POS0077 SEX DIFFERENCES IN EFFECTIVENESS OF FIRST-LINE TUMOR NECROSIS FACTOR INHIBITORS IN PSORIATIC ARTHRITIS; RESULTS FROM THIRTEEN COUNTRIES IN THE EuroSpA RESEARCH COLLABORATION NETWORK

Background

Evidence demonstrates sex differences in disease presentation, physical function, treatment response and drug retention in patients with psoriatic arthritis (PsA). Data from observational cohort studies indicate female sex is associated with reduced effectiveness of tumor necrosis factor inhibitors (TNFis)1,2. Although, conflicting results are also reported3,4. We sought to validate prior studies using data from a large multinational cohort based on real-life clinical practice.

Objectives

To investigate sex differences in treatment response and drug retention rates in clinical practice among patients with PsA, treated with their first TNFi.

Methods

Data from biologic-naïve PsA patients initiating a TNFi in the EuroSpA registries were pooled. In the primary analysis, propensity-score weighting was applied to assess the causal effect of sex on low disease activity (LDA) according to DAS28-CRP at 6 months. A generalized linear regression model was used to estimate the causal risk difference (RD) and relative risk (RR) of sex on LDA. Possible covariates influencing the outcome were determined a priori and selected based on availability in the database (<20% missing). The final covariates included were country, age, conventional synthetic disease-modifying antirheumatic drug use at baseline and TNFi start year. In the secondary analysis, drug retention was assessed over 24 months of follow-up by Kaplan-Meier curves and log-rank test.

Results

In total, 7,679 PsA patients with available data on DAS28-CRP at 6 months were assessed for treatment response. Baseline characteristics are shown in the Table 1. In the adjusted analysis, the probability for females to have LDA was 17% (RR, 0.83; 95% confidence interval [CI], 0.81 to 0.85) lower compared to males and the difference in probability for having LDA was 13 percentage points (RD, 0.13; 95% CI, 0.11 to 0.15). The survival analysis included 18,599 PsA patients with available data on retention rates. The TNFi 6/12/24-month retention rates were significantly lower in females (81%/68%/56%) compared to males (89%/80%/69%), see Figure 1.

Table 1.

Baseline characteristics of all biologic-naïve PsA patients treated with their first TNFi and available DAS28-CRP at 6 month, data pooled across all countries

FemaleMaleMean (SD), median [IQR] or percentagesMean (SD), median [IQR] or percentagesAge (years)49.7 (12.5)47.8 (11.9)Disease duration (years)4.0 [1.0, 10.0]4.0 [1.0, 10.0]TNFi start year 1999-200929%29% 2010-201326%27% 2014-201625%24% 2017-202020%20%Concomittant csDMARD75%77%DAS28-CRP4.4 (1.2)4.2 (1.2)DAPSA2832 (16)29 (16)CRP (mg/L)7.0 [3.0, 17.0]8.0 [3.3, 19.0]SJC (0-28)3.0 [1.0, 6.0]3.0 [1.0, 6.0]TJC (0-28)6.0 [2.0, 10.0]4.0 [2.0, 9.0]VAS pain, mm61 (23)55 (23)VAS fatigue, mm62 (26)53 (27)

Data are as observed, mean (SD), median [IQR] or percentage. TNFi, tumor necrosis factor inhibitor; csDMARD, Conventional synthetic disease-modifying antirheumatic drugs; DAS28-CRP, Disease Activity Score 28-joint count C reactive protein; DAPSA28, Disease Activity in PsA 28; CRP, C-reactive protein; SJC, swollen joint count; TJC, tender joint count.

Conclusion

Treatment efficacy and retention rates are lower among female patients with PsA initiating their first TNFi. Females presented with higher 28-tender joint count and higher scores on patient reported outcomes at baseline, reflecting differences in disease expression. Recognizing these sex differences is of relevance for customized patient care and may improve patient education.

References

[1]Højgaard, et al. Rheumatology (Oxford). 2018 Sep 1;57(9):1651-1660.

[2]Vieira-Sousa, et al. J Rheumatol. 2020 May 1;47(5):690-700.

[3]Kristensen, et al. Ann Rheum. Dis. 2008 Mar;67(3):364-9.

[4]Iervolino, et al. J Rheumatol. 2012 Mar;39(3):568-73.

Acknowledgements

Novartis Pharma AG and IQVIA for supporting the EuroSpA collaboration.

Disclosure of Interests

Pasoon Hellamand Grant/research support from: Novartis, Marleen G.H. van de Sande Speakers bureau: UCB, Consultant of: Abbvie, Eli Lily, Novartis, UCB, Grant/research support from: Novartis, Janssen, UCB and Eli Lilly, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Thomas Klausch: None declared, Nina Trokovic: None declared, Tuulikki Sokka-Isler Consultant of: Abbvie, Amgen, BMS, Celgene, DiaGraphIT, Medac, MSD, Novartis, Orionpharma, Pfizer, Roche, Sandoz, and UCB, Maria Jose Santos Speakers bureau: Abbvie, AstraZeneca, Lilly, Novartis and Pfizer, Elsa Vieira-Sousa Speakers bureau: MSD, Celgene, Novartis, Janssen, Abbvie and Pfizer, Consultant of: MSD, Celgene, Novartis, Janssen, Abbvie and Pfizer, Grant/research support from: MSD, Celgene, Novartis, Janssen, Abbvie and Pfizer, Anne Gitte Loft Speakers bureau: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Consultant of: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Grant/research support from: Novartis, Bente Glintborg Grant/research support from: Pfizer, Abbvie, BMS, Mikkel Østergaard Speakers bureau: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi and UCB, Consultant of: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi and UCB, Grant/research support from: Abbvie, BMS, Merck, Celgene, Novartis, Ulf Lindström: None declared, Johan K Wallman Consultant of: AbbVie, Amgen, Celgene, Eli Lilly and Novartis, Brigitte Michelsen Grant/research support from: Novartis, Burkhard Moeller Speakers bureau: MSD, Synergy, Eli Lilly, Bristol-Myers-Squibb, Janssen-Cilag, AbbVie and Pfizer, Raphael Micheroli: None declared, Catalin Codreanu Speakers bureau: AbbVie, Amgen, Boehringer Ingelheim, Ewopharma, Lilly, Novartis and Pfizer, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Ewopharma, Lilly, Novartis and Pfizer, Corina Mogosan Speakers bureau: AbbVie, Ewopharma, Lilly, Novartis and Pfizer, Consultant of: AbbVie, Ewopharma, Lilly, Novartis and Pfizer, Karin Laas Speakers bureau: Amgen, Janssen, Novartis and Abbvie, Ziga Rotar Speakers bureau: Abbvie, Novartis, MSD, Medis, Biogen, Eli Lilly, Pfizer, Sanofi, Lek and Janssen, Consultant of: Abbvie, Novartis, MSD, Medis, Biogen, Eli Lilly, Pfizer, Sanofi, Lek and Janssen, Karen Minde Fagerli: None declared, 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, Isabel Castrejon Speakers bureau: Lilly, BMS, Janssen, MSD and Abbvie, Consultant of: Lilly, BMS, Janssen, MSD and Abbvie, Manuel Pombo-Suarez Consultant of: Abbvie, MSD and Roche, Björn Gudbjornsson Speakers bureau: Amgen and Novartis, Consultant of: Amgen and Novartis, Thorvardur Love: None declared, Karel Pavelka Speakers bureau: Pfizer, MSD, BMS, UCB, Amgen, Egis, Roche and AbbVie, Consultant of: Pfizer, MSD, BMS, UCB, Amgen, Egis, Roche and AbbVie, Jakub Zavada Speakers bureau: Abbvie, Elli-Lilly, Sandoz, Novartis, Egis and UCB, Consultant of: Abbvie, Elli-Lilly, Sandoz, Novartis, Egis and UCB, Gökçe Kenar: None declared, Handan Yarkan-Tuğsal: None declared, 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 and Novartis, Irene van der Horst-Bruinsma Speakers bureau: BMS, AbbVie, Pfizer and MSD, Consultant of: Abbvie, UCB, MSD, Novartis and Lilly, Grant/research support from: MSD, Pfizer, AbbVie and UCB

POS0001 CAN SINGLE IMPUTATION TECHNIQUES FOR BASDAI COMPONENTS RELIABLY CALCULATE THE COMPOSITE SCORE IN AXIAL SPONDYLOARTHRITIS PATIENTS?

