Disease activity assessment for juvenile idiopathic arthritis in transitional care

OBJECTIVE

The indices to measure disease activity of chronic arthritis in adulthood and childhood are different. Therefore, assessing the status of the disease in young patients with juvenile idiopathic arthritis (JIA) can be tricky, especially when the transition to adult care is ongoing. The aim of our study was to assess the level of correlation between adult and juvenile scores in the measurement of disease activity in JIA patients during transitional care.

METHODS

We estimated the disease activity by using the Juvenile Arthritis Disease Activity Score 71 (JADAS71), clinical JADAS, adult Disease Activity Score (DAS28), Simplified Disease Activity Index (SDAI), and Clinical Disease Activity Index (CDAI) in JIA patients in transitional care. We enrolled patients older than 16 years at the time of the first transition visit, and disease activity was assessed at baseline and 12 months. Regression analyses were carried out to estimate the level of agreement among the different indices.

RESULTS

We recruited 26 patients with JIA; 11 patients were polyarticular (42.3%) and 15 patients were oligoarticular (53.1%). The mean age at diagnosis was 7.7±3.9 years and the age at the first evaluation was 20.9±3.7 years. The correlation between JADAS71 and DAS28 was r2=0.69, r2=0.86 between JADAS71 and SDAI, and r2=0.81 between JADAS71 and CDAI.

CONCLUSIONS

SDAI and JADAS71 showed the best correlation, but a few patients were not captured at the same level of disease activity. New prospective studies with a larger number of patients will be needed in this field.

Janus kinase inhibitors: between prescription authorization and reimbursability

Following the restrictions on the reimbursability of Janus kinase inhibitors introduced by the Italian Medicines Agency, the Italian Society of Rheumatology has drafted this document to shed light on the clinical conditions and reimbursability criteria set out in the prescription forms.

Plasma pentraxin 3 in idiopathic inflammatory myopathies: a possible new biomarker of disease activity

Pentraxin-3 (PTX3) is a component of humoral innate immunity with essential functions both in promotion and resolution of inflammation. We aimed to study the PTX3 in the plasma and in the muscle of patients with idiopathic inflammatory myopathies (IIM) and whether PTX3 may correlate with disease activity. Plasma PTX3 levels were assessed in 20 patients with IIMs, 10 dermatomyositis (DM), and 10 polymyositis (PM), compared to 10 patients with rheumatoid arthritis (RA) and 10 healthy donors (HDs) aged, sex, and body mass index matched. Disease activity in IIMs was assessed by Myositis Disease Activity Assessment Visual Analog Scale (MYOACT), while disease activity score on 28 joints (DAS28) was used for RA patients. Muscle histopathology and immunohistochemical (IHC) analyses were also performed. Mean plasma PTX3 levels were significantly higher in IIM patients than HDs (518 ± 260 pg/ml vs. 275 ± 114 pg/ml, P = 0.009). Linear regression analysis adjusted for age, sex, and disease duration showed a direct correlation between PTX3 and CPK levels (β: 0.590), MYOACT (β: 0.759), and physician global assessment of disease activity (β: 0.832) in IIMs. No association between PTX3 levels and DAS28 was found in RA. Global PTX3 pixel fraction was higher in IIM than HDs muscle, but a lower PTX3 expression was found in perifascicular areas of DM and in myofibers with sarcolemmal staining for membrane attack complement. PTX3 plasma levels were increased in IIMs and correlated with disease activity suggesting a possible role as biomarker of disease activity. PTX3 showed a different distribution in DM or PM muscle.

POS0295 OCCURRENCE OF SERIOUS INFECTIONS IN RHEUMATOID ARTHRITIS PATIENTS CONCURRENTLY TREATED WITH A BIOLOGIC AGENT AND DENOSUMAB: A RETROSPECTIVE STUDY WITH PROPENSITY SCORE

Background

Denosumab is a monoclonal antibody used in patients with osteoporosis. It inhibits the receptor activator NF-kB ligand (RANKL), an essential cytokine mediator of osteoclastogenesis. Some concerns have been raised about Denosumab safety profile, especially when it is administered concurrently with biologic drugs for rheumatoid arthritis (RA) (1,2). Indeed, RANK and RANKL have a known immunomodulatory effect (2). In a retrospective study, Lau et al. (1) showed that patients concurrently treated with Denosumab and biologic disease modifying anti-rheumatic drugs (bDMARDs) had a higher rate of serious infections compared to patients taking bDMARDs only, but no adjustment was made for any observed imbalances in potential confounders, such as age and disease activity, between the groups.

Objectives

This study aims to evaluate, in a monocentric cohort of RA patients concurrently treated with bDMARDs and Denosumab, the safety of such combination.

Methods

We retrospectively observed RA patients on bDMARDs ± methotrexate and denosumab (DEN group) for comorbid osteoporosis and RA patients treated with bDMARDs±methotrexate (noDEN group) who started treatment in a tertiary care centre from 2015 to 2020. Clinical characteristics were gathered at baseline and at 12-month follow up. We also recorded the occurrence of serious infections between groups (defined as infections requiring hospitalization and/or parenteral antibiotics). We deployed the nearest-neighbour matching algorithm (1:4), based on Propensity Score (PS), in order to adjust for non-randomization. The McNemar’s test was used to compare the frequency of serious infection in the two groups.

Results

DEN group consisted of 36 patients were recruited, while the cohort of patients in noDEN group consisted of 547 individuals (Table 1). After PS matching only 58 patients were noDEN group, matched for disease duration, presence/absence of ACPA antibodies, baseline BMI, baseline DAS28 and daily prednisone dosage. In the matched cohort, we found an increase in terms of frequency of serious infections in DEN group, even if not statistically significant (Figure 1). All the infections were completely resolved after hospitalization and/or parenteral antibiotic treatment, without fatal events or irreversible complications. Both groups were not stratified for bDMARDs mechanism of action (MoA). Of note, in the DEN group Rituximab therapy was admnistered in 22% of patients, while in noDEN group in 12% of them.

Table 1.

Patients’ characteristics at baseline.

Av. Obs.bDMARDs OnlyAv. Obs.bDMARDs + DenosumabFemale, n (%)547466 (85.2%)3834 (89.4%)Age, y (mean±sd)54753.3±13.23863.4±11.1Disease duration, m (mean±sd)472120.2±105.338207.9±126.5DAS28, n(mean±sd)5324.55±1.39382.90±1.44PCR, mg/dL (mean±sd)5391.77±4.51380.81±1.22HAQ, n (mean±sd)5161.28±0.86381.54±0.87ACPA, n. (%)541416 (76.8%)3817 (44.7%)Figure 1.

Occurrence of serious infections at 12-months follow-up.

Conclusion

The occurrence of serious infections among RA patients receiving denosumab in combination with bDMARDs ± MTX for RA was not significantly increased compared to those receiving bDMARDs ± MTX alone at 12 months from treatment baseline. Further studies powered for detecting difference between bDMARDs MoA are necessary in order to assess the infection risk of denosumab co-administration.

References

[1]Occurrence of Serious Infection in Patients with Rheumatoid Arthritis Treated with Biologics and Denosumab Observed in a Clinical Setting. J Rheumatol. 2018 Feb;45(2):170-176. doi: 10.3899/jrheum.161270. Epub 2017 Nov 15.

[2]Is denosumab associated with an increased risk for infection in patients with low bone mineral density? A systematic review and meta-analysis of randomized controlled trials. Int J Rheum Dis. 2021 Jul;24(7):869-879. doi: 10.1111/1756-185X.14101. Epub 2021 Apr 1.

Disclosure of Interests

None declared

POS0246 SEQUENTIAL RITUXIMAB AND MEPOLIZUMAB IN EOSINOPHILIC GRANULOMATOSIS WITH POLYANGIITIS

Background

Rituximab (RTX) is an effective remission-induction treatment in ANCA-associated vasculitides (AAVs). Some reports have suggested that it might be effective also in Eosinophilic Granulomatosis with Polyangiitis (EGPA), to induce and maintain remission of vasculitic manifestations [1,2]. However, its effects for preventing respiratory relapses seem to be poor. Mepolizumab (Mepo) (both 100 and 300mg/month) is effective in improving respiratory manifestations and lung function, while partially controlling also systemic activity [3,4]. Isolated case reports further indicate that the sequential therapy with RTX and Mepo might be effective [5-7].

Objectives

The study aimed to investigate the efficacy and safety of a therapeutic regimen based on sequential RTX and Mepo for the control of EGPA.

Methods

A multicenter, retrospective, cohort study was conducted on adult patients diagnosed with EGPA according to the ACR classification criteria [8] or MIRRA trial criteria [3]. Only patients who received induction therapy with RTX (any dosage), and subsequent treatment with Mepo (100-300 mg/4 weeks) within 12 months from last RTX administration were included. Patients receiving other induction therapies between RTX and Mepo were excluded. The effectiveness of sequential RTX and Mepo was assessed in terms of disease activity (by the Birmingham Vasculitis Activity Score, BVAS) and daily corticosteroid dosage. Safety data were also collected.

Results

Thirty-four EGPA patients treated with sequential RTX and Mepo were included (59% females, median age of 51 years (IQR 40-58); 41% ANCA positive).

In most cases (26/34; 76%), RTX was started at the dosage of 1g q2w, and all except two patients had active disease at time of RTX beginning [median BVAS of 9 (IQR 6-14)]. Specifically, most patients started RTX for the control of systemic manifestations (19/34; 56%), or of both systemic and respiratory symptoms (11/34; 32%). All except one patient were receiving oral corticosteroids, at a median dosage of 25 mg/day (10-38).

Mepo was started after a median of 14 months (6-23) from RTX initiation and after a median of 5 months (IQR 3-11) from the last RTX administration. Mepo was used at the dosage of 100mg/4 weeks in 32/34 (94%), mostly for the control of respiratory manifestations (25/34, 74%). At the time of starting Mepo, the median BVAS was 4 (2-8), and median prednisolone dose 10 mg/day (7-15). After a median follow-up of 28 months (IQR 23-33) from starting Mepo, the median BVAS decreased to 1.5 (IQR 0-4) and the median corticosteroid dosage to 5 mg/day (2.5-5), with 7/34 (21%) patients being off steroids. At last follow-up, most patients were off-RTX (28/34), typically due to stable disease remission (20/34; 59%).

Both RTX and Mepo were well-tolerated; 5 patients had adverse events on RTX (none serious), and 5 on Mepo (including one serious infection).

Conclusion

Sequential use of RTX and Mepo seems to be effective for remission induction and maintenance in EGPA.

References

[1]Emmi, Ann Rheum Dis, 2018

[2]Teixeira, RMD Open, 2019 3. Wechsler, NEJM, 2017

[4]Bettiol, Arthritis Rheumatol, 2021

[5]Shiroshita, Respir Med Case Rep, 2018

[6]Higashitani, Mod Rheumatol Case Rep, 2021

[7]Afiari, Cureus 2020

[8]Masi, Arthritis Rheum, 1990

Table 1.

Effectiveness of sequential RTX and Mepo in the 34 patients included in the study

RTX beginningMepo beginningLast follow-upMedian time elapsed (IQR)-14 months (6-23) from RTX beginning28 months (23-33) from Mepo beginningDosage1g q2w (26/34);100mg/4 weeks (32/34)6 patients off Mepo; 28 patients off RTX375mg/m2 for 4 weeks (8/34)300mg/4 weeks (2/34)Reason for treatment beginning (manifestations)Systemic (19/34);Respiratory (25/34);-Systemic + respiratory (11/34);Systemic (4/34);Only respiratory (3/34);Remission maintenance (5/34)Other (1/34)BVAS (median, IQR)9 (6-14)4 (2-8)1.5 (0-4)Prednisolone dosage (median, IQR), mg/day25 (10-38)10 (7-15)5 (2.5-5)

Disclosure of Interests

Alessandra Bettiol: None declared, Maria Letizia Urban: None declared, Federica Bello: None declared, Davide Fiori: None declared, Irene Mattioli: None declared, Giuseppe Lopalco: None declared, Florenzo Iannone: None declared, Allyson Egan: None declared, Luca Moroni: None declared, Lorenzo Dagna Consultant of: Consultation honoraria from GSK outside the current work, Marco Caminati: None declared, Simone Negrini: None declared, Paolo Cameli: None declared, Marco Folci: None declared, Paola Toniati: None declared, Roberto Padoan: None declared, Oliver Flossmann: None declared, Roser Solans-Laqué: None declared, Laura Losappio: None declared, Jan Schroeder Consultant of: Advisory Board fees from AstraZeneca and GSK, Marc André: None declared, Laura Moi: None declared, paola parronchi Consultant of: Consultation honoraria from GSK and Novartis, Fabrizio Conti: None declared, Savino Sciascia: None declared, David Jayne Consultant of: Consultant for Astra-Zeneca, Aurinia, BMS, Boehringer-Ingelheim, Chemocentryx, Chugai, CSL, GSK, Infla-RX, Janssen, Novartis, Roche/Genentech, Takeda and Vifor, Augusto Vaglio Consultant of: Consultation honoraria from GSK outside the current work, Giacomo Emmi Consultant of: Consultation honoraria from GSK outside the current work

OP0266 TREATMENT DISCONTINUATION DUE TO ADVERSE EVENTS AS AN OVERALL MEASURE OF TOLERANCE AND SAFETY OF JAK-INHIBITORS: AN INTERNATIONAL COLLABORATION OF REGISTRIES OF RHEUMATOID ARTHRITIS PATIENTS (THE “JAK-pot” STUDY)

Background

The recently presented “ORAL Surveillance Study” has suggested increased risk of serious adverse events (AEs) with tofacitinib, a JAK-inhibitor (JAKi), compared to a comparator TNF-inhibitor (TNFi). Currently, there is limited real world evidence for the tolerability and safety of JAKi (1).

