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200220212025

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1AB0068 LONG-TERM FOLLOW-UP OF PATIENTS WITH RHEUMATIC DISEASES AND SARS-CoV-2 INFECTION: DATA FROM THE SAR-COVID REGISTRY

Isnardi C.A.,Alfaro M.A.,Virasoro B.M.,Gómez G.,D´angelo M.E.,Saurit V.,Petkovic I.E.,Quintana R.,Tissera Y.,Pisoni C.,Berbotto G.,Haye Salinas M.,

Background: Patients with rheumatic diseases (RD) have a more severe SARS-CoV-2 infection and an unfavorable outcome particularly associated with the disease activity and some of the treatments used. Objectives: To describe the SARS-CoV-2 infection outcomes in patients with RD and to assess the post-covid syndrome development. Methods: Observational study. Patients with RD and confirmed SARS-CoV-2 infection (RT-PCR and/or positive serologies) from the SAR-COVID registry were included. The data were collected from August 2020 to June 2023. Patients with unknown outcome and/or with discordant dates in which the duration of symptoms could not be established were excluded. Post-COVID syndrome (PCS) was defined as a condition characterized by the persistence of symptoms for more than 4 weeks. Results: 2707 patients were included, 81.7% female, with a mean age of 51.4 (SD15.5) years. The most common RD were rheumatoid arthritis (44.2%) and systemic lupus erythematosus (16.4%). Most patients presented symptoms (94%), the most common being fever (60.4%), cough (51.6%) and headache (40.6%). The majority (78.1%) had an outpatient course, while 6.4% had a World Health Organization ordinal scale (WHO-OS) value ≥5 and 4.0% died. After excluding patients who died, 493/2598 (19%) PCS cases were identified. This group was older, with a greater frequency of Caucasian ethnicity and comorbidities. Likewise, symptoms such as fever, headache, cough, dyspnea, chest pain, confusion, arthromyalgia, anosmia and dysgeusia were more prevalent in this group. They were also hospitalized more frequently (35.1% vs 15.3%, p<0.01), the severity of COVID-19 was greater (EO-WHO≥5) (Figure 1) and they presented more complications, including respiratory distress syndrome (9.1 % vs 0.8%, p<0.01) and sepsis (2.4% vs 0.1%, p<0.01) (Figure 2). In the 189 patients with PCS with a 12-month follow-up, the most frequent symptoms were fatigue and dyspnea. In the multivariable analysis, the presence of some symptoms during the acute episode, including dyspnea, anosmia, chest pain, cough, fever (OR 2.96-1.57), and fibromyalgia diagnosis (OR 2.33, 95%CI 1.54, 3.48) were associated with the development of PCS. Follow-up data was collected from 1075 patients, of whom 89 reported at least a second SARS-CoV-2 infection. Conclusion: In this cohort of patients with RD and confirmed SARS-CoV-2 infection, 2 out of 10 patients developed PC, with fatigue and dyspnea being the most common prolonged symptoms. Patients who presented this condition had more severe acute COVID-19. REFERENCES: NIL. Acknowledgements: NIL. Disclosure of Interests: Carolina Ayelen Isnardi Pfizer, Elea Phoenix, Abbvie, Maria Agustina Alfaro: None declared, Belén María Virasoro: None declared, Gimena Gómez: None declared, Maria Eugenia D´Angelo: None declared, Verónica Saurit: None declared, Ingrid Eleonora Petkovic: None declared, Rosana Quintana: None declared, Yohana Tissera: None declared, Cecilia Pisoni: None declared, Guillermo Berbotto: None declared, Maria Haye Salinas: None declared, Sofia Ornella: None declared, Mariana Pera: None declared, Alvaro Andres Reyes: None declared, Roberto Baez: None declared, Dora Aida Pereira: None declared, Gelsomina Alle: None declared, Vanessa V. Castro Coello: None declared, Paula Alba: None declared, Adriana Karina Cogo: None declared, Carla G Alonso: None declared, Carla Gobbi: None declared, Josefina Gallino Yanzi: None declared, Guillermo Pons-Estel: None declared.

2024Annals of the Rheumatic Diseases（2024）

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2AB0855 SJÖGREN SYNDROME: PREVALENCE OF PERIPHERAL NEUROLOGICAL MANIFESTATIONS DURING DISEASE PROGRESSION

Pallo M., Marcé A., Bejarano V., Ingolotti L.,Amitrano C.,Asnal C.,Pucci P.,Duartes Noé D.,Gomez A.,Rollano Perasso A.,Zalles S.,Caeiro F.,

Background: Primary Sjogren´s syndrome (pSS) is an autoimmune disease that presents systemic manifestations one of the most significant is tehe involvement of the peripheral nervous system. It may appear as the onset of SSp, although the most severe forms occur as a late manifestation. Objectives: Describe the frequency of patients with pSS debuting with PNS involvement and those developing it during follow-up. Compare disease progression between patients with this involvement and those without, and between those debuting with PNS involvement versus those developing it during follow up. Methods: Observational, analytical, multicenter cross- sectional study. Included patients diagnosed with pSS according to ACR-EULAR 2016 and/or American-European 2002 classification criteria, aged 18 or older, and registered in the GESSAR group database who had at least one consultation. Patients with other autoimmune diseases and those with prior neurological pathology or attributable to other causes were excluded. Results: 681 patients were included with a mean age of 54 years (± 14), 95% female, with a mean follow-up of 4.6 years (±5). 10.57% presented PNS commitment; In 8.33% it was the debut of the disease. In the bivariate analysis, comparing patients with and without PNS manifestations, statistically significant differences were found in: Age (mean: 58 vs 54 p. 0.03), Arthritis (OR 1.93 95% CI 1.17- 3.18), Purpura (OR 2.59 95% CI 1.22-5.47), Raynaud (OR 2.06 95% CI 1.15-3.69), C3 (OR 2.08 95% CI 1.01- 4.31), C4 (OR 2.15 95% CI 1.18- 3.92), corticosteroids use (OR 1.84 95% CI 1.04-3.24), immunosuppressive drugs use (OR 2.05 95% CI 1.17 – 3.59). In the multivariate analysis, a significant and independent association was found with age (OR 1.02 95% CI 1- 1.04), arthritis (OR 1.89 95% CI 1.13-3.18), purpura (OR 2.31 95% CI 1.05-5.05) and Raynaud (OR 2 95% CI 1.10-3.66). No statistically significant differences were found when comparing PNS involvement at onset vs. during follow-up. Conclusion: We observed a frequency of PNS involvement within the range reported in the literature. Comparing both groups, we observed greater systemic involvement in patients with this manifestation; suggesting closer monitoring of this patient subgroup. REFERENCES: NIL Acknowledgements: NIL. Disclosure of Interests: None declared.