Background

In 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.

Objectives

To 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.

Methods

Real-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 BASDAI<40 mm was additionally evaluated. For the setting with one missing component, differences arising between missing one of components 1-4 versus 5-6 were explored. Finally, the performance of imputations in relation to the values of the original score was investigated.

Results

A 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 BASDAI<40 (Table 1). However, separate analyses of components 1-4 and 5-6 as a function of the BASDAI score suggested that imputing any one of the first four BASDAI components resulted in a level of agreement <90% for specific BASDAI values while imputing one of the stiffness components 5-6 always reached a level of agreement >90% (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 BASDAI<40 was less than 95% for values around the cutoff (Figure 1, lower panels).

Table 1.

Level of agreement between the original and calculated BASDAI and correct classification for BASDAI<40 mm

Level of agreement with Dif≤6.9 mm* (%)Correct classification for BASDAI<40 mm** (%)1 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 BASDAI<40 mm as a function of the original score

Conclusion

BASDAI 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.

Acknowledgements

Novartis Pharma AG and IQVIA for supporting the EuroSpA collaboration.

Disclosure of Interests

Stylianos 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

POS0567 SELF-PERCEIVED GENERAL HEALTH AT START OF ANTI-TNF THERAPY PREDICTS THERAPEUTIC RESPONSE IN PATIENTS WITH RHEUMATOID ARTHRITIS: ANALYSIS FROM THE CZECH BIOLOGICS REGISTRY ATTRA

Background

SF-36 and its components, as well as other PROs have been shown to predict various disease outcomes. We hypothesized that positive responses to questions (Q) 11A “I seem to get sick a little easier than other people“, and 11C “I expect my health to get worse“ from the general health (GH) domain of the SF-36 v1 questionnaire may correspond to a more fragile self-perceived GH status, and thus serve as possible predictors of future disease outcomes in patients with rheumatoid arthritis (RA).

Objectives

We aimed to investigate whether these 2 questions could predict therapeutic response in patients with RA starting their first anti-TNF therapy.

Methods

We have used two separate datasets from the Czech biologics registry ATTRA to validate our hypothesis. Dataset D1 included RA patients with at least 1 year follow-up and all relevant data available starting their first-line anti-TNF treatment within period 01/01/2012-31/12/2017 (N=1808), and dataset D2 pts starting in in 01/01/2018–01/01/2020 (N=734). Our primary outcome was DAS28-ESR remission (REM) at 12 months. REM was defined as DAS28<2.6. Patients were grouped according their response (definitely/mostly yes vs. definitely/mostly no) to Q11A and Q11C at baseline. REM rates after 12 months of 1st-line anti-TNF treatment were compared across patients‘ groups with Pearson chi-squared test. Firstly, odds ratios (ORs) using logistic regression (univariate, and then adjusted to baseline DAS28 and HAQ) were calculated to predict REM at 12M. Secondly, ORs were calculated after matching pts with positive or negative responses by a propensity score (PS) using sex, age, disease duration, baseline DAS28, calendar year and co-medication to balance baseline differences.

Results

At baseline, 79% and 80% pts were female, mean (SD) age was 52(12) and 54(13) years, DAS28 6.3 (0.9) and 6.2 (1.1), HAQ 1.5(0.6) and 1.5(0.6), 74% and 68% were RF+, 70% and 69% ACPA+ in D1 and D2 resp. In D1 34% and 31% pts, and in D2 32% and 30% responded positively to Q11A and 11C resp. Patients with positive responses to Q11A and 11C tended to have slightly (but statistically significantly) higher DAS28, HAQ, CRP or ESR, and patient- and physician global activity assessment at baseline. At 12 months, 40% (49%), 31% (37%), and 30% (40%) patients with positive, negative and neutral response to Q 11A reached REM; p<0.001 (p=0.018) in D1 (D2) resp. At 12 months, 42% (51%), 31% (37%), and 30% (40%) patients with positive, negative and neutral response to Q 11C reached REM; p<0.001 (p=0.04) in D1 (D2) resp. Crude and adjusted ORs for reaching REM according to responses to Q11A and Q11C are shown in the Table 1.

Conclusion

We provide a robust evidence that self-perceived general health at start of anti-TNF therapy predicts reaching remission at 12 months in pts with RA.

DatasetD1 (N=1808)D2 (N=734)Baseline parameterOR (95% CI)pOR (95% CI)pAnalysis 1: Patients‘ responses and occurrence of DAS28 remission after 12 months - Univariate logistic regression models (Remission (DAS28-ESR < 2.6) after 12 months (1 – yes vs. 0 – no)Q11A: yes vs. no1.62 (1.27; 2.05)< 0.0011.74 (1.20; 2.52)0.004Q11C: yes vs. no1.48 (1.15; 1.91)0.0031.66 (1.13; 2.45)0.010Analysis 2: Patients‘ responses and occurrence of remission after 12 months - Adjusted ORs using logistic regressionQ11A: yes vs. no1.86 (1.24; 2.79)0.0032.04 (1.37; 3.03)< 0.001HAQ0.48 (0.35; 0.64)< 0.0010.45 (0.33; 0.62)< 0.001DAS28-ESR0.74 (0.61; 0.88)< 0.0010.89 (0.76; 1.05)0.165Q11C: yes vs. no1.65 (1.28; 2.13)< 0.0011.91 (1.26; 2.88)0.002HAQ0.59 (0.49; 0.71)< 0.0010.46 (0.34; 0.62)< 0.001DAS28-ESR0.73 (0.64; 0.83)< 0.0010.91 (0.77; 1.06)0.232Analysis 3: Patients‘ responses and occurrence of remission after 12 months - Univariate logistic regression models after PS matchingQ11A: yes vs. no1.45 (1.12; 1.87)0.0041.70 (1.12; 2.59)0.013Q11C: yes vs. no1.33 (1.00; 1.77)0.0501.51 (0.97; 2.34)0.066

yes vs. no = definitely yes / mostly yes vs. definitely no / mostly no

Acknowledgements

This work was supported by the project (Ministry of Health, Czech Republic) for consensual development of research organization 023728

Disclosure of Interests

Jakub Zavada Speakers bureau: Abbvie, Elli-Lilly, Sandoz, Novartis, Egis, UCB, Lucie Nekvindova: None declared.

POS1142 INTERLEUKIN-37: ASSOCIATIONS OF PLASMA LEVELS AND GENETIC VARIANTS IN GOUT

Background:

IL-37, recently characterized IL-1 family member, has anti-inflammatory effects by suppression of IL-1ß and other proinflammatory cytokines. In this study we investigated the effects of genetics variants in IL-37 link with IL-37 plasma levels in a cohorts of patients with hyperuricemia/gout.

Objectives:

The aim of this study was to determine the association of IL-37 gene polymorphism and plasma IL-37 levels in patients with hyperuricemia and gout.

Methods:

The cohorts consisted of 50 control subjects, 50 subjects of primary hyperuricemia, 50 subjects of primary gout, 28 subjects of tophaceous gout and 19 subjects of acute gout flare. The analyzed cohorts were selected from a previously reported set of 250 hyperuricemia/gout patients and 132 normouricemic subjects (1) according to the descending level of serum urate. All coding regions and intron-exon boundaries of IL-37, exon 1-5, were amplified and sequenced directly. Comparisons of presence/absence of identified variants was performed using P-values binomial test. Levels of plasma IL-37 were measured using Enzyme-Linked ImmunoSorbent Assay. All tests were performed in accordance with standards set by the institutional ethics committees, which approved the project in Prague (no.6181/2015).

Results:

We identified 12 IL-37 genetic variants: five intron (rs28947188, rs2466448, rs3811045, rs3811048, rs2708944), and seven non-synonymous allelic variants (rs3811046, rs3811047, rs2708943, rs2723183, rs2723187, rs2708947, rs27231927). Minor allele frequency (MAF) of those variants in European population from ExAC databases were used for comparison. Our data showed that the rs28947188, rs3811045, rs3811046, rs3811047, rs2723187, rs2708947, and rs27231927 variants were under-represented in the Czech hyperuricemia, gout, and tophaceous gout cohort compared with the control cohort and general European population (P = 0.0082 – 0.0395).