Objectives

To assess the safety of JAKi compared to other biologic agents in rheumatoid arthritis (RA) patients in a real-world population, by evaluating treatment discontinuation for AEs.

Methods

Pooled patient database from 16 national RA registries from across Europe, Québec (Canada), Turkey, and Israel were used. Treatment discontinuation due to AEs by treatment groups, JAKi versus (vs) TNFi and JAKi vs bDMARDs with other modes of action (OMA), were compared as an overall measure of tolerability and safety of JAKi. Standard descriptive statistics were used for baseline characteristics. We plotted unadjusted cumulative incidence, then the cause-specific Cox model was used to account for competing risks, and to obtain association between covariates and the instantaneous hazard rate for AEs. Variables listed in Table 1 were used for adjustment in the fully-adjusted cause-specific Cox model.

Table 1.

Baseline characteristics of the study population

JAKi1(BARI, FILGO,TOFA,UPA)OMA2(ABA, ANAK, SARI, TOCI)TNFi3(ADA, CERT, ETAN, GOL, INFL)n = 9208n = 16737n = 64533Treatment duration* (yrs)0.7 [0.2, 1.7]1.1 [0.4, 2.8]1.5 [0.5, 3.9]Age57.556.853.2Female (%)81.380.773.2Disease duration (yrs)9.913.110.7Seropositivity (%)78.775.969.8Previous b/tsDMARD (%) 034.030.859.7 120.925.924.3 216.621.710.4 3 or more28.521.55.6Concomitant GC (%)44.650.741.3Concomitant CsDMARD (%)  MTX22.622.028.8  MTX + other9.59.713.1  None50.552.543.5  Other17.415.914.7CRP13.2 (24.1)13.3 (25.6)12.3 (24.1)CDAI23.7 (13.8)22.9 (13.5)22.6 (14.0)DAS 284.7 (1.5)4.7 (1.6)4.6 (1.6)HAQ1.2 (0.7)1.2 (0.7)1.1 (0.7)BMI27.1 (5.9)26.8 (5.8)26.8 (5.8)Patients with at least one Comorbidity (%)51.753.949.6

csDMARDs = classical synthetic DMARDs, MTX = methotrexate, GC = glucocorticoids, CRP = C-reactive protein, CDAI = Clinical Disease Activity Index, DAS 28 = Disease Activity Score 28, HAQ = Health Assessment Questionnaire, BMI = Body Mass Index, *Treatment duration (median [IQR]) = Last visit date – start date (if treatment is ongoing), treatment stop date – treatment start date (if treatment has stopped)

. 1BARI (baricitinib; 44.41 %), FILGO (filgotinib; 0.23%), TOFA (tofacitinib; 49.59%), UPA (upadacitinib; 5.78%); 2ABA (abatacept; 39.96%), ANAK (anakinra; 2.64%), SARI (sarilumab; 3.14%), TOCI (tocilizumab; 52.55%); 3ADA (adalimumab; 31.00%), CERT (certolizumab; 8.33%), ETAN (etanercept; 38.83%), GOLI (golimumab; 9.36%), INFL (infliximab; 12.56%)

Results

90,478 treatment courses were included in the analysis (Table 1). We observed similar crude incidence rate of treatment discontinuation due to AEs between JAKi and TNFi, but less in JAKi vs OMA (Figure 1). The fully adjusted hazard rate of treatment stop for AEs was also similar in JAKi vs TNFi (HR = 1.02 (95% CI 0.92 – 1.13)), and in JAKi vs OMA (HR= 1.08 (95% CI 0.97 – 1.20)). The rate of treatment stop for AEs was higher in women (HR = 1.29 (95% CI 1.21 – 1.37)) and with an increasing number of previous b/tsDMARDs (HR = 1.50; 1.48; 1.68 for 1, 2, and 3 or more previous b/ts DMARDs, respectively).

Figure 1.

Comparison of cumulative incidence of treatment discontinuation for adverse events in JAKi, TNFi, and OMA group

Conclusion

After adjusting for potential confounders, the rate of treatment discontinuation for AEs was comparable between JAKi and OMA or TNFi. Treatment discontinuation for AEs comprises a wide range of AEs; future analyses will be performed to investigate specific AEs, such as cancer, serious infections or major adverse cardiovascular events.

References

[1]Ann Rheum Dis 2022. doi: 10.1136/annrheumdis-2021-221915.

Disclosure of Interests

Eric Nham: None declared, Romain Aymon: None declared, Denis Mongin: None declared, Sytske Anne Bergstra: None declared, Denis Choquette Speakers bureau: DC reports speaker or consultant fees from Abbvie, Amgen, Eli Lilly, Fresenius-Kabi,Pfizer, Novartis, Sandoz, Tevapharm, Consultant of: Stated above, Catalin Codreanu Speakers bureau: CC reports speaker/consulting fees from AbbVie, Amgen, Astra Zeneca, Boehringer Ingelheim, Ewopharma, Lilly, Novartis, Pfizer, Richter, Consultant of: Stated above, Ori Elkayam Consultant of: OE has received consultant and honorary fees from Pfizer, Lilly, Abbvie, Novartis, Jansen, BI, Kimme Hyrich Speakers bureau: KLH has received speaker honoraria from Abbvie, Grant/research support from: KLH has received grant income from Pfizer and BMS, Florenzo Iannone Speakers bureau: FI has received consulting/speaker’s fees from Abbvie, BMS, Celgene, Eli Lilly, Galapagos, Janssen, MSD, Novartis, Pfizer, SOBI, Roche and UCB, Consultant of: Stated above, Nevsun Inanc Speakers bureau: NI has received consultant and speaker/honoraria from Abbvie, Lilly, MSD, Novartis, Pfizer, Roche, Amgen, Celltrion,UCB., Consultant of: Stated above, Lianne Kearsley-Fleet: None declared, Eirik kristianslund: None declared, Tore K. Kvien Speakers bureau: TKK has received fees for speaking and/or consulting from several companies among them Pfizer, AbbVie, Lilly and Galapagos/Gilead, Consultant of: Stated above, Burkhard Leeb Speakers bureau: BFL has received speaker honoraria from Sandoz, Abbvie, Eli-Lilly, Pfizer, Roche, Grünenthal, Biogen, Celgene, Galina Lukina Speakers bureau: GVL has received speaker fees from Abbvie, Lilly, Novartis, MSD, Roche, Pfizer, Dan Nordström Consultant of: DCN has acted as consultant for AbbVie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Karel Pavelka Speakers bureau: KP has received honoraria for lectures: MSD, Pfizer, Roche, Eli Lilly, Medac, UCB, SOBI, Biogen, Sandoz, Viatris, Manuel Pombo-Suarez Speakers bureau: MPS reports advisor and speaker honoraria from Janssen, Lilly, MSD, Novartis, Sanofi, Consultant of: Stated above, Ziga Rotar Speakers bureau: ZR has received fees for speaking/consulting from several companies among them Pfizer, AbbVie, and Eli Lilly, Consultant of: Stated above, Maria Jose Santos Speakers bureau: MJS has received speaker fees from Abbvie, AstraZeneca, Lilly, Novartis and Pfizer, Delphine Courvoisier: None declared, Kim Lauper Speakers bureau: KL reports speakers fees for Pfizer, Viatris and Celltrion, Consultant of: KL reports consulting fees for Pfizer, Axel Finckh Speakers bureau: AF reports honoraria and consultancies from Pfizer, BMS, MSD, Eli-Lilly, AbbVie, Galapagos, Mylan, UCB, Viatris, Consultant of: Stated above, Grant/research support from: AF reports grants from Pfizer INC, AbbVie, Galapagos, Eli Lilly

AB0134 IN-VITRO STUDY ON THE EFFECT OF SELECTIVE Jak-INHIBITORS ON PBMCs STAT3 PHOSPHORYLATION FROM SYSTEMIC SCLEROSIS PATIENTS

Background

Systemic sclerosis (SSc) is a rare autoimmune connective tissue disease characterized by autoimmunity-driven damage and vasculopathy leading to fibrosis of the skin and internal organs (1). The Janus kinase (Jak) - signal transducer and activator of transcription (STAT) pathway has been evidenced markedly activated in SSc patients (2, 3), and its inhibition has been proved in preclinical and clinical trials (4), but no data on Jak selective inhibition are available.

Objectives

To explore the effect of selective inhibition of Jak/STAT pathway in peripheral blood mononuclear cells (PBMC) from SSc patients.

Methods

In vitro Jak inhibition of the subunit 3 of phosphorylated (p) than activated STAT was measured by flow cytometry in peripheral blood mononuclear cells (PBMC) from SSc patients naïve to any immunosuppressive and/or corticosteroids (n.5). pSTAT3 activity was also assessed after stimulation with recombinant human 0.1 ng/ml IL-6 (Peprotech – NJ, USA). The PBMC were overnight incubated with IC50 concentrations of selective Jak1-, Jak2-, Jak3- and Tyk2-inhibitors (Biovision Inc. – CA, USA). Percentages of pSTAT3 positive cells were compared in presence of different compounds stimulation.

Results

After overnight incubation, percentage of pSTAT3 positive cells was significantly higher in CD14pos compared to CD4pos (16.3%; 95CI 10-22 vs 10.7%; 95CI 4--18, – p=0.02). pSTAT3posCD14pos cells were halved only by selective Jak3-inhibitor, while pSTAT3posCD4pos cells were reduced by 36% by selective Jak1-inhibitor. Selective Jak2- or Tyk2-inhibitors did not interfere with STAT3 phosphorylation in PBMC from SSc patients. After IL-6 stimulation, we observed a 2- and a 1.5-fold increase in percentage of pSTAT3posCD4pos and pSTAT3posCD14pos cells, respectively. pSTAT3posCD14pos cells were reduced in the PBMC co-culture with IL-6 and Jak-selective inhibitors, in contrast no effects were found in CD4pos cells. Specifically, selective Jak1- and Jak3-inhibitors reduced pSTAT3posCD14pos cells by an average of 37% and 25%, respectively. No effects were observed after co-culture with IL-6 and selective Jak2- or Tyk2-inhibitors.

Conclusion

Jak/STAT3 pathway of PBMC from SSc patients with active disease may be differently modulated by specific inhibitors. Selectivity of Jak1- and Jak3-inhibitors seems more relevant, especially in CD14pos monocytes after IL-6 stimulation. These preliminary findings highlight some evidence for effectiveness of selective Jak-inhibitors in SSc treatment.

References

[1]Benfaremo D, et al. Systemic Sclerosis: From Pathophysiology to Novel Therapeutic Approaches. Biomedicines. 2022;10(1):163.

[2]Talotta R. The rationale for targeting the JAK/STAT pathway in scleroderma-associated interstitial lung disease. Immunotherapy. 2021;13(3):241-256.

[3]Cacciapaglia F, et al. Phosphorylated signal transducer and activator of transcription 3 (pSTAT3) is highly expressed in CD14+ circulating cells of scleroderma patients. Rheumatology (Oxford). 2020;59(6):1442-1444.

