AB0762 Incidence Of Anterior Uveitis In Axial Spondyloarthritis During Secukinumab Treatment: TWO YEARS REAL LIFE EXPERIENCE FROM TURKBIO REGISTRY

Background

Secukinumab (SEC), a human anti-IL-17A monoclonal antibody, has similar treatment response rates to tumor necrosis factor (TNF) inhibitors in patients with axial spondyloarthritis (SpA). However, the efficacy of SEC on anterior uveitis (AU) is unclear.

Objectives

This study aimed to evaluate the risk of new-onset or relapsing AU in axial SpA patients treated with SEC.

Methods

In this prospective cohort study, 130 axial SpA patients receiving SEC at the TURKBIO registry between 2019 and 2021 were evaluated. Demographic and clinical characteristics and data about the presence of AU pre or post-treatment were collected. The univariate and multivariate logistic regression analyses were performed to evaluate the predictors of AU development.

Results

The mean age of the patients (F/M: 59/71) was 47.4±10.9 years. The median follow-up time was 540 days (IQR: 330-630). SEC was the first biological agent in 50 (38.4%) patients and 35 (26.9%) patients were using at least one concomitant conventional synthetic DMARD (Table 1). While continued SEC therapy was in 93 (71.5%) patients, treatment withdrawal was in 37 cases (in 26 due to ineffectiveness, two adverse events and nine other reasons). Overall, 15(11.5%) patients had a history of AU before the SEC. During follow-up, AU attacks were seen in the 6 cases (4 were new-onset and 2 were flare) and 5 of these patients have a history of inadequate response to TNF inhibitors. The frequency of AU was calculated as 3.42 per 100 patient-years during SEC treatment. The only significant predictor of AU development was the baseline high C-reactive protein (CRP) level on multivariate analysis (p=0.003, OR: 1.063 [95% CI 1.021-1.107]).

Table 1.

Demographics and clinical characteristics of the patients

Total (n:191)Gender (F/M)59/71Age (years) (mean±SD)47.4±10.9Diagnosis; n (%)   AS125 (96.2)   nr-axSpA5 (3.8)BASDAI (mean±SD)47.2±20.48   Missing n (%)4 (3.07)ASDAS (mean±SD)3.32±0.92   Missing n (%)14 (10.7)C-reactive protein (mg/L) median (IQR)12.6 (4.67-22.62)Sedimentation (mm/h) median (IQR)22 (9-42)Concomitant csDMARDs n (%)35 (26.9)Secukinumab dose n (%)   150 mg120 (92.3)   300 mg10 (7.7)TNFi-naive patients n (%)50 (38.5)Number of previous bDMARDs n (%)   136 (27.7)   223 (17.7)   ≥ 321 (16.1)History of previous TNFi n (%)   Monoclonal TNFi64   Etanercept16

AS; Ankylosing spondylitis, nr-axSpA; Non radiographic axial spondyloarthritis, BASDAI; Bath Ankylosing Spondylitis Disease Activity Index, ASDAS; Ankylosing Spondylitis Disease Activity Score, csDMARD; conventional synthetic disease modifying anti-rheumatic drug, TNFi; Tumor necrosis factor inhibitors, bDMARD; biological DMARD. Datas were expressed as number (%), mean±SD or median (IQR).

Conclusion

In this real-life data from the TURKBIO registry, the incidence of AU in axial SpA patients treated with SEC was calculated as 3.42 per 100 patient-years. A high baseline CRP level was an independent factor for developing AU.

Disclosure of Interests

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.

SAT0097 DO COMORBIDITIES IMPACT PERSISTENCE OF FIRST TUMOR NECROSIS FACTOR INHIBITOR TREATMENT IN RHEUMATOID ARTHRITIS? DATA FROM TURKBIO

Background:

Studies indicate that patients with rheumatoid arthritis (RA) are at increased risk of developing several comorbid disorders. Comorbidities affect treatment decisions, the effectiveness of the treatment, quality of life, RA prognosis, and survival rate [1].

Objectives:

The aim of thisstudyto investigate the impact of comorbidity on the first TNF inhibitor treatment persistence in RA.