2024Annals of the Rheumatic Diseases（2024）

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M A Cosatti,S A Muñoz, M T Tamborenea,M García,A Curti, A Cappuccio,O Rillo,P M Imamura,E Schneeberger,F Dal Pra, M Ballent,M L Cousseau,

OBJECTIVE:To assess the relationship between smoking exposure and organ damage accrual measured by Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index for Systemic Lupus Erythematosus score (SLICC-SDI) in consecutive patients with systemic lupus erythematosus (SLE) from Argentina. METHODS:623 consecutive SLE patients (fulfilling ≥4, 1997 ACR criteria) were included in this cross-sectional study. Sociodemographic and disease related variables including SLICC-SDI score and smoking status were collected. Patients currently smoking were considered "smokers", and "non-smokers" those who never smoked and former smokers. SLICC-SDI was divided into two categories: <3 and ≥3 was defined as severe damage. RESULTS:Six hundred and 23 patients were included in the analysis, 89% women. Eighty-four per cent were non-smokers and 16 % were current smokers 83 percent of patients had SLICC-SDI <3 and 17 % had SLICC-SDI ≥3. Twenty one percent of patients with SLICC-SDI ≥3 and 15% with <3 SLICC-SDI were current smokers (p 0.081). In the multiple regression analysis, current smoking (OR 1.82, CI 95% 1.01-3.31, p 0.046), older age (OR 1.04, CI 95% 1.00-1.05, p 0.034), disease duration (OR 1.03, CI 95% 1.00-1.07, p 0.021) and cyclophosphamide exposure (OR 2.97, CI 95% 1.49-5.88, p 0.002) were related to SLICC-SDI ≥3. CONCLUSION:In our sample of patients, current smoking, older age, disease duration and cyclophosphamide were related to severe damage (SLICC-SDI ≥3).

2024Lupus（2024）

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4POS0084 SAFETY OF TARGETED THERAPIES IN IMMUNE MEDIATED INFLAMMATORY DISEASES: COMBINED DATA FROM FIVE COUNTRIES OF LATIN AMERICA

De Abreu Trigueros P.,Alpizar-Rodriguez D.,Rivera Terán V., Laurindo I.M.,Pons-Estel G.,Haye Salinas M.,Alfaro M.A.,Saurit V.,Catay E., Medina G., Stadler Kahlow B.,Miranda J.R.,

Background: Biologic and targeted synthetic disease-modifying antirheumatic drugs (ts/bDMARDs) play a pivotal role in the treatment of Immune-mediated inflammatory diseases (IMID). Additionally, in the last few years, biosimilars and generic targeted synthetic (ts) DMARDs have been introduced. Objectives: Determine the frequency and severity of adverse event (AE) of patients under ts/bDMARDs in patients with IMID in four BIOBADA Registries in five Latin American countries. Methods: Data from four BIOBADA Registries from Latin America were collected, including Argentina, Brazil, Mexico, Paraguay, and Uruguay (the last two countries are included at the same registry). For this analysis, those patients with IMID, who had started at least one biological or small molecule drug until October 2023 were included. Results: A total of 12477 patients were included (9170 (73.5%) with ts/bDMARDs and 3307 (26.5%) were controls with conventional disease- modifying drugs, cDMARDs). 76.5% were women, the mean age at treatment initiation was 48.2 ±15.3 years. The most common diagnosis was rheumatoid arthritis with 70,7%, followed by ankylosing spondylitis with 8.4%.19516 treatment cycles were administered. Of the ts/bDMARDs the most frequent were the original TNF inhibitors (anti-TNFo) with 9075 (62,5%), the original Rituximab (RTXo) with 1168 (8%), IL-6 inhibitor with 1198 (8.3%) and the original JAKs inhibitors with 943 (6.5%). A total of 17248 AEs were reported of which 2478 (14.4%) were severe and 145 (0.8%) were mortal (Table 1). 35.9% (7004) of the total number of treatment cycles had at least 1 AE. Infections were the most frequently observed AE with 19.4% (3399), followed by respiratory and thoracic disorders 10.6% (1833), skin disorders 10.4% (1789), among the most frequent. In the multivariate analysis, cycles with IL-6 inhibitors were significantly associated with an increased risk of developing AE (OR= 1.9 IC [95%, 1.6-2.2] p<0.001), as well as with anti-TNFo (OR= 1.5 I [C 95%, 1.4-1.6 ]p<0.001), RTXo (OR= 1.7 [IC 95%, 1.5-2.0] p<0.001) and abatacept (OR= 1.4 [IC 95%, 1.3-1,7] p<0.001) (Figure 1). Also having a longer time of disease evolution at the beginning of the treatment cycle (OR= 1.0 IC 95 [%, 1.01-1.02] p<0.001), arterial hypertension (OR= 1.1 IC [95%, 1.1-1.2] p<0.001) and smoking habit (OR= 1.2 IC [95%, 1.1-1.3] p<0.001) were shown to have the same effect. Conclusion: We describe the real-life safety with targeted therapies in four BIOBADA Registries in five Latin American countries, being comparable to that found in other cohorts REFERENCES: NIL. Acknowledgements: NIL. Disclosure of Interests: None declared. Table 1Frequency of adverse events by countriesType of Adverse EventsArgentinan (%)Braziln (%)Mexicon (%)Paraguayn (%)Uruguayn (%)Totaln (%)Infections and infestations2441 (39.3)298 (2,3)77 (34.7)586 (43.3)87 (27.4)3399 (19.1)Respiratory/ thoracic disorders192 (3.1)1465 (16.0)5 (2.6)114 (8.4)57 (18.0)1833 (10.6)Skin disorders381 (6.1)1220 (13.4)28 (12.6)113 (8.3)47 (14.8)1789 (10.4)Musculoskeletal disorders211 (3.4)887 (9.7)4 (1.8)29 (2.1)6 (1.9)1137 (6.6)Renal disorders83 (1.3)1007 (11.0)8 (3.6)22 (1.6)9 (2.8)1129 (6.6)Gastrointestinal disorders372 (6.0)662 (7.2)14 (6.3)66 (4.9)9 (2.8)1123 (6.5)Metabolism and nutrition disorders163 (2.6)713 (7.8)6 (2.7)35 (2.6)5 (1.6)922 (5.4)Medical and surgical procedures282 (4.5)268 (2.9)6 (2.7)68 (5.0)1 (0.3)625 (3.6)Nervous system disorders247 (4.0)253 (2.8)9 (4.0)51 (3.8)6(81.9)566 (3.9)Others*6213 (29.6)2367 (25.9)65 (29.2)271 (20.0)91 (28.6)5350 (31.0)Total6213 (100)9140 (100)222 (100)1355 (100)318 (100)17248 (100)

