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Background:After the publication of the ORAL Surveillance trial1, the European Medical Agency (EMA) recently recommended prescribing JAK inhibitors (JAKi) in patients with rheumatoid arthritis (RA) only after an adequate risk/benefit assessment. Indeed, according to EMA recommendations, patients ≥65 year-old, former or current smokers, at high risk of developing major cardiovascular events (MACEs), thromboembolic events or cancers should receive JAKi only when other treatments, such as TNF-inhibitors, are not appropriate. Unlike randomised controlled trials, real-world data seem to be reassuring promising and, in fact, the prescription rate of JAKi has dramatically risen in the last years.Objectives:The primary objective was to assess whether being at high risk according to EMA recommendations can impact JAKi’s discontinuation rate. The secondary aim was to find out other possible predictors of JAKi’s discontinuation.Methods:This was a retrospective Italian study carried out in 22 Italian centres since 2017. All patients with RA on treatment with JAKi were included in the dataset. This cohort was subdivided into two groups: “high risk patients” and “low risk” according to EMA recommendations. The first group included patients ≥65 year-old, past or current smokers and having at least one cardiovascular or neoplastic comorbidity. The following variables were collected at baseline: sex, age, disease duration (years), smoking habit, BMI, comorbidities (diabetes, hypertension, dyslipidaemia, cancer, previous MACEs), positive RF/ACPA, associated conventional DMARDs, concomitant use of prednisone and dosage (mg/day), previous use of JAKi, discontinuation reasons, time to discontinuation (days), b/tsDMARDS naïve patients, DAS28-ESR at baseline.Results:A total of 693 patients were enrolled. 48 patients were excluded due to missing data. Overall features of our cohort are summarised in Table 1 (N=645). 372 (57.7%) patients received baricitinib, 135 (20.9%) tofacitinib, 86 (13.3%) upadacitinib and 52 (8.11%) filgotinib. 21 (3.2%). 141 (21.9%) patients discontinued JAKi after a median time of 366 days (IQR 155-914). “High-risk patients according to EMA” were the majority of our cohort (n=384, 59.5%) vs 261 “low-risk patients” (40.5%).Reasons for discontinuation were primary inefficacy (n=48, 7.4%), secondary inefficacy (n=25, 3.9%), infections (n=8, 1.2%), pulmonary embolism/deep venous thrombosis (n=6, 0.9%), cancer (n=5, 0.8%), deaths (n=2, 0.3%), and other causes (n=21, 3.3%) including remission status in 1 patient. Notably, VZV infection determined JAKi’s withdrawal in 3 patients and pulmonary embolism/deep venous thrombosis in 6 patients (all treated with baricitinib). At multivariate stepwise Cox analysis, predictors of discontinuation were: prednisone dosage [Hazard Ratio -(HR)- 1.1, 95% confidence interval- (CI)- 1.05-1.17], use of selective JAKis(HR 4.1, 95% CI 1.80-9.10), and absence of RF/ACPA (HR 0.46, 95% CI 0.26-0.83). Finally, being classified as “high risk” according to EMA was not statistically associated with JAKIs’ withdrawal (HR 1.96, 95% CI 0.96-4-01).Conclusion:Our study shows that only a minority of patients discontinued JAKi (21.9%). Notably, among discontinuation‘s causes, no MACE’s were found. Being classified at “high-risk” according to EMA was not associated with JAKi’s discontinuation. Conversely, higher prednisone dosages, treatment with selective JAKi and absence of RF/ACPA were predictors of JAKi’s withdrawal.REFERENCES:[1] Ytterberg SR, et al. Cardiovascular and cancer risk with tofacitinib in rheumatoid arthritis. New Engl J Med 2022;386(4):316-326.Acknowledgements:NIL.Disclosure of Interests:Maddalena Larosa UCB, ABBVIE, AMGEN, Andrea Becciolini: None declared, Simone Parisi: None declared, Eleonora Di Donato: None declared, Dario Camellino Astrazeneca, Boerhringer INgelheim, GSK, Janssen, Giuditta Adorni: None declared, Gianluca Lucchini: None declared, Daniele Santilli: None declared, Enrico Fusaro: None declared, Maria Chiara Ditto: None declared, Alberto Lo Gullo: None declared, Marino Paroli: None declared, Rosalba Caccavale: None declared, Alessandro Volpe: None declared, Antonio Marchetta: None declared, Bernd Raffeiner: None declared, Eleonora Celletti: None declared, Myriam Di Penta: None declared, Emanuela Sabatini: None declared, Francesco Cipollone: None declared, Massimo Reta: None declared, Olga Addimanda: None declared, Mirco Magnani: None declared, Elisa Visalli: None declared, Rosario Foti: None declared, Giorgio Amato: None declared, Francesco De Lucia: None declared, Roberta Foti: None declared, Antonella Farina: None declared, Francesco Girelli: None declared, Simone Bernardi: None declared, Matteo Colina: None declared, Romina Andracco: None declared, Natalia Mansueto: None declared, Giulio Ferrero: None declared, Patrizia Del Medico: None declared, Aldo Molica Colella: None declared, Veronica Franchina: None declared, Francesco Molica Colella: None declared, Federica Lumetti: None declared, Gilda Sandri: None declared, Carlo Salvarani: None declared, Dilia Giuggioli: None declared, Marta Priora: None declared, Francesca Serale: None declared, Aurora Ianniello: None declared, Valeria Nucera: None declared, Francesca Ometto: None declared, Cecilia Giampietro: None declared, Elena Bravi: None declared, Ilaria Platè: None declared, Eugenio Arrigoni: None declared, Fabio Mascella: None declared, Maria Cristina Focherini: None declared, Alessandra Bezzi: None declared, Palma Scolieri: None declared, Vincenzo Bruzzese: None declared, Viviana Ravagnani: None declared, Guido Rovera: None declared, Alessia Fiorenza: None declared, Rosetta Vitetta: None declared, Alarico Ariani Amgen, Janssen.