Methods:

In the TURKBIO database, patients with an ICD 10-diagnosis of RA (M05 or M06) who started TNF inhibitor therapy between January 2011 and June 2019 were enrolled. Demographic and clinical characteristics, acute phase reactants, disease activity scores (DAS 28 CRP, HAQ, CDAI, VAS global), initial comorbidities and numbers, drug persistence, were evaluated. Kaplan-Meier plots and Cox proportional hazard regression analyses were performed.

Results:

A total of 1172 patients >18 years of age treated with TNF-α inhibitors were included in the study. The most prevalent comorbidities were: hypertension in 262 patients (32.6%), obesity in 254 (32.6%), osteoporosis in 178 (22.3%), chronic lung disease in 143 (17.9%) and depression in 126 (15.8%). The baseline characteristics are summarised in Table 1. The presence of comorbidity did not affect the survival rate of the first TNF inhibitor therapy in the RA patients (p: 0.65). Comorbidities had no effect on DAS28 CRP (> 1.2 reduction) responses at 6 and 12 months of treatment (p: 0.18, p: 0.83, respectively). As the mean disease duration increases, the persistence of the first TNF inhibitor decreases by 5%.

Conclusion:

This study demonstrated the increasing burden of comorbidities in RA. However, it suggested that the presence and number of comorbidities did not influence the rate of persistence in the first TNF inhibitor drug and the response to treatment.

References:

[1] Gabriel, S.E. and K. Michaud,Epidemiological studies in incidence, prevalence, mortality, and comorbidity of the rheumatic diseases.Arthritis research & therapy, 2009.11(3): p. 229.

Disclosure of Interests:

None declared

THU0378 DO COMORBIDITIES DECREASE THE FIRST TNF-INHIBITOR RETENTION AND TREATMENT RESPONSE IN AXIAL SPONDYLOARTHRITIS PATIENTS? DATA FROM TURKBIO

Background:

The frequency of comorbidities has increased in spondyloarthritis patients compared to the general population. The effect of comorbidities on tumour necrosis factor alpha inhibitor (TNFi) drug retention and treatment response has not been well evaluated.

Objectives:

The purpose of this study to assess the impact of comorbidities on the first TNFi drug survival and treatment response in patients with axial spondyloarthritis (axSpA) registered in theTURKBIOdatabase.

Methods:

In this study, the frequency of comorbidities, disease activity scores at baseline and month 6 and drug retention were recorded in AxSpA patients iniating first TNFi treatment between 2011 and 2019. Kaplan Meier plot and log rank tests were used for drug survival analysis. Cox regression analysis with HR was performed to evaluate the correlation between comorbidities and drug survival.

Results:

There were 2428 patients with AxSpA (39.3% female) who used their first TNFi during the study period. Among them, a total of 770 (31%) had at least one comorbid disease. Hypertension was the most common comorbidity (9.7%), followed by the affective disorders (8%) and chronic lung disease (5.8%). The baseline characteristics of patients are shown in Table 1.The presence of any comorbidity did not impact the first TNFi retention (Figure 1). When comorbidities were analysed seperately, we found that only history of cerebrovascular event was negatively associated with drug retention rate (HR: 6.9, p:0.008). There was no statistically significant difference in Bath AS Disease Activity Index 50% (BASDAI50) response between patients with and without comorbidity at 6 months. Less axSpA patients with comorbidity achieved a ASDAS score ≤ 2.1 compared to patients without comorbidity at 6 months.

Table 1.

Baseline Characteristics of Patients

Radiographic Spondyloarthritis, n (%)2318 (95.5)Female, n(%)954 (39.3)Age, year42.2±11.8Age at diagnosis, years32.5± 11.3Age at initial TNFi, years39.4 ± 11.1Symptom duration, years9.7± 7.5Time to initial TNFi, years7±6.8HLA-B27- positivity, n (%)1144 (47.1)Smokers, n (%)1068 (44)Baseline BASDAI35.5±22.2Baseline ASDAS-CRP2.8±1.1Baseline CRP (mg/L)15.7±24.4VAS global patient46.6±28.7

-Quantitative variables are presented as mean ± SD, and qualitative variables are presented as frequency and percentage

-ASDAS-CRP, Ankylosing Spondylitis Disease Activity Score using C-reactive protein VAS, visual analogue scale

Conclusion:

The results of this study demonstrated that the presence of previous cerebrovascular event decreased the first TNFi survival in patients with axSpA. It also suggested that comorbidities might decrease TNFi treatment response.

