonmundsson: None declared, Björn Gudbjornsson Speakers bureau: Amgen and Novartis, Daniela Di Giuseppe: None declared, Merete Lund Hetland Speakers bureau: Orion Pharma, Biogen, Pfizer, CellTrion, Merck and Samsung Bioepis, Consultant of: Eli Lilly, Grant/research support from: BMS, MSD, AbbVie, Roche, Novartis, Biogen and Pfizer, Guðrún Björk Reynisdóttir: None declared, Bente Glintborg: None declared, Eirik kristianslund: None declared, Heikki Relas: None declared, Kalle Aaltonen: None declared, Dan Nordström Speakers bureau: Abbvie, BMS, Celgene, Eli Lilly, MSD, Novartis, Pfizer, Roche and UCB., Consultant of: Abbvie, BMS, Celgene, Eli Lilly, MSD, Novartis, Pfizer, Roche and UCB., Tore K. Kvien Speakers bureau: Amgen, Celltrion, Egis, Evapharma, Ewopharma, Hikma, Oktal, Sandoz, Sanofi., Consultant of: AbbVie, Amgren, Biogen, Celltrion, Eli Lilly, Gilead, Mylan, Novartis, Pfizer, Roche, Sandoz, Sanofi., Johan Askling Grant/research support from: Abbvie, BMS, Eli Lilly, Merck, Pfizer, Roche, Samsung Bioepis, and Sanofi

Background:In clinical practice, some patients with axial spondyloarthritis (axSpA) fail several consecutive biological treatments (bDMARDs). How this group of ”refractory” patients should best be defined, how common they are, and what their characteristics are, is poorly understood.Objectives:To explore the point prevalence of bDMARD refractory disease in axSpA over time, according to different definitions, and to describe the characteristics of refractory vs. not-refractory patients upon start of their first bDMARD.Methods:Observational prospective cohort study. Patients with axSpA (ankylosing spondylitis/non-radiographic axial SpA) starting a first bDMARD 2009-2018 were identified in biologic registries in Denmark, Sweden, Finland, Norway and Iceland. Clinical characteristics and treatments were retrieved, and data were pooled for analysis.Refractory disease was defined based on the number of different bDMARD treatments started in individual patients: mild (≥3 bDMARDs), moderate (≥4), and strict (5 or more). Restart of same bDMARD with another bDMARD in between counted as separate courses whereas switch from originator to corresponding biosimilar was ignored.Proportions of patients fulfilling each definition of refractory disease at 2 and 5 years after the start of 1st bDMARD were calculated.Point-prevalence per calendar-year was calculated as the number of patients with refractory disease at the end of each year, divided by the total number of patients ever having starting a first bDMARD before that time-point, and who were still alive and resident in the country.Results:The point prevalence of refractory axSpA increased with calendar-time (Figure). Among 12,037 included axSpA patients (64% male), the point-prevalence of bDMARD refractory disease in 2018 was 16%/7%/3% according to mild/moderate/strict definitions (Table).Table 1.Biologic refractory axSpA according to three definitionsA.Baseline characteristics upon start 1st bDMARDRefractory definitionOverall cohortMILDMODERATESTRICTN120371969832351Age, years42 (13)41 (12)41 (12)41 (12)Male, %64%57%54%56%Disease duration, years7 (10)6 (9)6 (8)5 (8)BASDAI, 0-10053 (28)60 (29)63 (27)66 (35)ASDAS3.3 (1.1)3.5 (1.2)3.6 (1.0)3.7 (1.1)CRP, mg/L16 (23)18 (26)21 (28)23 (32)Patient global, VAS, 0-10059 (25)65 (22)66 (22)67 (23)Patient Pain, VAS, 0-10057 (24)62 (22)63 (22)63 (22)Fatigue, VAS, 0-10059 (27)66 (26)66 (26)68 (25)B.Proportions of patients having refractory disease 2 and 5 years after start of their first bDMARD2 years, %5%1%0%5 years, %13%4%1%Numbers are means (SD) unless otherwise statedUpon start of their 1st bDMARD, patients later fulfilling the definitions for refractory axSpA were more frequently women, had shorter disease duration, higher C-reactive protein and higher patient reported outcomes.Overall, 5%/1%/0% had mild/moderate/strict refractory disease 2 years after start of first bDMARD, after 5 years it was 13%/4%/1% (Table).Conclusion:In this large Nordic observational cohort of axSpA patients treated in routine care, we could demonstrate that a substantial proportion of all patients had used multiple bDMARDs. In 2018, one in six patients had received ≥3 bDMARDs, indicating a bDMARD refractory disease. Multiple switching was more frequent during later years, probably due to more bDMARDs becoming available. The characteristics of refractory axSpA, including sex and disease activity, will have to be further explored, as will the impact of refractory disease on long-term outcomes.Acknowledgements:the DANBIO, SRQ, ICEBIO, ROB-FIN and NOR-DMARD registries.Partly sponsored by Nordforsk and Foreum.Disclosure of Interests:Daniela Di Giuseppe: None declared, Ulf Lindström: None declared, Kalle Aaltonen: None declared, Heikki Relas Speakers bureau: Abbvie, Celgene, MSD, Roche, Sella Aarrestad Provan: None declared, Björn Gudbjornsson Speakers bureau: Amgen and Novartis, Merete L. Hetland Grant/research support from: AbbVie, Biogen, BMS, Celtrion, Eli Lilly Denmark A/S, Janssen Biologics B.V, Lundbeck Fonden, MSD, Pfizer, Roche, Samsung Biopis, Sandoz. MLH chairs the steering committee of the Danish Rheumatology Quality Registry (DANBIO), which receives public funding from the hospital owners and funding from pharmaceutical companies. MLH co-chairs the EuroSpA research collaboration, which generates real-world evidence of treatment of psoriatic arthritis and axial spondyloarthritis based on secondary use of quality data and is partly funded by Novartis., Johan Askling: None declared, Tanja Schjødt Jørgensen: None declared, Lene Dreyer Speakers bureau: Eli-Lilly and Galderma, Grant/research support from: BMS, Dan Nordström: None declared, Brigitte Michelsen: None declared, Arni Jon Geirsson: None declared, Lennart T.H. Jacobsson: None declared, Bente Glintborg Grant/research support from: Abbvie, BMS, Pfizer, Lundbeck foundation

Background:Axial spondylarthritis (axSpA) patients treated with a tumour necrosis factor inhibitor (TNFi) may receive a concomitant conventional synthetic disease-modifying anti-rheumatic drug (csDMARD), although the value of combination therapy remains unclear.Objectives:Describe the proportion and phenotype of patients with axSpA initiating their first TNFi as monotherapy compared to TNFi+csDMARD combination therapy, and to compare the 1-year TNFi retention between the two groups.Methods:Data from 13 European registries was collected. Two exposure treatment groups were defined: TNFi monotherapy at baseline (=TNFi start date) and TNFi+csDMARD combination therapy. TNFi retention rates were assessed with Kaplan-Meier curves for each country and combined. Hazard ratios (HR, 95% CI) for discontinuing the TNFi were obtained with Cox models: (i) crude; adjusted for (ii) country, and (iii) country, sex, age, calendar year, disease duration and BASDAI. Participating countries were dichotomized into two strata, depending on their 1-year retention rate being above (stratum A) or below (stratum B) the average retention rate across all countries.Results:22,196 axSpA patients were included with 34% on TNFi+csDMARD combination therapy. Baseline characteristics are presented in table 1. Overall, the crude TNFi retention rate was marginally longer in the combination therapy group (80% (79-81%)) compared to the monotherapy group (78% (77-79%)) and was primarily driven by differences in stratum B (fig. 1). TNFi retention rates varied significantly across countries (range:-11.0% to +11.3%), with a clear distinction between the 2 strata. The HRs for discontinuation over 1-year (reference=TNFi monotherapy) in the 3 models were: (i) 0.88 (0.82-0.93), (ii) 0.87 (0.82-0.92), (iii) 0.88 (0.82-0.93).Table 1Baseline characteristicsAll patients(n=22196)Country stratum ACountry stratum BTNFi mono(n=4940)csDMARD + TNFi(n=2547)TNFi mono(n=9693)csDMARD + TNFi(n=5016)Age (years), mean (SD)42.6 (12.5)43.4 (12.0)42.8 (12.2)41.6 (12.7)43.7 (12.7)Females, %41.137.738.242.044.2Disease duration (yrs), mean (SD)5.7 (8.0)6.2 (7.7)6.7 (7.4)4.9 (8.2)6.1 (8.2)Enthesitis, %50.316.733.957.859.7SJC-28, median (IQR)0 (0-1)0 (0-0)0 (0-2)0 (0-0)0 (0-2)VAS pain (0-100), mean (SD)60.9 (24.5)63.3 (26.5)67.8 (23.3)60.2 (23.4)57.2 (24.3)CRP (mg/L), median (IQR)8 (3-20)7.8 (2-20)18 (6.7-32.6)6.0 (2.7-15)8.0 (3-22)BASDAI (0-10), mean (SD)5.7 (2.1)5.7 (2.2)6.2 (2.1)5.6 (2.0)5.4 (2.2)BASFI (0-10), mean (SD)4.4 (2.5)4.4 (2.6)4.9 (2.5)4.3 (2.4)4.2 (2.9)ASDAS, mean (SD)3.5 (1.1)3.7 (1.0)4.0 (1.0)3.3 (1.0)3.3 (1.1)On Infliximab, %25.721222436Baseline csDMARD use, %-Methotrexate045063-Sulfasalazine068033-Leflunomide0801Conclusion:Considerable differences were observed across countries in the use of combination therapy and TNFi retention in axSpA patients. The overall 1-year TNFi retention was higher with csDMARD co-therapy compared to TNFi monotherapy. TNFi monotherapy had a 12-13% higher risk of treatment discontinuation.Acknowledgments:Novartis Pharma AG and IQVIAMN and BD participated equallyDisclosure of Interests:Michael Nissen Grant/research support from: Abbvie, Consultant of: Novartis, Lilly, Abbvie, Celgene and Pfizer, Speakers bureau: Novartis, Lilly, Abbvie, Celgene and Pfizer, Bénédicte Delcoigne: None declared, Daniela Di Giuseppe: None declared, Lennart T.H. Jacobsson Consultant of: AbbVie, Eli Lilly, Janssen, Novartis and Pfizer, Karen Fagerli: None declared, Anne Gitte Loft Grant/research support from: Novartis, Consultant of: AbbVie, MSD, Novartis, Pfizer and UCB, Speakers bureau: AbbVie, MSD, Novartis, Pfizer and UCB, Adrian Ciurea Consultant of: Consulting and/or speaking fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Merck Sharp & Dohme, Novartis and Pfizer., Dan Nordström Consultant of: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Speakers bureau: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., 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., 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, Maria Jose Santos Speakers bureau: Novartis and Pfizer, Manuel Pombo-Suarez Consultant of: Janssen, Lilly, MSD and Sanofi., Speakers bureau: Janssen, Lilly, MSD and Sanofi., Björn Gudbjornsson Speakers bureau: Novartis and Amgen, Heřman Mann: None declared, Nurullah Akkoc: None declared, 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, Irene van der Horst-Bruinsma Grant/research support from: AbbVie, Novartis, Eli Lilly, Bristol-Myers Squibb, MSD, Pfizer, UCB Pharma, Consultant of: AbbVie, Novartis, Eli Lilly, Bristol-Myers Squibb, MSD, Pfizer, UCB Pharma, Brigitte Michelsen: None declared, Gary Macfarlane: None declared, Merete L. Hetland Grant/research support from: BMS, MSD, AbbVie, Roche, Novartis, Biogen and Pfizer, Consultant of: Eli Lilly, Speakers bureau: Orion Pharma, Biogen, Pfizer, CellTrion, Merck and Samsung Bioepis, Matija Tomsic: None declared, Burkhard Moeller: None declared, Pedro Ávila-Ribeiro Grant/research support from: Novartis, Carlos Sánchez-Piedra: None declared, Heikki Relas Grant/research support from: Abbvie., Consultant of: Abbvie, Celgene, and Pfizer., Speakers bureau: Abbvie, Celgene, and Pfizer., Arni Jon Geirsson: None declared, Lucie Nekvindova: None declared, Gozde Yildirim Cetin Speakers bureau: AbbVie, Novartis, Pfizer, Roche, UCB, MSD, Ruxandra Ionescu Consultant of: Consulting fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Speakers bureau: Consulting and speaker fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Niels Steen Krogh: None declared, Johan Askling Grant/research support from: JA acts or has acted as PI for agreements between Karolinska Institutet and the following entities, mainly in the context of the ARTIS national safety monitoring programme of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB Pharma, Bente Glintborg Grant/research support from: Grants from Pfizer, Biogen and Abbvie, Ulf Lindström: None declared