The levels of plasma IL-37 were significantly higher in patients with tophaceous gout compared to control subjects (P 0.0329) whereas no changes were observed in subjects with primary hyperuricemia, primary gout or acute gout flare compared to control subjects. However, IL-37 was elevated in cohorts of patients with gout, tophaceous gout and acute gout flare compared to primary hyperuricemia subjects (P 0.0198, 0.0005, 0.0099; respectively).

Conclusion:

Although further analyzes are needed to elucidate the role of IL-37 in the gout, our results show that genetic variants in anti-inflammatory cytokine IL-37 are probably implicated in the pathogenesis of gout.

References:

[1]Toyoda Y, et al. Functional characterization of clinically-relevant rare variants in ABCG2 identified in a gout and hyperuricemia cohort. Cells. 2019 Apr 18;8(4).

Acknowledgements:

This study was supported by the grant from the Czech Republic Ministry of Health RVO 00023728.

Disclosure of Interests:

None declared.

OP0220 SECULAR TRENDS IN BASELINE CHARACTERISTICS, TREATMENT RETENTION AND RESPONSE RATES IN 17453 BIONAÏVE PSORIATIC ARTHRITIS PATIENTS INITIATING TNFI – RESULTS FROM THE EUROSPA COLLABORATION

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) <2.6, 28-joint Disease Activity index for PsA (DAPSA28) ≤4, Clinical Disease Activity Index (CDAI) ≤2.8) and ACR50 response rates were assessed at 6, 12 and 24 months. No statistical comparisons were made.

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 TNFi

Baseline 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 / 8

Gr, 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

POS0596 THE THERAPEUTIC TARGET IS REACHED MORE OFTEN IN RA PATIENTS STARTING TNF INHIBITORS WITH MODERATE ACTIVITY THAN WITH HIGH DISEASE ACTIVITY – AN ANALYSIS FROM THE ATTRA REGISTRY

Background:

Treat to target guidelines recommend achieving remission or low disease activity in rheumatoid arthritis (RA). In the Czech Republic, anti-TNF therapy has been reimbursed only for patients with highly active RA until 2019, when pts with LDA have been also included in the reimbursement policy.

Objectives:

The aim of the study was to compare the results of treatment in patients with rheumatoid arthritis and moderate disease activity (MDA) or high disease activity (HDA) starting the therapy with the first anti-TNF drug in routine clinical practice.

Methods:

This was a retrospective cohort study of patients treated with the first anti-TNF drug in the Czech Republic. Propensity score was used to match pts starting anti-TNF in MDA or HDA for other important predictive factors. The propensity score was obtained by logistic regression with 10 covariates (gender, age, disease duration, seropositivity, comedication with MTX, comedication with other csDMARDs, number of previosu csDMARDs, anti-TNF drug),.Within the paired groups, one-dimensional logistic models were then calculated to estimate the odds of remission / low activity after 6 and 12 months of treatment.

Results:

A total of 2416 patients were analyzed in the study. 2231 patients had high activity (DAS 28> 5.1) and 185 patients had moderate activity (3.2 <DAS28 ≤ 5.1) at baseline. After 12 months, the low activity state (DAS28 < 3.2) was achieved by patients with MDA in 74.0% and patients with HDA in 52.2%, (p <0.001) (FIG 1). The differences btw groups were significant in all evaluated intervals of 0, 3, 6, 12 months. Furthermore, a comparison of patients with MDA and HAD by propensity score matching, who no longer differ in the baseline characteristics (except for disease activity and quality of life) was performed. Patients with MDA were 2.4x more likely to achieve remission or low activity according to DAS28-ESR after 6 months and 1.7x more likely to achieve remission or low activity after 12 months of treatment compared to patients with HDA at the beginning of treatment.

Conclusion:

This analysis of the results of treatment with anti-TNF drugs in the ATTRA Registry has shown that starting anti-TNF therapy in patients with RA and MDA leads more often to the target of remission or low activity, than in pts with HDA.

Acknowledgement:

Supported by the project of the Ministry of Health Care of the Czech Republic of the conceptual development of the research organization 00023728 Institute of Rheumatology

Disclosure of Interests:

Karel Pavelka Speakers bureau: Abbvie, Pfizer, Elli-Lilly, BMS, UCB, Sanofi, Novartis, Gilead, Paid instructor for: Abbvie, Consultant of: Abbvie, Pfizer, Elli-Lilly, BMS, UCB, Sanofi, Novartis, Gilead, Lucie Nekvindova: None declared, Jakub Zavada Speakers bureau: Abbvie, Elli-Lilly, UCB, Sanofi, Consultant of: Abbvie, UCB, Sanofi, Gilead

OP0105 FEASIBILITY AND USEFULNESS OF MAPPING BIOLOGIC REGISTRIES TO A COMMON DATA MODEL: ILLUSTRATION USING COMORBIDITIES

Background:

The Observational and Medical Outcomes Partnerships (OMOP) common data model (CDM) provides a framework for standardising health data with a view towards federated analyses, thus maximising the use and power of combining disparate datasets.

Objectives:

To assess feasibility and usefulness of mapping biologic registry data from different European countries to the OMOP CDM and present initial descriptive data regarding comorbidities.

Methods:

Five biologic registries, as part of a funded FOREUM project, have been mapped to the OMOP CDM: 1) the Czech biologics register (ATTRA), 2) Registro Español de Acontecimientos Adversos de Terapias Biológicas en Enfermedades Reumáticas (BIOBADASER), 3) British Society for Rheumatology Biologics Register for Rheumatoid Arthritis (BSRBR-RA), 4) German biologics register ‘Rheumatoid arthritis observation of biologic therapy’ (RABBIT), and 5) Swiss register ‘Swiss Clinical Quality Management in Rheumatic Diseases’ (SCQM). The mapping includes socio-demographic, observation period within the studies, baseline comorbidities, and baseline medications. Only patients with RA were included. Using R, registers received identical scripts to run on their mapped databases to produce an initial description of patient characteristics without the need to share patient-level data.

Results:

A total of 54,458 individuals are included the five registries being mapped to the OMOP CDM, see table. Age and gender distribution was similar across registries. All registers reported on cardiovascular system comorbidities, diabetes mellitus, mental disorders, and respiratory system comorbidities. However, it was noted that results of comorbidity mapping relies on what each register collect on each patient at the point of registration.

Whilst the Charlson comorbidity index could be calculated within each registry, due to lack of the specific coding needed, such as “uncomplicated diabetes mellitus” / “end-organ damage diabetes mellitus”, it was felt to be an inaccurate measure. The granularity of the comorbidities was insufficient, as many registers coded, for example, diabetes mellitus without any extra information.

Table 1.

OARSI scores

RegistryATTRABIOBADASERBSRBR-RARABBITSCQMCountryCzechiaSpainUnited KingdomGermanySwitzerlandNumber of Participants23343012251791365210281Gender FemaleMale1808 (77%)526 (23%)2372 (79%)640 (21%)18995 (75%)6184 (25%)10191 (75%)3461 (25%)7584 (74%)2697 (26%)Age at observation start date59 (52, 66)56 (47, 63)58 (49, 66)58 (50, 67)57 (47, 66)First observation start dateFeb-2002Oct-1999Oct-2001Aug-2006March-1995Number of comorbidities1 (1, 2)1 (0, 2)1 (0, 2)2 (1, 3)2 (1, 4)Disorder of cardiovascular system1609 (69%)208 (7%)2239 (9%)6330 (46%)3969 (39%)Diabetes mellitus331 (14%)273 (9%)1770 (7%)1591 (12%)792 (8%)Depressive Disorder165 (7%)04971 (20%)1023 (7%)1337 (13%)Disorder of respiratory system215 (9%)209 (7%)4125 (16%)1282 (9%)1630 (16%)

Conclusion:

This is the first analysis of data from the newly mapped OMOP CDM across five European registers. Through mapping the registers into a CDM, and using the same script, the ability to undertake collaborative analysis without sharing patient level data outside of the country can be realised. Due to differences in study design and data capture, there needs to be a focus on harmonising the coding and analysing of the comorbidities and drugs across registries.