[4]Karalilova RV, et al. Tofacitinib in the treatment of skin and musculoskeletal involvement in patients with systemic sclerosis, evaluated by ultrasound. Rheumatol Int. 2021;41(10):1743-1753.

Disclosure of Interests

None declared

AB0344 EFFICACY OF SUBCUTANEOUS INFLIXIMAB (CT-P13 SC) COMPARED WITH INTRAVENOUS INFLIXIMAB IN RHEUMATOID ARTHRITIS: A POST-HOC ANALYSIS OF A PHASE 3 RANDOMIZED CONTROLLED TRIAL

Background

Subcutaneous (SC) CT-P13 is the first and only subcutaneous formulation of infliximab (IFX) approved by the EMA.1 In the pivotal study (NCT03147248), non-inferiority of SC IFX to intravenous (IV) was demonstrated in rheumatoid arthritis (RA) patients using 28-joint Disease Activity Score (DAS28) C-reactive protein (CRP) improvement at Week 22, with a statistically significant treatment difference of 0.27 (95% CI 0.02, 0.52) favoring the SC versus the IV arm.2,3 At Week 30, numerical differences in efficacy outcomes were shown between SC and IV IFX favoring SC IFX. IV group patients switched to SC IFX by Week 30, and the difference between the groups was reduced at Week 54.2

Objectives

To investigate whether there was a statistically significant difference between SC and IV IFX at Weeks 30 and 54 in the phase 3 pivotal study of CT-P13 SC using conservative missing imputation methods.

Methods

Patients with active RA who had an inadequate response to MTX received IV IFX 3mg/kg at Weeks 0 and 2 for induction and were randomized at a 1:1 ratio to receive SC IFX 120mg every 2 weeks or IV 3mg/kg every 8 weeks thereafter for maintenance. Patients who were randomized to receive IV IFX switched to SC at Week 30. In this post-hoc analysis, non-responder imputation (NRI) and last observation carried forward (LOCF) methods were used to investigate whether the difference in efficacy outcomes between SC and IV IFX at Weeks 30 and 54 was statistically significant. Assessments included EULAR (CRP/ESR)/ACR response; remission rate and low disease activity (LDA) rate based on DAS28 (CRP/ESR), Clinical Disease Activity Index (CDAI) and Simplified Disease Activity Index (SDAI); Boolean remission rate; and the proportion of patients achieving a minimal clinically important difference (MCID) in Health Assessment Questionnaire (HAQ).

Results

Of the 343 randomized patients, 165 patients who received SC IFX and 174 patients who received IV IFX from the efficacy population were included in the analysis. There was a statistically significant difference in SC IFX compared to IV treated patients at Week 30 using both NRI and LOCF methods in almost all the clinical variables. However, the difference in efficacy outcomes between SC IFX and IV was reduced at Week 54 after the IV group switched to SC. This supports the improved efficacy of SC IFX at Week 30. Some of the key results (EULAR [CRP] responses, LDA rates based on DAS28 [CRP], CDAI, and SDAI) were presented in Figure 1. Analysis using LOCF and NRI methods yielded consistent results across most of the efficacy outcomes.

Figure 1.

Comparison of clinical outcomes between SC IFX and IV IFX in patients with active rheumatoid arthritis.

*P<0.05.

P-value for difference in proportion between SC and IV treatment group was obtained by asymptotic Wald test.

Low disease activity based on DAS28 (CRP) (< 3.2), CDAI (eatment group AI (≤ 11.0).

Conclusion

Statistical analyses using conservative missing imputation methods showed significantly greater improvements in clinical outcomes with SC IFX compared to IV at Week 30 in patients with RA. Between-group differences was reduced at Week 54, suggesting improved responses after switching from IV to SC.

References

[1]Remsima summary of product characteristics. https://www.ema.europa.eu/en/documents/product-information/remsima-epar-product-information_en.pdf. Published 2021. Accessed 10 January 2022.

[2]Westhovens R, Wiland P, Zawadzki M, et al. Efficacy, pharmacokinetics and safety of subcutaneous versus intravenous CT-P13 in rheumatoid arthritis: a randomized phase I/III trial. Rheumatology (Oxford). 2021;60(5):2277-2287.

[3]Combe B, Allanore Y, Alten R, et al. Comparative efficacy of subcutaneous (CT-P13) and intravenous infliximab in adult patients with rheumatoid arthritis: a network meta-regression of individual patient data from two randomised trials. Arthritis Res Ther. 2021;23(1):119.

Disclosure of Interests

Arnaud Constantin Speakers bureau: Abbvie, Amgen, Boehringer, Celltrion, Galapagos, Janssen, Lilly, Novartis, Sanofi, UCB, Consultant of: Abbvie, Amgen, Boehringer, Celltrion, Galapagos, Janssen, Lilly, Novartis, Sanofi, UCB, Roberto Caporali Speakers bureau: Abbvie, Amgen, BMS, Celltrion, Galapagos, Lilly, Pfizer, Fresenius-Kabi, MSD, UCB, Roche,Janssen, Novartis, Sandoz, Consultant of: Abbvie, Amgen, BMS, Celltrion, Galapagos, Lilly, Pfizer, MSD, UCB, Janssen, Novartis, Sandoz, Christopher John Edwards Speakers bureau: Abbvie, Astra Zeneca, Celltrion, Chugai, Fresenius, Galapagos, Gilead, GSK, Lilly, Janssen, Pfizer, Roche, Consultant of: Abbvie, Astra Zeneca, Chugai, Galapagos, Gilead, GSK, Lilly, Janssen, Pfizer, Roche, Grant/research support from: Celltrion, Pfizer, Abbvie, Joao Eurico Fonseca Speakers bureau: Abbvie, Ache, Janssen, Lilly, Medac, Novartis, Pfizer, Consultant of: Abbvie, Celltrion, Janssen, Lilly, Pfizer, Grant/research support from: Abbvie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, Florenzo Iannone Speakers bureau: Abbvie, BMS, Celltrion, Galapagos, MSD, Eli-Lilly, Janssen, Novartis, Pfizer, UCB, Consultant of: Abbvie, BMS, Celltrion, Galapagos, MSD, Eli-Lilly, Janssen, Pfizer, Grant/research support from: BMS, MSD, Edward Keystone Speakers bureau: Amgen, AbbVie, Celltrion, F. Hoffmann-La Roche Inc., Janssen Inc., Merck, Pfizer Pharmaceuticals, Sandoz, Sanofi Genzyme, Consultant of: AbbVie, Amgen, Celltrion, Myriad Autoimmune, F. Hoffmann-La Roche Inc, Janssen Inc, Lilly Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, Sanofi-Genzyme, Samsung Bioepsis, Grant/research support from: Amgen, Merck, Pfizer Pharmaceuticals, Hendrik Schulze-Koops Consultant of: Celltrion, Taeksang Kwon Employee of: Celltrion Healthcare, Seungmin Kim Employee of: Celltrion Healthcare, Sangwook Yoon Employee of: Celltrion Healthcare, Dong-Hyeon Kim Employee of: Celltrion Healthcare, Gahee Park Employee of: Celltrion Inc., DaeHyun Yoo Speakers bureau: Celltrion, Celltrion Healthcare

AB0631 Impact of Behçet’s Syndrome on work activity and productivity: results from a sub-analysis of the BODI Project cohort

Background

Behçet’s Syndrome (BS) is a multisystem recurring inflammatory disorder characterised by a wide spectrum of clinical manifestations, which can vary from limited mucocutaneous lesions up to severe and even life-threatening events.

Objectives

To evaluate the impact of BS on the patients’ work activity and productivity.

Methods

A sub-cohort of 148 patients from the original Behçet’s syndrome Overall Damage Index (BODI) Project study was enrolled. The Work Productivity and Activity Impairment: General Health (WPAI:GH) questionnaire was administered. Demographics, disease duration, comorbidity, major organ involvement, ongoing therapy, Behçet's Disease Current Activity Form (BDCAF), Physician Global Assessment (PGA), Patient Global Assessment (PtGA), and the BODI were recorded. Multiple regression models were built to investigate the independent effect of BS features on WPAI.

Results

Overall, 97 (65.6%) out of 148 patients who completed the WPAI:GH questionnaire resulted working for pay; 22 out of 97 (27.8%) patients reported missing work in the past week due to their health, accounting for a mean (SD) of 34.4% (17.8) of their working time (absenteeism). The only factor significantly associated with absenteeism in multivariate analysis was the presence of ocular damage, as assessed by the BODI (β 0.255, p = 0.027).

Although 93 patients reported that they worked in the previous week, mean 27.3% (30.7) of their actual work productivity was impaired due to their health problem (presenteeism), with only 37 (38.5%) patients reporting no such loss. Factors associated with work impairment were female gender (β 0.319, p = 0.001), higher PtGA (β 0.298, p = 0.002), and an increased BODI score in the last 2 years follow-up (β 0.212 for one-point increased BODI score, p = 0.024).

Finally, 99 (66.9%) of the total 148 patients complained of a daily activity impairment, reporting that a mean of 33.3% (30.6) of their regular daily activities had been prevented due to their health problems. Factors significantly associated with patients’ daily activity impairment were younger age at enrolment (β 0.187, p = 0.021), higher BDCAF disease activity (β 0.235, p = 0.002) and fibromyalgia (β 0.324, p = 0.033).

Conclusion

BS can lead to missing work time and significantly affect both the patient’s work productivity and daily activities. Active disease seems to be one of the major determinants together with a higher burden of damage and the association of some specific comorbidities, such as fibromyalgia.

Table 1.

WPAI:GH questionnaire results

Variablesn°Mean (SD)All patients148Patients working for pay97Percent work time missed due to health977.9 (21.7)Percent work time missed due to health (patients with missed time >0) *2234.4 (17.8)Patients who actually worked in the past seven days**93Percent impairment while working due to health9327.3 (30.7)Percent impairment while working due to health (pts with % impairment while working > 0) ***5645.4 (27.2)Percent activity impairment due to health14833.3 (30.6)Percent activity impairment due to health (those with % activity impairment >0)9949.8 (23.9)

* Patients working for pay who missed at least on hour of work, 22/97 = 22.7%.

** Patients working for pay, but who worked for > 0 hours in the last week = 93/97

*** Patients with impairment while working > 0 among patients who actually worked in the previous 7 day = 56/93.

Disclosure of Interests

None declared

AB1184 SAFETY PROFILE OF SARS COV-2 VACCINES IN PATIENTS WITH CONNECTIVE TISSUE DISEASE, VASCULITIS AND POLYMYALGIA RHEUMATICA. BI-CENTRIC STUDY

Background

In recent times, safety and potential adverse effects (AEs) of Sars-CoV-2 vaccines have gained great relevance and have been a central topic in scientific discussion.

Objectives

The aim of this study was to evaluate the incidence of AEs after Sars-CoV-2 vaccine administration in patients affected by Connective Tissue Disease, Vasculitis or Polymyalgia Rheumatica. Moreover, we assessed patients’ adherence to the American College of Rheumatology (ACR)1 or Italian Rheumatology Society (SIR)2 recommendations.

Methods

139 patients affected by Connective Tissue Disease, Vasculitis or Polymyalgia Rheumatica were enrolled at the Rheumatology Units of University Hospitals of Bari and Foggia. All patients were given a questionnaire to evaluate vaccine type and dose number, AEs, potential pre-vaccine prophylaxis, immunosuppressive therapy and its possible suspension according to the clinical guidance summary proposed by ACR or SIR.

Results

Among the 139 enrolled patients (120 females and 19 males, mean age 54 ± 14,7 year, mean disease duration 8,6 ± 7,4 years), 31 subjects (19%) received anti Sars-CoV-2 vaccination. 5 patients received the AstraZeneca COVID-19 vaccine, 23 the BioNTech-Pfizer COVID-19 vaccine and 3 the Moderna vaccine. Only 48% of subjects received two doses. 42% of patients reported non-severe AEs after the first dose of vaccine, specifically 45% of patients who received the BioNTech-Pfizer COVID-19 vaccine, 40% of those who were administered the AstraZeneca vaccine and 33% of those who received the Moderna vaccine. Most frequent AEs were site injection pain (19%), fatigue (13%), headache (13%), myalgia (6%), fever (6%), nausea (3%), rheumatic disease flare (3%) (the latest was reported only among the Polymyalgia Rheumatica patients). Considering the different diseases, the highest trend of AEs was observed in Polymialgya Rheumatica (66%), Systemic Sclerosis (57%), Sjogren Syndrome (40%) and undifferentiated connective tissue disease (23%) patients. 30% of patients who received the second vaccine dose reported AEs. All of them were administered the BioNTech-Pfizer COVID-19 vaccine. Most reported AEs after the second vaccine dose were site injection pain (6%), headache (3%), myalgia (6%), fever (6%). The highest trend of AEs was observed in undifferentiated connective tissue disease (60%) and Sjogren Syndrome (33%) patients. Only 13 % of subjects who reported AEs after the first vaccine administration, reported AEs also after the second dose. Only 9,7% of patients did not comply with the COVID-19 vaccine clinical guidance prosed by ACR or SIR regarding immunosuppressive treatment management before and after immunization.