Background:Tumor necrosis factor inhibitors (TNFi) have been available for more than a decade for treatment of spondyloarthrtitis (SpA). Secukinumab (SEC) represents a new mode of action, but few studies have compared outcomes in patients(pts) treated with SEC vs TNFi – and the optimal treatment strategy in routine care remains to be established. Comparative studies between SEC and adalimumab (ADA) are ongoing.Objectives:To describe baseline characteristics and compare 1-yr treatment retention of SEC vs TNFi (ADA/certolizumab pegol(CLZ)/etanercept(ETN)/golimumab(GOL)/infliximab(IFX)) in SpA-pts from 5 Nordic countries.Methods:Observational, prospective cohort study. Pts with SpA (ankylosing spondylitis/non-radiographic axial SpA/undifferentiated SpA) starting SEC or any TNFi during 2015-2018 were identified in clinical rheumatology registries of the Nordic countries. Baseline characteristics were retrieved. Country-specific data were pooled. 1-yr treatment retention of SEC vs TNFi was assessed through crude survival probability curves, retention rates and adjusted Cox regression analyses (ADA reference). Analyses were stratified by line of bDMARD and TNFi type.Results:In total, 10692 treatment courses (834 SEC, 9858 TNFi) in 7952 patients were included. SEC was rarely used as 1stbDMARD (Table 1), whereas it was the drug most frequently used as 3rd+ line (Table 2). Baseline characteristics were numerically similar for SEC vs TNFi (Table 1).Table 1.Patient characteristics at treatment start1stline2ndline3rd+ lineSECTNFiSECTNFiSECTNFiN70518615626056082067Male, %535544534546Age, yrs45 (14)41 (14)45 (12)44 (13)47 (12)46 (13)BASDAI, mm45 (28)53 (22)52 (22)52 (24)63 (22)58 (24)Concomitant csDMARD, %182723232726Means (SD) unless otherwise statedTable 2.Table 2. 1-yr treatment retention (Kaplan Meier, Cox Regression)DrugRetentions rates, 1 yr % (95% CI)Adjusted* HR (95% CI) for discontinuation1stlineADA76 (73-79)1CLZ68 (63-72)1.4 (1.1-1.8)ETN74 (71-76)1.1 (0.9-1.3)GOL80 (77-84)0.8 (0.6-1.0)IFX65 (62-67)1.5 (1.3-1.8)SEC76 (62-85)0.9 (0.5-1.6)2ndlineADA72 (68-75)1CLZ58 (51-64)1.5 (1.2-1.9)ETN65 (61-68)1.2 (1.0-1.5)GOL73 (67-77)0.9 (0.7-1.2)IFX67 (63-71)1.2 (0.9-1.5)SEC67 (58-74)1.1 (0.8-1.5)3rd+ lineADA73 (68-77)1CLZ52 (46-57)2.0 (1.6-2.6)ETN65 (61-70)1.3 (1.0-1.6)GOL65 (60-70)1.3 (1.0-1.7)IFX61 (56-66)1.5 (1.2-1.9)SEC61 (57-65)1.4 (1.1-1.8)* by sex, baseline age, BASDAI, concomitant csDMARD (y/n/missing). Pts with missing baseline BASDAI (41-60%) excluded1-yr treatment retention varied between the TNFi (Figure,Table 2), with SEC showing retention rates comparable to ADA when used as 1stor 2ndline therapy. However, SEC retention was poorer than ADA when used as 3rd+ therapy, but comparable to retention of other TNFi.In adjusted Cox regression analyses, confidence intervals were wide and included 1 for SEC vs ADA (1st, 2ndline), whereas there was slightly poorer retention of SEC versus ADA when used as 3rd+ bDMARD (Table 2).Conclusion:These observational data in >10.000 biological treatment courses in SpA, showed that SEC was mainly used in bDMARD experienced pts. Baseline characteristics were similar in pts treated with SEC vs TNFi. The 1-yr retention for SEC was similar to that of the TNFi when used as 1stor 2ndline, but poorer than ADA regarding 3rd+ courses. Further analyses are planned to explore confounding by indication and channeling towards treatment.Acknowledgments:Glintborg/Lindström shared 1st author, Kristensten/Jacobsson shared last.Partly funded by NordForsk and FOREUMDisclosure of Interests:Bente Glintborg Grant/research support from: Grants from Pfizer, Biogen and Abbvie, Ulf Lindström: None declared, Daniela Di Giuseppe: None declared, Sella Aarrestad Provan Consultant of: Novartis, Björn Gudbjornsson Speakers bureau: Novartis and Amgen, Merete L. Hetland Grant/research support from: BMS, MSD, AbbVie, Roche, Novartis, Biogen and Pfizer, Consultant of: Eli Lilly, Speakers bureau: Orion Pharma, Biogen, Pfizer, CellTrion, Merck and Samsung Bioepis, Brigitte Michelsen Grant/research support from: Research support from Novartis, Consultant of: Consulting fees Novartis, Johan K Wallman Consultant of: AbbVie, Celgene, Eli Lilly, Novartis and UCB Pharma, Kalle Aaltonen: None declared, Anna-Mari Hokkanen Grant/research support from: MSD, Tanja Schjødt Jørgensen Speakers bureau: Abbvie, Pfizer, Roche, Novartis, UCB, Biogen, and Eli Lilly, Rebekka L. Hansen: None declared, Arni Jon Geirsson: None declared, Kathrine L. Grøn Grant/research support from: BMS, Niels Steen Krogh: None declared, Johan Askling Grant/research support from: JA acts or has acted as PI for agreements between Karolinska Institutet and the following entities, mainly in the context of the ARTIS national safety monitoring programme of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB Pharma, Lars Erik Kristensen Consultant of: UCB Pharma (Advisory Board), Sannofi (Advisory Board), Abbvie (Advisory Board), Biogen (Advisory Board), Speakers bureau: AbbVie, Amgen, Biogen, Bristol-Myers Squibb,Celgene, Eli Lilly, Gilead, Forward Pharma, Janssen Pharmaceuticals, MSD, Novartis, Pfizer, and UCB Pharma, Lennart T.H. Jacobsson Consultant of: AbbVie, Eli Lilly, Janssen, Novartis and Pfizer