Disclosure of Interests:

Lianne Kearsley-Fleet: None declared, Kimme Hyrich: None declared, Martin Schaefer: None declared, Doreen Huschek: None declared, Anja Strangfeld: None declared, Jakub Zavada Speakers bureau: Abbvie, Eli-Lilly, UCB, Sanofi., Consultant of: Abbvie, UCB, Sanofi, Gilead., Markéta Lagová: None declared, Delphine Courvoisier Speakers bureau: Medtalks Switzerland, Christoph Tellenbach: None declared, Kim Lauper Speakers bureau: Medtalks Switzerland, Carlos Sánchez-Piedra: None declared, Nuria Montero: None declared, Jesús-Tomás Sánchez-Costa: None declared, Daniel Prieto-Alhambra Consultant of: Amgen (speaker fees and advisory board membership fees paid to DPA’s department) and UCB (consultancy fees paid to DPA’s department), Grant/research support from: grants and other from AMGEN, grants, non-financial support and other from UCB Biopharma, grants from Les Laboratoires Servier, outside the submitted work., Edward Burn: None declared

POS0027 SECULAR TRENDS IN BASELINE CHARACTERISTICS, TREATMENT RETENTION AND RESPONSE RATES IN 27189 BIO-NAÏVE AXIAL SPONDYLOARTHRITIS PATIENTS INITIATING TNFI – RESULTS FROM THE EUROSPA COLLABORATION

Background:

Knowledge of changes over time in baseline characteristics and tumor necrosis factor inhibitor (TNFi) response in bio-naïve axial spondyloarthritis (axSpA) patients treated in routine care is limited.

Objectives:

To investigate secular trends in baseline characteristics and retention, remission and response rates in axSpA patients initiating a first TNFi.

Methods:

Prospectively collected data on bio-naïve axSpA 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 (Ankylosing Spondylitis Disease Activity Score (ASDAS) <1.3, Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) <20) and response (ASDAS Major and Clinically Important Improvement (MI/CII), BASDAI 50) rates were assessed at 6, 12 and 24 months. No statistical comparisons were made.

Results:

In total, 27189 axSpA patients were included (5945, 11255 and 9989 in groups A, B and C).

At baseline, patients in group A were older, had longer disease duration and a larger proportion of male and HLA-B27 positive patients compared to B and C, whereas disease activity was similar across groups.

Retention rates at 6, 12 and 24 months were highest in group A (88%/81%/71%) but differed little between B (84%/74%/64%) and C (85%/76%/67%).

In all groups, median ASDAS and BASDAI had decreased markedly at 6 months (Table 1). The ASDAS values at 12 and 24 months and BASDAI at 24 months were higher in group A compared with groups B and C. Similarly, crude remission and response rates were lowest in group A. After adjustments for drug retention (LUNDEX), remission and response rates showed less pronounced between-group differences regarding ASDAS measures and no relevant differences regarding BASDAI measures.

Conclusion:

Nowadays, axSpA patients initiating TNFi are younger with shorter disease duration and more frequently female and HLA-B27 negative than previously, while baseline disease activity is unchanged. Drug retention rates have decreased, whereas crude remission and response rates have increased. This may indicate expanded indication but also a stable disease activity threshold for TNFi initiation over time, an increased focus on targeting disease remission and more available treatment options.

References:

[1]Arthritis Rheum 2006; 54: 600-6.

Table 1.

Secular trends in baseline characteristics, treatment retention, remission and response rates in European axSpA patients initiating a 1st TNFi

Baseline characteristicsGroup A(1999–2008)Group B(2009–2014)Group C(2015–2018)Age, years, median (IQR)57 (49–66)51 (42–60)46 (37–56)Male, %666057HLA-B27, %877772Years since diagnosis, median (IQR)5 (1–12)2 (0–8)2 (0–7)Smokers, %232425ASDAS, median (IQR)3.5 (2.8–4.1)3.4 (2.8–4.1)3.5 (2.8–4.1)BASDAI, median, (IQR)57 (42–71)59 (43–72)57 (41–71)TNFi drug, % (Adalimumab /Etanercept / Infliximab /Certolizumab / Golimumab)22 / 35 / 43 / 0 / 037 / 21 / 20 / 4 / 1827 / 28 / 24 / 8 / 13Follow up6 months12 months24 monthsGr AGr BGr CGr AGr BGr CGr AGr BGr CRetention rates, %, (95% CI)88 (88–89)84 (83–85)85 (84–86)81 (80–82)74 (74–75)76 (75–76)71 (70–72)64 (63–65)67 (66–68)ASDAS, median, (IQR)1.8 (1.2–2.8)1.9 (1.2–2.8)1.8 (1.2–2.6)1.9 (1.3–2.6)1.7 (1.2–2.5)1.6 (1.1–2.4)1.9 (1.4–2.6)1.7 (1.1–2.4)1.5 (1.1–2.2)ASDAS inactive disease, %, c/L28 / 2528 / 2430 / 2624 / 1932 / 2434 / 2623 / 1634 / 2039 / 23ASDAS CII, %, c/L57 / 5159 / 5063 / 5461 / 5063 / 4767 / 5159 / 4168 / 4074 / 45ASDAS MI, %, c/L31 / 2732 / 2737 / 3232 / 2637 / 2741 / 3130 / 2042 / 2546 / 28BASDAI, median, (IQR)23 (10–40)26 (11–48)24 (10–44)21 (10–38)23 (10–42)20 (8–39)22 (9–40)20 (8–39)16 (6–35)BASDAI remission, %, c/L44 / 4040 / 3443 / 3645 / 3645 / 3450 / 3844 / 3048 / 2956 / 34BASDAI 50 response, %, c/L53 / 4750 / 4253 / 4557 / 4656 / 4258 / 4457 / 3960 / 3563 / 38

Gr, Group; c/L, crude/LUNDEX adjusted.

Acknowledgements:

Novartis Pharma AG and IQVIA for supporting the EuroSpA Research Collaboration Network.

Disclosure of Interests:

Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Sara Nysom Christiansen Speakers bureau: BMS and GE, 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, Ulf Lindström: None declared, Jakub Zavada: None declared, Florenzo Iannone: None declared, Fatos Onen: None declared, Michael J. Nissen Speakers bureau: Novartis, Eli Lilly, Celgene, and Pfizer, Consultant of: Novartis, Eli Lilly, Celgene, and Pfizer, Brigitte Michelsen Consultant of: Novartis, Grant/research support from: Novartis, Maria Jose Santos Speakers bureau: AbbVie, Novartis, Pfizer, Gary Macfarlane Grant/research support from: GlaxoSmithKline, Dan Nordström Consultant of: Abbvie, BMS, MSD, Novartis, Pfizer, Roche, UCB, Manuel Pombo-Suarez: None declared, Catalin Codreanu Speakers bureau: AbbVie, Amgen, Egis, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Amgen, Egis, Novartis, Pfizer, UCB, Matija Tomsic Speakers bureau: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Consultant of: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Irene van der Horst-Bruinsma Speakers bureau: Abbvie, BMS, MSD, Novartis, Pfizer, Lilly, UCB, Björn Gudbjornsson Speakers bureau: Amgen and Novartis, Johan Askling: None declared, Bente Glintborg Grant/research support from: Pfizer, Biogen, AbbVie, 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, Elisa Gremese: None declared, Nurullah Akkoc: None declared, Adrian Ciurea Speakers bureau: Abbvie, Eli-Lilly, MSD, Novartis, Pfizer, Eirik kristianslund: None declared, Anabela Barcelos: None declared, Gareth T. Jones Grant/research support from: Pfizer, AbbVie, UCB, Celgene, Amgen, GSK, Anna-Mari Hokkanen Grant/research support from: MSD, Carlos Sánchez-Piedra: None declared, Ruxandra Ionescu Speakers bureau: Abbvie, Amgen, Boehringer-Ingelheim Eli-Lilly,Novartis, Pfizer, Sandoz, UCB, Ziga Rotar Speakers bureau: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Consultant of: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Marleen G.H. van de Sande: None declared, Arni Jon Geirsson: None declared, 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, Merete L. Hetland Speakers bureau: Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis.

AB1233 GENDER DIFFERENCE IN DISEASE SEVERITY AND TREATMENT OUTCOMES AMONG PATIENTS WITH RHEUMATOID ARTHRITIS (RA), AXIAL SPONDYLOARTHRITIS (AXSPA) AND PSORIATIC ARTHRITIS (PSA) STARTING TREATMENT WITH TARGETED THERAPY IN THE CZECH REPUBLIC

Background:

The ATTRA registry captures more than 95% of patients with RA, AxSpA, or PSA treated with biologics in the Czech Republic (CZ). In CZ, anti-TNF therapy is reimbursed for RA if DAS28>5.1 despite therapy with csDMARDs, for PSA if disease is not “adequately controlled” with csDMARDs and for AS if BASDAI>4 and CRP/ESR elevated above normal.