Background:Since 2022 clinicians have been consistently aware by the European Medical Agency (EMA) of prescribing Jak-inhibitors (JAKi) after assessing a risk/benefit ratio, especially in patients with rheumatoid arthritis (RA)1. Nevertheless, during the last years, uptake of selective JAKis has consistently increased, although limited data regarding differences between selective and unselective JAKis are available to date.Objectives:To assess differences between selective and unselective JAKIs in terms of discontinuation’s rate.Methods:In this retrospective study, all patients with RA treated with JAKis were prospectively enrolled from 22 Italian centres since 2017. Selective JAKi included filgotinib and upadactinib, whereas unselective JAKIs included tofacitinib and baricitinib. Reasons of discontinuation rates were: primary and secondary inefficacy, remission, adverse events [deaths, infections, onset of major cardiovascular events-(MACEs)-, deep vein thrombosis-(DVT)-, pulmonary embolism-PE, cancers].The following variables were collected at JAKi’s first prescription: sex, age, disease duration (years), smoking, BMI, comorbidities (diabetes, hypertension, dyslipidaemia, cancer, major cardiovascular events-MACEs), positive RF/ACPA, associated cDMARDs, prednisone and prednisone dosage (mg/day), previous use of JAKi, time to discontinuation (days), reasons of discontinuation, discontinuation rates for each JAKi, line of treatment, DAS28-ESR, b/tsDMARDS naïve patients.Results:693 patients were included in study. 395 (57%) patients received baricitinib, 150 (21.7%) tofacitinib, 94 (13.6%) upadacitinib and 54 (7.8%) filgotinib. The majority of patients were treated with unselective JAKi (78.6% vs 21.4% of selective JAKi). 157 (22.7%) patients discontinued JAKI after a median time of 334 days (IQR 152-869). Details of discontinuation rates for each drug are reported in Table 1.Reasons of discontinuation were primary inefficacy (n=55, 7.9%), secondary inefficacy (n=29, 4.2%), infections (n=9, 1.3%), PE/DVT (n=6, 0.9%), cancer (n=6, 0.9%), deaths (n=2, 0.3%), and other causes (n=7, 3.5%) including remission status in 1 patient. No MACEs were observed in this cohort during the follow up period, although 348 patients (50.2%) had at least one comorbidity at baseline. Notably, both VZV infection (n=3) and DVT/PE (N=6) occurred in patients on treatment with baricitinib.Among 157 patients who discontinued JAKi, a statistical difference between selective and unselective JAKIs was found (15.9% on selective JAKi vs. 84.1% on unselective JAKI, p value <0.001 at log-rank test, Figure 1). Finally selective JAKi were withdrawn before unselective JAKi (median 173 days, IQR 129-22 vs median 401.5 days, IQR 173.5-981).Conclusion:In this real-world cohort, only a minority of patients discontinued JAKi (22.7%). Primary and secondary inefficacy were the most common reasons of JAKi’s withdrawal. All TVP/PE and VZV infections occurred in the baricitinib group, probably due to different overall time of drug’s exposition. Finally, selective JAKis were discontinued earlier than unselective JAKi.REFERENCES:[1] Smolen JS, et al. Ann Rheum Dis 2023.Acknowledgements:NIL.Disclosure of Interests:Maddalena Larosa UCB, ABBVIE, AMGEN, Dario Camellino AStrazeneca, Boerhinger Ingelheim GSK, and Janssen, Andrea Becciolini: None declared, Eleonora Di Donato: None declared, Giuditta Adorni: None declared, Gianluca Lucchini: None declared, Daniele Santilli: None declared, Eugenio Arrigoni: None declared, Elena Bravi: None declared, Ilaria Platè: None declared, Alessandra Bezzi: None declared, Alessandra Bezzi: None declared, Maria Cristina Focherini: None declared, Fabio Mascella: None declared, Vincenzo Bruzzese: None declared, Palma Scolieri: None declared, Simone Parisi: None declared, Maria Chiara Ditto: None declared, Enrico Fusaro: None declared, Viviana Ravagnani: None declared, Guido Rovera: None declared, Alessia Fiorenza: None declared, Rosetta Vitetta: None declared, Antonio Marchetta: None declared, Alessandro Volpe: None declared, BERND RAFFEINER: None declared, Eleonora Celletti: None declared, Myriam Di Penta: None declared, Emanuela Sabatini: None declared, Francesco Cipollone: None declared, Francesca Ometto: None declared, Cecilia Giampietro: None declared, Valeria Nucera: None declared, Aurora Ianniello: None declared, Francesca Serale: None declared, Marta Priora: None declared, Dilia Giuggioli: None declared, Carlo Salvarani: None declared, Gilda Sandri: None declared, Federica Lumetti: None declared, FRANCESCO MOLICA COLELLA: None declared, Veronica Franchina: None declared, Aldo Molica Colella: None declared, Patrizia Del Medico: None declared, Rosalba Caccavale: None declared, Marino Paroli: None declared, Giulio Ferrero: None declared, Natalia Mansueto: None declared, Romina Andracco: None declared, Matteo Colina: None declared, Simone Bernardi: None declared, Francesco Girelli: None declared, Antonella Farina: None declared, Roberta Foti: None declared, Francesco De Lucia: None declared, Giorgio Amato: None declared, Rosario Foti: None declared, Alberto Lo Gullo: None declared, Mirco Magnani: None declared, Olga Addimanda: None declared, Massimo Reta: None declared, Alarico Ariani AMGEN, JANSSEN.