Disclosure of Interests:

None declared

THU0390 THE INFLUENCE OF OBESITY ON RETENTION AND TREATMENT RESPONSE OF SECUKINUMAB IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS: REAL LIFE DATA FROM THE TURKBIO REGISTRY

Background:

Axial spondyloarthritis (axSpA) is a chronic, inflammatory disease that primarily affects the axial skeleton. Secukinumab is a human monoclonal antibody that binds to the protein interleukin (IL)-17A. Although some studies showed that obesity had a negative effect on the efficacy of tumor necrosis factor alpha inhibitor (TNFα -i) treatment in AS patients (1), no data is available for secukinumab.

Objectives:

To evaluate the effect of obesity on the treatment response and drug survival of secukinumab in patients with axSpA.

Methods:

We performed an observational cohort study based on the TURKBIO between 2018-2020. A total of 185 patients were included in the study. The patients were divided into three groups as obese (BMI≥30 kg/m2), overweight (BMI:25-30 kg/m2), and normal (BMI<25 kg/m2). Disease activity was evaluated at baseline and 3, 6 and 12 months of secukinumab therapy. Clinical response was evaluated as achievement of BASDAI50, ASAS20/40, and ASDAS-Clinical and improvement (CII and MI) rates.

Results:

185 axSpA patients were identified in the registry; 135 (72%) had available BMI data. Thirty nine (28.8%) patients were obese. The mean age of obese patients was higher (p=0.002). The frequency of HLA-B27 and male gender was lower in obese group (p=0.012 and p=0.013, respectively). There was no significant difference between groups in terms of clinical response parameters at 3, 6 and 12 months (Table 1). Drug retention rates were higher in biologic naive patients(p=0.007) (Figure 1).

Table 1(BMI <25) (n=33)(BMI 25-30)(n=63)(BMI ≥ 30)(n=39)PAll patients (n=185)Age (years)40.2±11.345.7±11.750.0±10.60.002 *45.2±11Male Gender n (%)25 (75.8)34 (54.0)16 (41.1)0.012 **104 (56.2)HLA-B27 (+) n (%)14 (73.6)37 (84.0)11 (44.0)0.013 **76 (64.3)Prior Naive/1/≥2 bDMARD n (%)12 (36.3)/9 (27.3)/12 (36.3)17 (26.9)/13 (20.6)/33 (52.4)10 (25.6)/14 (35.8)/27 (69.2)0.30256 (30.3)/ 49 (26,5)/ 80 (43,2)ASAS20 response¶13 (61.9)/11 (57.9)/4 (57.1)19 (48.7)/16 (59.3)/8 (42.1)11 (40.7)/7 (29.1)/3 (50.0)0.345/0.073/0.88659 (518)/47 (49.5)/20 (42.6)ASAS40 response¶9 (42.9)/7 (36.8)/3 (42.9)15 (39.5)/10 (37)/1 (5.3)6 (24)/5 (20,8)/3 (50.0)0.334/0.386/0.01240 (35.0)/29 (30.5)/11 (23.4)BASDAI50 response ¶10 (47.6)/9 (47.4)/4 (57.1)15 (39.5)/11 (40.5)/3 (15.8)9 (34.6)/5 (21.7)/3 (50.0)0.634/0.192/0.07748 (42.1)/37 (38.9)/16 (34.0)ASDAS-CII ¶3 (14.3)/5 (26.3)/1 (14.3)6 (17.6)/8 (30.8)/5 (27.8)6 (23.1)/5 (21.7)/2 (33.3)0.237/0.162/0.53123 (21.4)/22 (23.6)/11 (23.9)ASDAS-MI ¶5 (23.8)/3 (15.8)/0 (0)8 (23.5)/6 (23.1)/2 (11.11 (3.8)/1 (4.3)/1 (16.7)0.237/0.162/0.53118 (16.8)/18 (19.3)/8 (17.4)

§; Mean±SD. ¶; at 3/6/12 Months, n (%),*One-way ANOVA test, ** Pearson Chi-Sqaure Test

Figure 1

Conclusion:

This study demonstrated that obesity had no impact on the efficacy and retention of secukinumab treatment in patients diagnosed with axSpA. The drug survival was found to be higher among biologic-naive axSpA patients compared to biologic-experienced.

