Exposure to TNF inhibitors is rare at MOGAD diagnosis

Background:Gender differences in prevalence and disease course are known in various rheumatic diseases; however, investigations of gender difference concerning therapeutical response have yielded variable results.Objectives:The aim of this retrospective study was to investigate, whether a gender difference in response rate to biological disease-modifying antirheumatic drugs (bDMARDs) and apremilast in bDMARD-naïve patients could be observed across the three most prevalent inflammatory arthritis diseases: rheumatoid arthritis (RA), spondylarthritis (SpA) and psoriatic arthritis (PsA). Additionally, a response to individual TNF blockers was investigated in this respect.Methods:Data from bDMARD-naïve RA-, SpA- and PsA-patients from Bioreg, the Austrian registry for biological DMARDs in rheumatic diseases, were used. Patients with a baseline (Visit 1=V1) and follow-up visits at 6 months (Visit 2=V2) and 12 months (Visit 3=V3) were included and response to therapy with TNF-inhibitors (TNFi), furthermore to therapy with rituximab, tocilizumab and apremilast was analyzed according to gender. The remaining bDMARDs were not analyzed due to small numbers. Key response-parameter for RA was disease activity score (DAS28), whereas for PsoA the Stockerau Activity Score for Psoriatic Arthritis (SASPA) and for SpA the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) were employed; in addition, the Health assessment Questionnaire (HAQ) was used. Data were analyzed in R Statistic stratified by gender using Kruskal-Wallis and Wilcoxon tests.Results:354 women and 123 men with RA (n=477), 81 women and 69 men with PsA (n=150), 121 women and 191 men with SpA (n=312) were included. No significant differences in biometrics was seen between female and male patients at baseline in all diseases.In RA patients overall DAS28 decreased from baseline (V1) to V2 and V3 (DAS28: V1: male: 4.38 [3.66, 5.11], female: 4.30 [3.68, 5.03], p(m/f) = 0.905; V2: male: 2.66 [1.73, 3.63], female: 3.10 [2.17, 3.98], p(m/f) = 0.015; V3: male: 2.25 [1.39, 3.36], female: 3.01 [1.87, 3.87], p(m/f) = 0.002). For TNF inhibitors (n=311), there was a significant difference between genders at V2 (Fig.1a). Patients receiving Rituximab (n=41) displayed a significantly higher DAS28 at baseline in females, which diminished in the follow up: V1: (p(m/f) p=0.002; V2: p=0.019; V3: p=0.13); response to tocilizumab (n=63) did not show any gender differences.In PsA patients overall SASPA decreased from baseline (V1) to V2 and V3 (SASPA: V1: male: 4.00 [2.80, 5.20], female: 4.40 [2.80, 5.80], p(m/f) = 0.399; V2: male: 2.20 [1.20, 3.50], female: 3.40 [2.00, 5.00], p(m/f) = 0.071; V3: male: 1.80 [0.80, 2.70], female: 3.01 [2.35, 4.80], p(m/f) = 0.001). For TNF inhibitors (n=79), there was a significant difference between genders at V3 (Fig 1a). For Apremilast (n=39), there was a significant difference between genders at V2 (Fig.1c).In SpA patients overall BASDAI decreased from baseline (V1) to V2 and V3 (BASDAI: V1: male: 4.70 [2.88, 6.18], female: 4.80 [3.30, 6.20], p(m/f) = 0.463; V2: male: 3.05 [2.00, 4.60], female: 3.64 [2.62, 5.41], p(m/f) = 0.039; V3: male: 3.02 [1.67, 4.20], female: 3.65 [2.18, 5.47], p(m/f) = 0.016). In V3 a differential BASDAI in response to TNFi (n=299) was observed (Fig.1a).Possible differences of response to individual TNFi (etanercept, infliximab, other TNFi) measured by HAQ were investigated in all diseases together. The difference between male and females was significant at baseline for all 3 TNFi; whereas with the use of ETA the significant difference was carried through to V2 and V3, it was lost with the use of IFX and was variable with the other TNFi (Fig.1b)Figure 1.Conclusion:Female patients showed a statistically lower response to TNFi in all three disease entities (RA, SpA and PsoA) to a variable degree in our homogenous central european population. Interestingly, the difference was not uniform across individual TNFi when measured by HAQ. Gender differences were also seen in response to Apremilast.Disclosure of Interests:Elisabeth Loibner: None declared, Valentin Ritschl: None declared, Burkhard Leeb Speakers bureau: AbbVie, Roche, MSD, Pfizer, Actiopharm, Boehringer-Ingelheim, Kwizda, Celgene, Sandoz, Grünenthal, Eli-Lilly, Grant/research support from: TRB, Roche, Consultancies: AbbVie, Amgen, Roche, MSD, Pfizer, Celgene, Grünenthal, Kwizda, Eli-Lilly, Novartis, Sandoz;, Peter Spellitz: None declared, Gabriela Eichbauer-Sturm: None declared, Jochen Zwerina: None declared, Manfred Herold: None declared, Miriam Stetter: None declared, Rudolf Puchner Speakers bureau: AbbVie, BMS, Janssen, Kwizda, MSD, Pfizer, Celgene, Grünenthal, Eli-Lilly, Consultant of: AbbVie, Amgen, Pfizer, Celgene, Grünenthal, Eli-Lilly, Franz Singer: None declared, Ruth Fritsch-Stork: None declared