Conclusion

Patients enrolled in this study developed mild AEs. Only among Polymyalgia Rheumatica patients were described disease flares and higher trend of AEs. Although patients affected by Systemic Lupus Erythematosus, Antiphospholipid Syndrome and Vasculitis were enrolled, none of them reported severe AEs, included the extensively discussed post-vaccine thrombosis. We found no significant dissimilarity of AEs relating to different types of vaccine and good patient compliance to physician recommendations about treatment management.

References

[1]Curtis JR, Johnson SR, Anthony DD, Arasaratnam RJ, Baden LR, Bass AR, et al. American College of Rheumatology Guidance for COVID-19 Vaccination in Patients with Rheumatic and Musculoskeletal Diseases – Version 1. Arthritis Rheumatol 2021.

[2]A proposito della vaccinazione anti SARS-COV 2 nei pazienti reumatologici (aggiornamento del 13.03.2021).

Disclosure of Interests

None declared

POS0928 THE IDENTIFICATION OF PENTRAXIN 3 AS BIOMARKER OF DISEASE ACTIVITY IN IDIOPATHIC INFLAMMATORY MYOPATHIES

Background

Muscle involvement is only one feature of idiopathic inflammatory myopathies (IIM). Muscle enzymes do not always represent the best marker of disease activity and other inflammation markers such as ESR and CRP may be normal even with an active disease. Pentraxin-3 (PTX3) is an inflammatory marker produced in many inflammatory and non-inflammatory cells and serum level has been related to higher risk of major cardiovascular events and atherosclerosis1. PTX3 levels have been examined in various rheumatic and autoimmune diseases2, but data of PTX3 levels in patients affected with IIM have not been reported.

Objectives

The aim of the current study was to identify whether serum PTX3 level could be a marker of disease activity in patients affected with IIM.

Methods

Twenty patients affected with IIM (13 Dermatomyositis and 7 Polymyositis), 10 rheumatoid arthritis patients and 10 healthy controls (HC) aged, sex and BMI matched were evaluated. PTX3 levels was assessed using a commercially available enzyme-linked immunosorbent assay (Human Pentraxin3 ELISA Kit, Abcam) kit. Three different cardiovascular risk scores were used to estimate the 10-years CV risk. Carotid intima media thickness (cIMT) was measured with a My Lab XPro80 (Esaote SpA, Genova, Italy) using a linear array ultrasound probe small parts broadband transducer (5–15 MHz) both in right and left carotid. Myositis disease activity was evaluated by using myositis disease activity assessment visual analog scales (MYOACT) [19] established by the International Myositis Assessment and Clinical Studies (IMACS) group. Manual muscle test (MMT8) was used to assess muscle impairment. Exclusion criteria were a diagnosis of diabetes or a history of previous major CV events.

Results

Demographic and disease characteristics of our cohort are showed in Table 1. IIM patients showed higher levels of PTX3 compared to HCs (518±260 pg/ml vs 275±114 pg/ml, p<0.05), while no difference was observed compared to RA patients (383±260 pg/ml). PTX3 levels do not correlate with lipid levels, QIMT and cardiovascular risk scores both in IIM, RA and HC. No correlation was found between DAS28-ESR and PTX3 levels in RA patients. Of note, a direct correlation was found between PTX3 levels and MYOACT-GLOBAL DISEASE ACTIVITY (r=0.675, p=0.002), PTX3 levels and MYOACT- GLOBAL-EXTRA-SKELETAL MUSCLE DISEASE ACTIVITY (r=0.542, p=0.013), while an inverse correlation was found between PTX3 levels and MMT8 (r=-0.510, p=0.02).

Table 1.IIM 20pz (13 DM, 7 PM)RA 10pzHealthy Control 10pzFemale, n. (%)18 (90%)9 (90%)9 (90%)Age55,3 (7,8)58,3 (5,9)54,6 (6,5)BMI25,5 (4,1)23,9 (3,1)24,6 (3,5)Duration of disease, median (IQR)7,3 (4 – 12,8)13,5 (10,5 – 18,5)*Physician Global Assessment2,1 (2,1)2 (2,2)Patient Global Assessment4 (3,6)2,7 (2,3)Health Assessment Questionnaire0,7 (0,8)0,9 (0,9)Manual Muscle Testing 876,2 (6,6)DAS282,6 (1,1)Skin involvement, n. (%)13 (65)Lung involvement, n. (%)7 (35)Dysphagia, n. (%)11 (55)Arthritis, n. (%)4 (20)Malignancies, n. (%)0 (0)0 (0)0 (0)Arterial hypertension, n. (%)6 (30)2 (20)1 (10)Current steroid therapy2,5 (0 – 5)0 (0 – 3,8)Smoking, n. (%)6 (30)2 (20)3 (30)Total cholesterol, mg/dl203,3 (28,6)215,0 (29,5)216,2 (27,3)HDL cholesterol, mg/dl62,7 (14,7)62,6 (14,2)65,1 (18,2)ESR, mm/h16,7 (12,2)19 (11,7)PCR, mg/l2,9 (2,1)4,1 (5)SCORE median (IQR)0,5 (0 – 2)1 (0 – 3)1 (0,8 – 1,3)CUORE median (IQR)1,9 (0,6 – 3,5)1,6 (1 – 4)1,7 (1,2 – 2,8)QRISK3 median (IQR)4,7 (2,1 – 11,3)7,5 (3,2 – 13,6)4,2 (3,1 – 5,5)QIMT Max, median (IQR)742,5 (636,8 – 804)833 (685,3 – 961) *756 (711 – 820)Mean QIMT, median (IQR)679 (613,1 – 736,3)764,3 (664,5 – 854,1) *703,3 (697,3 – 742,8)Pentraxin 3, pg/ml518 (260)383 (146)275 (114)*

Data are expressed as “mean (SD)” where not otherwise specified.

*p<0.05, **p<0.01, ***p<0.001 vs IIM

Conclusion

In IIM patients, PTX3 levels are higher than HC and correlate with disease activity, both for muscular and extra-muscular manifestations, being a possible biomarkers of disease activity.

References

[1]Front Immunol. 2019; 10: 823

[2]Arch Med Sci. 2020; 16(1): 81–86

Disclosure of Interests

None declared

AB0920 Safety of Apremilast in PsA patients with history of malignancies or active cancer: a retrospective study

Background

One of the most intriguing aspects in the management of patients with inflammatory arthritis is the safety of novel therapies in those with a recent history of malignancy or active neoplasm. In this regard, apremilast (APR), an oral PDE4 inhibitor, is emerging as one of the safest therapeutic options in patients with PsA with comorbid cancer.

Objectives

This retrospective study aims to assess the effectiveness and safety of APR in PsA patients with a recent history of malignancy or active cancer.

Methods

We retrospectively observed patients with a history of neoplasm diagnosed from 1997 to 2021, who underwent apremilast treatment from 2017 to 2021 in a tertiary care centre. We recorded demographic and clinical characteristics at APR baseline and last visit. Furthermore, we recorded the eventual recurrence of primary cancer or the onset of new neoplasms. Paired t-test was used to assess the difference of continuous variables at different follow-ups.

Results

Thirteen patients (sex: female 6/13, 46,15%; mean age (mean ± 63,7 years sd ± 9,9 years)) started Apremilast between 2017 to 2021 in a tertiary care center. We assessed their clinical condition using DAPSA, LEI and PASI score in the baseline and in the last visit. Mean follow-up time was 32,02 ± 18,92 months.

Mean DAPSA at baseline 20,55 ± 9,15 decreased to 16,21 ± 1,73 at last visit. Similarly mean LEI at baseline was 1,23 ± 1,58 and decreased to 0,61 ± 0,35 at last visit, even in absence of statistical significance (p=0,15). Conversely mean PASI at baseline (1,76 ± 2,57) did not show a decrease (1,61 ± 0,93);

Ten patients were still treated with apremilast at last available follow-up. Patient 6 (Table 1) experienced the relapse of Ductal Breast Papilloma. For patient 8, a relapse of primary cancer occurred. Patient 9 had the onset of a new neoplasm. The APR was not discontinued as such malignancies were not considered as treatment associated.

Three patients (4, 6, 10) discontinued APR due to intolerance or lack of efficacy.

Conclusion

APR seems a safe option in PsA patients with a recent history of malignancy or active cancer, improving articular involvement.

Disclosure of Interests

None declared

POS1062 HARNESSING THE POWER OF MACHINE LEARNING TO PREDICT REMISSION IN PATIENTS WITH PSORIATIC ARTHRITIS ON SECUKINUMAB: IMPLEMENTATION AND VALIDATION OF A CANDIDATE ALGORITHM ON 121 PATIENTS

Background

Although novel therapies with biotechnological agents and small molecules may lead to the complete clearing of psoriasis in the vast majority of patients, the latter drugs only allow Psoriatic Arthritis (PsA) disease control in up to 50% of patients (1). In an increasing number of clinical scenarios, machine learning (ML) is emerging as a tool for the implementation of multi-parametric decision algorithms. ML allows to handle complex non-linear relationships between patient attributes that are hard to model with traditional statistical methods, merging them to output a forecast or a probability for a given outcome, enabling personalized medicine (2).

Objectives

We aimed to develop a ML algorithm capable of predicting the probability of remission in PsA patients on Secukinumab to support clinicians in choosing the optimal treatment strategy.

Methods

Patients with classified PsA according to CASPAR criteria undergoing Secukinumab treatment between September 2017 and September 2020 at our tertiary Centre were retrospectively observed.Either at treatment baseline and at 12-month follow up, we retrieved demographic and clinical characteristics, including Body Mass Index (BMI), disease phenotypes, Disease Activity in PsA (DAPSA), Leeds Enthesitis Index (LEI) and Ankylosing Spondylitis Disease Activity Score (ASDAS, on C-Reactive Protein). After a ML variable selection method, based on an eXtreme Gradient Boosting (XGBoost) wrapper, an attribute core set with the least number of predictors was used for implementing n.3 ML algorithms, namely Logistic Regression (LR), Decision Trees (DT) and XGBoost. Each algorithm was trained and validated with 10-fold cross-validation. The performance of each algorithm in both phases was assessed in terms of of accuracy and area under receiver operating characteristic curve (AUROC).

Results

The dataset consisted of n.121 PsA patients (62/121 female, 51.2%), with mean age (±SD) 52.9±10.1 years and mean disease duration of 5.9 ±10.4 years. Twenty-five of them (20.7%) had axial involvement whereas 88/121 (72.7%) had polyarticular involvement. Psoriasis was present in 84/121 patients (69.4%). At baseline, mean DAPSA was 14.9 ± 9.2, mean HAQ-DI 1.1 ± 0.7, mean LEI 0.6 ± 1, mean ASDAS 2.5 ± 0.8, mean PASI 2 ± 2.9, mean BMI 28.4 ± 4.9 . Secukinumab at 300 mg dose was administered to 79/121 patients (65.3%). At 12 months DAPSA remission was achieved by 24/121 patients (19.8%). Accuracy of LR, DT and XGBoost was of 0.70 ± 0.11, 0.81 ± 0.07 and 0.89 ± 0.05, respectively. Consistently AUROC (Figure 1 Panels ABC) were 0.63 ± 0.2, 0.79 ± 0.2 and 0.93 ± 0.1, respectively. A sample decision tree explaining XGBoost algorithm function has been provided (Figure 1 Panel D). LEI and DAPSA at baseline were shown as the most important attributes for such algorithm (Figure 1 Panel E).

Figure 1.

Conclusion

ML can support Rheumatologists in profiling those patients more likely to respond to Secukinumab.

References

[1]Scher JU, Ogdie A, Merola JF, Ritchlin C. Preventing psoriatic arthritis: focusing on patients with psoriasis at increased risk of transition. Nat Rev Rheumatol. 2019 Mar;15(3):153-166. doi: 10.1038/s41584-019-0175-0.