Background:In the last years, there was a dramatic increase of advanced DMARDs for psoriatic arthritis (PsA). There are many b/tsDMARDs with different mechanisms of action (MoA) to consider after the failure of the first advanced line of therapy. As a consequence, the rheumatologists can implement a cycling (same MoA) or swap strategy.Objectives:The aim of this real world based study is to investigate if, after the failure of a TNF inhibitor (TNFi), another TNFi or an interleukin 17 inhibitor (IL17i) is the most effective choice (from a clinical practice point of view).Methods:For this retrospective observational multicenter study, PsA (according to CASPAR criteria) patients who failed a first line TNFi and subsequently received a TNFi or IL17i were enrolled. For each subject, the following characteristics were recorded: anamnestic (age, sex) and disease-related (duration, presence of axial PsA, DAPSA, advanced therapies carried out, csDMARDs and steroids association) data, treatment duration and cause of failure. Patients were divided in two groups according to the strategy used: cycling (i.e. from TNFi to TNFi) (CG) or swap (i.e from TNFi to IL17i) (SG). The Kaplan-Meier curves compared the effectiveness of the two strategies, while multivariable Cox analysis (stepwise) identified the risk factors affecting treatment retention rate.Results:347 subjects were enrolled (M:F 160:187; age 56 years IQR 47-63). In CG and SG were 217 and 130 patients, respectively. The 5 years retention rate in SG was higher than in CG (57,8% vs 45,2%; p=0.1) (Figure 1). Taking into account the whole cohort, the factors predictive of treatment interruption were DAPSA (HR 1.03 CI95% 1.01-1.05; p=0.0009) and swap strategy (HR 0.49 CI95% 0.27-0.90; p=0.02).Conclusion:The swap strategy (i.e. from TNFi to IL17i) was the best choice in PsA patients who failed the first line of advanced treatment. This finding supports the hypothesis that changing the MoA can improve the chances to identify the most effective PsA treatment.Figure 1.REFERENCES:NIL.Acknowledgements:NIL.Disclosure of Interests:Alarico Ariani Amgen, Janssen, Federica Lumetti: None declared, Simone Parisi: None declared, Olga Addimanda: None declared, BERND RAFFEINER: None declared, Alberto Lo Gullo: None declared, Rosario Foti: None declared, Antonella Farina: None declared, Francesco Girelli: None declared, Maddalena Larosa Abbvie, Amgen, UCB, Romina Andracco: None declared, Marino Paroli: None declared, Patrizia Del Medico: None declared, Aldo Molica Colella: None declared, Marta Priora: None declared, Aurora Ianniello: None declared, Francesca Ometto: None declared, Elena Bravi: None declared, Alessandra Bezzi: None declared, Palma Scolieri: None declared, Rosetta Vitetta: None declared, Alessandro Volpe: None declared, Massimo Reta: None declared, Mirco Magnani: None declared, Elisa Visalli: None declared, Giorgio Amato: None declared, Francesco De Lucia: None declared, Roberta Foti: None declared, Simone Bernardi: None declared, Dario Camellino: None declared, Gerolamo Bianchi: None declared, Natalia Mansueto: None declared, Giulio Ferrero: None declared, Rosalba Caccavale: None declared, Veronica Franchina: None declared, FRANCESCO MOLICA COLELLA: None declared, Gilda Sandri: None declared, Carlo Salvarani: None declared, Dilia Giuggioli: None declared, Francesca Serale: None declared, Valeria Nucera: None declared, Cecilia Giampietro: None declared, Eleonora Di Donato: None declared, Giuditta Adorni: None declared, Gianluca Lucchini: None declared, Daniele Santilli: None declared, Ilaria Platè: None declared, Eugenio Arrigoni: None declared, Maria Cristina Focherini: None declared, Fabio Mascella: None declared, Vincenzo Bruzzese: None declared, Enrico Fusaro: None declared, Maria Chiara Ditto: None declared, Alessia Fiorenza: None declared, Guido Rovera: None declared, Antonio Marchetta: None declared, Andrea Becciolini: None declared.