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FRI0434 PREDICTIVE FACTORS OF SERIOUS INFECTIONS IN PATIENTS WITH CHRONIC INFLAMMATORY ARTHRITIS ON TREATMENT WITH TNF INHIBITORS: REAL LIFE DATA

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-eular.4347 ◽

2020 ◽

Vol 79 (Suppl 1) ◽

pp. 815.1-815

Author(s):

A. Ruiz Ochoa ◽

J. Escudero Argaluza ◽

B. Alvarez Rodríguez ◽

M. Vasques Rocha ◽

C. Stoye ◽

...

Keyword(s):

Inflammatory Arthritis ◽

Associated Factors ◽

Statistical Tests ◽

Univariate Analysis ◽

Real Life ◽

Tnf Inhibitors ◽

Charlson Index ◽

Multivariable Logistic Regression Model ◽

Serious Infections ◽

Usual Clinical Practice

Background:Serious infections are one of the most feared adverse events in patients treated with biologics. To this regard data coming from randomized and long-term extension studies may not totally applied to the usual clinical practice due to the different profile of the treated patients. To study the associated factors for serious infections in patients with inflammatory arthritis treated with TNF inhibitorsObjectives:To study the associated factors for serious infections in patients with inflammatory arthritis treated with TNF inhibitorsMethods:All the medical records of the patients with inflammatory arthritis being treated with TNF inhibitors at the beginning of 2016 were retrospectively reviewed. All serious infections suffered for these patients until the end of 2018 were recorded. Serious infections were defined as those which required to admitted at the hospital for intravenous treatment. Potential variables associated with the development of these infections including: demographic and clinical characteristics, concomitant treatments or comorbidity (by Charlson index) were studied. Standard statistical tests for descriptive and univariate analyses were used and a multivariable logistic regression model was built to check independent associations.Results:Overall 334 patients (50.3% women) with a mean age of 56.67 (±12.853) were studied: 140 (41.92%) Rheumatoid arthritis (RA), 55 (16.46%) psoriatic arthritis (PsA) and 138 (41.62%) spondyloarthritis (Sp). Forty-five serious infections were observed in 30 patients, being respiratory (40%) and urinary (8.8%) the most frequent localizations. Only one patient died. By univariate analysis, disease duration, age, concomitan use of glucocorticoids (GC) (but not of synthetic DMARDs), Charlson index and specifically Diabetes Mellitus were associated with infection (p< 0.05). The type of arthritis was not associated and the results in the subset of RA patients were overall similar. In the multivariate analysis the use of GC [OR: 5.31 (1.98.14.26)] and the Charlson index [OR:2.48 (1.70;3.60)] were found to be independently associated to infection.Conclusion:In patients with inflammatory arthritis and treated with TNF inhibitors around a 10% developed any serious infection along three years of follow up. Use of GC and comorbidity emerged as the main risk factors for this complication.Disclosure of Interests:None declared

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AB0652 MACHINE LEARNING TO PREDICT EARLY TNF INHIBITOR USERS IN PATIENTS WITH ANKYLOSING SPONDYLITIS

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-eular.3743 ◽

2020 ◽

Vol 79 (Suppl 1) ◽

pp. 1620.1-1621

Author(s):

J. Lee ◽

H. Kim ◽

S. Y. Kang ◽

S. Lee ◽

Y. H. Eun ◽

...

Keyword(s):