[2]Venerito V, Angelini O, Cazzato G, Lopalco G, Maiorano E, Cimmino A, Iannone F. A convolutional neural network with transfer learning for automatic discrimination between low and high-grade synovitis: a pilot study. Intern Emerg Med. 2021 Sep;16(6):1457-1465. doi: 10.1007/s11739-020-02583-x. Epub 2021 Jan 2.

Disclosure of Interests

Vincenzo Venerito Speakers bureau: Abbvie, Paid instructor for: Pfizer, Lilly, Marco Fornaro: None declared, Fabio Cacciapaglia Speakers bureau: Lilly, Abbvie, BMS. Pfizer, Paid instructor for: Lilly, Sabina Tangaro: None declared, Giuseppe Lopalco Speakers bureau: SOBI NOVARTIS BMS ABBVIE, Paid instructor for: PFIZER, Florenzo Iannone Speakers bureau: Abbvie Pfizer UCB BMS Galapagos Novartis Lilly SOBI ROCHE, Paid instructor for: pfizer

AB0636 Relationship between organ damage and impairment of health-related quality of life in patients with Behçet’s Syndrome: results from a longitudinal extension of the BODI Project

Background

Preventing accrual of organ damage represents a primary goal in the treatment of Behçet’s Syndrome (BS), as it may result in impairment of other outcomes, including the health-related quality of life (HR-QoL).

Objectives

The objective of this study was to investigate whether the recent accrual of organ damage, rather than its extent at a single time point, correlate with an impairment of the HR-QoL.

Methods

A sub-analysis of data from patients recruited in the longitudinal phase of the BODI Project validation cohort was performed. The HR-QoL and damage were measured by the Short-form 36 questionnaire (SF-36) and the BS Overall Damage Index (BODI), respectively, at the baseline visit and at a follow-up (FU) 24 ±3 months later. Then the possible increase of damage over FU was assessed by calculating the difference between the BODI score (Δ-BODI) in the two visits. Then, the relationship between the Δ-BODI and the individual and summary domains of the SF-36 was analysed by building multivariate regression models, including age, gender, concomitant fibromyalgia and/or depression, current disease activity as assessed by the BDCAF, as confounding variables.

Results

From the BODI validation cohort, 147 patients were recruitable for this sub-analysis;73 (49.8%) were males. The mean (SD) age and disease duration at enrolment were, respectively, 46.2 (12.4) and 13.4 (10.1) years. BODI score did not influence the SF-36 domains assessed at the baseline visit. In contrast, a significant correlation was recorded between the Δ-BODI and the following SF-36 domains: physical function (PF) (β -0.158 for 1 unit increase in BODI score, p 0.025), role physical (RP) (β -0.150, p 0.044), general health (GH) (β -0.199, p 0.004), role emotional (RE) (β -0.180, p 0.001), mental health (MH) (β -0.244, p 0.001), and the mental components summary (MCS) (-0.203, p 0.008)(Figure 1). Gender, age, fibromyalgia and disease activity were also confirmed to significantly influence HR-QoL (Table 1).

Table 1.

Multiple regression for the assessment of the relationship between Δ-BODI and SF-36 domains

Δ-BODIMaleAgeFBMDPRBDCAFPhysical function (PF)-0.158 (p 0.025)0.180 (p 0.010)-0.299 (p<0.001)-0.358 (p<0.001)-- (p 0.552)-0.141 (p 0.044)Role-physical (RP)-0.150 (p 0.044)0.154 (p 0.039)-0.212 (p 0.001)-0.278 (p<0.001)-- (0.086)-0.251 (p<0.001)Body-pain (BP)-- 0.8680.266 (p<0.001)-0.286 (p<0.001)-0.276 (p<0.001)-- (p 0.799)-262 (p<0.001)General health (GH)-0.199 (p 0.004)0.187 (p 0.010)-- (0.136)-0.296 (p<0.001)-- (0.861)-0.352 (p<0.001)Vitality (VT)-- (p 0.868)0.238 (p 0.001)-0.178 (p 0.008)-0.213 (0.002)-- (p 0.855)-0.371 (p<0.001)Social function (SF)-- (p 0.239)0.299 (p 0.004)-0.166 (p 0.024)-0.242 (p 0.001)-- (0.831)-0.202 (p 0.010)Role emotional (RE)-0.180 0.003)0.158 (p 0.047)-0.157 (p 0.048)-0.233 (p 0.003)-- (0.531)-0.191 (p 0.016)Mental health (MH)-0.244 (p 0.001)-- (p 0.142)-- (p 0.142)-0.292 (p<0.001)-- (p 0.073)-0.254 (p 0.001)Physical Component Summary (PCS)-- 0.1050.229 (p 0.001)-0.298 (p<0.001)-0.296 (p<0.001)-0.254 (p<0.001)Mental Component Summary (MCS)-0.203 (p 0.008)-- (p 0.068)-- (0.246)-0.255 (p 0.001)-- (0.122)-0.302 (p<0.001)

FBM: fibromyalgia; DPR: depression

Conclusion

The recent accrual of organ damage, rather than its extent assessed in a single visit, is associated with impairment of different aspects of heath related quality of life, especially those mental related. Such phenomenon is similar to that observed in other systemic rheumatic disease, may be due to coping mechanisms.

Disclosure of Interests

None declared

POS0703 BIOLOGIC-DMARDS AND TARGETED SYNTHETIC-DMARDS EFFECT ON RAPID WITHDRAWAL OF STEROID IN 6 MONTHS OBSERVATIONAL PERIOD IN RHEUMATOID ARTHRITIS PATIENT’S COHORT: REAL LIFE DATA EXTRACTED FROM BIOPURE REGISTRY

Background

Considering the highest adverse events risk (predominantly infectious disease and osteoporosis) of glucocorticoids (GCs), EULAR recommended a short-term use of GCs with rapid tapering as soon as clinically feasible in rheumatoid arthritis (RA) patients. Although a prednisone dose less than or equal to 7,5 mg/die is considered more safety, the complete discontinuation of the GCs would be desirable. Few data are available on real tapering or withdrawal of GCs in RA patients treated with DMARDs both in clinical trial and registry study.

Objectives

To evaluate the steroid tapering rate and the discontinuation of GCs in RA patients treated with biological-DMARDs (b-DMARDs) or target synthetic DMARDs (ts-DMARDs) in different treatment lines.

Methods

We revised retrospectively 1616 clinical records of RA patients who started b/ts-DMARDs between December 2017 and June 2021. We recruited 420 RA patients who were stably treated for at least 6 months with b/ts-DMARDs with or without cs-DMARDs and were taken GCs at baseline visit. The evaluations of GCs discontinuation time were realized by Kaplan-Meier estimate, followed by log-rank (Mentel-Cox) test for the comparison among different b/ts-DMARDs groups. Statistical significance was set at p ⩽ 0.05.

Results

RA patients treated with different b/ts-DMARDs were comparable for disease duration (anti TNF-alpha: 76 weeks ± 64; JAK-I: 121 weeks ± 122; anti-IL6: 78 weeks ± 70; abatacept: 111 weeks ± 121), disease activity (DAS 28 ESR: anti TNF alpha: 3,9 ± 1,3; JAK-I: 4,1 ± 1; anti IL-6: 4 ± 1,3; abatacept: 4 ± 1,2; p=0,958), and GCs dose (anti TNF alpha: 5,7 mg ± 7,5; JAK-I 5,5 mg ± 2,5; anti IL-6 5,7 mg ± 4,1; abatacept 5,6 mg ± 2,5; p=0,879) at baseline visit. 158 RA patients started for the first-time b/ts-DMARDs, 83 patients started 2nd line of b/ts-DMARDs, 66 patients started 3rd line b/ts-DMARDs and 113 patients were failure to more than 3 b/ts-DMARDs.

Considering RA patients who started b/ts-DMARDs for the first time, the groups treated with anti-IL6 or JAK-I showed a shorter discontinuation time than those treated with anti TNF-alpha or Abatacept (respectively 22 weeks ± 0,7, 22,6 weeks ± 0,7, 23,8 weeks ± 0,1, 23,1 weeks ± 0,4; p=0,046). As regards the steroid sparing in 6th month of follow-up, the rates of GCs dose spared than the staring GCs dose were higher in JAK-I (44%) and anti-IL 6 (42%) compared to abatacept (30%) and anti-TNF alpha (33%).

Considering the group of RA patients treated in 2nd or other lines of b/ts-DMARDs, no differences were found among various treatments in GCs discontinuation time.

Conclusion

In clinical practice GCs are useful therapeutic tools to reach as rapidly as possible low disease activity in RA patients; but the possible adverse effects of long-term GCs treatment limit their use. The introduction of biotechnological drugs has significantly improved clinical management of RA patients, achieving the aim of rapid GCs discontinuation or their dose reduction. In particular, the mechanisms of action of anti-IL6 and JAK-I seems perform more quickly on steroid discontinuation than anti TNF alpha or abatacept, above all in 1st line of b/ts-DMARDs in RA patients.

Disclosure of Interests

None declared

POS0634 SAFETY PROFILE OF b/tsDMARD IN RHEUMATOID ARTHRITIS PATIENTS WITH IMPAIRED GLOMERULAR FILTRATION RATE. AN ANALYSIS FROM THE GISEA REGISTRY

Background

In real-life setting, a greater number of elderly rheumatoid arthritis (RA) patients with impaired glomerular filtration rate (GFR) needs treatment with biologic or target synthetic disease-modifying anti-rheumatic drugs (b/tsDMARD) to achieve disease control and reduce NSAIDs intake. Long-term observational data from the real-life on the use of b/tsDMARD in these patients are scarce.

Objectives

The aim of this study was to evaluate the retention rate of b/tsDMARD in RA patients with impaired GFR in real-life setting.

Methods

Data of RA patients treated with at least one b/tsDMARD were retrospectively analyzed form the national Italian GISEA registry from January 2016 to December 2021. Estimated-GFR (eGFR) was calculated with the Cockcroft-Gault equation at the time of any b/tsDMARD prescription. For the purpose of this study, patients were divided in two groups, patients with impaired GFR (eGFR ≤60) and patients with normal GFR (eGFR >60). The retention rate was calculated by the Kaplan-Meier method and compared between these two groups by a log-rank test.

Results

The study population included 2443 treatment-line with b/tsDMARD from 1888 patients (female 80.4%, age 57±12 years, mean baseline CDAI 17±12, FR/ACPA+ 69.5%) who started a new b/tsDMARD. Disease characteristics are shown in Table 1. 288 treatments with b/tsDMARD were started in patients with impaired eGFR and 2155 in patients with normal eGFR. Compared to patients with eGFR >60, patients with eGFR ≤60 showed higher HAQ-DI (1.3±0.8 vs 1±0.8, p<0.001) at the start of b/tsDMARD treatment. Glucocorticoids were more prescribed in patients with impaired eGFR (80.2% vs 72.8%, p<0.01), while csDMARDs were more prescribed in association with b/tsDMARD in patients with normal eGFR (83.1% vs 76.4%, p<0.01). Of note, CTLA4-Ig treatment was more prescribed in patients with impaired eGFR (26% vs 17.1%, p<0.05), while no difference in b/tsDMARD prescription was observed for other mechanism of actions. Drug survival was similar between RA patients with impaired eGFR [58.2%, mean survival time 35 months (CI95% 31-39)]and RA patients with normal eGFR [55%, mean survival time 34.4 months (CI95% 33-36), log rank: 0.88] (Figure 1). Cox regression model adjusted for age, sex and b/tsDMARD showed no impact of eGFR on drug survival [HR: 0.9 (CI95%: 0.7-1.2).

Conclusion

Our data show that impaired eGFR seems to not influence the persistence of b/tsDMARD treatment in RA patients.

Disclosure of Interests

None declared

POS1267 LONG-TERM SURVEY STUDY OF THE IMPACT OF COVID-19 ON SYSTEMIC AUTOIMMUNE DISEASES. LOW DEATH RATE DESPITE THE INCREASED PREVALENCE OF SYMPTOMATIC INFECTION. ROLE OF PRE-EXISTING INTERSTITIAL LUNG DISEASE AND ONGOING TREATMENTS

Background

Patients with autoimmune systemic diseases (ASDs) can be counted among frail populations as regards the predisposition to COVID-19 due to the frequent visceral organ involvement and comorbidities, as well as the ongoing immunomodulating treatments.