BackgroundRecently, the new class of drugs, namely targeted synthetic (ts) DMARDs, has broadened the possibilities of treating rheumatoid arthritis (RA). In particular, Janus Kinase inhibitors (JAKi) are used in RA and are currently represented by four drugs: baricitinib, tofacitinib, upadacitinib and filgotinib. One of the first to be used in Italy was baricitinib, a JAKi acting on JAK1 and JAK2.ObjectivesThe aim of this study was to evaluate the clinical efficacy of baricitinib in a real-life setting in a cohort of RA patients.MethodsThis multicenter retrospective observational study included patients from 25 rheumatology centers diagnosed with RA and treated with baricitinib. The following were recorded for each patient: gender; age; duration of disease; presence of rheumatoid factor and anti-citrulline antibodies; concomitant treatment with conventional synthetic (cs) DMARDs; previous treatments with biological (b) or ts DMARDs. In order to evaluate the clinical efficacy, the retention rate was evaluated, calculated by means of the Kaplan-Meier method. The variables under examination were reported as frequencies and median with relative interquartile range.ResultsWe included 478 patients of which 380 (79.5%) were female. 286 (60.1%) patients tested positive for rheumatoid factor (RF) and 264 (55,2%) for anti-citrulline antibody (ACPA). The parameters analyzed are shown in Table 1. 105 (22.0%) patients were treated with baricitnib as first line (after csDMARD), the remaining patients had failed at least one bDMARD and 9 (1.9%) also failed a tsDMARD. In 34,7% of cases baricitinib was used as monotherapy, the most frequently used csDMARD was methotrexate (29.2%). The median period of therapy was 674 days (298-1087).The survival rate at 6 months was 94.6%, at 12 months it was 87,9%, at 24 months was 81.7% and at 48 months was 53.4% (Figure 1).The main causes that led to the discontinuation of baricitinib therapy were: primary ineffectiveness (7,3%), secondary ineffectiveness (4.2%) and adverse events (3,7% 5 TEP/DVT). The concomitant steroid therapy seems to be a negative prognostic factor (HR 1,65 95% CI 1.03-2.63; p=0.035) as well as the line of therapy (HR 1.35 95% CI 1.15-1.58; p=0.000).Table 1.CharacteristicsValueM:F98:380Age, median [IQR] yrs60 [51-70]Smokers, n (%) (**)YesFormerNo84 (18,8)76 (17,0)288 (64,2)Body Mass Index, median [IQR] kg/m^2 (*)24,8 [23,0-27,0]Disease Duration, median [IQR], months78 [32-163]RF positivity, n (%)286 (60,1)ACPA positivity, n (%)264 (55,2)SJC, median [IQR]5 [3-8]TJC, median [IQR]8 [4-12]ESR, median [IQR], mm/h33 [20-46]CRP, median [IQR], mg/dl1,3 [0,5-2,9]VAS Patient (0-100), median [IQR]70 [50-80]DAS28, median [IQR]5,4 [4,8-6,1]Line of treatment, [IQR]2 [2-3]Concomitant csDMARDs use, n (%)MTXLFNSSZHCQ140 (29,2)11 (2,3)3 (0,6)12 (2,5)Concomitant steroids use, n (%)237 (49,6)Steroids dose (PDN-Eq), median, mg/die5 [4-5]Prior bDMARDs use, n (%)TNFiIL6iIL1iCD20iCD80i164 (34,3)84 (17,6)08 (1,7)54 (11,3)Prior tsDMARDs use, n (%)Tofacitinib9 (1,9)Concomitant relevant disease, n (%)DiabetesHypercholesterolemiaMACEArterial HypertensionCancer36 (7,5)119 (24,9)28 (5,9)179 (37,4)24 (5,0)Figure 1.4 year retention rate of baricitinibConclusionThe efficacy of baricitinib in the treatment of RA in a real-life context appears consistent with what was reported by the pivotal studies. Furthermore, from this preliminary experience, seropositivity and combo therapy seems to not correlate with a better retention rate, while concomitant steroid therapy and line of treatment are a negative prognostic factor.References[1] Guidelli GM et al. Clin Exp Rheumatol. 2021 Jul-Aug;39(4):868-873.[2] Spinelli FR et al. Clin Exp Rheumatol. 2021 May-Jun;39(3):525-531.Acknowledgements:NIL.Disclosure of InterestsNone Declared.