2024ANNALS OF THE RHEUMATIC DISEASES（2024）

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5CLUSTER ANALYSIS TO IDENTIFY PATIENT GROUPS AND ASSESS THE PRESENCE OF ADVERSE EVENTS. REAL WORLD EVIDENCE FROM THE BIOBADASAR 3.0 REGISTRY

J. A. Brigante,K. Roberts,C. Isnardi,G. Gomez,M. Haye,M. Garcia,C. Gobbi,G. Casado,L. L. Holguin Arias,J. M. Dapena,S. Papasidero,G. Berbotto,

2023ANNALS OF THE RHEUMATIC DISEASES（2023）

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6AB0580 PREGNANCY OUTCOMES IN SYSTEMIC LUPUS ERYTHEMATOSUS (SLE): DATA FROM A MULTIETHNIC, MULTINATIONAL LATIN AMERICAN COHORT

R. M. Serrano Morales,R. Nieto,R. Quintana,P. Alba,S. Porta,L. Hernandez,G. Berbotto,V. I. Bellomio, N. Da Silva,O. Monticielo,F. Cavalcanti,F. Machado Ribeiro,

Background Obstetric morbidity (OM) is higher in SLE women than in healthy ones. Few data on SLE pregnancy outcomes in Latin America (LA) have been reported. Objectives To study SLE pregnancy outcomes in LA. Methods GLADEL 2.0 is an observational prevalent/incident cohort started in 2019. To date, 43 centers from 10 LA countries have enrolled 1030 SLE patients (1982/1997 ACR or SLICC criteria). Women with ≥1 pregnancy were included. Past and ongoing (6, 12, 24 months follow-up) OM (miscarriages, fetal deaths, preeclampsia, prematurity, neonatal lupus) were evaluated. Results At inclusion, 329 women have had at least one pregnancy [median (IQR): 2 (1-3)]: Table 1. Of them, 293 (89.1%) had ≥1 live birth and 183 (55.6%) developed OM. Preeclampsia occurred in 49 (14.9%). Among 71 (21.6%) women with anti-SS-A(Ro)/SS-B(La) antibodies, 3 (4.2%) developed neonatal lupus (no cardiac involvement). Antiphospholipid syndrome (APS) was associated with higher risk of OM (52.2% vs 10.0%; p< 0.001). Of the 755 pregnancies reported, 551 (73.0%) resulted in live births, of which 79 (14.3%) were premature. The remaining pregnancies ended in 178 (23.6%) miscarriages and 41 (5.4%) fetal deaths. During 2-follow-up years (Figure 1), 24 singles pregnancies occurred. All were under antimalarials; 16 (66.7%) resulted in live births, 4 (25.0%) premature; 12 (50.0%) developed OM. There were seven (29.2%) miscarriages and one fetal loss (4.2%) related to severe preeclampsia. One cholestasis gravidarum (4.2%) lead to prematurity. There were no new cases of neonatal lupus. Conclusion In GLADEL 2.0 cohort, around half of the studied women presented OM being frequently related to APS. Miscarriages, prematurity, preeclampsia and fetal deaths were the most common pregnancy complications. The incidence of neonatal lupus was lower than previously reported [1]. Reference [1]Cimaz R, et al. Incidence and spectrum of neonatal lupus erythematosus: a prospective study of infants born to mothers with anti-Ro autoantibodies. J Pediatr 2003; 142: 678–83. Acknowledgements: NIL. Disclosure of Interests Rosa Maria Serrano Morales: None declared, Romina Nieto: None declared, Rosana Quintana: None declared, Paula Alba: None declared, Sabrina POrta: None declared, Lucia Hernández: None declared, Guillermo Berbotto: None declared, Verónica Inés Bellomio: None declared, Nílzio da Silva: None declared, Odirlei Monticielo: None declared, Fernando Cavalcanti: None declared, Francinne Machado Ribeiro: None declared, Eduardo Borba: None declared, Eloisa Bonfa: None declared, loreto massardo: None declared, Gustavo Aroca Martínez: None declared, Andrés Cadena Bonfanti: None declared, GERARDO QUINTANA LOPEZ: None declared, Mario Javier MORENO ALVAREZ: None declared, Jorge Antonio Esquivel Valerio: None declared, Isabel Acosta-Colman: None declared, Astrid Paats: None declared, CLAUDIA MORA: None declared, Marina Scolnik: None declared, Diana Fernández Ávila: None declared, Carmen Funes Soaje: None declared, Veronica Saurit: None declared, Mercedes García: None declared, Eduardo Kerzberg: None declared, Graciela Gomez: None declared, Cecilia Pisoni: None declared, Edgard Reis Neto: None