Objectives

Our long-term multicenter telephone survey prospectively investigated the prevalence, prognostic factors, and outcomes of COVID-19 in Italian ASD patients during the first 3 pandemic waves.

Methods

A large series of 3,918 ASD patients (815 M, 3103 F; mean age 59±12SD years) was consecutively recruited at the 36 referral centers of COVID-19 & ASD Italian Study Group. In particular, ASD series encompassed the following conditions: rheumatoid arthritis (n: 981), psoriatic arthritis (n: 471), ankylosing spondylitis (n: 159), systemic sclerosis (n: 1,738), systemic lupus (172), systemic vasculitis (n: 219), and a miscellany of other ASDs (n: 178). The development of COVID-19 was recorded by means of telephone survey using standardized symptom-assessment questionnaire (1).

Results

A significantly increased prevalence of COVID-19 (8.37% vs 6.49%; p<0.0001) was observed in our ASD patients, while the cumulative death rate revealed statistically comparable to the Italian general population (3.65% vs 2.95%; p: ns). In particular, among the 328 ASD patients complicated by COVID-19, 57 (17%) needed hospitalization, while mild-moderate manifestations were observed in the large majority of individuals (83%). In addition, 12/57 hospitalized patients died due to severe interstitial pneumonia and/or cardiovascular manifestations.

Interestingly, a significantly higher COVID-19-related death rate was observed in systemic sclerosis patients compared to the Italian general population (6.29% vs 2.95%; p=0.018). Other adverse prognostic factors to develop COVID-19 were the patients’ older age, male gender, pre-existing ASD-related interstitial lung involvement, and chronic steroid treatment. Conversely, patients treated with conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) showed a significantly lower prevalence of COVID-19 compared to those without (3.58% vs 46.99%; p=0.000), as well as the chronic administration of low dose aspirin in a subgroup of SSc patients (with 5.57% vs without 27.84%; p=0.000).

Conclusion

The cumulative impact of COVID-19 on ASD patients after the first 3 pandemic waves revealed less severe than that observed during the first phase of pandemic (1), especially with regards to the death rate that was comparable to the Italian general population in spite of the increased prevalence of complicating COVID-19 in the same ASD series.

Ongoing long-term treatments, mainly csDMARDs, might usefully contribute to generally positive outcomes of in this frail patients’ population.

Of note, a significantly increased COVID-19-related mortality was recorded in only SSc patients’ subgroup, possibly favored by pre-existing lung fibrosis. Among different ASD, SSc deserves special attention, since it shares the main pathological alterations with COVID-19, namely the interstitial lung involvement and the endothelial injury responsible for diffuse microangiopathy.

Besides SSc, the patients’ subgroups characterized by older age, chronic steroid treatment, pre-existing interstitial lung disease, and/or impaired COVID-19 vaccine response (1-3), may deserve well-designed prevention and management strategies.

References

[1]Ferri C, et al. Ann Rheum Dis. 2020 Oct 14 doi: 10.1136/annrheumdis-2020-219113.

[2]Ferri C et al. J Autoimmun. 2021 Dec;125:102744. doi: 10.1016/j.jaut.2021.102744.

[3]Visentini M et al. Ann Rheum Dis. 2021 Nov 24. doi: 10.1136/annrheumdis-2021-221248

Disclosure of Interests

None declared

AB0070 INHIBITION OF STAT3 IN PBMCs FROM RHEUMATOID ARTHRITIS PATIENTS: CLUES TO UNDERSTAND SELECTIVITY OF JANUS KINASE INHIBITORS

Background

The Janus kinase (Jak) - signal transducer and activator of transcription (STAT) pathway has 4 Jak proteins and 7 STAT factors that mediate intracellular downstream of cytokine receptors. Targeted small-molecule therapies with different bond affinity to Jak proteins have been demonstrated effective in rheumatoid arthritis (RA) treatment, but the clinical significance of selective inhibition remains unclear.

Objectives

To explore the effect of selective inhibition of Jak-STAT pathway in peripheral blood mononuclear cells (PBMC) from RA patients compared to healthy donors (HD).

Methods

In vitro Jak inhibition of the subunit 3 of phosphorylated (p) than activated STAT was measured by flow cytometry in peripheral blood mononuclear cells (PBMC) from RA patients with active disease (DAS28>5.1) naïve to any DMARDs (n.5) and HD (n.5), following recombinant human 0.1 ng/ml IL-6 (Peprotech – NJ, USA) stimulation. After blood separation, PBMC were overnight incubated with IC50 concentrations of selective Jak1-, Jak2-, Jak3- and Tyk2-inhibitors (Biovision Inc. – CA, USA) with or without IL-6 stimulation. Mean fold-increase of pSTAT3 was then compared in presence of different compounds stimulation.

Results

Mean pSTAT3 activity after overnight incubation was significantly higher in RA patients compared to HD (37%; 95CI 8.2-56.7 vs 17.9%; 95CI 4.6-21 – p=0.01). After IL-6 stimulation, a 2-fold and a 1.4-fold increase in pSTAT3 levels was observed in PBMC from RA patients and HD, respectively. In unstimulated PBMC from HD Jak-inhibitors didn’t significantly reduced pSTAT3 activity. In CD14+ cells from RA patients, pSTAT3 activity was reduced with no differences between all four selective Jak-inhibitors, while in CD4+ cells only Jak1-inhibition was able to reduce by 40% pSTAT3 activity. After IL-6 stimulation, the co-culture with Jak1- or JaK3- selective inhibitors was able to significantly reduce pSTAT3 levels in CD4+ lymphocytes, by an average of 20%. While in CD14+ monocytes Jak1-, Jak2- and Jak3- selective inhibitors were able to reduce pSTAT3 activity by a mean of 30%. Tyk-2 selective inhibitor did not interfere with STAT3 activation by IL-6 stimulation of PBMC from RA patients and HD.

Conclusion

Jak/STAT3 activity of PBMC from RA patients with active disease may be differently modulated by specific inhibitors. Selectivity of Jak-inhibitors seems more relevant in lymphocytes after IL-6 stimulation. These preliminary findings may explain discrepancies in effectiveness of selective Jak-inhibitors and pave the way for different choices in clinical practice.

References

[1]Tanaka Y, et al. Nat Rev Rheumatol. 2022 Jan 5:1–13.

[2]Traves PG, et al. Ann Rheum Dis. 2021 Jul;80(7):865-875.

[3]Choy EH. Rheumatology (Oxford). 2019 Jun 1;58(6):953-962.

Disclosure of Interests

None declared

AB1191 SAFETY PROFILE OF COVID VACCINES IN ARTHRITIS PATIENTS. A TWO-CENTERS STUDY

Background

Coronavirus 19 disease (COVID-19) represents the most important pandemic of the last century. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection has produced more than 170 million cases and more than 3 million deaths. Due to the easy spread of the infection and the possibility of serious clinical manifestations, the role of anti-COVID 19 vaccination is essential. Vaccines with different mechanisms of action have been developed: mRNA-based, such as Biontech-Pfizer and Moderna, and viral vectored, such as AstraZeneca and Janssen. Despite possible adverse events, benefits afforded by these vaccines significantly outweigh potential risks associated with their administration in the general population.

Objectives

This study aimed to evaluate incidence and severity of adverse events (AEs), secondary to vaccination, in patients with Rheumatoid Arthritis (RA), Psoriatic Arthritis (PsA) and Spondyloarthritis (SpA), immune-mediated diseases treated with immunomodulating drugs, by administering a questionnaire.

Methods

294 patients (201 f and 93 m) were enrolled with a diagnosis of arthritis (RA 28%, PsA 43%, SpA 28%).

Results

Of the 294 enrolled patients, 107 underwent COVID vaccination, 73% with Biontech-Pfizer vaccine, 20% Astrazeneca and 6% Moderna. 50% of patients completed the entire vaccination cycle.

46% of patients presented AEs after the first dose of vaccine (45% of vaccinated with Biontech-Pfizer; 48% of vaccinated with Astrazeneca, 33% of vaccinated with Moderna). The most frequently observed AEs are: pain at the injection site (17%), fever (13%), headache (12%), myalgia (12%), fatigue (7.5%). Only 2.9% of patients had arthritis flares. The greatest trend of AEs was observed in patients with PsA (48%), and RA (26%).

32% of patients receiving the second dose of vaccine presented AEs (40% Moderna, 32% Biontech-Pfizer). The most frequently observed AEs after the second dose are: pain at the injection site (4.7%), fever (9%), headache (2.8%), myalgia (6%). No patient had arthritis flare after the second dose. The greatest trend of AEs was observed in patients with SpA (66%).

Only 11% of patients presented AEs after the administration of both doses.

Thirteen percent of patients did not follow the clinician’s recommendations for immunomodulatory drug management, provided as per ACR or SIR recommendations.

Conclusion

The incidence of adverse events in arthritis patients was in line with that of the general population, without presenting serious manifestations, such as thrombosis, and without indicating a preference on the type of vaccine.

References

[1]Tsai SC, Lu CC, Bau DT, Chiu YJ, Yen YT, Hsu YM, Fu CW, Kuo SC, Lo YS, Chiu HY, Juan YN, Tsai FJ, Yang JS. Approaches towards fighting the COVID‑19 pandemic (Review). Int J Mol Med. 2021 Jan;47(1):3-22. doi: 10.3892/ijmm.2020.4794. Epub 2020 Nov 20. PMID: 33236131; PMCID: PMC7723515.

[2]Hodgson SH, Mansatta K, Mallett G, Harris V, Emary KRW, Pollard AJ. What defines an efficacious COVID-19 vaccine? A review of the challenges assessing the clinical efficacy of vaccines against SARS-CoV-2. Lancet Infect Dis. 2021 Feb;21(2):e26-e35. doi: 10.1016/S1473-3099(20)30773-8. Epub 2020 Oct 27. PMID: 33125914; PMCID: PMC7837315.

Disclosure of Interests

None declared

POS1218 RELAPSES OF IDIOPATHIC INFLAMMATORY MYOPATHIES AFTER VACCINATION AGAINST COVID19: A REAL-LIFE ITALIAN STUDY

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination plays a crucial role as pivotal strategies to curb the coronavirus disease-19 (COVID-19) pandemic. Despite the mass-scale vaccination, literature data about the incidence of disease flares in IIM patients are still not reported as well as the immunological condition.

Objectives

The present study aimed to describe the clinical status of patients affected by IIM after vaccination against COVID19 in order to assess the number of relapses or immune-mediated reactions in a cohort of Italian patients with such disease.

Methods

We included all patients affected by IIM and followed by Myositis Clinic, Rheumatology and Respiratory Diseases Units, Siena University Hospital, Bari University Hospital, Policlinico Umberto I, Sapienza University, Rome, and Policlinico Paolo Giaccone, Palermo. Inclusion criteria were a recent (<3 months) clinical and serological assessment before the survey and a definite diagnosis of dermatomyositis, polymyositis and anti-synthetase syndrome. All patients underwent a telephone survey in order to establish their clinical status and potential relapses after vaccination.

Results

A total of 119 IIM patients (median, IQR 58 (47-66) years; 32 males) were consecutively enrolled. Fifty had a diagnosis of DM, 39 had PM and 30 had ASS. The median months of disease duration was 79.62±83.98. According to number of organs involvement, forty-two had only one, 45 had two organs involvement, 20 had three, 11 had four and one had five. The majority of them received two doses of COVID-19 vaccine, except four patients who refused the vaccination: 94 (78.9%) Cominarty, 16 (13.4%) Moderna, 5 (0.04%) AZ. Seven (0.06%) patients had flare after vaccination, the majority of them were mild except one major with three organs involved and one life-threatening with systemic involvement. In order to understand or predict the effect of demographic and clinical features on the flare development after vaccination, a logistic regression analysis was performed. The goodness-of-fit statistics showed a Chi2 associated with the Log ratio (L.R.) of 0.045. From the probability associated with the Chi-square tests, the Type II analysis showed the variable that most influences the development of flare was the number of organs involved (p=0.047).

Sixty-eight patients received the third dose of COVID-19 vaccination: 51 (75%) Cominarty and 17 (25%) Moderna. Only one (0.01%) patient (the same who had life-threatening flare with systemic involvement after two doses) had flare after third dose and eventually died.