Objectives:

We aimed to investigate gender-related differences in baseline characteristics and treatment effectiveness among patients with RA, AxSpa, and PsA starting first targeted therapy (TT) in CZ.

Methods:

In this observational cohort study, the ATTRA register provided prospectively collected data on RA, AxSpA and PsA patients who initiated their first TT (mostly by TNFi) in 2012–6/2018. Treatment effectiveness and adherence was assessed at 12 months by a change in patient-reported outcomes (PROs), CRP and % drug survival. Differences in categorical and continuous data btw males and females were assessed using the Pearson X2test (of Fisher exact test, as appropriate), or Mann-Whitney test resp. This study was largely descriptive, and no statistical adjustments have been made.

Results:

A total of 1602 RA, 1306 AxSpa, and 493 PsA patients were included. The difference in baseline characteristics btw women and men starting TT are shown in table 1. Their response and adherence to TT after one year is shown in table 2.

Conclusion:

When starting their first TT, males tended to have higher levels of CRP, while females were more often (ex)smokers and reported worse parameters of quality of life across the diagnostic groups. The improvement of PROs was similar in males and females, while males with axSpA and PsA showed larger improvements in CRP. Survival on drug at one year was similar, save for AxSpA, where males showed better survival.

References:

Acknowledgments:

Supported by project 00023728 of Ministry of Health, CZ

Disclosure of Interests:

Jakub Zavada Speakers bureau: Abbvie, UCB, Sanofi, Elli-Lilly, Novartis, Zentiva, Accord, Lucie Nekvindova: None declared, Karel Pavelka Consultant of: Abbvie, MSD, BMS, Egis, Roche, UCB, Medac, Pfizer, Biogen, Speakers bureau: Abbvie, MSD, BMS, Egis, Roche, UCB, Medac, Pfizer, Biogen, Pavel Horak Speakers bureau: Pfizer, Abbvie, Eli lilly. Novartis, Roche, Sanofi, Jiří Vencovský: None declared

OP0285 TOWARDS IMPLEMENTING THE OMOP CDM ACROSS FIVE EUROPEAN BIOLOGIC REGISTRIES

Background:

The Observational and Medical Outcomes Partnerships (OMOP) common data model (CDM) provides a framework for standardising health data.

Objectives:

To map national biologic registry data collected from different European countries to the OMOP CDM.

Methods:

Five biologic registries are currently being mapped to the OMOP CDM: 1) the Czech biologics register (ATTRA), 2) Registro Español de Acontecimientos Adversos de Terapias Biológicas en Enfermedades Reumáticas (BIOBADASER), 3) British Society for Rheumatology Biologics Register for Rheumatoid Arthritis (BSRBR-RA), 4) German biologics register ‘Rheumatoid arthritis observation of biologic therapy’ (RABBIT), and 5) Swiss register ’Swiss Clinical Quality Management in Rheumatic Diseases’ (SCQM).

Data collected at baseline are being mapped first. Details that uniquely identify individuals are mapped to the person table, with the observation_period table defining the time a person may have had clinical events recorded. Baseline comorbidities are mapped to the condition_occurrence CDM table, while baseline medications are mapped to the drug_exposure CDM table. This mapping is summarised in Figure 1.

Figure 1.

Overview of initial mapping

Results:

A total of 64,901 individuals are included in the 5 registries being mapped to the OMOP CDM, see table 1. The number of unique baseline conditions being mapped range from 17 in BSRBR-RA to 108 in RABBIT, while the number of baseline medications range from 26 in ATTRA to 802 in BSRBR-RA. Those registries which captured more comorbidities or medications generally allowed for these to be inputted as free text.

Table 1.

Summary of initial code mapping

RegistryNumber of individualsNumber of mapped baseline conditionsNumber of mapped baseline medicationsATTRA5,3262626BIOBADASER6,4963051BSRBR-RA21,69517802RABBIT13,06210878SCQM18,3222633

Conclusion:

Due to differences in study design and data capture, the baseline information captured on comorbidities and drugs across registries varies greatly. However, these data have been mapped and mapping biologic registry data to the OMOP CDM is feasible. The adoption of the OMOP CDM will facilitate collaboration across registries and allow for multi-database studies which include data from both biologic registries and other sources of health data which have been mapped to the CDM.

Disclosure of Interests:

Edward Burn: None declared, Lianne Kearsley-Fleet: None declared, Kimme Hyrich Grant/research support from: Pfizer, UCB, BMS, Speakers bureau: Abbvie, Martin Schaefer: None declared, Doreen Huschek: None declared, Anja Strangfeld Speakers bureau: AbbVie, BMS, Pfizer, Roche, Sanofi-Aventis, Jakub Zavada Speakers bureau: Abbvie, UCB, Sanofi, Elli-Lilly, Novartis, Zentiva, Accord, Markéta Lagová: None declared, Delphine Courvoisier: None declared, Christoph Tellenbach: None declared, Kim Lauper: None declared, Carlos Sánchez-Piedra: None declared, Nuria Montero: None declared, Jesús-Tomás Sanchez-Costa: None declared, Daniel Prieto-Alhambra Grant/research support from: Professor Prieto-Alhambra has received research Grants from AMGEN, UCB Biopharma and Les Laboratoires Servier, Consultant of: DPA’s department has received fees for consultancy services from UCB Biopharma, Speakers bureau: DPA’s department has received fees for speaker and advisory board membership services from Amgen

THU0398 DRUG RETENTION RATES AND TREATMENT OUTCOMES IN 1860 AXIAL SPONDYLOARTHRITIS PATIENTS TREATED WITH SECUKINUMAB IN ROUTINE CLINICAL PRACTICE IN 13 EUROPEAN COUNTRIES IN THE EUROSPA RESEARCH COLLABORATION NETWORK

Background:

To determine the real-life 6- and 12-month secukinumab effectiveness in Europe overall, as well as stratified by prior biologic disease-modifying anti-rheumatic drug (bDMARD)/targeted synthetic (ts)DMARD use.

Objectives:

Real-life data from axSpA patients treated with secukinumab from 13 countries in the European Spondyloarthritis (EuroSpA) Research Collaboration Network were pooled. We calculated proportions of patients achieving Bath Ankylosing Spondylitis Disease Activity Score (BASDAI) <2/<4 and Ankylosing Spondylitis Disease Activity Score (ASDAS) <1.3/<2.1 at 6 and 12 months, including with LUNDEX adjustments (crude value adjusted for drug retention). Retention rates were compared between b/tsDMARD naïve, 1 prior and ≥2 prior b/tsDMARD users with Kaplan-Meier analyses with log rank test and disease states by Chi-square test.

Methods:

A total of 1860 axSpA patients were included (Table 1). Overall 6/12-month secukinumab retention rates were 82%/72% and higher in bionaïve patients (Table 2, Figure). Significant differences in retention rates in-between the registries were found. Inactive disease/low-disease-activity (LDA) were achieved more often in bionaïve patients (Table 2).

Table 1All patients (n=1860)b/tsDMARD naïve (n=414)1 prior b/tsDMARD (n=448)≥2 prior b/tsDMARDs (n=998)Age (years), mean (SD)47 (12)45 (12)47 (12)48 (12)Men, %57%68%58%49%Years since diagnosis, mean (SD)10 (9)8 (9)10 (9)11 (9)Current smokers, %25 %27%25%23%Patient’s global (0-100), median (IQR)70 (50-81)80 (60-90)64 (50-80)70 (50-82)Physician’s global (0-100), median (IQR)45 (25-63)64 (43-78)45 (22-60)40 (20-58)C reactive protein (mg/L), median (IQR)8 (3-25)15 (5-31)7 (3-25)6 (2-22)Erythrocyte sedimentation rate (mm/h), median (IQR)22 (9-44)30 (14-44)24 (8-45)18 (8-42)Pain (0-100), median (IQR)70 (50-81)80 (65-90)65 (49-80)70 (50-80)BASDAI, median (IQR)6.2 (4.6-7.6)6.8 (5.2-8.0)5.9 (4.2-7.2)6.1 (4.4-7.6)BASFI, median (IQR)5.5 (3.2-7.3)6.1 (3.2-7.6)4.8 (2.8-6.8)5.5 (3.3-7.2)ASDAS, median (IQR)3.6 (2.9-4.3)4.2 (3.5-4.8)3.5 (2.7-4.2)3.5 (2.8-4.2)Table 2MonthsAll patients (n=1860)b/tsDMARD naïve (n=414)1 prior b/tsDMARD (n=448)≥2 prior b/tsDMARDs (n=998)p-value*Secukinumab retention rate, % (95%CI)682% (80-84%)90% (87-93%)83% (79-86%)78% (76-81%)0.0011272% (69-74%)84% (81-88%)73% (69-78%)66% (63-69%)<0.001BASDAI <2, % Crude626373518<0.001 LUNDEX adjusted21342813<0.001 Crude1225412918<0.001 LUNDEX adjusted16311811<0.001BASDAI <4, % Crude651716040<0.001 LUNDEX adjusted40654730<0.001 Crude1251765639<0.001 LUNDEX adjusted32573623<0.001ASDAS <1.3, % Crude69131360.001 LUNDEX adjusted712115<0.001 Crude1211181570.002 LUNDEX adjusted713940.002ASDAS <2.1, % Crude6243226200.002 LUNDEX adjusted19292115<0.001 Crude1227442721<0.001 LUNDEX adjusted17331712<0.001