BackgroundJanus kinase (JAK) inhibitors have been approved for the treatment of Rheumatoid Arthitis (RA) and other systemic or organ-specific autoimmune diseases. Sustained remission or low disease activity are target treatments recomended by European League Against Rheumatism (EULAR) in RA patients [1]. Upadacitinib (UPA), a reversible, oral JAK inhibitor, has been engineered to have a greater selectivity for JAK1 vs JAK2, JAK3, and tyrosine kinase. In the Phase 3 SELECT clinical trial program, UPA has been shown to be effective and well tollerate in patients with RA [2]. However, data on the use of UPA in real-world clinical practice are limited.ObjectivesTo evaluate UPA effectiveness in RA patients and to report the main reasons of suspension and the most relevant factor related to treatment persistence.MethodsIn 25 Italian rheumatological referral centers, all RA consecutive patients who received UPA were enrolled. Anamnestic data, treatment history and RA disease activity at baseline were recorded.The 6 and 12 months UPA retention rate was assessed with the Kaplan-Meier curve methods. The Cox analysis investigated the effect of age, sex, smoke habit, ACPA/RF presence, disease duration, DAS28-CRP, line of treatment, concomitant csDMARD treatment on UPA retention rate. A p-value < 0.05 was considered statistically significant.ResultsThe one-hundred-eleven enrolled patients median age 57 (IQR 50-65 yrs); M:F 28:83; disease duration 78 (IQR 40-170 months). The median observation period was 6.1 (IQR 3.2-10.2) months. The observation lasted 812 patients-months. The majority of patients (54.0%) were in mono-therapy and received steroids (respectively 54.0% and 58.6%) (Table 1).The UPA retention rate at 6, 12 months was, respectively 90.4% and 74.7% (Figure 1). The main discontinuation reason was lack of efficacy (42% of interruptions), cancer onset and infections (both 11%). No thromboembolic events were reported.According to the Cox analysis, no one of the above mentioned parameters were associated to high risk of treatment interruption.Table 1.Baseline characteristics UPACharacteristicsValueM:F28:83Age, median [IQR] yrs58 [50-65]Smokers, n (%) (**)YesFormerNo16 (16,5)17 (17,5)64 (66,0)Body Mass Index, median [IQR] kg/m^2 (*)24,7 [22,4-27,7]Disease Duration, median [IQR], months78 [40-170]RF positivity, n (%)72 (64,9)ACPA positivity, n (%)68 (61,3)SJC, median [IQR]4 [3-8]TJC, median [IQR]8 [5-11]ESR, median [IQR], mm/h32 [20-53]CRP, median [IQR], mg/dl1,2 [0,5-3,3]VAS Patient (0-100), median [IQR]70 [50-80]DAS28, median [IQR]5,5 [4,9-5,9]Line of treatment, [IQR]3 [2-4]Concomitant csDMARDs use, n (%)MTXLFNSSZHCQ41 (36,9)3 (2,7)1 (0,9)5 (4,5)Concomitant steroids use, n (%)65 (58,6)Steroids dose (PDN-Eq), median, mg/die5 [5-6]Prior bDMARDs use, n (%)TNFiIL6iIL1iCD20iCD80i53 (47,7)13 (11,7)02 (1,8)11 (9,9)Prior tsDMARDs use, n (%)BaricitinibTofacitinib9 (8,1)2 (1,8)Concomitant relevant disease, n (%)DiabetesHypercholesterolemiaMACEArterial HypertensionCancer12 (10,8)23 (20,7)5 (4,5)34 (30,6)4 (3,6)Figure 1.ConclusionUPA effectiveness appears to be confirmed. The safety profile of UPA 15 mg in real-world practice is consistent with data from Phase 3 SELECT trials, with no new safety signals.References[1]Smolen JS, et al. Ann Rheum Diseases 2023;82:3-18.[2]Burmester GR et al.Lancet 2018; 23;391(10139):2503-2512Acknowledgements:NIL.Disclosure of InterestsNone Declared.