Conclusion

Vaccines against SARS-CoV2 have provided, both in registratory studies and in preliminary real-life evidence, an overall good efficacy and safety. Nevertheless, only scanty data are available for rheumatic patients in general and the ones affected by IIM in particular. To the best of our knowledge, ours represent the largest cohort of IIM patients in which immunogenicity of anti-SARS-CoV2 vaccine was assessed. In line with real-life data from other diseases, we found a non-statistically significant risk of relapse in our patients, which occurred seldom, usually mild and in patients with a more severe and aggressive course of disease.

ParametersFlare after two doses (n=7)No-flare after two doses (n=108)P valueAge (years)55 (51-68)59 (47-67)NSGender (M/F)2/530/82NSDiagnosis (DM/PM/ASS)2/2/348/36/28NSAntibodiesJo1225PL7-3PL12-1Ku-2Mi217PM/Scl15Ro5217TIG1g-5MDA5-6SRP-1SAE-2cN1a--NPX-1SSA-12Ds-DNA-1ANA (only positivity)-3negative227Length of disease (months)50 (19-200)60 (24-108)NSNumber of organs involved:One0360.0004Two243Three319Four110Five10Type of vaccination:Cominarty688NSModerna115AZ05Disease activity (PhGA≥2/PhGA<2)3/427/81NSMDI3 (1-6.5)2 (1-4)NSCRP (mg/dL)0.1 (0.01-0.3)0.99 (0.3-2.9)0.0041ESR32 (14-39)15.5 (8-27.5)NSCPK111 (63-905)97.5 (63-158)NSTreatment at time of vaccination: GCs010NS Immunosuppressive319 Biologic12 Combination365 no-treatment-12

Disclosure of Interests

None declared

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

AB0630 Assessment of organ damage accrual in Behçet's Syndrome over 2-year follow-up: results from the BODI Project longitudinal extension

Background

Preventing accrual of organ damage is a major goal in the treatment of Behçet’s Syndrome (BS). The BS Overall Damage Index (BODI) is the first damage assessment tool developed and preliminarily validated for BS.

Objectives

To assess the prevalence, extent, and determinants of organ damage accrual in the BODI validation cohort over 24 months of follow-up.

Methods

Overall, 189 patients from the multicenter BODI cohort underwent a 24 ±3 months follow-up (FU) visit. Demographics, ongoing medication, Behçet’s Disease Current Activity Form (BDCAF) score, Physician (PGA) and Patient Global Assessment (PtGA) of disease activity, disease relapsing (defined by any treatment change due to increased disease activity), and the BODI score were recorded. Damage accrual was defined as any increase ≥1 in the BODI score between baseline and follow-up visit (Δ-BODI). Logistic regression models were built to identify factors associated with BODI damage accrual.

Results

The mean age (standard deviation) at enrolment and the disease duration was 46.2 (12.1) and 10.8 (8.3) years, respectively, and 92/189 (48.7%) patients were males. During 24 months, 36 (19.0%) patients had an increase in the BODI score of at least 1 point (mean increase of 1.7 points). The BODI score increased from 1.6 (2.1) to 1.9 (2.1), with a mean Δ-BODI of 0.3 (0.8). Overall, 61 new BODI items of damage were recorded (Figure 1); 22 (34%) were steroid-related (diabetes, osteoporotic fractures, cataract). Factors independently associated with increased BODI score were longer glucocorticoids exposure (OR 1.01 per month, 95%CI 1.01-1.02, p<0.001), and occurrence of flares (OR 3.1, 95%CI 1.1-8.9, p = 0.035), whereas stable treatment with conventional and/or biologic immunosuppressants was negatively associated with an increase in the BODI score (OR 0.19, 95% 0.07-0.97, p <0.001) (Table 1).

Table 1.

Determinants of organ damage accrual over 2 years of follow-up.

Univariate analysisMultivariate analysisCandidate determinantsΔ-BODI ≥1 (n 36)Δ-BODI = 0 (n 153)pOR (95%CI)pMales16 (44.4%)76 (49.7%)0.572Age at enrolment56.2 (42.9-62.0)46.6 (35.4-53.1)0.001----Disease duration12.9 (7.1-22.0)11.1 (5.4-21.2)0.483Major organ involv.22 (61.1%)72 (47.1%)0,129BDCAF at BL3 (0-5)2. (0-5)0.365BDCAF at FU visit3.0 (3-5)3 (0-7)0.188GC duration112 (26.0-147.0)24.0 (8.0-72.0)<0.0011.012 (1.006-1.018<0.001cIS or TNFì ever24 (66.7%)133 (86.9%)0.0040.194 (0.073-0.972)<0.001Relapse9 (25.0%)20 (13.1%)0.0703.093 (1.066-8.972)0.038BODI score at BL1.0 (0-2.0)1 (0-2)0.579

Continuous variables are presented as median (IQR). Dichotomic variable are presented as n (%). BODI, Behçet’s Syndrome Overall Damage Index. FU, follow-up. cIS, conventional immunosuppressant. Δ-BODI increase of BODI score from baseline to the FU visit.

Conclusion

Despite the relatively high disease duration in the studied cohort, organ damage accrual was recorded in a relevant proportion of patients. BODI proved to capture the damage associated with major determinants such as inadequate control of disease activity and prolonged exposure to glucocorticoids.

Disclosure of Interests

None declared

AB1236 CLINICAL CHARACTERISTICS OF JUVENILE ONSET SYSTEMIC SCLEROSIS PATIENTS FROM THE JUVENILE SCLERODERMA INCEPTION COHORT COMPARED TO ADULT AGE JUVENILE-ONSET PATIENTS FROM EUSTAR. ARE THESE DIFFERENCES SUGGESTING RISK FOR MORTALITY?

Background

Juvenile systemic sclerosis (jSSc) is an orphan autoimmune disease with a prevalence of 3 in 1 000 000 children. Information on long-term development of organ involvement and clinical characteristics of jSSc patients in adulthood are lacking. It was believed that patients in adult cohorts may represent a survival biased population.

Objectives

To assess differences in clinical characteristics of jSSc-onset patients from the pediatric age group, with a mean disease duration of 3 years, compared to the adult age jSSc-onset group, with a mean disease duration of 18.5 years.

Methods

We extracted clinical data at time of inclusion into the cohorts from the Juvenile Scleroderma Inception Cohort (jSScC) and data from juvenile-onset adult SSc patients from the European Trials and Research Group (EUSTAR) cohort. We compared the clinical characteristics of the patients by descriptive statistics.

Results

We extracted data of 187 jSSc patients from the jSScC and 236 patients from EUSTAR. The mean age at time of assessment was 13.4 years old in the jSScC and 32.4 years old in EUSTAR. The mean disease duration since first non-Raynaud was 3.0 years in jSScC and 18.5 years in the EUSTAR (Table 1).

We found significant differences between the cohorts. There were more female patients in EUSTAR (87.7% versus 80.2%, p=0.04). More patients had diffuse subtype in jSScC (72.2% versus 40%, p<0.001). The modified Rodnan skin score (mRSS) was significantly higher in jSScC (14.2 versus 12.1, p=0.02). Active digital ulceration occurred more often in EUSTAR (26.6%, versus 17.8% p=0.01), but history of active ulceration was more frequent in jSScC (54.1% versus 43%, p<0.001). Mean DLCO was lower in jSScC (75.4 versus 86.3, p<0.001). Intestinal involvement was significantly more common in jSSc (33.2% versus 23.8%, p=0.04). Esophageal involvement was more common in EUSTAR (63.7% versus 33.7%, p<0.001). (Table 1).

Table 1.

Clinical characteristics of juvenile onset SSc patients at time point of the inclusion into the juvenile scleroderma inception (jSScC) cohort and in the adult EUSTAR- cohort

jSScCEUSTAR CohortP valueNumber of patients1872360.04Age in years, mean (SD)13.4 (3.6)32.4 (15.4)Female patients, n (%)150 (80.2%)207 (87.7%)jSSC Subtype, n (%)diffuse135 (72.2%)87 (38.1%)<0.001limited52 (27.8%)121 (53.3%)Age at Raynaud onset in years, mean (SD)10.0 (3.9)13.7 (9.1)Age at non-Raynaud onset in years, mean (SD)10.3 (3.9)11.7 (3.7)Duration since first Raynaud symptoms in years, mean (SD)3.4 (2.7)20.6 (15.9)Duration since first non-Raynaud symptoms in years, mean (SD)3.0 (2.7)18.5 (15.6)Raynaud´s, n (%)170 (90.9%)222 (94.9%)ANA positive, n (%)166 (91.7%)210 (92.9%)0.99Anti-Scl 70 positive, n (%)62 (34.4%)73 (33.3%)0.68Modified Rodnan Skin Score, mean (SD)5%Data missingModified Rodnan Skin Score, mean (SD)14.2 (11.7)12.1 (14.5)0.02Digital ulceration, n (%)At the time of inclusion33 (17.8)21 (26.6%)0.01In the past history100 (54.1%)34 (43%)<0.001Telangiectasia62 (37.4%)42 (53.2%)0.04FVC, mean (SD)84.1 (18.6)84 (22.4)0.96DLCO, mean (SD)75.4 (19.2)86.3 (19.9)<0.001Arterial hypertension, n (%)10 (5.4%)20 (8.5%)0.26Renal crisis, n (%)03 (1.3%)0.26Esophageal involvement, n (%)63 (33.7%)149 (63.7%)<0.001Intestinal involvement, n (%)62 (33.2%)56 (23.8%)0.04Articular involvement, n (%)34 (18.3%)27 (11.6%)0.06Muscular involvement, n (%)31 (19.3%)46 (19.8%)0.45

Conclusion

Patients with jSSc-onset who are currently adult age (defined as >18 years of age) are less frequently male and from the diffuse subset, have lower mRSS, less digital ulcers and intestinal involvement. This might represent a combination of both survival bias and/or be explained by the longer observation time with less active disease (i.e. natural progression decreased mRSS over time). Further long-term observational studies with jSSc patients are required to address this issue.

Disclosure of Interests

None declared

AB0467 EFFECTIVENESS OF GOLIMUMAB AFTER TNF-INHIBITOR FAILURE IN PATIENTS WITH ACTIVE RHEUMATOID ARTHRITIS, PSORIATIC ARTHRITIS, OR AXIAL SPONDYLOARTHRITIS: RESULTS AT 3 MONTHS FROM THE GO-BEYOND ITALY STUDY

Background:

Golimumab showed trial efficacy in subjects with active rheumatoid arthritis (RA) previously treated with TNF-inhibitors (TNFi); no trial data are available for psoriatic arthritis (PsA) and axial spondyloarthritis (axSpA).

Objectives:

To assess the effectiveness of golimumab after TNFi failure in patients with RA, PsA, or axSpA in a real-world setting.

Methods:

GO-BEYOND-Italy is an ongoing, multicenter, prospective, observational study of RA, PsA, or axSpA patients starting golimumab after TNFi failure. Patients were enrolled between July 2017 and December 2019, and followed for 1 year, with evaluations at 3, 6, and 12 months. This interim analysis estimates the effectiveness after 3 months of golimumab therapy. Differences from baseline were tested by paired t-tests.

Results:

193 patients were enrolled: 38 (19.7%) with RA (median age 54 years; median disease duration 9.5 years), 91 (47.2%) with PsA (median age 53 years; median disease duration 9.0 years) and 64 (33.2%) with axSpA (median age 54 years; median disease duration 7.2 years). Majority of the RA (73.7%), PsA (51.6%) and axSpA (53.1%) were females. Previous TNFi treatment included etanercept (44.6% of patients), adalimumab (42.0%), infliximab (8.8%) and certolizumab (4.7%). The main reason for switching to golimumab was loss of efficacy of TNFi (78.9% in RA, 83.5% in PsA, 75% in axSpA). Comorbidities were highly prevalent (RA 65.8%, PsA 65.9%, axSpA 75%); hypertension (31.1%), dyslipidaemia (13.5%), fibromyalgia (10.4%) were the most common ones. DAS28-CRP significantly reduced in RA and PsA (p<0.01) after 3 months of treatment. In RA, rates of DAS28-CRP remission and low disease activity (LDA) were 29.6% and 22.2%, respectively, and 65.2% of patients achieved good/moderate EULAR response. As for PsA, good/moderate EULAR response was observed in 78.8% of patients and 28% of patients achieved minimal disease activity. In axSpA, ASDAS-CRP (p<0.01), BASDAI (p<0.01) and ASAS-HI (p=0.032) significantly reduced; rates of ASDAS-CRP inactive disease and LDA were 15.2% and 26.1%, respectively; 14% of patients had a ≥50% improvement in baseline BASDAI. After 3 months of golimumab treatment, there was a decrease in the prevalence of enthesitis (32.9% to 16.5%), nail (17.6% to 12.9%) and skin psoriasis (42.4% to 34.1%) in PsA patients; the frequency of extra articular manifestations tended to decrease also in axSpA patients.