References:

[1]Ottaviani S.et al. ‘’Body mass index influences the response to infliximab in ankylosing spondylitis’’,Arthritis Res Ther 2012; 14: R11

Disclosure of Interests:

None declared

OP0109 CO-MEDICATION WITH A CONVENTIONAL SYNTHETIC DMARD IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS IS ASSOCIATED WITH IMPROVED RETENTION OF TNF INHIBITORS: RESULTS FROM THE EUROSPA COLLABORATION

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-Leflunomide0801

Conclusion:

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 IQVIA

MN and BD participated equally

Disclosure 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

AB0202 GENETIC SUSCEPTIBILITY AND PHENOTYPE OF RHEUMATOID ARTHRITIS IN DANISH AND TURKISH PATIENTS

Background:

Previous studies indicate that genetic susceptibility and phenotype of rheumatoid arthritis (RA) differ between the populations.

Objectives:

To compare the clinical, serologic expression and the presence of shared epitopes (SE) of incident RA in two different populations, one from Northern and the other from Southern Europe.

Methods:

Data on incident RA patients fulfilling EULAR/ACR 2010 classifications criteria for RA were collected at Rheumatology Departments in Denmark and Turkey in 2015-2016. Patients were assessed using the same standardized protocol in both populations. SE carrier status were assigned, according to the du Montcel classification based, into six allele groups:S1, S2,S3D,S3PandX, where S2 and S3P are RA risk-enhancing alleles and S1 and S3D are RA protective alleles of the shared epitope(1).

Results:

109 incident RA patients from Denmark and 114 incident RA patients from Turkey were enrolled. Genetic data were available from 87% of the patients.

Table 1.

Characteristics of incident rheumatoid arthritis patients in Denmark and Turkey

Danish patientsn=109Turkish patientsn=114P-valueAge at diagnosis, years60 (49-69)52 (43-64)0.003Female, %64740.12Symptom duration, months7 (4-21)6 (2-22)0.6Smoking status Never smoker, %43440.98 Former smoker, %28310.68 Current smoker, %29250.54VAS pain (0-100 mm)45 (28-66)60 (41-72)0.01VAS fatigue (0-100 mm)51 (29-69)50 (20-70)0.32VAS global, patient (0-100 mm)60 (31-80)60 (41-73)0.77Swollen joint count (0-28)7 (4-11)3 (1-6)<0.00001Tender joint count (0-28)7 (3-11)5 (2-8)0.04HAQ score (0-3)0.75 (0.34-1.25)1.0 (0.25-1.75)0.02DAS284.7 (4.1-5.5)4.3 (3.3-5.2)0.01CRP, mg/l7 (3.0-18.5)8 (3.1-22.6)0.54IgM RF positive, %70660.58ACPA positive, %63750.1

Medians (interquartile range) for continuous variables

VAS – Visual Analog Scale, HAQ - Health Assessment Questionnaire, DAS28 - Disease Activity Score 28 joints, CRP – C-reactive protein, RF – Rheumatoid Factor, ACPA - Anti-Citrullinated Protein Antibodies.

Table 2.

Shared epitope allele carrier frequencies.

AlleleDanish patientsn=98Turkish patientsn=95P-valueS1, % (n)19 (37)22 (42)0,43S2, % (n)26 (51)8 (16)<0,00001S3D, % (n)6 (12)21 (39)0,000029S3P, % (n)27 (52)29 (56)0,52X, % (n)22 (44)19 (37)0,47

We found no associations between the risk-enhancing alleles and the presence of IgM rheumatoid factor or ACPA.

Conclusion:

The Turkish patients were younger and had lower disease activity than Danish at the time of diagnosis. Our study found an enhanced genetic susceptibility to RA in Danish compared to Turkish patients with a higher prevalence of risk-enhancing RA alleles and a lower prevalence of protective alleles.