BackgroundCurrent and previous EULAR recommendations (1,2) suggest using JAK-inhibitors (JAKis) for treating Rheumatoid Arthritis (RA). However, little is known about differences of patients who are JAK-inhibitors (JAKis) naïve and patients who have already experienced at least one JAKi.ObjectivesTo analyse differences between JAK-naïve and JAKis not naive patients in a real life setting.MethodsAll patients with RA on JAKis were prospectively followed up for 12 months in this multicentric study conducted in 23 centres. For each patient, the following variables were recorded: sex, age, disease duration at JAKi prescription, smoking, BMI, comorbidities, positive RF/ACPA, DAS28-ESR at baseline, 6 and 12 months, cDMARDs and prednisone at baseline, JAKis discontinuation, JAK-naïve. Statistics were performed by R (2022.12.0).Results864 patients were included (Table 1). Among them, 731 (84.60%) were JAKis naïve, whereas 122 (14.12%) were not naïve (missing data in 11-1.27%-patients). 473 (55.22%) patients were treated with baricitinib (JAK-naïve were 412, 87.3%), 213 (24.6%) with tofacitinib (JAKis-naïve 187, 87.79%), 111 (12.84%) with upadacitinib (JAKis-naïve 78.37%) and 62 (7.17%) with filgotinib (JAKis-naïve 72.58%). Significant differences between JAKis-naïve and not naïve were found for hypercholesterolemia (p=0.04), hypertension (p=0.02), previous cancer (p<0.001), disease duration (p<0.001), line of treatment (p<0.001). No difference was found for JAKis discontinuation (p=0.13) (Table 1).ConclusionOur data suggest that line of treatment and disease duration result higher in JAKis not naive compared to naïve ones. Notably, JAKis naïve and not naïve did not differ regarding drug discontinuation, suggesting a similar retention rate irrespective of previous JAKis.References[1] Smolen JS, et al. Ann Rheum Dis 2020.[2] Smolen JS, et al. Ann Rheum Dis 2023.Table 1.Differences between JAKis naïve and not naïve patientsTotalTotal (N=864)JAKis naive (N=731)JAKis not naïve (N=122)P valueN (%)N (%)N(%)Mean age at baseline (SD) (N=852)58.83 (12.87)58.54 (12.92)60.61 (12.45)0.10Females (N=853)668 (78.31)564 (77.15)104 (85.25)0.05Mean BMI (Kg/cm2) (SD) (N=616)25.15 (3.77)25.18 (3.62)25.02 (4.46)0.68Smoking (N=788)0.13 Yes150 (19.03)135 (19.97)15 (13.39) No496 (62.94)425 (62.87)71 (63.39) Former142 (18.02)116 (17.16)26 (23.31)Positive RF (N=800)527 (65.89)444 (64.91)83 (71.55)0.16Positive ACPA (N=787)491 (62.39)411 (61.43)80 (67.80)0.19Diabetes (N=760)68 (8.95)56 (8.78)12 (9.84)0.71Hypertension (N=761)297 (39.03)238 (37.25)59 (48.36)0.02Hypercholesterolemia (N=759)195 (25.36)155 (24.29)40 (33.06)0.04Previous MACE (N=758)47 (6.20)39 (6.13)8 (6.56)0.86Previous cancer (N=760)42 (5.52)39 (6.10)3 (2.48)<0.001Disease duration (months), (median, IQR) (N=844)76 (29-155)71 (24-142.50)142 (69-226)<0.001Mean DAS28-ESR at baseline (SD) (N=736)5.29 (1.06)5.27 (1.09)5.40 (0.89)0.22cDMARDs at baseline (N=771)280 (36.31)235 (36.21)45 (36.89)0.88PDN at baseline (N=438)438 (50.69)368 (57.38)70 (56.79)0.90Median dosage (IQR) of PDN (mg/day) (N= 438)5 (4.00-5.00)2.50 (0.00-5.00)4.00 (0.00-5-00)0.08Line of JAKis treatment (N=853)<0.001 1^244 (28.60)244 (33.38)0 (0.00) 2^211 (24.74)207 (28.32)4 (3.28) 3^175 (20.63)172 (23.53)(3.28) 4^109 (12.78)56 (7.66)53 (3.44) 5^65 (7.62)32 (4.38)33 (27.05) 6^28 (3.28)12 (1.64)6 (13.11) 7^12 (1.41)6 (0.82)6 (4.92) 8^3 (0.35)1 (0.14)2 (1.64) 9^2 0.23)1 (0.14)1 (0.82) 10^3 (0.35)0 (0.00)(2.46)Patients who discontinued JAKis (N=853)192 (22.51)158 (21.61)34 (27.87)0.13SD: standard deviation; BMI: Body Mass Index; RF: Rheumatoid Factor; ACPA: Autoantibodies against citrullinated proteins; MACE: Major cardiovascular events; PDN: prednisone; IQR: interquartile range; DAS28-ESR: Disease Activity Score-28 for Rheumatoid Arthritis with ESR; cDMARDs: conventional Disease-modifying antirheumatic agents; JAKis: JAK inhibitors.Acknowledgements:NIL.Disclosure of InterestsMaddalena Larosa: None declared, Andrea Becciolini: None declared, Elena Bravi: None declared, Dario Camellino Speakers bureau: Abiogen, GSK, Paid instructor for: Mylan, Ilaria Platé: None declared, eugenio arrigoni: None declared, Francesca Ometto: None declared, Eleonora Di Donato: None declared, Giuditta Adorni: None declared, Gianluca Lucchini: None declared, Daniele Santilli: None declared, Alessandra Bezzi: None declared, Maria Cristina Focherini: None declared, Fabio Mascella: None declared, Vincenzo Bruzzese: None declared, Palma Scolieri: None declared, Simone Parisi: None declared, Enrico Fusaro: None declared, Maria Chiara Ditto: None declared, Viviana Ravagnani: None declared, Gilda Sandri: None declared, Carlo Salvarani: None declared, Marta Priora: None declared, Marino Paroli: None declared, rosalba caccavale: None declared, Romina Andracco: None declared, Natalia Mansueto: None declared, Matteo Colina: None declared, Massimo Reta: None declared, Olga Addimanda: None declared, Alberto Lo Gullo: None declared, elisa visalli: None declared, Rosario Foti: None declared, Giorgio Amato: None declared, Francesco De Lucia: None declared, antonella farina: None declared, Francesco Girelli: None declared, Patrizia Del Medico: None declared, Aldo Molica Colella: None declared, Veronica Franchina: None declared, Francesco Molica Colella: None declared, Federica Lumetti: None declared, Aurora Ianniello: None declared, Valeria Nucera: None declared, Rosetta Vitetta: None declared, Alessia Fiorenza: None declared, Guido Rovera: None declared, Alessandro Volpe: None declared, Giulio Ferrero: None declared, Antonio Marchetta: None declared, Simone Bernardi: None declared, Gerolamo Bianchi: None declared, Alarico Ariani: None declared.