Background:Only few studies have looked at the association between tea consumption and risk of rheumatoid arthritis (RA) with inconclusive results.Objectives:To estimate the association between tea consumption and risk of RA in a large population-based case-control study.Methods:We used data from the Swedish Epidemiological Investigation of RA (EIRA), a population-based case-control study including incident RA cases with 2 controls randomly matched from the general population, based on age, sex and residential area at the date of diagnosis. All participants filled in a comprehensive questionnaire on lifestyle factors, including a 124-item food frequency questionnaire (FFQ). Data from October 2005 - May 2018 was used.Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated using conditional logistic regression, overall and stratified by anti-citrullinated protein antibody (ACPA) and smoking status. We adjusted for smoking status, coffee and alcohol consumption, educational level and BMI. The dose-response trend of the association between tea consumption and risk of rheumatoid arthritis was estimated using restricted cubic spline with knots at 0, 0.29, and 2.29 cups per day. Missing tea values (44.8%) were imputed based on the zero-consumption assumption. A sensitivity analysis was performed to evaluate the influence of the assumption on the main result, with 70% of the missing randomly imputed as no consumption, and the remaining 30% randomly assigned to the other categories (10% per category).Results:We included 2237 cases and 4661 controls. Controls were more likely to drink ≥2 tea cups/day compared to RA cases (22.1% vs. 19.7%).The crude odds of developing RA was 22% lower (OR=0.78, 95% CI: 0.66-0.92) among those who consumed ≥2 tea cups/day compared to those who drank =2 cups/day compared to irregular tea drinkers (OR=0.76, 95% CI: 0.62-0.94). In analyses stratified by smoking, an inverse association between tea intake and RA was found only among current smokers (OR=0.58, 95% CI: 0.37-0.92), while no association was found in never smoker. The sensitivity analysis showed results similar to the main analysis, although the OR in the no consumption category was not significant (OR=0.88, 95% CI: 0.76-1.02) while the OR in the highest category was statistically significant (OR=0.85, 95% CI: 0.73-0.99).Overall tea consumption0 cups/day1-2 cups/day>=2 cups/dayOverall Number955/1941453/847388/845441/1028 OR crude*0.89 (0.77-1.03)Ref0.84 (0.71-1.00)0.78 (0.66-0.92) OR adjusted±0.82 (0.70-0.95)Ref0.87 (0.73-1.04)0.85 (0.71-1.01)ACPA positive Number637/1156321/527268/501277/630 OR adjusted0.81 (0.67-0.97)Ref0.88 (0.71-1.09)0.76 (0.62-0.94)ACPA negative Number312/571129/221119/251162/288 OR adjusted0.87 (0.66-1.14)Ref0.87 (0.63-1.19)1.07 (0.78-1.46)Never smokers Number290/859164/436142/433213/563 OR adjusted0.90 (0.72-1.14)Ref0.88 (0.68-1.15)1.04 (0.81-1.33)Current smokers Number296/37189/9659/7859/99 OR adjusted0.81 (0.57-1.14)Ref0.83 (0.52-1.31)0.58 (0.37-0.92)Figure 1.Dose-response odds ratio for risk of rheumatoid arthritis (RA) by tea consumption.Conclusion:In this large population-based case-control study, high tea consumption, as well as no consumption, was associated with a decreased risk to develop ACPA positive, but not negative, RA, when compared to irregular tea drinking (Disclosure of Interests:Helga Westerlind: None declared, Ida Palmqvist: None declared, Saedis Saevarsdottir Employee of: part-time employee of deCODE genetics, Lars Alfredsson: None declared, Lars Klareskog: None declared, Daniela Di Giuseppe: None declared

Background:In contrast to the increased mortality reported in other inflammatory diseases such as rheumatoid arthritis and psoriasis, prior mortality studies in psoriatic arthritis (PsA) have shown inconsistent results.Objectives:To compare all-cause mortality between PsA patients in Sweden and matched general population controls, and to describe cause of death distributions in the two groups.Methods:All individuals in Sweden with ≥1 main diagnosis of PsA (ICD-10: L40.5/M07.0-M07.3) from outpatient visits to rheumatology or internal medicine clinics at age ≥18 years (y) 2001-2017 were identified from the Swedish National Patient Register. Each case was matched to 5 general population controls based on sex, county and age in the year of the first registered arthritis diagnosis for the case. Cases and controls were followed from 1 Jan, 2007, or from first PsA diagnosis thereafter for index cases, until first occurrence of death (data from the Swedish Cause of Death Register), emigration or 31 Dec, 2018. Mortality was assessed overall, as well as stratified by sex (45% males) and disease duration (PsA diagnosis prior to 2007 [38% of cases] vs. 2007-2017), using matched Cox proportional hazard regression, or – in case the Cox assumption regarding proportionality did not hold – matched Breslow test. To account for potential PsA misclassification (in a previous validation study, 86% of 400 cases fulfilled PsA classification criteria), a sensitivity analysis was performed by randomly replacing 20% of cases with one of their own controls. Moreover, incidence rate ratios (IRR) of death were calculated overall and stratified by sex, disease duration and age. Finally, causes of death (from the Cause of Death Register) were described for PsA cases and controls.Results:Over the 12y follow-up, 3 121 deaths occurred among 33 036 PsA cases (268 402 person-years at risk) and 12 884 deaths among 161 144 controls (1 302 250 person-years), resulting in an increased mortality among the PsA cases (HR 1.11 [95%CI 1.07-1.16], pTable 1.Mortality rates and incidence rate ratiosPsA casesPopulation controlsNumber of deathsPerson-yearsat riskMortality rate*Number of deathsPerson-yearsat riskMortality rate*Incidence rate ratio (95%CI)Overall3 121268 40211.612 8841 302 2509.91.18 (1.13-1.22)Males1 459120 51712.16 468580 28511.11.09 (1.03-1.15)Females1 662147 88611.26 416721 9668.91.27 (1.20-1.34)Longer disease duration1 943139 37913.97 459670 17411.11.25 (1.19-1.32)Shorter disease duration1 178129 0239.15 425632 0778.61.06 (1.00-1.13)Age intervals (years)1833 5680.598163 2780.60.89 (0.54-1.48)40-499050 5521.8322246 9551.31.37 (1.08-1.73)50-5928065 8204.31 131321 7303.51.21 (1.06-1.38)60-6972370 22410.33 132341 5879.21.12 (1.04-1.22)70-7996037 23225.84 160178 90923.31.11 (1.03-1.19)≥801 05011 00795.44 04149 79181.21.18 (1.10-1.26)* Per 1000 person-years.Conclusion:In this nationwide 12y assessment, the mortality risk among PsA patients in Sweden was increased by around 10% as compared to the general population, mainly driven by increased risks among females and patients with longer disease duration. Cause of death distributions were numerically similar between PsA cases and controls.References:Disclosure of Interests:Sofia Exarchou Consultant of: AbbVie, Novartis, Daniela Di Giuseppe: None declared, Gerd-Marie Alenius: None declared, Eva Klingberg Speakers bureau: Eli Lilly, Consultant of: Novartis, Grant/research support from: Roche, Valgerdur Sigurdardottir Consultant of: Novartis, Sanofi, Sara Wedrén: None declared, Ulf Lindström: None declared, Carl Turesson Speakers bureau: AbbVie, BMS, Pfizer, Roche, Consultant of: Roche, Grant/research support from: BMS, Lennart T.H. Jacobsson Consultant of: AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, Johan Askling Grant/research support from: For ARTIS: AbbVie, BMS, Eli Lilly, Merck, Pfizer, Roche, Samsung Bioepis, Sanofi, UCB. This study was supported by AbbVie, Amgen, Eli Lilly, Novartis and Pfizer. The sponsors were allowed to comment on the study protocol and were provided with a report of the results, but had no influence on the study design or decision to submit the abstract., Johan K Wallman Consultant of: Celgene, Eli Lilly, Novartis

Background:Biosimilar products of biological disease-modifying antirheumatic drugs (bDMARDs) entered the Swedish market in 2015, with regulatory approvals based on head to head trials of limited duration. Longer-term comparative drug survival, in clinical practice, remains less well documented.Objectives:To compare survival on drug between biosimilars and their originator products among first starters of etanercept, infliximab, adalimumab and rituximab.Methods:Data from the Swedish Rheumatology Quality register (SRQ) was used to identify and follow patients who started a first ever treatment with etanercept since April 2015 (originator=ETA,biosimilar= SB4), infliximab since March 2014 (originator=IFX,biosimilar= CT-P13), adalimumab since January 2018 (originator=ADA biosimilars=SB5, ABP501), or rituximab since January 2018 (originator=RIT,biosimilar= GP2013), through December 31st, 2019, date of first discontinuation of the drug, or death. Discontinuation was defined as lack of effectiveness or adverse events, while other reasons for interruption of the drug (including non-medical switch) were considered censoring events. Descriptive characteristics were collected from the SRQ and tabulated. Hazard ratios (HR) of discontinuation were estimated using Cox regression, with each drug analyzed separately, adjusted for age,sex,indication,line of treatment,disease duration,year of treatment start,region and concomitant use of csDMARD.Results:9274 patients started etanercept(49% SB4), 3609 started infliximab(64% CT-P13), 3117 started adalimumab(27% SB5, 14% ABP 501), and 763 started rituximab(39% GP2013), Table 1. Patients starting CT-P13 and GP2013 were less likely to be biologics-naïve compared to those starting the originator product. Initiators of SB5,ABP501 and GP2013 were more likely,and those starting CT-P13 were less likely,to be on concomitant csDMARDs compared to those starting the originator products. Patients characteristics of ETA and SB4 were similar.The introduction of a biosimilar was typically followed by a decrease in the uptake of the originator, but for ETA a change in pricing in 2018 later led to a reversal of this pattern (Figure 1).For IFX,ADA,and RIT, survival on drug was similar for the originator and its biosimilar(s). For ETA,risk of discontinuation was somewhat lower for the biosimilar than for the originator(adjusted HR:0.87,95% confidence interval:0.79-0.95), Table 1.Table 1.Hazard ratios of discontinuation and descriptive characteristics of biosimilar vs. originator among first starters of each molecule, until 31st December 2019.EtanerceptInfliximabAdalimumabRituximabOriginatorSB4OriginatorCT-P13OriginatorSB5ABP 501OriginatorGP2013N47214553130823011834852431465298Discontinuation12891236582878399139805726Adjusted hazard ratios*Ref0.87 (0.79-0.95)Ref1.14 (0.99-1.31)Ref1.02 (0.83-1.26)1.16 (0.88-1.52)Ref1.12 (0.68-1.85)Age, mean years (std)51 (16)51 (15)49 (16)49 (16)48 (15)52 (15)51 (15)59 (15)60 (15)Female, %67%65%61%64%62%64%65%75%76%RA, %46%48%39%35%33%42%43%61%76%Bionaïve, %72%72%76%69%45%52%43%53%38%Disease duration, mean years (std)11 (12)11 (11)11 (11)11 (11)12 (13)12 (11)14 (15)14 (19)15 (11)DAS28, mean4.0 (1.3)4.0 (1.4)4.1 (1.4)4.1 (1.4)3.7 (1.4)3.8 (1.3)4.0 (1.3)4.5 (1.4)4.7 (1.4)Concomitant csDMARDs, %45%47%57%48%37%49%42%36%43%Abbreviations: RA=rheumatoid arthritis. csDMARDs=conventional synthetic DMARD, std=standard deviation.Figure 1.Number of starts of biosimilars compared to the originator during the follow-up time, by moleculeConclusion:Despite their identical indications and therapeutic positioning, there are some differences in the baseline characteristics between patients who start ADA, IFX and RIT and their biosimilars. There are no differences in drug survival between originator and biosimilar with the possible exception of etanercept although the observed difference should be interpreted in light of possible unmeasured or residual channeling.Disclosure of Interests:Daniela Di Giuseppe: None declared, Hannah Bower: None declared, Bénédicte Delcoigne: None declared, Thomas Frisell: None declared, Katerina Chatzidionysiou Consultant of: Eli Lilly, AbbVie and Pfizer, Ulf Lindström: None declared, Christopher Sjowall: None declared, Elisabet Lindqvist: None declared, Johan Askling Grant/research support from: Abbvie, Astra-Zeneca, BMS, Eli Lilly, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB

Background:Knowledge of changes over time in baseline characteristics and tumor necrosis factor inhibitor (TNFi) response in bionaïve psoriatic arthritis (PsA) patients treated in routine care is limited.Objectives:To investigate secular trends in baseline characteristics and retention, remission and response rates in PsA patients initiating a first TNFi.Methods:Prospectively collected data on bionaïve PsA patients starting TNFi in routine care from 15 European countries were pooled. According to year of TNFi initiation, three groups were defined a priori based on bDMARD availability: Group A (1999–2008), Group B (2009–2014) and Group C (2015–2018).Retention rates (Kaplan-Meier), crude and LUNDEX adjusted1 remission (Disease Activity Score (DAS28) Results:A total of 17453 PsA patients were included (4069, 7551 and 5833 in groups A, B and C).Patients in group A were older and had longer disease duration compared to B and C. Retention rates at 6, 12 and 24 months were highest in group A (88%/77%/64%) but differed little between B (83%/69%/55%) and C (84%/70%/56%).Baseline disease activity was higher in group A than in B and C (DAS28: 4.6/4.3/4.0, DAPSA28: 29.9/25.7/24.0, CDAI: 21.8/20.0/18.6), and this persisted at 6 and 12 months. Crude and LUNDEX adjusted remission rates at 6 and 12 months tended to be lowest in group A, although crude/LUNDEX adjusted ACR50 response rates at all time points were highest in group A. At 24 months, disease activity and remission rates were similar in the three groups (Table).Table 1.Secular trends in baseline characteristics, treatment retention, remission and response rates in European PsA patients initiating a 1st TNFiBaseline characteristicsGroup A(1999–2008)Group B(2009–2014)Group C(2015–2018)Age, median (IQR)62 (54–72)58 (49–67)54 (45–62)Male, %514847Years since diagnosis, median (IQR)5 (2–10)3 (1–9)3 (1–8)Smokers, %161717DAS28, median (IQR)4.6 (3.7–5.3)4.3 (3.4–5.1)4.0 (3.2–4.8)DAPSA28, median (IQR)29.9 (19.3–41.8)25.7 (17.2–38.1)24.0 (16.1–35.5)CDAI, median (IQR)21.8 (14.0–31.1)20.0 (13.0–29.0)18.6 (12.7–26.1)TNFi drug, % (Adalimumab / Etanercept / Infliximab / Certolizumab / Golimumab)27 / 43 / 30 / 0 / 036 / 31 / 14 / 5 / 1421 / 40 / 21 / 8 / 10Follow up6 months12 months24 monthsGr AGr BGr CGr AGr BGr CGr AGr BGr CRetention rates, % (95% CI)88 (87–89)83 (82–84)84 (83–85)79 (78–80)72 (71–73)72 (71–73)68 (67–69)60 (59–61)60 (59–62)DAS28, median (IQR)2.7 (1.9–3.6)2.4 (1.7–3.4)2.3 (1.7–3.2)2.5 (1.8–3.4)2.2 (1.6–3.1)2.1 (1.6–2.9)2.1 (1.6–3.1)2.0 (1.6–2.9)1.9 (1.5–2.6)DAPSA28, median (IQR)10.6 (4.8–20.0)9.5 (3.9–18.3)8.7 (3.6–15.9)9.1 (4.1–17.8)7.7 (3.1–15.4)7.6 (2.9–14.4)6.7 (2.7–13.7)6.6 (2.7–13.5)5.9 (2.4–11.8)CDAI, median (IQR)7.8 (3.0–15.2)8.0 (3.0–15.0)6.4 (2.6–12.2)6.4 (2.5–13.0)6.2 (2.5–12.1)5.8 (2.2–11.4)5.0 (2.0–11.0)5.5 (2.0–11.2)5.0 (2.0–9.0)DAS28 remission, %, c/L47 / 4255 / 4661 / 5153 / 4362 / 4566 / 4864 / 4268 / 3775 / 41DAPSA28 remission, %, c/L22 / 1926 / 2228 / 2325 / 2031 / 2232 / 2336 / 2334 / 1938 / 21CDAI remission, %, c/L23 / 2123 / 1926 / 2227 / 2127 / 2029 / 2134 / 2231 / 1735 / 19ACR50 response, %, c/L26 / 2322 / 1824 / 2027 / 2223 / 1721 / 1523 / 1518 / 1014 / 8Gr, Group; c/L, crude/LUNDEX.Conclusion:Over the past 20 years, patient age, disease duration and disease activity level at the start of the first TNFi in PsA patients have decreased. Furthermore, TNFi retention rates have decreased while remission rates have increased, especially remission rates within the first year of treatment. These findings may reflect a greater awareness of early diagnosis in PsA patients, a lowered threshold for initiating TNFi and the possibility for earlier switching in patients with inadequate treatment response.References:[1]Arthritis Rheum 2006; 54: 600-6.Acknowledgements:Novartis Pharma AG and IQVIA for supporting the EuroSpA Research Collaboration Network.Disclosure of Interests:Sara Nysom Christiansen Speakers bureau: BMS and GE, Grant/research support from: Novartis, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Simon Horskjær Rasmussen: None declared, Anne Gitte Loft Speakers bureau: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, UCB, Consultant of: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, UCB, Grant/research support from: Novartis, Johan K Wallman Consultant of: Celgene, Eli Lilly, Novartis, Florenzo Iannone Speakers bureau: Abbvie, MSD, Novartis, Pfizer and BMS, Brigitte Michelsen Consultant of: Novartis, Grant/research support from: Novartis, Michael J. Nissen Speakers bureau: Novartis, Eli Lilly, Celgene, and Pfizer, Consultant of: Novartis, Eli Lilly, Celgene, and Pfizer, Jakub Zavada: None declared, Maria Jose Santos Speakers bureau: AbbVie, Novartis, Pfizer, Manuel Pombo-Suarez: None declared, Kari Eklund: None declared, Matija Tomsic Speakers bureau: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Consultant of: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Björn Gudbjornsson Speakers bureau: Amgen and Novartis, İsmail Sari: None declared, Catalin Codreanu Speakers bureau: AbbVie, Amgen, Egis, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Amgen, Egis, Novartis, Pfizer, UCB, Daniela Di Giuseppe: None declared, Bente Glintborg Grant/research support from: Pfizer, Biogen, AbbVie, Marco Sebastiani: None declared, Karen Minde Fagerli: None declared, Burkhard Moeller: None declared, Karel Pavelka Speakers bureau: AbbVie, Roche, MSD, UCB, Pfizer, Novartis, Egis, Gilead, Eli Lilly, Consultant of: AbbVie, Roche, MSD, UCB, Pfizer, Novartis, Egis, Gilead, Eli Lilly, Anabela Barcelos: None declared, Carlos Sánchez-Piedra: None declared, Heikki Relas: None declared, Ziga Rotar Speakers bureau: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Consultant of: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Thorvardur Love: None declared, Servet Akar: None declared, Ruxandra Ionescu Speakers bureau: Abbvie, Amgen, Boehringer-Ingelheim Eli-Lilly,Novartis, Pfizer, Sandoz, UCB, Gary Macfarlane Grant/research support from: GlaxoSmithKline, Marleen G.H. van de Sande: None declared, Merete L. Hetland Speakers bureau: Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis., Mikkel Østergaard Speakers bureau: AbbVie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Centocor, GSK, Hospira, Janssen, Merck, Mundipharma, Novartis, Novo, Orion, Pfizer, Regeneron, Schering-Plough, Roche, Takeda, UCB and Wyeth, Consultant of: AbbVie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Centocor, GSK, Hospira, Janssen, Merck, Mundipharma, Novartis, Novo, Orion, Pfizer, Regeneron, Schering-Plough, Roche, Takeda, UCB and Wyeth