declared, Iris Guerra Herrera: None declared, Oscar Neira: None declared, Carlos Cañas: None declared, Miguel A Saavedra: None declared, Margarita Portela: None declared, Hilda Fragoso loyo: None declared, Luis Humberto Silveira Torre: None declared, Ignacio Garcia-De La Torre: None declared, Manuel F. Ugarte-Gil: None declared, Armando Calvo Quiroz: None declared, Roberto Muñoz Louis: None declared, RICARDO ROBAINA: None declared, Vicente Juarez: None declared, ALVARO DANZA: None declared, Carlos Enrique Toro Gutierrez: None declared, Carlos Abud-Mendoza: None declared, Ana Malvar: None declared, Graciela S Alarcon: None declared, Ashley Orillion Shareholder of: Janssen Research & Development, Spring House, USA, Speakers bureau: Janssen Research & Development, Spring House, USA, Paid instructor for: Janssen Research & Development, Spring House, USA, Consultant of: Janssen Research & Development, Spring House, USA, Grant/research support from: Janssen Research & Development, Spring House, USA, Employee of: Janssen Research & Development, Spring House, USA, Urbano Sbarigia Shareholder of: Janssen Pharmaceutica NV, Beerse, Belgium, Speakers bureau: Janssen Pharmaceutica NV, Beerse, Belgium, Paid instructor for: Janssen Pharmaceutica NV, Beerse, Belgium, Consultant of: Janssen Pharmaceutica NV, Beerse, Belgium, Grant/research support from: Janssen Pharmaceutica NV, Beerse, Belgium, Employee of: Janssen Pharmaceutica NV, Beerse, Belgium, Federico Zazzetti Shareholder of: Janssen Pharmaceutical Companies of Johnson & Johnson, Horsham, PA, USA;, Speakers bureau: Janssen Pharmaceutical Companies of Johnson & Johnson, Horsham, PA, USA;, Paid instructor for: Janssen Pharmaceutical Companies of Johnson & Johnson, Horsham, PA, USA;, Consultant of: Janssen Pharmaceutical Companies of Johnson & Johnson, Horsham, PA, USA;, Grant/research support from: Janssen Pharmaceutical Companies of Johnson & Johnson, Horsham, PA, USA;, Employee of: Janssen Pharmaceutical Companies of Johnson & Johnson, Horsham, PA, USA;, Guillermo Pons-Estel: None declared, Bernardo Pons-Estel: None declared.Figure 1SLE pregnancy outcome 2-year follow-up.Table 1Characteristics of SLE women with ≥1 pregnancy at cohort inclusion related to OM1.VARIABLESOM1p value2VARIABLESOM1p value2Epidemiological/ComorbiditiesNo (n=146)Yes (n=183)SLE backgroundNo (n=146)Yes (n=183)Age (years)341 (34-47)39 (31.5-50)0.542Disease duration (months)376 (28-153)100 (36.5-162.5)0.136Education (years)312 (10.2-15)12 (10-15)0.664Antiphospholipid syndrome3/30 (10%)24/46 (52.2%)0.001Ethnicity0.299LaboratoryAfro-Latin American14/146 (9.6%)8/183 (4.4%)Anti-dsDNA antibodies107/134 (79.9%)139/172 (80.8%)0.885White30/146 (20.5%)42/183 (23.0%)Anti-Ro antibodies51/109 (46.8%)57/135 (42.2%)0.518Amerindian3/146 (2.1%)4/183 (2.2%)Anti-La antibodies20/107 (18.7%)18/132 (13.6%)0.293Mestizo99/146 (67.8%)129/183 (70.5%)C3 and/or C4, low117/141 (83.0%)147/174 (84.5%)0.760Socioeconomic level0.184Lupus anticoagulant17/92 (18.5%)34/121 (28.1%)0.109High29/143 (20.3%)41/181 (22.7%)aCL4 IgG21/101 (20.8%)34/129 (26.4%)0.353Medium42/143 (29.4%)67/181 (37.0%)aCL4 IgM15/101 (14.9%)33/130 (25.4%)0.071Low72/143 (50.3%)73/181 (40.3%)Anti-ß2GP15 IgG11/79 (13.9%)15/95 (15.8%)0.832Medical coverage0.260Anti-ß2GP15 IgM10/79 (12.7%)15/95 (15.8%)0.666Complete/partial94/141 (66.7%)133/182 (73.1%)TreatmentNo Coverage47/141 (33.3%)49/182 (26.9%)Corticosteroids143/146 (97.9%)176/181 (97.2%)0.736Hypertension47/83 (56.6%)73/110 (66.4%)0.180Antimalarials141/146 (96.6%)177/181 (97.8%)0.520Diabetes mellitus9/83 (10.8%)6/110 (5.5%)0.184Immunosuppressors118/146 (80.8%)152/179 (84.9%)0.373Dyslipidemia23/78 (29.5%)31/109 (28.4%)0.872Aspirin30/42 (71.4%)53/65 (81.5%)0.243Smoking22/50 (44.0%)34/58 (58.6%)0.176Anticoagulation18/42 (42.9%)33/66 (50.0%)0.5541 Obstetric morbidity; 2 statistically significance: p < 0.05; 3 median (interquartile range); 4 anti-cardiolipin antibodies; 5 beta-2 glycoprotein I antibodies.