BackgroundThe recent EULAR recommendations [1,2] suggest using JAK-inhibitors (JAKis) for treating RA patients. These drugs include both selective (upadactinib and filgotinib) and unselective (tofacitinib and baricitinib) JAKis.ObjectivesTo describe JAKis’ discontinuation rate and to determine predictors of JAKIs’ discontinuation in a real life setting.MethodsAll patients with RA treated with JAKis were prospectively followed up for at least 12 months in this multicentric study carried out on 23 Italian centres. For each patient, the following variables were collected: sex, age, disease duration, smoking, BMI, comorbidities (diabetes, hypertension, hypercholesterolemia, cancer, major cardiovascular events), positive RF/ACPA, cDMARDs at baseline, prednisone at baseline, previous use of JAKis, discontinuation, time to discontinuation, JAKis line of treatment, DAS28-ESR at baseline, 6 and 12 months. Statistical analyses were performed using R (2022.12.0).Results864 patients were included (Table 1). 487 (55.2%) received baricitinib, 213 (24.6%) tofacitinib, 111 (12.8%) upadacitinib and 62 (7.2%) filgotinib. 192 (22.2%) patients discontinued JAKis after a median time of 334 days (IQR 154.5-879.5). Among them, a statistical difference was found between selective-JAKis and other JAKis (p=0.03, 14.6% of selective JAKis vs 85.4% of other JAKis); finally unselective JAKis were discontinued later than selective JAKis (p<0.001, median 401.5 days, IQR 197.5-976 for unselective JAKis vs median 74 days, IQR 129-212 for selective JAKis). Discontinuation’s causes are reported in Figure 1. Notably, VZV infection determined JAKis withdrawal in 4 patients and pulmonary embolism/deep venous thrombosis in 6 patients (both with baricitinib). Regarding discontinuations’ causes, no differences between selective JAKis and other JAKis were found with factor logistic regression model. At multivariate analysis, predictors of discontinuation were prednisone at baseline (OR 1.48, p=0.03), treatment with unselective JAKis (OR 1.79, p=0.01), and line of treatment (OR 1.29 p<0.001).ConclusionOur study showed that only a minority of patients discontinued JAKis. Among discontinuation‘s causes, no differences between selective JAKis and other JAKis were found. Predictors of JAKis discontinuation were prednisone at baseline, treatment with unselective JAKis and line of treatment (with more advanced lines of treatment associated with a higher risk of discontinuation).References[1] Smolen JS, et al. Ann Rheum Dis 2020.[2] Smolen JS, et al. Ann Rheum Dis 2023.Table 1.General features of 864 RA patientsVariableN (%)Mean age at baseline (SD) (N=863)58.79 (12.84)Females678 (78.47)Mean BMI (Kg/cm2) at baseline (SD) (N=626)25.19 (3.79)Smoking (N=799)Yes151 (18.89)No504 (63.01)Former144 (18.02)Positive RF (N=809)533 (65.88)Positive ACPA (N=796)498 (61.56)Diabetes (N=770)70 (9.09)Hypertension (N=771)302 (39.17)Hypercholesterolemia (N=769)196 (25.49)Previous MACE (N=768)47 (6.12)Previous cancer (N=770)42 (5.45)Disease duration (months), (median, IQR) (N=855)77 (30-157)Mean DAS28-ESR at baseline (SD) (N=746)5.29 (1.06)cDMARDs at baseline (N=781)287 (36.75)PDN at baseline (N=780)444 (56.92)Median dosage (IQR) of PDN (mg/day)5.00 (4.00-5.00)JAKis naïve (N=853)731 (85.70)Line of JAKis treatment  1^247 (26.59) 2^211 (24.42) 3^181 (20.64) 4^111 (12.84) 5^65 (7.52) 6^29 (3.35) 7^12 (1.39) 8^3 (0.35) 9^2 (0.23) 10^3 (0.35)Patients who discontinued JAKis192 (22.2)Time to discontinuation (days), (median, IQR) (N=863)334 (154.5-879.5)Legends to Table 1: RA: rheumatoid arthritis; SD: standard deviation; BMI: Body Mass Index; RF: Rheumatoid Factor; ACPA: Autoantibodies against citrullinated peptides/proteins; MACE: Major cardiovascular events; PDN: prednisone; IQR: interquartile range; DAS28-ESR: Disease Activity Score-28 for Rheumatoid Arthritis with ESR; cDMARDs: conventional Disease-modifying antirheumatic agents; JAKis: JAK inhibitors.Acknowledgements:NIL.Disclosure of InterestsMaddalena Larosa: None declared, Alarico Ariani: None declared, Dario Camellino Speakers bureau: Abiogen, GSK, Paid instructor for: Mylan, Andrea Becciolini: None declared, Gerolamo Bianchi: None declared, Eleonora Di Donato: None declared, Giuditta Adorni: None declared, Daniele Santilli: None declared, Gianluca Lucchini: None declared, Massimo Reta: None declared, Olga Addimanda: None declared, Alberto Lo