Background:Randomized controlled trials indicate that compared to tumor necrosis factor inhibitors (TNFi), secukinumab (SEC) has similar efficacy regarding axial inflammation in spondyloarthritis (SpA), better efficacy regarding cutaneous psoriasis, but is inferior in inflammatory bowel disease (IBD). However, the efficacy of SEC compared to TNFi in anterior uveitis (AU) has not been extensively studied.Objectives:To compare the occurrence of AU in patients with SpA treated with SEC, adalimumab (ADA), infliximab (IFX) or etanercept (ETN), in clinical practice.Methods:Patients with ankylosing spondylitis or undifferentiated SpA starting either SEC, ADA, IFX or ETN, in 2015 through 2017, were identified in the Swedish Rheumatology Quality register, and were linked to the national patient register for identification of AU. AU-flares were defined as the number of visits with an AU diagnosis, separated by a ≥60 days penalty interval, within ophthalmology outpatient care, during the respective bDMARD treatment.Follow-up started at the bDMARD initiation, and ended at the first of Dec 31st2017, death, emigration or discontinuation date of the bDMARD.To assess and accommodate treatment channeling, crude incidence rates for AU-flares were determined (A) for all bDMARD treatment starts, (B) excluding patients with an AU diagnosis during the year prior to the bDMARD start, and (C) in addition, excluding all first line bDMARD treatment starts.Hazard ratios (HR) for time until a first on-treatment AU diagnosis were estimated using Cox regression (ADA=reference), adjusted for sex, age, and any history of AU, and estimating robust confidence intervals to account for the individuals contributing multiple lines of treatment.Results:In total, 2,684 patients (52% women) contributed 3,255 treatment initiations. SEC was less frequently used as first line bDMARD and there was channeling of patients with previous AU, towards treatment with ADA, and away from ETN (Table 1). Further, AU occurred almost exclusively in patients with a pre-treatment history of AU (data not shown).Table 1.AnalysisTreat-ment starts, NPrevious AU1Age at treat-ment start, mean (sd)N Previous bDMARD, medianHR (95% CI) for first AU-diagnosisAU flares, NFollow-up2, yearsA. All treatment starts, N=3255SEC33321%48 (13)22.0 (1.2-3.3)52241ADA87234%44 (12)1Ref175973IFX71421%43 (14)00.9 (0.6-1.4)68677ETN133617%44 (14)00.9 (0.7-1.3)1021290B. Excluding patients with prior AU within 1 year before treatment start, N=2907SEC30413%47 (13)23.1 (1.4-7.3)10212ADA71119%44 (13)1Ref18792IFX63311%43 (14)01.0 (0.4-2.3)8599ETN125912%44 (14)01.8 (1.0-3.4)431204C. Excluding patients with prior AU within 1 year before treatment start and first line bDMARD, N=1288SEC28414%48 (13)22.5 (1.0-6.2)10198ADA37418%45 (13)1Ref11384IFX18512%45 (14)21.3 (0.4-4.0)4166ETN44517%47 (14)11.9 (0.9-4.0)234391) Anterior uveitis between 2001 and treatment start; 2) Total follow-up time for analyses of incidence rate.The incidence rates of AU-flares were higher for SEC and ETN compared to ADA and IFX, in the analyses (B, C) accommodating for channeling, figure 1.Compared to ADA, the adjusted HRs of a first on-treatment AU-diagnosis were also higher for SEC and ETA, Table 1.Conclusion:In clinical practice, SEC and ETN are associated with a higher incidence of AU than ADA and INF, suggesting a poorer protective effect of SEC and ETN against AU. These preliminary results should be interpreted in light of pronounced treatment channeling, which was only partly accommodated for.Disclosure of Interests:Ulf Lindström: None declared, Karin Bengtsson: None declared, Tor Olofsson: None declared, Daniela Di Giuseppe: None declared, Bente Glintborg Grant/research support from: Grants from Pfizer, Biogen and Abbvie, Helena Forsblad-d’Elia Grant/research support from: Unrestricted grant from Novartis., Consultant of: Advisory Board Fees from Sandoz, Novartis, and Abbvie, Lennart T.H. Jacobsson Consultant of: AbbVie, Eli Lilly, Janssen, Novartis and Pfizer, Johan Askling Grant/research support from: JA acts or has acted as PI for agreements between Karolinska Institutet and the following entities, mainly in the context of the ARTIS national safety monitoring programme of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB Pharma

Background:A head-to-head trial (EXCEED) has indicated similar effectiveness of secukinumab (SEC) and the tumor necrosis factor inhibitor (TNFi) adalimumab (ADA) in psoriatic arthritis (PsA). In the clinical setting, treatment retention serves as a combined measure of overall effectiveness and tolerability.Objectives:To explore baseline patient characteristics, and compare treatment retention rates for SEC and each of etanercept (ETN), infliximab (IFX), golimumab (GOL), certolizimab (CZP) and ADA in PsA.Methods:Patients starting SEC or any TNFi in 2015-2018, in the 5 Nordic countries, were identified in clinical rheumatology registers. Data were pooled for analysis and stratified by 1st, 2ndand ≥3rdline of treatment. One year treatment retention was compared by crude Kaplan-Meier curves and a proportional hazard model for risk of discontinuation, censored at 1 year and adjusted for sex, age, country and baseline CRP, patient global and use of csDMARD, with ADA as reference.Results:In total, 6062 patients with PsA were included, contributing 8172 treatment starts (table 1). SEC was mainly used as 2ndor ≥3rdline treatment. The survival curves and 1-year treatment retention rates, stratified by line of treatment, were similar for SEC compared to the TNFis, with some differences between the different TNFi (fig 1, table 2). Adjusted hazard ratios (HR) also indicated similar risk of SEC withdrawal compared to ADA (table 2).Table 1.Patient characteristics at treatment start1stline2ndline≥3rdlineSECN=164TNFiN=3808SECN=273TNFiN=1767SECN=767TNFiN=1393Females48%47%44%42%36%39%Age, years52 (13)49 (13)50 (12)50 (13)52 (12)51 (12)Disease duration, years12 (10)10 (10)13 (10)13 (10)16 (10)16 (10)Swollen joint count 283 (4)2 (3)2 (3)2 (3)3 (4)2 (3)CRP, mg/L10 (18)10 (17)7 (11)9 (17)13 (22)11 (20)Patient global score57 (24)58 (24)60 (25)59 (26)68 (23)65 (24)Concomitant therapycsDMARD30%60%41%57%49%53% Methotrexate24%49%31%48%40%44% Sulphasalazine2%9%5%5%4%6%Numbers are mean (SD) unless noted otherwiseTable 2.One year treatment retention and hazard of discontinuation for SEC and TNFiLine of treatmentDrugN1 year treatment retention % (95% CI)Adjusted HR (95% CI) for discontinuation1stlineADA56973 (69-76)RefCZP27366 (60-72)1.2 (0.9-1.6)ETN174773 (71-75)0.9 (0.7-1.1)GOL21267 (60-73)1.2 (0.9-1.7)IFX100762 (59-65)1.4 (1.1-1.7)SEC16472 (63-78)1.0 (0.7-1.4)2ndlineADA41569 (63-73)RefCZP17651 (43-58)1.6 (1.2-2.2)ETN70163 (59-66)1.2 (0.9-1.5)GOL15169 (61-76)0.9 (0.6-1.2)IFX32465 (59-70)1.0 (0.8-1.4)SEC27369 (62-74)0.9 (0.7-1.2)≥3rdlineADA34667 (62-72)RefCZP22149 (42-56)1.5 (1.2-2.0)ETN37262 (57-67)1.1 (0.9-1.5)GOL20656 (49-63)1.3 (1.0-1.8)IFX24857 (50-63)1.3 (1.0-1.8)SEC76763 (59-67)1.0 (0.8-1.3)Conclusion:In this large study of bDMARD treatment of PsA in clinical practice, SEC was most often used as 2ndor ≥3rdline treatment, and the treatment retention of SEC was comparable with that of TNFi. Further analyses, taking into account other comorbidities, channeling and effectiveness will be presented.Acknowledgments:UL and BG are shared first, and LJ and LEK shared last authors.Partly funded by Nordforsk and FOREUM.Disclosure of Interests:Ulf Lindström: None declared, Bente Glintborg Grant/research support from: Grants from Pfizer, Biogen and Abbvie, Daniela Di Giuseppe: None declared, Tanja Schjødt Jørgensen Speakers bureau: Abbvie, Pfizer, Roche, Novartis, UCB, Biogen, and Eli Lilly, Björn Gudbjornsson Speakers bureau: Novartis and Amgen, Kathrine L. Grøn Grant/research support from: BMS, Sella Aarrestad Provan Consultant of: Novartis, Brigitte Michelsen: None declared, Merete L. Hetland Grant/research support from: BMS, MSD, AbbVie, Roche, Novartis, Biogen and Pfizer, Consultant of: Eli Lilly, Speakers bureau: Orion Pharma, Biogen, Pfizer, CellTrion, Merck and Samsung Bioepis, Johan K Wallman Consultant of: AbbVie, Celgene, Eli Lilly, Novartis and UCB Pharma, Dan Nordström Consultant of: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Speakers bureau: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Nina Trokovic: None declared, Thorvardur Love: None declared, Niels Steen Krogh: None declared, Johan Askling Grant/research support from: JA acts or has acted as PI for agreements between Karolinska Institutet and the following entities, mainly in the context of the ARTIS national safety monitoring programme of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB Pharma, Lennart T.H. Jacobsson Consultant of: AbbVie, Eli Lilly, Janssen, Novartis and Pfizer, Lars Erik Kristensen Consultant of: UCB Pharma (Advisory Board), Sannofi (Advisory Board), Abbvie (Advisory Board), Biogen (Advisory Board), Speakers bureau: AbbVie, Amgen, Biogen, Bristol-Myers Squibb,Celgene, Eli Lilly, Gilead, Forward Pharma, Janssen Pharmaceuticals, MSD, Novartis, Pfizer, and UCB Pharma