2023ANNALS OF THE RHEUMATIC DISEASES（2023）

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7OUTCOMES OF SARS-COV-2 INFECTION IN PATIENTS WITH ASSOCIATED ANCA VASCULITIS. DATA FROM THE NATIONAL SAR-COVID REGISTRY

J. A. Brigante,C. A. Isnardi, D. Emili,V. Saurit,Y. Tissera,M. E. D'Angelo,I. Petkovic,C. Pisoni,R. Quintana,R. Baez,S. Ornella,V. V. Castro Coello,

2023ANNALS OF THE RHEUMATIC DISEASES（2023）

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8AB1666 CLUSTER ANALYSIS TO IDENTIFY PATIENT GROUPS AND ASSESS THE PRESENCE OF ADVERSE EVENTS. REAL WORLD EVIDENCE FROM THE BIOBADASAR 3.0 REGISTRY

J.A. Brigante,K. Roberts,C. Isnardi,G. Gómez,M. Haye,M. García,C. Gobbi,G. Casado,L.L. Holguín Arias,J.M. Dapeña,S. Papasidero,G. Berbotto,

Background The clinical manifestations of patients with rheumatic diseases are highly heterogeneous. The appearance of adverse events (AEs) related to the treatments received for these diseases considerably increases the morbidity and mortality of these patients. This is why obtaining real-world data on these AEs and analyzing their causes is paramount. The BIOBADASAR registry has data from 5,676 patients over ten years of follow-up. Classifying patients in treatment with biological drugs into subgroups with different phenotypes through unsupervised grouping could provide valuable information on the characteristics associated with specific AE. Objectives Through cluster analysis, this study aimed to identify different clinical phenotypes related to Adverse events in patients treated with biological drugs. Methods Retrospective, multicenter study of patients with rheumatic diseases treated with original biological drugs, biosimilars, or original and generic targeted therapies in Argentina; follow-up from August 2010 to July 2021. Demographic and clinical data, time of initiation and completion of treatments, data on disease activity, and the AEs presented were collected.Patients were unbiasedly matched based on their clinical and phenotypic profiles using a k-means pooling method. The initiation of biological disease-modifying antirheumatic drugs (b-DMARD) was evaluated in the segregated groups to investigate each group's clinical course and differential characteristics. Results A total of 5676 patients were analyzed. Three different clusters were obtained:Cluster 1: 1041 patients. Was observed an evolution time of the disease of 30.5 years (Q1 25.8; Q3 35.6) longer than other clusters and a longer delay in starting treatment at 18.3 years (Q114.4; Q3 24) p < 0.0001.Cluster 2: 2136 patients. We observed a higher frequency of patients with Systemic Lupus Erythematosus: 156 (7.3%) p<0.0001 and a lower frequency of AEs 190 (8.9%) p <0.0001Cluster 3: 2499 patients. We observed a higher mean age than in the other two clusters, 57.3 (SD 8.3) p < 0.001.The use of systemic corticosteroids was evenly distributed among the 3 clusters. Conclusion The unsupervised grouping of patients from the BIOBADASAR registry demonstrated the existence of clusters based on clinical and demographic characteristics. Identifying high-risk patients through a combination of these parameters may be helpful for the early identification of risk factors and their association with adverse events.Based on our hierarchical cluster analysis, we identified different patient phenotypes.Our results show that within the heterogeneity of patient characteristics, common elements provide a basis for future analyses of these variables and their relationship with certain AEs. REFERENCES: NIL. Acknowledgements: NIL. Disclosure of Interests Jorge Alejandro Brigante Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Karen Roberts Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Carolina Isnardi Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Gimena Gómez Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Maria Haye Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Mercedes García Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Carla Gobbi Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Gustavo Casado Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Laura Lucia Holguín Arias Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Joan Manuel Dapeña Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Silvia Papasidero Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Guillermo Berbotto Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Malena Viola Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Veronica Saurit Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Ingrid Petkovic Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Ana Bertoli Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Monica Patricia Diaz Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Erika Catay Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Ida Elena Exeni Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Bernardo Pons-Estel Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Gladys Bovea Castelblanco Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Mercedes Elena De La Sota Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Maria Silvia Larroude Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Dora Aida Pereira Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Amelia Beatriz Granel Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Gustavo Medina Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Cecilia Pisoni Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., MONICA SACNUN Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Edson Velozo Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Nora Aste Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Cecilia Castro Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Eduardo Kerzberg Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Veronica Savio Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., JULIETA GAMBA Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Anastasia Secco Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Gustavo Citera Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Enrique Soriano Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Cesar Graf Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Guillermo Pons-Estel Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database., Maria de la Vega Grant/research support from: BIOBADASAR has received an unrestricted Grant from Pfizer. Pfizer has not participated in or influenced the project's development, data collection, analysis, interpretation, or report writing. They do not have access to the information collected in the database.Graphics 1K-means cluster analysis graph. Distribution of patients according to the cluster they belong to.Dim1: Principal component 1; Dim2: Principal component 2.