*Comparisons between b/tsDMARD naïve, 1 prior and ≥2 prior b/tsDMARD users were performed with Kaplan-Meier with log-rank test or Chi-Square test, as appropriate

Conclusion:

In this real-life study of 1860 patients with axSpA in 13 European countries secukinumab retention was high and significantly higher for bionaïve patients. Overall, a higher proportion of bionaïve than previous b/tsDMARD users achieved inactive disease/LDA.

Figure

Acknowledgments:

Novartis and IQVIA for supporting the EuroSpA RCN

Disclosure of Interests:

Brigitte Michelsen Grant/research support from: Research support from Novartis, Consultant of: Consulting fees Novartis, Ulf Lindström: 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, Adrian Ciurea Consultant of: Consulting and/or speaking fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Merck Sharp & Dohme, Novartis and Pfizer., Jakub Zavada Speakers bureau: Abbvie, UCB, Sanofi, Elli-Lilly, Novartis, Zentiva, Accord, Anne Gitte Loft Grant/research support from: Novartis, Consultant of: AbbVie, MSD, Novartis, Pfizer and UCB, Speakers bureau: AbbVie, MSD, Novartis, Pfizer and UCB, Manuel Pombo-Suarez Consultant of: Janssen, Lilly, MSD and Sanofi., Speakers bureau: Janssen, Lilly, MSD and Sanofi., Fatos Onen: None declared, Tore K. Kvien Grant/research support from: Received grants from Abbvie, Hospira/Pfizer, MSD and Roche (not relevant for this abstract)., Consultant of: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Paid instructor for: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Speakers bureau: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Maria Jose Santos Speakers bureau: Novartis and Pfizer, 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, Anna-Mari Hokkanen: None declared, Björn Gudbjornsson Speakers bureau: Novartis and Amgen, 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, 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, Michael Nissen Grant/research support from: Abbvie, Consultant of: Novartis, Lilly, Abbvie, Celgene and Pfizer, Speakers bureau: Novartis, Lilly, Abbvie, Celgene and Pfizer, Karel Pavelka Consultant of: Abbvie, MSD, BMS, Egis, Roche, UCB, Medac, Pfizer, Biogen, Speakers bureau: Abbvie, MSD, BMS, Egis, Roche, UCB, Medac, Pfizer, Biogen, Carlos Sánchez-Piedra: None declared, Servet Akar: None declared, Joe Sexton: None declared, Matija Tomsic: None declared, Helena Santos Speakers bureau: AbbVie, Eli-Lilly, Janssen, Pfizer, Novartis, Marco Sebastiani: None declared, Jenny Osterlund: None declared, Arni Jon Geirsson: None declared, Gareth T. Jones Grant/research support from: Pfizer, AbbVie, UCB, Celgene and GSK., 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, Stylianos Georgiadis Grant/research support from: Novartis, Cecilie Heegaard Brahe Grant/research support from: Novartis, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, 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, 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

FRI0283 CO-MEDICATION WITH CSDMARD HAS LITTLE EFFECT ON THE RETENTION OF TNF INHIBITORS IN PSORIATIC ARTHRITIS, RESULTS FROM THE EUROSPA COLLABORATION

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 <33% missing data for DAS28 were included.

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 characteristics

Country 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

OP0206 ALLANTOIN - A BIOMARKER OF OXIDATIVE STRESS - IS HIGHER IN PATIENTS WITH GOUT THAN IN HEALTHY VOLUNTEERS, AND CORRESPONDS WITH SEVERITY OF DISEASE

Background:

Uric acid can be non-enzymatically oxidized into allantoin and other products by reactive oxygen species. Allantoin has emerged as a reliable biomarker for monitoring oxidative status bothin vitroandin vivo1. In gout patients, significantly increased plasma levels of allantoin have been found compared to healthy controls2.

Objectives:

The aim of this pilot study was to measure allantoin as a biomarker of oxidative stress in patients with gout using newly developed UHPLC-HILIC-MS/MS method3and to investigate whether the allantoin levels are higher in patients with more severe disease (tophaceous gout).

Methods:

We used clinical data and frozen serum (-80°C) from 10 patients with chronic tophaceous gout, 10 patients with chronic gout without tophi and 10 healthy controls. Allantoin was determined in serum with sensitive UHPLC-MS/MS method using an isotopically labeled internal standard as we described before3. In addition, the concentrations of serum CRP, creatinine and uric acid were measured. Data are summarized as medians with interquartile range [IQR]. Differences between two patient groups were evaluated using the Wilcoxon signed-rank test.

Results:

The median concentrations of allantoin in the serum from patients with tophaceous gout were significantly higher than in patients with gout without tophi (4.2 [2.6] vs. 3.2 µM [1.5], p = 0.0273). There was no significant difference in other biochemical or demographic parameters (CRP, uric acid, creatinine, BMI, weight) between these two groups. Allantoin levels in healthy controls were significantly lower (0.5 vs. 4.2 [2.6], p = 0.0020, 0.5 vs. 3.2 [1.5], p < 0.0001) (Fig. 1).

Fig. 1.

Box plots of allantoin concentration in patients with tophaceous gout with tophi, without tophi and in healthy controls.

Conclusion:

We have observed significantly higher levels of serum allantoin in the patients with more advanced gout with tophi compared with the patients with chronic gout without tophi. We have found elevated values of allantoin in both groups in comparison with healthy controls. In our small cohort the level of allantoin correspond with the severity of disease presented by tophi. However, further studies in large cohorts are needed. We can speculate, whether higher level of oxidative stress may contribute to increased cardiovascular risk and mortality in patients with gout (and more so in severe gout)4.

References:

[1]Marrocco I, Altieri F, Peluso I Measurement and Clinical Significance of Biomarkers of Oxidative Stress in Humans. Oxidative med and cell. longev. 2017:6501046.

[2]Stamp LK, Turner R, Khalilova IS, Zhang M, Drake J, Forbes LV, Kettle AJ. Myeloperoxidase and oxidation of uric acid in gout: implications for the clinical consequences of hyperuricaemia. Rheumatology (Oxford, England) 53 (11):1958-1965

[3]Kozlik P, Hasikova L, Stiburkova B, Zavada J, Kalikova K. Rapid and reliable HILIC-MS/MS method for monitoring allantoin as a biomarker of oxidative stress. Anal. Biochem. 2020 Jan 15; 589:113509

[4]Perez-Ruiz F, Martinez-Indart L, Carmona L, Herrero-Beites AM, Pijoan JI, Krishnan E. Tophaceous gout and high level of hyperuricaemia are both associated with increased risk of mortality in patients with gout. Ann Rheum Dis. 2014 Jan; 73(1):177-182.

Acknowledgments:

This work was supported by the project (Ministry of Health, Czech Republic) for consensual development of research organization 00023728 (Institute of Rheumatology).

Disclosure of Interests:

Lenka Hasikova: None declared, Petr Kozlik: None declared, Kveta Kalikova: None declared, Blanka Stiburkova: None declared, Jakub Zavada Speakers bureau: Abbvie, UCB, Sanofi, Elli-Lilly, Novartis, Zentiva, Accord

THU0404 INFLUENCE OF URATE TRANSPORTOSOME FOR HYPERURICEMIA AND GOUT

Background:

Gouty arthritis, caused by a persistent increase in serum uric acid level, can be caused by underexcretion of uric acid by uric transporters; however, the effects of allelic variants of urate transportosome are yet to be fully determined.