Background:Giant cell arteritis (GCA) is the most common form of systemic vasculitis in adults. GCA is often associated with comorbidities related to the disease itself or caused by its treatment, here: mainly glucocorticosteroids. Since 2017, tocilizumab (TCZ) is approved for the treatment of GCA, but its uptake and treatment outcomes in clinical practice remain to be characterized.Objectives:To describe characteristics of GCA patients treated with tocilizumab (TCZ) in clinical practice, to evaluate the use of prednisolone up until and following TCZ treatment start, and to describe the TCZ treatment duration.Methods:We linked together the Swedish Rheumatology Quality Register (SRQ), the national Prescribed Drug register, and national Patient register, covering data from July 2009 until July 2019. Through these linkages, we identified GCA patients treated with TCZ including start and discontinuation, their comorbidities and use of other medications. TCZ treatment durations were evaluated through survival probability curves.Results:We identified 468 patients with GCA treated with TCZ, before and after its formal approval for GCA, Table 1. Over calendar time, the proportion who started TCZ as first ever bDMARD increased, as did the mean age at start of TCZ. The pattern of co-morbidities and health care utilisation demonstrated substantial burden from, e.g., diabetes and infections (Table). Patients starting treatment with TCZ were characterized by an increasing average dose of prednisolone during the last 1.5 years before TCZ start. Thereafter, prednisolone use declined substantially, from a mean of 15 mg/day in the six months before the start of TCZ to 6 mg/day 1 year after its start (Figure 1). Analysis of the duration of TCZ treatment (from start until discontinuation) suggested that at one year, two thirds of patients were still on treatment (Figure 2).Table.Swedish GCA patients starting treatment with tocilizumab July 2009 - Nov 2019.July 2009 -July 2015July 2016 - July 2017July 2017 -July 2018July 2018 - Nov 2019Patients8914014099Female64%77%73%71%Age, mean (sd)67 (7.9)68 (8.8)69 (8)70 (7.8)Previous use of bDMARDs27%21%11%11%Hospitalisations most recent 5 years, mean (sd)3.9 (4.2)3.2 (2.6)2.9 (2.5)3.3 (3)Co-morbidities, most recent 5 years:Chronic obstructive pulmonary disease6%2%4%3%Ischemic heart disease12%7%14%11%Diabetes mellitus, type 1&234%26%26%26%Fractures (any location)15%14%11%10%Knee/hip replacement7%10%7%8%Myocardial infarction2%1%4%3%Stroke2%4%2%5%Hospitalisation listing infection39%40%39%37%Figure 1.Average daily dose of prednisolone before and after* start of tocilizumab, based on cumulative dose every 6 months. *The average daily dose of prednisolone after the start of TCZ is calculated only among patients who were still on treatment at the end of each period (351 patients in the first 6 months, 251 in 6m-1y, 161 in 1 – 1.5 y, 95 in 1.5 – 2y).Figure 2.Kaplan-Meier curve for tocilizumab in GCA by time since treatment start.Conclusion:Patients treated with TCZ for GCA in clinical practice are characterized by a significant burden of co-morbidities, many of which may be related to prolonged use of glucocorticosteroids. This study confirms a marked reduction in the use of oral prednisolone following treatment with TCZ, and demonstrates that in a majority of patients in clinical practice, treatment with TCZ for GCA is extended beyond one year. Future analyses will evaluate the association of these observed treatment patterns with the level of GCA disease control, co-morbidities and quality of life, over time.Acknowledgments:These analyses was partly funded through an agreement between Roche and Karolinska Institutet.Disclosure of Interests:Daniela Di Giuseppe: None declared, Ann Knight: None declared, Aladdin J Mohammad Speakers bureau: lecture fees from Roche and Elli Lilly Sweden, PI (GiACTA study), Carl Turesson Grant/research support from: Unrestricted grant from Bristol-Myers Squibb, Consultant of: Roche, Speakers bureau: Abbvie, Bristol Myers-Squibb, Pfizer, Roche, Johan Askling Grant/research support from: JA acts or has acted as PI for agreements between Karolinska Institutet and the following entities, mainly in the context of the ARTIS national safety monitoring programme of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB Pharma

Background:The clinical diagnosis of psoriatic arthritis (PsA) may be challenging. In Sweden, the vast majority of PsA cases are diagnosed within rheumatology or internal medicine (IM). Knowledge of the correspondence between clinical ICD diagnoses and classification criteria fulfillment is crucial to interpret studies identifying cases based on ICD codes.Objectives:To assess the degree to which patients with clinical PsA diagnoses in Sweden fulfill established PsA classification criteria.Methods:Four hundred patients with ≥1 outpatient physician visit to one of five rheumatology or IM departments (3 university/2 county departments, spread across Sweden) 2013-2015 with a main ICD-10 diagnosis of PsA (L40.5/M07.0-M07.3), were randomly selected from the Swedish National Patient Register (80 cases/site). Based on a structured medical record review, positive predictive values (PPV) of a clinical PsA diagnosis (i.e. ≥1 visit with a PsA ICD-10 code) for fulfillment of the following classification criteria were assessed: CASPAR,[1] Moll & Wright,[2] Vasey & Espinoza,[3] and Modified ESSG criteria for PsA,[4] respectively (as well as for any of these); ASAS criteria for peripheral or axial spondyloarthritis (SpA) [5]; and the 1987 ACR criteria for rheumatoid arthritis (RA).[6] Subanalyses regarding CASPAR fulfillment were also performed restricted to patients with available rheumatoid factor and peripheral X-ray status (central CASPAR items; n=227), and among patients with ≥2 ICD codes for PsA, of which ≥1 from a rheumatology/IM department (n=353).Results:Out of 400 clinically diagnosed PsA patients, 343 (86%) fulfilled any of the 4 PsA classification criteria, with a PPV for CASPAR fulfillment of 69% (rising to 73-82% in the subanalyses;Figure 1). Substantial overlap was seen regarding fulfillment of the 4 PsA criteria (Figure 2A). Moreover, 86% fulfilled the ASAS peripheral or axial SpA criteria, while the 1987 ACR definition of RA was met by 27% – in both cases with the great majority also classifiable as PsA (Figure 2B). Most patients not fulfilling any PsA criteria had either no verified arthritis or polyarticular disease (Table). Overall, only 6.5% of the clinical PsA diagnoses were judged as clearly wrong by the rheumatologists performing the medical record assessments.Conclusion:The validity of clinical ICD-10 diagnoses for PsA in the Swedish National Patient Register is good, with a PPV of 86% for the fulfillment of established PsA classification criteria.References:[1]Arthritis Rheum2006;54:2665-73[2]Semin Arthritis Rheum 1973;3:55-78[3]In: Calin A, editor. Spondyloarthropathies. Orlando: Grune & Stratton; 1984:151-85[4]Ann Rheum Dis2005;64(Suppl II):ii3–ii8[5]Ann Rheum Dis2011;70:25-31[6]Arthritis Rheum1988;31:315-24Patient characteristics (n=400), stratified by classification criteria fulfillmentFulfilling anyPsA criterian=343Not fulfilling anyPsA criterian=57Male sex, %4644Age, yrs; mean (SD)59 (14)62 (15)Symptom duration, yrs; mean (SD)18 (12)16 (13)Psoriasis, %8947Nail psoriasis, %3811Arthritis, %9358 Monoarthritis, %*7.90 Oligoarthritis, %*4522 Polyarthritis, %*4778DIP-joint arthritis, %287.0Dactylitis, %281.8Enthesitis, %4219Inflammatory back pain, %275.3RF positive, %5.814ACPA positive, %4.43.5Arthritic X-ray changes in hands/feet, %3321* % of patients with arthritis of known distribution. Missing data: 0-4%, except forRF (33%), ACPA (37%) and X-ray changes (20%).Acknowledgments:This work was supported by Celgene, Novartis, Pfizer, Reumatikerförbundet and Psoriasisförbundet.Disclosure of Interests:Johan K Wallman Consultant of: AbbVie, Celgene, Eli Lilly, Novartis and UCB Pharma, Gerd-Marie Alenius: None declared, Eva Klingberg Grant/research support from: Roche, Consultant of: Novartis, Speakers bureau: Eli Lilly, Valgerdur Sigurdardottir Consultant of: Novartis, Sara Wedrén: None declared, Sofia Exarchou: None declared, Ulf Lindström: None declared, Daniela Di Giuseppe: None declared, Johan Askling Grant/research support from: JA acts or has acted as PI for agreements between Karolinska Institutet and the following entities, mainly in the context of the ARTIS national safety monitoring programme of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB Pharma, Lennart T.H. Jacobsson Consultant of: AbbVie, Eli Lilly, Janssen, Novartis and Pfizer