Conclusion:

Preliminary results of the GO-BEYOND-Italy study showed a good short-term effectiveness of golimumab in RA, PsA and axSpA after TNFi failure.

Table 1.

Effectiveness of golimumab at 3 months in the GO-BEYOND-Italy study

Rheumatoid arthritis (n=38)Psoriatic arthritis (n=91)Axial spondyloarthritis (n=64)DAS28-CRP, mean (SD)n=27DAS28-CRP, mean (SD)n=47ASDAS-CRP, mean (SD)n=44V0 / V14.05 (0.8) / 3.10* (1.0)V0 / V13.66 (1.0) / 2.79* (1.2)V0 / V12.86 (1.0) / 2.33* (1.0)V1: DAS28-CRP disease activity, n (%)n=27V1: EULAR response, n (%)n=33V1: ASDAS-CRP disease activity, n (%)n=46Remission8 (29.6)Good16 (48.5)Inactive disease7 (15.2)Low disease activity6 (22.2)Moderate10 (30.3)Low disease activity12 (26.1)Moderate disease activity13 (48.1)No response7 (21.2)High disease activity22 (47.8)Very high disease activity5 (10.9)V1: EULAR response, n (%)n=23V1: MDA, n (%)n=75Good7 (30.4)Yes21 (28.0)BASDAI, mean (SD)n=50Moderate8 (34.8)V0 / V15.99 (2.1) / 4.92 (2.3)*No response8 (34.8)V1: BASDAI50, n (%)7 (14.0)ASAS-HI, mean (SD)n=48V0 / V110.67 (3.8) / 9.68 (4.6)^

*p value for the difference from V0 <0.01. ^ p for the difference from V0=0.032

Abbreviations: ASDAS: Ankylosing Spondylitis Disease Activity Score; ASAS-HI: Assessment of SpondyloArthritis international society Health Index; BASDAI: Bath Ankylosing Spondylitis Disease Activity Index; CRP: C-reactive protein; DAS: disease activity score; EULAR: European League Against Rheumatism; MDA: Minimal Disease Activity; SD: standard deviation; V0: baseline; V1: 3 months evaluation.

Disclosure of Interests:

Salvatore D’Angelo Speakers bureau: AbbVie, BMS, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, UCB, Consultant of: AbbVie, BMS, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, UCB, Enrico Tirri Speakers bureau: AbbVie, Eli Lilly, Novartis, Pfizer, Angela Maria Giardino Employee of: MSD Italia, Marco Matucci-Cerinic Speakers bureau: BMS, Pfizer, Actelion, Consultant of: Eli-Lilly, Celgene, Chemomab, CSL Behring, Grant/research support from: BMS, Pfizer, Celgene, CSL Behring, Lorenzo Dagna Consultant of: Abbvie, Amgen, Biogen, Bristol-Myers Squibb, Celltrion, Novartis, Pfizer, Roche, Sanofi-Genzyme, and SOBI, Leonardo Santo: None declared., francesco ciccia: None declared., Bruno Frediani: None declared., Marcello Govoni: None declared., Francesca Bobbio Pallavicini: None declared., Rosa Daniela Grembiale: None declared., Andrea Delle Sedie: None declared., Stefania Cercone Employee of: MSD Italia, RITA MULE’: None declared., Francesco Paolo Cantatore Speakers bureau: Pfizer, Sanofi Genzyme and Roche, Consultant of: Pfizer, Sanofi Genzyme and Roche outside this work., Rosario Foti: None declared., Elisa Gremese: None declared., Roberto Perricone: None declared., Fausto Salaffi: None declared., Ombretta Viapiana Speakers bureau: Novartis, UCB, Abbvie, MSD, Fresenius kabi, Gilead, Biogen, Consultant of: Novartis, Abbvie, Fresenius kabi, Gilead, Biogen, Alberto Cauli Speakers bureau: Abbvie, Alfa-Sigma, BMS, Celgene, Galapagos, Glaxo, MSD, Novartis, Janssen, Pfizer, Sanofi, UCB, Consultant of: Abbvie, Alfa-Sigma, BMS, Celgene, Galapagos, Glaxo, MSD, Novartis, Janssen, Pfizer, Sanofi, UCB, Rorberto Giacomelli: None declared., Luisa Arcarese: None declared., Giuliana Guggino Speakers bureau: Novartis, Celgene, Abbvie, Sandoz, Eli Lilly, Pfizer, Jansen, ROMUALDO RUSSO: None declared., Domenico Capocotta: None declared., Francesca Nacci: None declared., Maria Grazia Anelli: None declared., valentina picerno: None declared., Florenzo Iannone Speakers bureau: Pfizer, AbbVie, Janssen, Celgene, Novartis, MSD, BMS, UCB, Roche, Consultant of: Pfizer, AbbVie, Janssen, Celgene, Novartis, MSD, BMS, UCB, Roche outside this work.

POS1021 THE PsABio STUDY IN ITALY: A REAL-WORLD COMPARISON OF THE PERSISTENCE, EFFECTIVENESS AND SAFETY OF USTEKINUMAB AND TUMOUR NECROSIS FACTOR INHIBITORS IN PATIENTS WITH PSORIATIC ARTHRITIS

Background:

There are still unmet needs in the treatment of psoriatic arthritis (PsA), including in terms of treatment persistence, which is a function of effectiveness, safety and patient satisfaction. Ustekinumab (UST) was the first new biologic drug to be developed for the treatment of PsA after tumour necrosis factor inhibitors (TNFi).

Objectives:

To compare treatment persistence, effectiveness and safety of UST and TNFi in Italian patients within the PsABio cohort.

Methods:

PsABio (NCT02627768) is an observational study of 1st/2nd/3rd-line UST or TNFi treatment in PsA in 8 European countries. The current analysis set includes 222 eligible patients treated in 15 Italian centres, followed to Month 12 (±3 months). Treatment persistence/risk of stopping was analysed using Kaplan−Meier (KM) and Cox regression analysis. Proportions of patients reaching minimal disease activity (MDA)/very low disease activity (VLDA) and clinical Disease Activity Index for PsA (cDAPSA) low disease activity (LDA)/remission were analysed using logistic regression, including propensity score (PS) adjustment for imbalanced baseline covariates, and non-response imputation of effectiveness endpoints if treatment was stopped/switched before 1 year. Last observation carried forward data are reported.

Results:

Of patients starting UST and TNFi, 75/101 (74.3%) and 77/121 (63.6%), respectively, persisted with treatment at 1 year. The observed mean persistence was 410 days for UST and 363 days for TNFi. KM curves and PS-adjusted hazard ratios confirmed significantly higher persistence (hazard ratio [95% confidence interval (CI)]) for UST versus TNFi overall (0.46 [0.26; 0.82]; Figure 1). Persistence was also higher for UST than TNFi in patients receiving monotherapy without methotrexate (0.31 [0.15; 0.63]), in females (0.41 [0.20; 0.83]), and in patients with body mass index (BMI) <25 kg/m2 (0.34 [0.14; 0.87]) or >30 kg/m2 (0.19 [0.06; 0.54]). There was no significant difference in persistence between treatments in patients with BMI 25−30 kg/m2. While patients receiving 1st- and 3rd-line UST or TNFi showed similar risk of discontinuation (0.60 [0.27; 1.29] and 0.36 [0.10; 1.25], respectively), patients receiving 2nd-line UST showed better persistence than those receiving 2nd-line TNFi (0.33 [0.13; 0.87]). Other factors added to the PS-adjusted Cox model did not show significant effects. In patients with available follow-up data, the mean (standard deviation) baseline cDAPSA was 26.3 (15.4) for UST and 23.5 (12.3) for TNFi; at 1-year follow-up, 43.5% of UST- and 43.6% of TNFi-treated patients reached cDAPSA LDA/remission. MDA was reached in 24.2% of UST- and 28.0% of TNFi-treated patients, and VLDA in 12.5% of UST- and 10.2% of TNFi-treated patients. After PS adjustment (stoppers/switchers as non-responders), odds ratios (95% CI) at 1 year did not differ significantly between UST and TNFi groups for reaching cDAPSA LDA/remission (1.08 [0.54; 2.15]), MDA (0.96 [0.45; 2.05]) or VLDA (0.98 [0.35; 2.76]). In total, 23 (20.4%) patients reported ≥1 treatment emergent adverse event with UST and 30 (22.2%) with TNFi; 6 (5.3%) and 10 (7.4%) patients, respectively, discontinued treatment because of an adverse event.

Conclusion:

In the Italian PsABio cohort, UST had better overall persistence compared with TNFi, as well as in specific subgroups: females, patients on monotherapy without methotrexate, with BMI <25 or >30 kg/m2, and patients receiving UST as 2nd-line treatment. At 1 year, both treatments showed similar effectiveness, as measured by cDAPSA responses and MDA/VLDA achievement.

Acknowledgements:

This study was funded by Janssen. Contributing author: Prof. Piercarlo Sarzi-Puttini, ASST Fatebenefratelli-Sacco, University of Milan, Italy

Disclosure of Interests:

Elisa Gremese: None declared, Francesco Ciccia Speakers bureau: AbbVie, Abiogen, Bristol-Myers Squibb, Celgene, Janssen, Lilly, Novartis, Pfizer, Roche, Consultant of: Celgene, Janssen, Lilly, Novartis, Pfizer, Roche, Grant/research support from: Celgene, Janssen, Novartis, Pfizer, Roche, Carlo Selmi Speakers bureau: AbbVie, Alfa-Wassermann, Amgen, Biogen, Celgene, Eli Lilly, Gilead, Janssen, MSD, Novartis, Pfizer, Sanofi-Genzyme, Consultant of: AbbVie, Alfa-Wassermann, Amgen, Biogen, Celgene, Eli Lilly, Gilead, Janssen, MSD, Novartis, Pfizer, Sanofi-Genzyme, Grant/research support from: AbbVie, Amgen, Janssen, Pfizer, Giovanna CUOMO: None declared, Rosario Foti Speakers bureau: AbbVie, Bristol-Myers Squibb, Celgene, Lilly, MSD, Janssen, Roche, Sanofi, Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Lilly, MSD, Janssen, Roche, Sanofi, Marco Matucci Cerinic Speakers bureau: Actelion, Biogen, Janssen, Lilly, Consultant of: Chemomab, Grant/research support from: MSD, Fabrizio Conti Consultant of: AbbVie, Bristol-Myers Squibb, Galapagos, Lilly, Pfizer, Enrico Fusaro Speakers bureau: AbbVie, Amgen, Lilly, Grant/research support from: AbbVie, Pfizer, Giuliana Guggino Speakers bureau: AbbVie, Celgene, Novartis, Pfizer, Sandoz, Grant/research support from: Celgene, Pfizer, Florenzo Iannone Speakers bureau: AbbVie, Bristol-Myers Squibb, Celgene, Lilly, MSD, Novartis, Pfizer, Sanofi, UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Lilly, MSD, Novartis, Pfizer, Sanofi, UCB, Andrea Delle Sedie: None declared, Roberto Perricone: None declared, Luca Idolazzi Speakers bureau: AbbVie, Eli Lilly, Janssen, MSD, Novartis, Sandoz, Paolo Moscato: None declared, Elke Theander Employee of: Janssen, Wim Noel Employee of: Janssen, Paul Bergmans Shareholder of: Johnson & Johnson, Employee of: Janssen, Silvia Marelli Employee of: Janssen, Laure Gossec Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Biogen, Celgene, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Samsung Bioepis, Sanofi-Aventis, UCB, Grant/research support from: Amgen, Galapagos, Janssen, Lilly, Pfizer, Sandoz, Sanofi, Josef S. Smolen Speakers bureau: AbbVie, Amgen, AstraZeneca, Astro, Bristol-Myers Squibb, Celgene, Celltrion, Chugai, Gilead, ILTOO, Janssen, Lilly, MSD, Novartis- Sandoz, Pfizer, Roche, Samsung, Sanofi, UCB, Grant/research support from: AbbVie, AstraZeneca, Lilly, Novartis, Roche.