Gullo: None declared, elisa visalli: None declared, Rosario Foti: None declared, Giorgio Amato: None declared, Francesco De Lucia: None declared, antonella farina: None declared, Francesco Girelli: None declared, Simone Bernardi: None declared, Giulio Ferrero: None declared, Romina Andracco: None declared, Marino Paroli: None declared, Natalia Mansueto: None declared, rosalba caccavale: None declared, Patrizia Del Medico: None declared, Aldo Molica Colella: None declared, Veronica Franchina: None declared, Francesco Molica Colella: None declared, Federica Lumetti: None declared, Gilda Sandri: None declared, Carlo Salvarani: None declared, Marta Priora: None declared, Aurora Ianniello: None declared, Valeria Nucera: None declared, Francesca Ometto: None declared, Ilaria Platé: None declared, eugenio arrigoni: None declared, Alessandra Bezzi: None declared, Maria Cristina Focherini: None declared, Fabio Mascella: None declared, Vincenzo Bruzzese: None declared, Palma Scolieri: None declared, Simone Parisi: None declared, Maria Chiara Ditto: None declared, Enrico Fusaro: None declared, Viviana Ravagnani: None declared, Rosetta Vitetta: None declared, Alessia Fiorenza: None declared, Guido Rovera: None declared, Alessandro Volpe: None declared, Antonio Marchetta: None declared, Matteo Colina: None declared, Elena Bravi: None declared.

BackgroundFew studies have analized the persistence of ultrasound (US) abnormalities in patients (pts) with Psoriatic Artritis (PA) during the phase of minimal disease activity (MDA)ObjectivesTo investigate the prevalence of US alterations at enthesis, joint and tendon levels in pts with psoriatic arthritis (PA) during a phase of MDA.MethodsPts treated with anti-tumor necrosis factor (TNF) for at least 12 months and with at least 6 months duration of MDA were consecutively recruited at 6 Italian centers. In every center, the local rheumatologists provided PA pts to be examined by US. Personal history, demographic and clinical data were recorded. Each patient underwent the following US examinations: metacarpophalangeal (MCP), knee and tibio-tarsal (TT) joint, flexor and extensor tendon of hand digit, flexor and extensor tendon at carpal area, flexor and extensor tendon of foot, and enthesis of common extensor tendon insertion on the lateral epicondyle of the humerus, quadriceps tendon, patellar tendon, Achilles tendon and plantar fascia insertions on the calcaneus. Each examination were performed by rheumatologists expert in US, to assess synovitis (joint effusion, synovial proliferation, and power Doppler (PD) signal), and bone erosions, flexor tendon tenosynovitis, hand finger extensor tendon tenonitis, and enthesel involvement using an Esaote MyLabClass with a 5–13 or 6–18 MHz linear probe. The following elementary lesions were assessed at each enthesis: morphologic abnormalities (hypoechogenicity and/or thickening), entheseal calcific deposits, cortical abnormalities (bone erosion and/or proliferation), adjacent bursitis and intraenthesis and perienthesis (tendon body and/or bursa) PD signal. All US findings were scored using a 4 degree semiquantitative scoring system. US acute enthesitis was defined by the presence of entheseal edema or PD signal. US chronic entheseal alterations by the presence of calcifications, erosions, or enthesophytes. US peripheral active synovitis if synovial hypertrophy was associated with the presence of PD signal. US examinator were blind of clinical data of the pts.ResultsSixty-three pts were recruited (mean age 53±13y, mean PA duration 13±8y, mean MDA duration 21±11m). At US examination 66.7% of pts had at least one peripheral joint involved (17.5% had peripheral active synovitis), 47.6% had acute enthesitis and 95.2% chronic enthesopathy. US bursitis was present in 22.2% of pts, 3.7% had hand extensor finger tendon involvement.Table 1shows clinical and demographical data of the pts and table 2 the US resultsNail involvementPrevious dactylitisFamHystIBP Patients with abnormality (%)28.342.923.919.7Table 2.US abnormalities in 63 pts in MDAPerypheral active sinovitisJoint peripheral involvementChronic entheseal alterationsAcute entheseal alterationsTenosynovitis Patients with abnormality (%)17.566.795.247.629.6ConclusionsJoint, entheseal and tendon abnormalities have a high prevalence in PA patients treated with anti-TNF during MDA.Disclosure of InterestNone declared