Machine Learning ◽

Ankylosing Spondylitis ◽

Tnf Inhibitors ◽

Tnf Inhibitor ◽

Ann Model ◽

Learning Models ◽

Feature Importance ◽

Importance Analysis ◽

Baseline Characteristics ◽

Machine Learning Models

Background:Tumor necrosis factor (TNF) inhibitors are important drugs in treating patients with ankylosing spondylitis (AS). However, they are not used as a first-line treatment for AS. There is an insufficient treatment response to the first-line treatment, non-steroidal anti-inflammatory drugs (NSAIDs), in over 40% of patients. If we can predict who will need TNF inhibitors at an earlier phase, adequate treatment can be provided at an appropriate time and potential damages can be avoided. There is no precise predictive model at present. Recently, various machine learning methods show great performances in predictions using clinical data.Objectives:We aim to generate an artificial neural network (ANN) model to predict early TNF inhibitor users in patients with ankylosing spondylitis.Methods:The baseline demographic and laboratory data of patients who visited Samsung Medical Center rheumatology clinic from Dec. 2003 to Sep. 2018 were analyzed. Patients were divided into two groups: early TNF inhibitor users treated by TNF inhibitors within six months of their follow-up (early-TNF users), and the others (non-early-TNF users). Machine learning models were formulated to predict the early-TNF users using the baseline data. Additionally, feature importance analysis was performed to delineate significant baseline characteristics.Results:The numbers of early-TNF and non-early-TNF users were 90 and 509, respectively. The best performing ANN model utilized 3 hidden layers with 50 hidden nodes each; its performance (area under curve (AUC) = 0.75) was superior to logistic regression model, support vector machine, and random forest model (AUC = 0.72, 0.65, and 0.71, respectively) in predicting early-TNF users. Feature importance analysis revealed erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and height as the top significant baseline characteristics for predicting early-TNF users. Among these characteristics, height was revealed by machine learning models but not by conventional statistical techniques.Conclusion:Our model displayed superior performance in predicting early TNF users compared with logistic regression and other machine learning models. Machine learning can be a vital tool in predicting treatment response in various rheumatologic diseases.Disclosure of Interests:None declared

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AB0115 COMPARISON OF ULTRASOUND FINDINGS BETWEEN TNF INHIBITORS AND NON-TNF INHIBITORS AT FIRST BIOLOGICS IN PATIENTS WITH RHEUMATOID ARTHRITIS

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2021-eular.1377 ◽

2021 ◽

Vol 80 (Suppl 1) ◽

pp. 1086.2-1087

Author(s):

T. Okano ◽

T. Koike ◽

K. Inui ◽

K. Mamoto ◽

Y. Yamada ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Disease Activity ◽

Disease Duration ◽

Power Doppler ◽

Tnf Inhibitors ◽

Tnf Inhibitor ◽

Significant Difference ◽

The Us ◽

Us Findings ◽

Improvement Ratio

Background:In rheumatoid arthritis (RA), biologics treatment is one of the effective treatment options. Usually, there is no difference in therapeutic effect regardless of which biologics is used, but the effect for joint synovitis is unknown. Recently, ultrasound (US) has played a role of sensitive imaging modality in the diagnosis and follow-up of patients with RA.Objectives:The aim of this study was to compare the improvement of US findings between TNF inhibitors and non-TNF inhibitors at first biologics in patients with RA.Methods:Fifty-four RA patients who started the first biologics from September 2016 to December 2018 were included in this longitudinal study (SPEEDY study, UMIN000028260). All the patients were performed clinical examination, blood test and US examination at baseline, 4, 12, 24, 36 and 52 weeks. A US examination was performed at the bilateral first to fifth metacarpophalangeal (MCP) joints, first interphalangeal (IP) and second to fifth proximal interphalangeal (PIP) joints, wrist joints (three part of radial, medial and ulnar) and first to fifth metatarsophalangeal (MTP) joints, by using HI VISION Ascendus (Hitachi Medical Corporation, Japan) with a multifrequency linear transducer (18-6 MHz). The gray scale (GS) and power Doppler (PD) findings were assessed by the semi-quantitative method (0-3). GS score and PD score (both 0-108 points) were defined as the sum of each score. The change of disease activity and US findings were compared between TNF group and non-TNF group.Results:Among 54 cases, 32 patients were used TNF inhibitor and 22 were non-TNF inhibitor. Age and duration of RA were significantly higher in the non-TNF group, and MTX dose was significantly lower in the non-TNF group. The baseline inflammatory markers tended to be higher in the non-TNF group and the disease activity was also higher in the non-TNF group. However, the US findings showed no significant difference in both GS and PD between two groups at baseline. US improvement ratio was no difference between TNF group and non-TNF group at 4, 12, 24, 36 and 52 weeks in both GS and PD score. Regardless of the type of biologics, patients with long-term disease duration tended to have poor improvement in US synovial fingings.Table 1.Baseline patient and disease characteristicsTNF (n=32)non-TNF (n=22)P valueFemale patients, n (%)21 (65.6)16 (72.7)0.767Age (years)63.5±15.471.0±9.00.030Disease duration (years)6.5±8.213.0±11.70.032CRP (mg/dl)1.8±2.53.0±3.20.170DAS28-ESR5.0±1.45.8±1.20.022GS score26.1±18.831.8±21.10.313PD score17.6±11.423.1±14.60.150Figure 1.GS and PD improvement ratio at 4, 12, 24, 36 and 52 weeksConclusion:There was no difference in the US findings improvement between patients with TNF inhibitor and non-TNF inhibitor at first biologics in patients with RA.References:[1]Grassi W, Okano T, Di Geso L, Filippucci E. Imaging in rheumatoid arthritis: options, uses and optimization. Expert Rev Clin Immunol. 2015;11:1131-46.[2]Nishino A, Kawashiri SY, Koga T, et al. Ultrasonographic Efficacy of Biologic andTargeted Synthetic Disease-ModifyingAntirheumatic Drug Therapy in RheumatoidArthritis From a Multicenter RheumatoidArthritis Ultrasound Prospective Cohort in Japan. Arthritis Care Res (Hoboken). 2018;70:1719-26.Acknowledgements:We wish to thank Atsuko Kamiyama, Tomoko Nakatsuka for clinical assistant, Setsuko Takeda, Emi Yamashita, Yuko Yoshida, Rika Morinaka, Hatsue Ueda and Tomomi Iwahashi for their special efforts as a sonographer and collecting data.Disclosure of Interests:None declared