2023Annals of the Rheumatic Diseases（2023）

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9AB0767 OUTCOMES OF SARS-COV-2 INFECTION IN PATIENTS WITH ASSOCIATED ANCA VASCULITIS. DATA FROM THE NATIONAL SAR-COVID REGISTRY

J.A. Brigante,C.A. Isnardi, D. Emili,V. Saurit,Y. Tissera,M.E. D'Angelo,I. Petkovic,C. Pisoni,R. Quintana,R. Baez,S. Ornella,V.V. Castro Coello,

Background Systemic vasculitis are rare autoimmune diseases that can lead to multiple organs and systems involvement. ANCA-associated vasculitis presents characteristics that differentiate them from other vasculitides. There is evidence that infection by (SARS-CoV-2) impacts differently in patients with various underlying diseases and different comorbidities, even generating differences in the morbidity and mortality of the viral infection. Objectives To describe the clinical characteristics and outcomes of SARS-CoV-2 infection in patients with systemic vasculitis. Methods Observational, multicenter, cross-sectional analytical study in patients 18 or older diagnosed with systemic vasculitis with confirmed SARS-CoV-2 infection (RT-PCR or serology) included in the SAR-COVID registry. Patients were evaluated from July 2020 to February 2022. Patients diagnosed with ANCA-associated vasculitis (AAV), other systemic vasculitides (Giant cell arteritis, Takayasu), and a control group of patients with other rheumatological diseases matched by age, sex, comorbidities, and date of SARS-CoV-2 infection. The survival curve of the groups was studied by Kaplan-Meier and compared through the Log-Rank Test. A Cox regression model will be performed to adjust survival for different variables (sex, age, treatments for underlying disease, treatments for viral infection, smoking, obesity, d-dimer level, and disease activity). Results A total of 282 out of 2694 patients in the SAR-COVID registry were included, 57.4% women with a mean age of 55.7 years (SD 14.1). Fifty-four patients in the AAV group, 32 in the other vasculitis group, and 196 controls were studied. In 51.1% of the cases, one or more comorbidities were observed. We found caucasian ethnicity at 50.7%, mestizo at 39.7%, and other ethnic groups at 9.6%. PCR made the diagnosis of COVID-19 in 81.2% of the cases. The controls had treatment with corticosteroids before the onset of symptoms in 30.1% of the cases, while 64.8% and 68.8% in the AAV group and other vasculitides, respectively (p < 0.001). Hospitalization was required in 53.7% of the AAV group, 37.5% in other vasculitides, and 26.2% in the control group. 5.6% of patients in the control group presented acute respiratory distress syndrome (ARDS), 15.6% in the other vasculitis group, and 22.2% in the AAV group (p<0.001), requiring invasive mechanical ventilation in 13% of the control group. 33.3% of the other vasculitis group and 57% of the patients in the AAV group (p<0.001) Complete recovery was observed in 82.3% of patients in the control group, 75% in the other vasculitis group, and 63% in the AAV group. We observed that 5.7% of the patients in the control group died from COVID-19, 9.4% from other vasculitides, and 27.8% in the AAV group (p<0.001). We found a lower survival in the AAV group compared to the control group (p <0.005). In the multivariate Cox regression model, we can see that older age (HR:1.05 IC95% 1.01-1.09 p=0.01), BMI>40 (HR:13.2 IC95% 2.1-83.2 p=0.01), and high activity of the underlying disease (HR:16 95% CI 3.7-69.4 p<0.005) were associated with lower survival. Conclusion In conclusion, we can mention that patients diagnosed with AAV presented a worse evolution of the disease caused by SARS-CoV-2 with a more frequent requirement for invasive mechanical ventilation. Likewise, these patients showed lower survival compared to other autoimmune diseases. REFERENCES: NIL. Acknowledgements: NIL. Disclosure of Interests Jorge Alejandro Brigante Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Carolina Ayelen Isnardi Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Daiana Emili Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Veronica Saurit Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Yohana Tissera Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Maria Eugenia D´ angelo Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Ingrid Petkovic Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Cecilia Pisoni Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Rosana Quintana Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Roberto Baez Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Sofia Ornella Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Vanessa Viviana Castro Coello Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Mariana Pera Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Maria Haye Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Dora Aida Pereira Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Guillermo Berbotto Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Carla G Alonso Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Carla Gobbi Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Alvaro Andres Reyes Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Paula Alba Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Edson Velozo Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., María Julieta Gamba Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Romina Tanten Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., María Severina Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., David Zelaya Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Gelsomina Alle Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Adriana Karina Cogo Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Romina Nieto Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., CECILIA ASNAL Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Juan A Albiero Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Micaela Cosatti Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Jaime Villafañe Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Federico Maldonado Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database., Guillermo Pons-Estel Grant/research support from: Grant/research support from: SAR-COVID is a multisponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them. participated or infuenced the development of the project, data collection, analysis, interpretation, or. writing the report. They do not have access to the information collected in the database.

2023Annals of the Rheumatic Diseases（2023）

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10POS1199 IS PSORIATIC ARTHRITIS A RISK FACTOR FOR SEVERE COVID -19 INFECTION? DATA FROM THE ARGENTINIAN REGISTRY SAR-COVID

V. Savio,C. Maldini,P. Alba,V. Saurit,G. Berbotto,C. Pisoni,Y. Tissera,R. Nieto,F. Maldonado,S. Ornella,C. Gobbi, A. R. Banos,