Objectives:

In this study we investigated the effects of 10 genes of urate transportosome in a cohort of patients with primary hyperuricemia and gout.

Methods:

The cohort consisted of 114 hyperuricemic individuals; 207 gout patients; and 274 normouricemic controls.

Results:

We identified 39 non-synonymous allelic variants in the 10 genes of urate transportosome in hyperuricemia/gout cohort. For 22 variants, a European MAF <0.0001 is documented. From the total of 39 identified variants we selected 23 variants for functional characterization based on a) finding of a newly identified variant, b) MAF variant was significantly different in the group of patients with hyperuricemia/gout, c) with high probability, in silico predictions showed devastating influence of variant on protein function.

Conclusion:

Although further analyzes are needed to elucidate the contribution of urate transportosome to urate homeostasis, our results clearly show that ABCG2 transporter analysis has significant clinical potential. Of the identified non-synonymous allelic variants of the urate transportosome, rs2231142 (p.Q141K) in the ABCG2 gene, proved to be the most clinically significant on the age onset (P < 0.0002, Kruskal-Wallis test).

References:

[1]Toyoda Y, et al. Cells. 2019 Apr 18;8(4). 2. Stiburkova B, et al. Rheumatology (Oxford). 2016 Jan;55(1):191-4. 3. Toyoda Y, et al. Arthritis Res Ther. 2019 Oct 28;21(1):219.

Acknowledgments:

This study was supported by the grant from the Czech Republic Ministry of Health AZV 15-26693A and RVO 00023728.

Disclosure of Interests: :

Blanka Stiburkova: None declared, Katerina Pavelcova: None declared, Jana Bohata: None declared, Marketa Pavlikova: None declared, Tappei Takada: None declared, Yu Toyoda: None declared, Lenka Hasikova: None declared, Jakub Zavada Speakers bureau: Abbvie, UCB, Sanofi, Elli-Lilly, Novartis, Zentiva, Accord, Karel Pavelka Consultant of: Abbvie, MSD, BMS, Egis, Roche, UCB, Medac, Pfizer, Biogen, Speakers bureau: Abbvie, MSD, BMS, Egis, Roche, UCB, Medac, Pfizer, Biogen

2016 updated EULAR evidence-based recommendations for the management of gout

Background

New drugs and new evidence concerning the use of established treatments have become available since the publication of the first European League Against Rheumatism (EULAR) recommendations for the management of gout, in 2006. This situation has prompted a systematic review and update of the 2006 recommendations.

Methods

The EULAR task force consisted of 15 rheumatologists, 1 radiologist, 2 general practitioners, 1 research fellow, 2 patients and 3 experts in epidemiology/methodology from 12 European countries. A systematic review of the literature concerning all aspects of gout treatments was performed. Subsequently, recommendations were formulated by use of a Delphi consensus approach.

Results

Three overarching principles and 11 key recommendations were generated. For the treatment of flare, colchicine, non-steroidal anti-inflammatory drugs (NSAIDs), oral or intra-articular steroids or a combination are recommended. In patients with frequent flare and contraindications to colchicine, NSAIDs and corticosteroids, an interleukin-1 blocker should be considered. In addition to education and a non-pharmacological management approach, urate-lowering therapy (ULT) should be considered from the first presentation of the disease, and serum uric acid (SUA) levels should be maintained at<6 mg/dL (360 µmol/L) and <5 mg/dL (300 µmol/L) in those with severe gout. Allopurinol is recommended as first-line ULT and its dosage should be adjusted according to renal function. If the SUA target cannot be achieved with allopurinol, then febuxostat, a uricosuric or combining a xanthine oxidase inhibitor with a uricosuric should be considered. For patients with refractory gout, pegloticase is recommended.

Conclusions

These recommendations aim to inform physicians and patients about the non-pharmacological and pharmacological treatments for gout and to provide the best strategies to achieve the predefined urate target to cure the disease.

Transient transformation of mammalian cells by MN protein, a tumor-associated cell adhesion molecule with carbonic anhydrase activity

The MN protein is associated with certain human carcinomas, but absent in most normal tissues. It is a transmembrane protein; its extracellular part contains a domain homologous with carbonic anhydrases (CAs) and a proteoglycan-like region. In the present study, we observed that cells (human CGL1 and mouse NIH3T3 cells) transfected with MN cDNA showed morphologic transformation, but reverted to normal phenotype after 4-5 weeks. This reversion was not due to the loss, silencing, or mutations of MN insert. We also found that MN protein exerted CA enzymatic activity, but this was not relevant for morphologic transformation of cells. MN is an adhesion protein, involved in cell-to-cell contacts, this probably could explain its role in tumorigenesis.

Cyclosporine A or intravenous cyclophosphamide for lupus nephritis: the Cyclofa-Lune study

Intravenous cyclophosphamide is considered to be the standard of care for the treatment of proliferative lupus nephritis. However, its use is limited by potentially severe toxic effects. Cyclosporine A has been suggested to be an efficient and safe treatment alternative to cyclophosphamide. Forty patients with clinically active proliferative lupus nephritis were randomly assigned to one of two sequential induction and maintenance treatment regimens based either on cyclophosphamide or Cyclosporine A. The primary outcomes were remission (defined as normal urinary sediment, proteinuria <0.3 g/24 h, and stable s-creatinine) and response to therapy (defined as stable s-creatinine, 50% reduction in proteinuria, and either normalization of urinary sediment or significant improvement in C3) at the end of induction and maintenance phase. Secondary outcomes were incidence of adverse events, and relapse-free survival. At the end of the induction phase, 24% of the 21 patients treated by cyclophosphamide achieved remission, and 52% achieved response, as compared with 26% and 43%, respectively of the 19 patients treated by the Cyclosporine A. At the end of the maintenance phase, 14% of patients in cyclophosphamide group, and 37% in Cyclosporine A group had remission, and 38% and 58% respectively response. Treatment with Cyclosporine A was associated with transient increase in blood pressure and reversible decrease in glomerular filtration rate. There was no significant difference in median relapse-free survival. In conclusion, Cyclosporine A was as effective as cyclophosphamide in the trial of sequential induction and maintenance treatment in patients with proliferative lupus nephritis and preserved renal function.(ClinicalTrials.gov identifier: NCT00976300)

Soluble form of carbonic anhydrase IX (CAIX) in transitional cell carcinoma of urinary tract

We investigated the expression of cell-associated CAIX protein in histological sections of the transitional cell carcinoma (TCC) of the urinary tract and of the soluble form of CAIX (s-CAIX) shed by the tumor into the serum and urine of TCC patients. A total of 23 patients with histologically confirmed TCC or squamous cell carcinoma (SCC) were enrolled in the pilot study. Sixteen healthy individuals served as controls. Membrane-bound CAIX was present in the tumor cells near the endoluminal surface. Necrosis was observed in only 4 samples. Using Western blots, s-CAIX concentrated from urine was visualized as a double band at 50 and 54 kDa. In most cases, the presence of s-CAIX in the urine correlated with CAIX expression in the tumor. On the other hand, s-CAIX did not exceed the normal level in the serum of TCC patients. Urine from patients with TCC of the urinary bladder and renal pelvis contained s-CAIX, allowing the detection of tumors in approximately 70% of the patients. Moreover, two additional patients with suspected, but unconfirmed bladder tumor, with s-CAIX detected in urine, developed tumors identified as TCC within six months. We suggest that after a simple, rapid and sensitive test, monitoring s-CAIX levels in urine will be developed, it may be useful for early detection of relapse in patients following transurethral tumor resection.