Background:Previous studies have suggested similar effectiveness, but longer treatment retention, for tumor necrosis factor inhibitors (TNFi), when used in combination with a conventional synthetic disease modifying anti-rheumatic drug (csDMARD) in psoriatic arthritis (PsA).Objectives:To describe patients with PsA initiating a first TNFi as monotherapy compared to combination therapy, and to explore 1-year treatment retention of TNFi in the two groups.Methods:Patients with PsA starting a first TNFi (2006-2017) were identified in biologics registers of 13 European countries, and data were pooled for analysis. Co-medication with csDMARD was determined at TNFi start.Because of large inter-country variation in TNFi retention, countries were split into two strata, depending on each country’s 1-year retention rate for TNFi being above (stratum A) or below (stratum B) the average 1-year retention rate.TNFi treatment retention was compared through Kaplan-Meier curves; the proportion remaining on the TNFi at one year; and hazard ratios (HR) during the first year: (i) crude; adjusted for (ii) country-strata, and (iii) country-strata, sex, age, calendar year, DAS28 and disease duration. In model (iii) only registers contributing >1000 patients or Results:A total of 14778 patients with PsA starting a first TNFi were included. Baseline disease activity was similar within stratum B, but higher for the combination treatment group in stratum A (table 1).Table 1.Baseline characteristicsCountry strataStratum AStratum BTNFimonotherapyN=2120TNFi/csDMARDcombinationN=2128TNFimonotherapyN=3369TNFi/csDMARDcombinationN=7161Females52%51%53%51%Age, years49.7 (12.2)48.7 (11.8)48.8 (13.0)48.9 (12.2)Disease duration, yrs6.4 (7.0)6.8 (6.8)5.9 (7.5)5.9 (7.1)Tender joints 285.5 (6.3)8.0 (6.3)5.6 (6.0)5.6 (5.7)Swollen joints 282.8 (4.3)5.6 (5.0)3.0 (3.8)3.3 (3.8)VAS pain54 (29)62 (24)59 (23)56 (24)DAPSA-2824.6 (18.6)36.2 (17.6)27.3 (15.6)27.2 (15.2)DAS28 (CRP)3.5 (1.4)4.7 (1.3)4.0 (1.2)4.0 (1.1)Concomitant csDMARDMethotrexate-76%-79%Sulfasalazine-15%-15%Other csDMARD-49%-25%Numbers are means (sd) unless otherwise stated.The Kaplan-Meier curves for the treatment groups were similar within each stratum (fig 1), as were the proportions remaining on TNFi after one year, stratum A: monotherapy 86% (95%CI: 85-88) vs. combination 86% (84-87), stratum B: 71% (69-72) vs. 73% (72-74). The HRs for TNFi discontinuation (ref=TNFi monotherapy) were: (i) 1.06 (0.98-1.13), (ii) 0.94 (0.87-1.01), (iii) 0.89 (0.83-0.96), including 13078 patients (9 countries) for model (iii).Conclusion:In this exploratory study no benefit in TNFi retention was observed for csDMARD combination therapy in crude analyses, while in adjusted analyses an 11% lower risk of TNFi discontinuation was found. These preliminary results offer limited support for use of combination therapy in PsA. Further analyses will explore to what extent the results are affected by inter-country heterogeneity and differences between TNFi.Acknowledgments:UL and DDG contributed equally.Novartis Pharma AG and IQVIA support the EuroSpA collaboration.Disclosure of Interests:Ulf Lindström: None declared, Daniela Di Giuseppe: None declared, Bénédicte Delcoigne: None declared, Bente Glintborg Grant/research support from: Grants from Pfizer, Biogen and Abbvie, Burkhard Moeller: None declared, Manuel Pombo-Suarez Consultant of: Janssen, Lilly, MSD and Sanofi., Speakers bureau: Janssen, Lilly, MSD and Sanofi., Carlos Sánchez-Piedra: None declared, Kari Eklund Consultant of: Celgene, Lilly, Speakers bureau: Pfizer, Roche, Heikki Relas Grant/research support from: Abbvie., Consultant of: Abbvie, Celgene, and Pfizer., Speakers bureau: Abbvie, Celgene, and Pfizer., Björn Gudbjornsson Speakers bureau: Novartis and Amgen, Thorvardur Love: None declared, Gareth T. Jones Grant/research support from: Pfizer, AbbVie, UCB, Celgene and GSK., Adrian Ciurea Consultant of: Consulting and/or speaking fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Merck Sharp & Dohme, Novartis and Pfizer., 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, Ruxandra Ionescu Consultant of: Consulting fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Speakers bureau: Consulting and speaker fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Lucie Nekvindova: None declared, Jakub Zavada Speakers bureau: Abbvie, UCB, Sanofi, Elli-Lilly, Novartis, Zentiva, Accord, Nuh Atas: None declared, Servet Yolbaş: None declared, Karen Fagerli: None declared, Brigitte Michelsen Grant/research support from: Research support from Novartis, Consultant of: Consulting fees Novartis, 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., Matija Tomsic: None declared, 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, Maria Jose Santos Speakers bureau: Novartis and Pfizer, Pedro Ávila-Ribeiro Grant/research support from: Novartis, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Mikkel Ǿstergaard Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Merck, and Novartis, Consultant of: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Lennart T.H. Jacobsson Consultant of: AbbVie, Eli Lilly, Janssen, Novartis and Pfizer, Johan Askling Grant/research support from: JA acts or has acted as PI for agreements between Karolinska Institutet and the following entities, mainly in the context of the ARTIS national safety monitoring programme of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB Pharma, Michael Nissen Grant/research support from: Abbvie, Consultant of: Novartis, Lilly, Abbvie, Celgene and Pfizer, Speakers bureau: Novartis, Lilly, Abbvie, Celgene and Pfizer

Background:Disease activity in rheumatoid arthritis (RA) patients is measured through composite scores which are considered treatment targets and thus facilitate clinical decision making. Scores often combine a mix of objective and subjective measures, and, although the latter (e.g. pain, patient’s global, 28 tender joint count (TJC)) may be impacted by contextual and cultural factors, these clinical metrics are often assumed to be comparable across different settings and reflecting the RA disease.Objectives:To explore whether there are systematic differences in patient-reported measures of RA disease activity (i.e. TJC and a measure of pain on a Visual Analog Scale (VAS)) across countries, at similar time-points in the course of the RA disease, taking objective measures of concomitant disease activity and other factors into account.Methods:RA patients starting a first ever tumor necrosis factor inhibitor (TNFi) 2008 through 2017 were identified in rheumatologic registers in five Nordic countries. Data were pooled for analysis. Clinical metrics were retrieved at three time-points: at TNFi start, and after three and twelve months, irrespective of treatment.Baseline clinical variables distributions were compared between countries. The correlation between pain and patient’s global VAS was calculated with the Pearson correlation coefficient (r). At each time-point the subjective measures (TJC and pain) were compared between countries and analyzed with linear models: (i) crude; (ii) adjusted for age, sex, birth decade, disease duration (DD), year of TNFi treatment start (year), C-reactive protein (CRP) and 28 swollen joint count (SJC)) from the time-point in question.Results:A total of 23 796 RA patients were included (Table 1). At baseline, the significant differences between Nordic countries for TJC and pain (crude model) were slightly modified after adjustment but remained statistically significant (Table 2). Compared to baseline, the inter-countries differences were reduced at 3 and 12 months, but also were statistically significant (Figure 1).Table 1.RA patients starting a first TNFi baseline characteristics, median [Interquartile range].SwedenDenmarkFinlandNorwayIcelandN (% female)†13621 (75)6701 (75)1946 (73)1113 (71)415 (73)CRP (mg/L)‡6 [3-17]9 [3-20]8 [3-20]6 [3-14]8 [3-19]Physician’s global VAS‡30 [14-50]31 [19-47]35 [20-50]32 [23-45]60 [43-70]Patient’s global VAS#‡50 [28-70]67 [46-82]50 [28-70]48 [26-69]71 [53-86]Pain VAS‡50 [26-70]60 [37-76]52 [30-71]42 [23-65]67 [49-79]SJC‡4 [1-8]4 [1-7]4 [1-9]4 [1-7]6 [3-11]TJC‡4 [1-9]6 [3-11]4 [1-10]4 [1-9]7 [4-12]DAS28‡5 [3-5]5 [4-5]4 [3-5]4 [3-5]5 [4-6]#Patient’s global and pain correlation: r=0.85†χ2test; p-value=0.04‡One-way ANOVA; all p-values < 0.001Table 2.Mean crude and adjusted differences in baseline TJC and pain between countries, using the largest (Sweden) as reference.SEDKFINOISCrude modelTJCref1.80.80.5*3.7Painref7.21.4†-4.011.1Adjusted model#TJCref2.30.70.6**2.4Painref7.90.7NS-3.37.2**All p-values NS> 0.10;†< 0.10; * < 0.05; ** < 0.01#adjusted for age, sex, birth decade, year, DD, CRP, SJCConclusion:In this observational study of 23 796 RA patients from 5 Nordic countries starting 1stTNFi, patient-reported variables related to RA disease activity (pain VAS, TJC) varied across countries. These differences were not explained by differences in demographic (age, sex, birth decade, year) or objective RA measures (DD, CRP, SJC). This implies a limit to the direct comparability of results obtained from subjective measures from different countries.Acknowledgments:Partly funded by grants from Nordforsk and ForeumDisclosure of Interests:Bénédicte Delcoigne: None declared, Sella Aarrestad Provan: None declared, Hilde Berner Hammer Consultant of: Has received fees as consultant from Roche, AbbVie and Novartis., Speakers bureau: Has received fees for speaking from AbbVie, BMS, Pfizer, UCB, Roche, MSD and Novartis, Daniela Di Giuseppe: None declared, Thomas Frisell: None declared, Bente Glintborg Grant/research support from: Grants from Pfizer, Biogen and Abbvie, Gerdur Gröndal: None declared, Björn Gudbjornsson Speakers bureau: Novartis and Amgen, Merete L. Hetland Grant/research support from: BMS, MSD, AbbVie, Roche, Novartis, Biogen and Pfizer, Consultant of: Eli Lilly, Speakers bureau: Orion Pharma, Biogen, Pfizer, CellTrion, Merck and Samsung Bioepis, Brigitte Michelsen: None declared, Dan Nordström Consultant of: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Speakers bureau: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Heikki Relas Grant/research support from: Abbvie., Consultant of: Abbvie, Celgene, and Pfizer., Speakers bureau: Abbvie, Celgene, and Pfizer., Niels Steen Krogh: None declared, Johan Askling Grant/research support from: JA acts or has acted as PI for agreements between Karolinska Institutet and the following entities, mainly in the context of the ARTIS national safety monitoring programme of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB Pharma

Objective: The Swedish Rheumatology Quality Register has implemented an internet-based method (PER) for registering patient-recorded outcome measures. The aim of this study was to compare the agreement between visual analogue scales (VASs) reported via PER and clinic-based reporting using paper forms. Methods: In a cross-sectional study (70 patients), the results of 79 registrations of VASs for global health, pain, and fatigue from PER were compared with corresponding clinic-based paper registrations. For patients with polyarthritis, 28-joint count Disease Activity Scores (DAS28) were computed. Patients with axial disease also completed Bath Ankylosing Spondylitis Disease Activity Index and Functional Index (BASDAI and BASFI) questionnaires. Mean differences and intraclass correlation coefficients (ICCs) were calculated. Agreement was visualized using Bland–Altman plots. Results: No statistically significant differences in VASs were found comparing PER and paper forms for VAS Global, VAS Pain, and VAS Fatigue (p = 0.295, 0.463, and 0.288, respectively). ICCs for VAS Global, Pain, and Fatigue ranged from 0.889 to 0.952, indicating excellent agreement. Bland–Altman plots for VAS did not show any proportional bias. The mean difference for DAS28 calculated by VASs from paper vs PER was −0.02 (n = 65, p = 0.660), and the mean difference for BASDAI was 0.04 (n = 11, p = 0.742). ICCs for DAS28 and BASDAI were 0.962 and 0.985, respectively. Of the participating patients, 60% preferred PER. Conclusion: Internet-based reporting for patient-reported outcomes in a clinical setting resulted in similar data for VASs and corresponding disease activity scores to clinic-based reporting on paper forms.