Background Comorbidities, particularly cardio-metabolic disorders, are highly prevalent in patients with psoriatic arthritis (PsA) and they were associated with an increased risk of atherosclerotic cardiovascular disease, which have been associated with higher morbidity and mortality. Whether PsA enhances the risk of SARS-CoV-2 infection or affects the disease outcome remains to be ascertained. Objectives To describe the sociodemographic, clinical and treatment characteristics of patients with PsA with confirmed SARS-CoV-2 infection from the SAR-COVID registry and to identify the variables associated with poor COVID-19 outcomes, comparing them with those with rheumatoid arthritis (RA). Methods Cross-sectional observational study including patients ≥18 years old, with diagnosis of PsA (CASPAR criteria) and RA (ACR / EULAR 2010 criteria), who had confirmed SARS-CoV-2 infection (RT-PCR or serology) from the SAR-COVID registry. Recruitment period was between August 13, 2020 and July 31, 2021. Sociodemographic variables, comorbidities, and treatments were analyzed. To assess the severity of the infection, the ordinal scale of the National Institute of Allergy and Infectious Diseases (NIAID)1 was used, and it was considered that a patient met the primary outcome, if they presented criteria of categories 5 or higher on the severity scale. For this analysis, Chi2 test, Fisher’s test, Student’s test or Wilcoxon test, and binomial logistic regression using NIAID>=5 as dependent variable were performed. Results A total of 129 PsA patients and 808 with RA were included. Clinical characteristics are shown in Table 1. Regarding PsA treatment, 12.4% of PsA were receiving IL-17 inhibitors, 5.4% IL12-23 inhibitors, one patient apremilast and one abatacept. The frequency of NIAID≥5 was comparable between groups (PsA 19.5% vs RA 20.1%; p=0.976). (Figure 1). Table 1. Characteristics of patients with PsA and RA who presented COVID-19 in the SAR-COVID registry. Psoriatic arthritis (n=129) Rheumatoid arthritis (n=808) P value Total (n=937) Age (years), mean (SD ) 51.7 (12.7) 53.1 (12.9) 0.239 52.9 (12.9) Female 72 (55.8) 684 (84.7) <0.001 756 (80.7) Comorbidities 65 (50.4) 355 (43.9) 0.203 420 (44.8) Obesity (BMI ≥30 ) 19 (15.2) 102 (13.4) 0.692 121 (13.7) Morbid obesity (BMI ≥40 ) 1 (0.8) 10 (1.3) 1 11 (1.25) Hypertension 35 (28.5) 205 (26.8) 0.783 240 (27.0) Diabetes 16 (13.0) 67 (8.8) 0.188 83 (9.39) Dyslipidemia 24 (19.5) 102 (13.5) 0.106 126 (14.4) Cardiovascular or cerebrovascular disease 5 (11.4) 32 (3.9) 0.033 37 (4.2) Two or more comorbidities 55 (42.6) 219 (27.1) <0.001 274 (29.2) Current smoking 4 (3.6) 60 (8.4) 0.79 64 (7.7) High disease activity 0 (0) 29 (3.8) 0.027 29 (3.23) Glucocorticoids treatment 5 (20.0) 95 (60.1) <0.001 100 (54.6) Conventional DMARDs 47 (36.4) 443 (54.8) <0.001 490 (52.3) Biologic DMARDs 60 (46.5) 193 (23.9) <0.001 253 (27.0) JAK inhibitors 4 (3.10) 72 (8.9) 0.038 76 (8.1) Full recovery of COVID-19 105 (84.0) 644 (81.7) 0.127 749 (82.0) COVID-19 complications 16 (12.5) 68 (8.7) 0.227 84 (9.2) Death due to COVID-19 1 (0.8) 34 (4.3) 0.074 35 (3.8) Notes=values n (%) unless otherwise indicated; BMI: Body Mass Index; DMARDs: disease-modifying antirheumatic drugs; JAK inhibitors: Janus kinase inhibitors. PsA patients with NIAID≥5 in comparison with NIAID<5 were older (58.6±11.4 vs 50±12.5; p=0.002), had more frequently hypertension (52.2% vs 23%; p=0.011) and dyslipidemia (39.1% vs 15%; p=0.017). In the multivariate analysis, age (OR 1.06; 95% CI 1.02–1.11) was associated with a worse outcome of the COVID-19 (NIAID≥5) in patients with PsA, while those who received methotrexate (OR 0.34; 95% CI 0.11–0.92) and biological DMARDs (OR 0.28; 95% CI 0.09–0.78) had a better outcome. Conclusion Although PsA patients have a higher frequency of cardiovascular and metabolic comorbidities than those with RA, the COVID-19 severity was similar. Most of the patients had mild SARS-CoV-2 infection and a low death rate. References [1]Beigel JH, et al. Remdesivir for the Treatment of Covid-19 - Final Report. N Engl J Med. 2020 Nov 5;383(19):1813-1826. Disclosure of Interests None declared

2022ANNALS OF THE RHEUMATIC DISEASES（2022）

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11Rheumatoid Arthritis Monotherapy in the Jak Inhibitors Era. Current Prevalence and Associated Factors in a Multicenter Study.

Rodrigo Garcia-Salinas,Fernando Sommerfleck,Alfredo Vargas-Caselles,Luis Palomino-Romero,Javier Rosa,Mariana Benegas,Etel Saturansky,Pamela Giorgis,Florencia Martinez,Marcelo Abdala,Jimene Sanchez-Alcover,Emma Civit,

BACKGROUND:Combined therapy constitutes the standard of care in RA. Jak inhibitors (Jaki) have shown efficacy in monotherapy, a modality used in cases where it is not possible to use Disease-Modifying Anti Rheumatic Drugs (csDMARDs).OBJECTIVES:To estimate the prevalence (total and by drug), reason for using and the increase over the time of bDMARDs or tsDMARDs as monotherapy after the availability of the Jaki. To analyze the differential characteristics between patients with monotherapy vs combined therapy.METHODS:Cross-sectional multicenter study. Consecutive patients with a diagnosis of RA (ACR/EULAR 2010) under treatment with bDMARDs or tsDMARDs started from 2013 were included. Socio-demographic, clinic, and therapeutic data were collected.RESULTS:A total of 505 RA patients were included. Since 2013, the prevalence of monotherapy usage was (any) 49%. The drugs used as monotherapy were Jaki in 41% and TNF-blockers in 30%. The leading causes of monotherapy use were intolerance/adverse events (62%), medical decision or lack of adherence (37.7%). The highest socioeconomic level and a better functional status at diagnosis were predictors of monotherapy use. The use of the second line of treatments and less polypharmacy were independent factors associated with this therapeutic modality.CONCLUSIONS:The current prevalence of monotherapy in RA was 49%, the Jaki were the most used drug in this modality. Monotherapy increases from year to year. There are differential characteristics in patients using monotherapy.