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Reactivation of latent tuberculosis with TNF inhibitors: critical role of the beta 2 chain of the IL-12 receptor

Cellular and Molecular Immunology ◽

10.1038/s41423-021-00694-9 ◽

2021 ◽

Author(s):

Marie Robert ◽

Pierre Miossec

Keyword(s):

Critical Role ◽

Latent Tuberculosis ◽

Tnf Inhibitors ◽

Beta 2

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AB0302 USE OF TNF-INHIBITORS BEFORE, DURING AND THE FIRST YEAR AFTER PREGNANCY AMONG WOMEN WITH RHEUMATOID ARTHRITIS

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-eular.3622 ◽

2020 ◽

Vol 79 (Suppl 1) ◽

pp. 1450.2-1450

Author(s):

H. Bjørngaard ◽

H. Koksvik ◽

B. Jakobsen ◽

M. Wallenius

Keyword(s):

Rheumatoid Arthritis ◽

Disease Activity ◽

Post Partum ◽

Tnf Inhibitors ◽

Treat To Target ◽

Inflammatory Rheumatic Diseases ◽

Tnf Inhibitor ◽

Rheumatic Arthritis ◽

Quality Register ◽

In Pregnancy

Background:Treat to target is a goal, also in pregnant women with Rheumatoid arthritis (1). There is increasing evidence on safe use with TNF inhibitors during pregnancy. Adjusted use of TNF inhibitors preconception and throughout pregnancy may stabilize disease activity and prevent flares (2). Low disease activity is also beneficial for the fetus.Objectives:To study the use of TNF-inhibitors among women with Rheumatic arthritis during and after pregnancy.Methods:RevNatus is a Norwegian, nationwide quality register that monitors treatment of inflammatory rheumatic diseases before, during and after pregnancy. Data from RevNatus in the period October 2017 to October 2019 was used to map the use of all types of TNF inhibitors among 208 women with rheumatoid arthritis, diagnosed by the ACR/EULAR criteria. The use of medication was reported at the time of visit in outpatient clinic. The frequency of use of TNF inhibitors registered at seven timepoints from pre-pregnancy to twelve months after delivery.Results:The use of medication was reported at each visit for all the women with rheumatoid arthritis. Most of the women were not using TNF inhibitors before and beyond conception. Most of the women continuing TNF inhibitors beyond conception used certolizumab or etanercept. Adalimumab and infliximab were used in pregnancy (tabell 1).Tabell 1.certoliz-umabetane-rceptadalim-umabgolim-umabinflixi-mabNo TNF-inhibitorBefore pregnancyn=10521% (22)9% (10)3% (3)1% (1)66% (69)1.trimestern=8119% (15)10% (8)71% (58)2.trimestern=8810% (9)10% (9)80% (70)3.trimestern=9111% (10)5% (5)83% (76)6 weeks post partum n=9622% (21)13% (13)1% (1)1% (1)63% (60)6 months post partum n=8824% (21)18% (16)4% (4)1% (1)53% (46)12 months post partum n=8421% (18)17% (15)7% (6)2% (2)53% (43)Conclusion:Most of the women with rheumatic arthritis were not treated with TNF inhibitors before or in pregnancy. Women with rheumatic arthritis that continuing treatment with TNF inhibitors through pregnancy were using certilozumab and etanercept.References:[1]Gotestam Skorpen C, Hoeltzenbein M, Tincani A, Fischer-Betz R, Elefant E, Chambers C, et al. The EULAR points to consider for use of antirheumatic drugs before pregnancy, and during pregnancy and lactation. 2016;75(5):795-810.[2]van den Brandt S, Zbinden A, Baeten D, Villiger PM, Ostensen M, Forger F. Risk factors for flare and treatment of disease flares during pregnancy in rheumatoid arthritis and axial spondyloarthritis patients. Arthritis Res Ther. 2017;19(1):64.Disclosure of Interests:None declared

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