The management of chronic hand eczema is usually difficult. The aim of this open-label study is to assess the effectiveness and ‘steroid-sparing’ activity of a barrier cream containing polyvinylpyrrolidone in patients with chronic hand eczema. Rescue treatment with topical corticosteroids (TCs) was permitted in the event of eczema worsening, whereas preventive measures were maintained unchanged with respect to those adopted by patients in the past. Among the 207 participants, the main diagnosis was irritant contact dermatitis, followed by allergic contact dermatitis and atopic dermatitis. Nearly half of the patients (49%) applied the barrier cream once or twice a day, while the remaining patients used it three or more times per day. Regardless of rescue therapy with TCs, regular use of the barrier cream caused a progressive significant improvement of eczema severity, as indicated by dermatologists' and patients' assessments. A significant reduction in the amount of the TC applied in the last 3 months and in the number of TC treatment days during the previous 4 weeks was found at the end of 12-week treatment with the barrier cream as compared with baseline. The product was also well-tolerated and accepted by the majority of patients. The results of this study suggest that a barrier cream containing polyvinylpyrrolidone can represent a useful tool in the management of chronic hand eczema and may show steroid-sparing effects.

Background Dietary intake of omega-3 fatty acids (FA) may play a role in etiology of RA [1] and has also been shown to be anti-inflammatory in RA [2]. Increased intake of omega-6 FA as well as omega-6:3 FA ratio are associated with inflammation in RA [3]. However, little is known about how omega-3 FA may affect pain in RA. Objectives To study the association between omega-3, omega-6, omega-6:3 FA ratio and pain, despite inflammatory control, after three months of MTX treatment in early RA patients. Methods We included newly diagnosed RA patients with MTX monotherapy from Epidemiological Investigation of Rheumatoid Arthritis (EIRA) study linked to clinical data from Swedish Rheumatology Quality register (SRQ). Data on omega-3, omega-6, and omega-6:3 FA ratio (dietary questionnaires) were linked with data on self-assessed pain after three months of MTX treatment. Pain despite inflammatory control (Remaining Pain) was defined based on the Patient Acceptance Symptom Scale (PASS)[4] together with low systemic inflammation (VAS pain >40mm and CRP Results We included 591 patients (median age: 55 years; females: 70.6%; ACPA+: 67.9%). Mean values for clinical measures at baseline were: DAS28 5.2±1.3, VAS pain 53.9±24.7 and HAQ 1.1±0.6. Mean BMI was 25.8±4.7 kg/m2. Omega-3 FA supplements were used by 19.5% of the patients. After three months, 92 patients (15.6%) had Remaining Pain. These patients had lower intake of omega-3 FA compared to those without Remaining Pain (0.6±0.4 vs. 0.7±0.3 g/day, p=0.004). Omega-3 FA intake was inversely associated with Remaining Pain (OR=0.5 [95% CI 0.3–0.9]), after adjustment. Omega-6:3 FA ratio but not omega-6 FA alone was directly associated with remaining pain (OR=2.3 [95% CI 1.3–4.2]). Similar ORs were found after adjustment for ACPA and physical activity. Omega-3 FA was not associated with CRP or EULAR response at the follow-up. Conclusions Omega-3 FA was inversely associated with Remaining Pain and omega-6:3 FA ratio was directly associated with Remaining Pain. These associations were independent of inflammation. Our data suggest that dietary omega-3 FA may dampen the development of chronic pain in early RA. References Di Giuseppe, D., et al., Long-term intake of dietary long-chain n-3 polyunsaturated fatty acids and risk of rheumatoid arthritis: a prospective cohort study of women. Ann Rheum Dis, 2014. 73(11): p. 1949–53. Ariza-Ariza, R., M. Mestanza-Peralta, and M.H. Cardiel, Omega-3 fatty acids in rheumatoid arthritis: an overview. Semin Arthritis Rheum, 1998. 27(6): p. 366–70. Sundrarjun, T., et al., Effects of n-3 fatty acids on serum interleukin-6, tumour necrosis factor-alpha and soluble tumour necrosis factor receptor p55 in active rheumatoid arthritis. Journal of International Medical Research, 2004. 32(5): p. 443–454. Pham, T. and F. Tubach, Patient acceptable symptomatic state (PASS). Joint Bone Spine, 2009. 76(4): p. 321–3. Disclosure of Interest None declared

Background The Swedish Rheumatology Quality register (SRQ) started in 1995 and is one of the largest register collecting data on rheumatoid arthritis and other rheumatic diseases in the world. The aim of the register has always been to support health care along with collect data for research. The national coverage is 82.7% in rheumatoid arthritis. However, the extraction of useful real-time data in every day practice have been so far only limited. Objectives To design and implement a tool connected to the SRQ that allows users to monitoring their local data and results of care in comparison to national data. Methods We designed a Visualization and Analysis Platform (VAP) based on R language, using the web framework of Shiny (© RStudio, Inc.). The platform is based on predefined types of analyses such as flexible tabular presentations, cross-sectional and longitudinal comparisons. A user interface with reactive programming was implemented to control the appearance of interactive graphs and tables, and to explore the changes in outcome measures. Results A web-based platform for live visualization of data was developed and linked to the SRQ, a register containing ca. 75,000 patients and 500,000 registered visits, as long as 60,000 prescriptions of biological treatments. The users is able to control the specifics of the data analysis using a flexible interface, and it can visualize the results in a graph as long as in a table, that can easily be download. An explanation of the graph is included, to support the user in the understanding of what is represented. The VAP tool has been used to visualize data on the so called Open Comparison diagrams, 5 quality indicators that have been discussed at national level and that have been used to evaluate performances of care across counties in Sweden. We also applied this tool to the analysis of use of biological treatments in Stockholm (Fig.1). The user is therefore able to visualize how many times a specific biological treatment has been prescribed in his unit and compare it to the national value, as long as select different periods of time of interest and different diagnosis. Conclusions The VAP offers a flexible tool for visualization and analysis of real-time SRQ9s data and it is aimed to satisfy the growing request of data by clinicians, patients, researchers, care providers and pharma companies. Moreover, the VAP tool by its nature allows the possibility of fast changes in this structure, following the changes in everyday rheumatology care in real-time. Disclosure of Interest None declared

Background The past decade has seen the introduction of many biological DMARDs (bDMARDs) for treating RA, but there is only limited evidence from comparative studies to guide the choice of therapy for specific patients. Whilst a TNF inhibitor (TNFi) is typically used as the first bDMARD, many patients will switch from this initial therapy. The choice of the next bDMARD is, however, largely a matter of patient and physician preference. Perceived or established differences between available bDMARDs may lead to non-random allocation of treatment, a quantification of which is essential for a correct assessment of comparative effectiveness and safety in observational studies. Objectives To describe baseline patient characteristics at initiation of different bDMARDs after a switch from a TNFi as first bDMARD Methods Patients with RA who initiated a second bDMARD in 2010–2012 within one year of discontinuing initial TNFi treatment were identified using the Swedish Rheumatology register (SRQ). Data on disease history, defined as ever diagnosed with relevant co-morbidities, were retrieved by linking to the nationwide and virtually complete Swedish Patient Register. Results The most common bDMARDs after initial TNFi therapy were rituximab and etancercept; the least common was infliximab. Across drugs, there were only modest differences in demographics and RA characteristics, and moderate differences in disease history. Those initiating a second TNFi were slightly younger, less often RF+, and had slightly lower DAS28 than those initiating a non-TNFi bDMARD. Initiators of rituximab had longest disease duration, highest proportion RF+ and with history of malignancy or COPD, while etanercept-initiators had the lowest proportion with history of malignancy. Those initiating a second TNFi had more often switched due to adverse events, though lack of effect was the most common reason for all drugs. Conclusions We observed some evidence for channeling regarding disease history, both by class and by drug within class. These differences were small compared to previously reported channeling to non-TNFi as first bDMARD, but should still be taken into account in observational studies of comparative effectiveness and safety of different biological therapies. Disclosure of Interest None declared

Background Only one study has evaluated the association between exercise and risk of developing RA, showing no association [1]. Objectives To examine the association between physical activity and risk of developing rheumatoid arthritis (RA) in middle age and elderly women from the Swedish Mammography Cohort, a population-based prospective study [2]. Methods Data on physical activity were collected in 1997 by self-administrated food-frequency questionnaire (FFQ). Risk of RA associated with physical activity was estimated using Cox proportional hazard regression models. Results Among 30,112 women born between 1914 and 1948 followed-up from January 1, 2003 to December 31, 2010, 201 RA cases were identified (226,477 person-years). There was a statistically significant 35% lower risk of RA (relative risk (RR), 0.65; 95% confidence interval (CI), 0.43-0.96) among women in the highest category of leisure-time activity (combining more than 20 minute per day of walking/bicycling (median 40-60 minute per day) and more than 1 hour per week of exercise (median 2-3 hours per week)) as compared to women in the lowest category (less than 20 minute per day of walking/bicycling and less than 1 hour per week of exercise). A non-statistically significant decreased risk was observed for household work (-32%) and work/occupation (-15%), while an increased risk was observed for leisure-time physical inactivity (+27%). Daily energy expenditure was not associated with risk of RA. Conclusions This prospective population-based cohort study of women supports the hypothesis that physical activity can be a protective factor in the etiology of rheumatoid arthritis. Our results add to accumulated evidence on benefits of modifiable leisure-time physical activity for prevention of many other chronic diseases. References Cerhan JR, Saag KG, Criswell LA, Merlino LA, Mikuls TR: Blood transfusion, alcohol use, and anthropometric risk factors for rheumatoid arthritis in older women. J Rheumatol 29(2), 246-254 (2002). Harris H, Hakansson N, Olofsson C, Julin B, Akesson A, Wolk A. The Swedish mammography cohort and the cohort of Swedish men: Study design and characteristics of 2 population-based longitudinal cohorts. OA Epidemiology 2013 Oct 01;1(2):16. Disclosure of Interest None declared DOI 10.1136/annrheumdis-2014-eular.1737