References:

[1]Tezenas du Montcel S, Michou L, Petit-Teixeira E, Osorio J, Lemaire I, Lasbleiz S, et al. New classification of HLA–DRB1 alleles supports the shared epitope hypothesis of rheumatoid arthritis susceptibility.Arthritis Rheum2005; 52: 1063–8.

Disclosure of Interests:

None declared

SAT0423 LONG-TERM SURVIVAL OF THE FIRST BIOLOGIC TREATMENT IN PSORIATIC ARTHRITIS AND THE EFFECT OF THE SELECTED TREATMENT ON DRUG SURVIVAL; TURKBIO REGISTRY

Background:

Currently, biologic treatments are used effectively in patients with psoriatic arthritis (PsA).

Objectives:

The aim of this study was to evaluate and compare long-term drug survival of the first biologic treatments including adalimumab, certolizumab, etanercept, golimumab, infliximab, secukinumab and ustekinumab in patients with PsA.

Methods:

PsA patients, electronically registered at each visit in the TURKBIO database between 2011 and 2019 were included in the study. PASW 18.0 for Windows was used for statistical analysis. Drug survival rates were calculated by Kaplan Meier method.

Results:

355 patients (227 women; axial PsA = 48, peripheral PsA = 307) were included in the study (Table 1). Adalimumab was the most commonly used first biologic treatment (n=125; 37.6%). The rate of drug survival was found to be 0.75 at month 60 in patients receiving the first biologic treatment (Figure 1). There was no significant difference in drug survival rate between tumor necrosis factor alpha inhibitor (TNFi) and non-TNFi biologic drugs (p=0.56). No difference was also found in drug survival rates between each biologic treatment.

Table 1.

Initial demographic and clinical datas of patients with PsA

PsA Patients (n=355)Females, n (%)227 (63,9)Age of diagnosis, years*34,6 (27-42)CRP baseline*6 mg/ L (3-15)ESR baseline*24 mm/h (10-38)Smoking, n (%)Current99 (28,5)Never192 (55,3)Previous56 (16,2)HLA B27 positivity,n (%)41 (26,4)First biologic agent, n (%)-TNFi332 (95,4)AdalimumabEtanercept125 (37,6)80 (24,1)Golimumab52 (15,6)Certolizumab44 (13,3)Infliximab31 (9,4)- Other biologic agents16 (4,6)Secukinumab13 (81,3)Ustekinumab3 (18,7)

*median (min-max)

Conclusion:

The results of this study establish that more than half of patients with PsA can remain in their initial biologic treatment over a long term. It has been observed that the choice of biologic treatment did not effect the drug survival in PsA.

Disclosure of Interests:

None declared

The prevalence of gout in an urban area of Izmir, Turkey: a population-based epidemiological study

OBJECTIVES

This study aimed to determine the prevalence of gout in a general Turkish population, according to the American College of Rheumatology (Wallace) criteria proposed for gout classification.

METHODS

This study was conducted in two districts of Izmir Province in Turkey, and involved 2835 subjects of ≥ 20 years of age. In the first stage, face-to-face interviews were performed at the subjects' registered households. In the second stage, subjects who gave positive answers in the screening questionnaire were invited to the hospital for a full examination, which included a detailed medical history, medication use and blood tests.

RESULTS

A total of 2887 subjects were contacted, and complete interviews were obtained for 2835 (1551 women, 1284 men). A total of 312 subjects (227 women, 85 men) reported experiencing a short period of joint pain accompanied by swelling, redness or reduced range of movement, and 247 (79%) of these patients underwent a detailed clinical examination in the hospital. Gout was diagnosed in 11 patients (8 men, 3 women). We found minimum age- and sex-adjusted prevalence rates of gout of 0.31% (95% CI: 0.16-0.61) in subjects of ≥ 20 years of age, and 0.72% (95% CI: 0.37-1.24) in subjects of ≥ 40 years of age.

CONCLUSIONS

Our data suggest that the estimated prevalence of gout (0.31%) is lower than the previously published estimated prevalence of rheumatoid arthritis (0.36%) in the same study population (14 definite rheumatoid arthritis cases among the 2835 subjects).