Identification of the MN/CA9 protein as a reliable diagnostic biomarker of clear cell carcinoma of the kidney

The MN/CA9 protein is a tumor-associated antigen that has been shown to have diagnostic utility in identifying cervical dysplasia and carcinoma. MN/CA9 expression is limited to very few normal tissues. We have now extended those observations to further investigate expression of the MN/CA9 protein in histological sections and fine-needle aspiration biopsy smears of normal kidney, benign renal cell lesions, all categories of renal cell carcinomas (clear/granular/spindle cell, chromophilic cell, chromophobic cell, and collecting duct cell RCCs), metastatic RCCs, and non-renal cell clear cell adenocarcinomas. We have found that high levels of MN/CA9 expression is seen in all primary RCCs, cystic RCCs, and metastatic RCCs, with the exception of two cases of the chromophobe cell type, which were MN/CA9 negative. Identical MN/CA9 immunostaining was also observed in the aspiration cytological smears. In contrast, all benign lesions, including pyelonephritis, renal cysts, adenomas, oncocytomas, and normal kidney, did not express the MN/CA9 protein. Thus, we conclude that MN/CA9 protein expression could serve as a valuable adjunct to the cytological and histological diagnosis of benign renal cysts versus cystic RCC, adenoma versus RCC, and oncocytoma versus granular cell RCC. Diffuse membraneous staining of all RCCs (with the exception of chromophobic cell RCC) suggests that MN/CA9 protein expression might have an important clinical utility in the early detection and treatment of RCC. Absence of MN/CA9 expression in non-renal cell clear cell adenocarcinoma also indicates that MN/CA9 protein expression may be used as a differential diagnostic biomarker of metastatic clear cell RCC.

A study of biomarkers in cervical carcinoma and clinical correlation of the novel biomarker MN

The MN protein is a newly described biomarker found to be overexpressed in most cervical carcinomas. This study was an effort to evaluate the prognostic importance of tumor MN expression, HPV status, and the presence of other biomarkers in cervical cancers. Tumor DNA and protein for study were extracted from archived frozen tissue. Tumor tissues and controls were evaluated by Western blot analysis for MN, intestinal alkaline phosphatase (IAP), c-myc, and p53 protein overexpression. Immunohistochemistry was performed for MN quantification and the study of expression patterns in histologic subtypes of cervical cancer. HPV data were obtained by PCR amplification of extracted DNA using consensus and type-specific primers. Clinical data were obtained from the patients' records and from the cancer registry. Clinical and molecular data were correlated by chi2, Fisher's exact test, and logistic regression. The results demonstrate that IAP is not overexpressed in clinical specimens of cervical carcinoma, although in somatic cell hybrid experiments, overexpression of IAP correlates with the malignant state. None of 47 tumors, including those which were HPV negative, overexpressed p53. c-myc protein overexpression occurred in 11 of 52 tumors, most of which contained HPV 16, but this was not significantly different from the tumors as a whole. There was no apparent association between MN protein expression and the overexpression of c-myc protein. MN was overexpressed in all cancers and quantitatively varied with the histologic subtype. Specifically, lower expression of MN correlated with adenosquamous and less-differentiated histology (P < 0.01 for grade 3 tumors). Low expression of MN protein also correlated with HPV negativity (P < 0.05). In stage IB and IIA cancers, low expression of MN was associated with deeper cervical stromal invasion (P < 0.03). Further, low expression of MN correlated with lymph node metastases in small (<3.5 cm) IB and IIA cervical cancers (P < 0.04). These data suggest that MN is emerging as a potentially important new biomarker for cervical carcinoma. The overexpression commonly seen in cervical cancer is possibly associated with loss of a critical tumor suppressor gene located on chromosome 11. Low expression of MN antigen appears to correlate with several adverse prognostic features and further prospective study is warranted.

Mapping of B-neutralizing and T-helper cell epitopes on the bovine leukemia virus external glycoprotein gp51

A battery of 19 synthetic peptides was used to characterize efficient neutralizing and helper T-cell epitopes on the bovine leukemia virus (BLV) external envelope glycoprotein gp51. Four of the antipeptide antisera raised in rabbits inhibited the formation of BLV-induced syncytia; these antisera are directed against peptides 64-73, 98-117, and 177-192. Only antisera directed against the 177-192 region also neutralized vesicular stomatitis virus-BLV pseudotypes. This study clearly demonstrates that neutralizing properties can be observed with antibodies raised to regions undescribed so far and included in both the amino-terminal and central parts of the antigen. In addition, some helper T-cell determinants were defined from gp51-immunized mice and from BLV-infected cattle. Although none of the peptides tested behaved as a universal helper T-cell epitope, peptide 98-117 stimulated T-cell proliferation from BALB/c mice and from three infected cows, while peptide 169-188 strongly stimulated T-cell proliferation from one infected cow. Further experiments performed with three peptides overlapping the 169-188 region (177-192, 179-192, 181-192) demonstrated the particular relevance of residue(s) P-177 and/or D-178 in the helper T-cell epitope. These data should assist in the design of an efficient subunit vaccine against BLV infection that contains peptides possessing both B-neutralizing and helper T-cell determinants.

Recombinant vaccinia virus expression of the bovine leukaemia virus envelope gene and protection of immunized sheep against infection

The bovine leukaemia virus (BLV) envelope gene encoding extracellular glycoprotein gp51 and transmembrane glycoprotein gp30 was cloned into the HA locus of vaccinia virus (Copenhagen strain), downstream of the vaccinia virus early-late promoter, H6, or a triple promoter element consisting of the promoter for the vaccinia virus H6 gene, the promoter for the cowpox virus A-type inclusion (ATI) gene and the promoter for the vaccinia virus HA gene. Inoculation of rabbits or sheep with the recombinant vaccinia virus coding for gp51 and gp30 or an uncleaved env precursor induced neutralizing antibodies to BLV. These antibodies competed with monoclonal antibodies directed against gp51 epitopes F, G, and H previously shown to be of crucial importance for BLV infection. Seven out of eight sheep vaccinated with the vaccinia recombinants resisted a drastic challenge (1.5 x 10(3) sheep infectious doses) with BLV-infected lymphocytes. These results show that vaccination with BLV env vaccinia recombinants protects sheep against infection with extremely high doses of BLV-infected heterologous lymphocytes.

Synthetic peptides approach to identification of epitopes on bovine leukemia virus envelope glycoprotein gp51

Peptides corresponding to residues 21-28, 39-48, 57-67, 59-69, 78-92, 144-155, 144-157, 195-205, 255-268, and 260-268 of envelope glycoprotein gp51 of bovine leukemia virus (BLV) were chemically synthesized and coupled to keyhole limpet hemocyanin or tetanus toxoid. All peptides were immunogenic in rabbits and induced production of antipeptide antibodies. Enzyme-linked immunosorbent assays using Tween 80-purified gp51 or BLV particles showed that antibodies against peptides 78-92, 255-268, and to a lesser extent 39-48 and 144-157 were able to react with the parent glycoprotein, purified or as an integer part of BLV particles. Antisera against peptides 39-48, 78-92, and 144-157 neutralized VSV (BLV) pseudotypes in vitro, the highest neutralization titer being obtained with the 78-92 cyclized peptide. These observations confirm that the NH2 moiety of gp51 carries epitopes involved in virus infectivity.

Identity of HeLa cell determinants acquired by vesicular stomatitis virus with a tumor antigen

Growth of vesicular stomatitis virus (VSV) in HeLa cells results in progeny containing non-VSV antigens with a molecular weight around 75,000. The non-VSV antigens were detected by antiserums to HeLa cell determinants. These antiserums precipitate whole virions but do not neutralize them. Because one of the antiserums is directed to a tumor-specific surface antigen of HeLa cells, it appears that VSV specifically acquires such antigens during its passage through human tumor cells.

Pseudotypes of vesicular stomatitis virus with the envelope properties of mammalian and primate retroviruses

By employing improved techniques it has been possible to produce and characterize a representative spectrum of mammalian and primate retrovirus pseudotypes of vesicular stomatitis virus (VSV). Selection of appropriate cell lines for both the production and subsequent detection of the VSV pseudotypes has been the most important factor in permitting their demonstration. The host range for penetration of these retrovirus pseudotypes of VSV has been defined and found to differ from that reported for the replication of the corresponding retroviruses. Additionally, retroviruses having an identical host range for replication were distinguishable by differences in their host range for penetration, implying that restriction of replication may be occurring by different mechanisms. Studies of the plaque-forming efficiency of retrovirus pseudotypes of VSV in cell lines nonpermissive for replication of the corresponding retroviruses permitted a distinction to be made between the restriction of replication occurring as a consequence of postpenetration events and that occurring as a consequence of a block of penetration itself. The demonstration of primate retrovirus pseudotypes of VSV permits the use of VSV as a probe for the detection of this group of viruses.

Phenotypic mixing of vesicular stomatitis virus and D-type oncornavirus

After mixed infection of cells with vesicular stomatitis virus (VSV, thermolabile mutant tl 17) and oncornavirus type D, phenotypically mixed virions are formed containing the VSV genome and oncornavirus and VSV envelope. The virions are thermostable and have serologic characteristics of both viruses.