2022ARP rheumatology（2022）引用：1

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12POS0655 SURVIVAL AND SAFETY OF BIOLOGICAL AND TARGETED SYNTHETIC THERAPIES AS REGARDS TO AGE GROUPS. BIOBADASAR 3.0 REGISTRY.

A. Brigante,C. A. Isnardi,G. Gomez,R. Quintana,M. Haye,K. Roberts,M. Garcia,C. Gobbi,G. Casado,J. Rebak,J. M. Dapena,G. Berbotto,

Background Advances in rheumatology and new therapeutic options have certainly impacted patient survival, changing the age range, from youth to seniors. The differences between the age groups could influence the evolution of the disease and the adverse events (AEs) related to the treatments. There are few real-world data on the safety and efficacy of treatments in different age groups. Objectives To evaluate the frequency of AEs and the survival of treatments according to the age in patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA) or ankylosing spondylitis (AS). Methods Retrospective, observational, multicenter study of real-life data of patients included in the BIOBADASAR 3.0 registry; exposed and not exposed to original biological treatments (b-DMARDs), biosimilars, targeted synthetic drugs (ts-DMARDs). The unexposed group received treatment with conventional disease-modifying drugs (cDMARDs). A Kaplan-Meier and Log Rank Test analysis was performed to study AEs-free survival and treatment in different age groups (young people <25; young adults 25-34; mature adults 34-65; old adults >65). Factors related to treatment survival were evaluated using Cox regression models. Results 5,297 patients were included, 80.3% female, mean age 43.7 years (SD 15.6) and median disease progression 14.3 [IQR 11.5]. RA 4658 (87.9%); APs 490 (9.25%) and EA 149 (2.8%). The main reason for treatment discontinuation was ineffectiveness, in 624 patients in the exposed group and in 53 (2.5%) patients in control group, followed by the presence of AEs in 352 (11.2%) and 83 (3.9%), respectively (p=0.001). A mean Charlson Score of 0.268 (SD 0.6) in the exposed group and 0.306 (SD 0.7) in the control group (p=0.095). Median EAs-free survival in the exposed group was 12.5 years [IQR 16.6] while in controls was 28 years [IQR 11], p<0.0001. Median AEs-free survival was 12 years (IQR 11) in young people, 11.5 years [IQR: 4.9] in young adults, 10 years [IQR: 3.25] in mature adults and 7.6 years [IQR: 6] in old adults with a difference statistically significant (p>0.017). The exposed group presented a median treatment survival in years of 11.25 years [IQR: 10] in young people; 12.5 years [IQR: 4.7] in young adults, 7.5 years [IQR: 12.1] in mature adults and 4.5 years [IQR: 1.14] in old adults (p>0.0001). Considering only the first line of treatment, a median survival of 11.5 years [IQR: 10] was evidenced in the age group <25; 12 years [IQR: 2.6] between 25-34 years old, 10 years [IQR: 12] in the group between 34-65 years old and 5.5 years [IQR: 1.14] in the group > 65 years old (p>0.004). (Figure 1). Considering the second line of treatment, the differences between the groups were not statistically significant (p=0.57). In the multivariate regression model for patients with RA, the factors with the greatest impact on treatment survival were female sex (HR 1.3, 95% CI 1.2-1.4), old age (HR 1.01, 95% CI 1.008-1.01), treatment with steroids (HR 1.19, 95% CI1.1-1.2) and longer disease duration (HR 1.01, 95% CI1.01 – 1.02). Conclusion In the present study we were able to demonstrate a greater occurrence of AEs in old adults and mature adults compared to young people and young adults. Conversely, survival for b-DMARDs and ts-DMARDs were greater in youth and young adults. In patients with RA, female sex, corticosteroid therapy, old aged and longer disease duration were associated with treatment discontinuation. References [1]Souto A, et al. Rate of discontinuation and drug survival of biologic therapies in rheumatoid arthritis: a systematic review and meta-analysis of drug registries and health care databases. Rheumatology (Oxford). 2016;55(3):523–34. [2]Ray D, et al. Immune senescence, epigenetics and autoimmunity. Clin Immunol. 2018 Nov;196:59-63. doi: 10.1016/j.clim.2018.04.002. Epub 2018 Apr 11. [3]Vela P, et al. Influence of age on the occurrence of adverse events in rheumatic patients at the onset of biological treatment: data from the BIOBADASER III register. Arthritis Res Ther. 2020 Jun 15;22(1):143. doi: 10.1186/s13075-020-02231-x. Disclosure of Interests None declared

2022ANNALS OF THE RHEUMATIC DISEASES（2022）

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13AB0389 EVOLUTION OF MONOTHERAPY IN RHEUMATOID ARTHRITIS: IMPACT OF THE RISE OF JAK INHIBITOR

R. Garcia Salinas,F. Sommerfleck,A. Vargas Caselles,L. Palomino Romero,J. Rosa,M. Benegas,E. Saturansky,P. Giorgis,F. Martinez,M. Abdala,J. Sanchez Alcover,E. E. Civit De Garignani,

Background According to different international registries, the frequency of use of biological agents in monotherapy in RA ranges from 12 to 39%. Targeted synthetic DMARDs (tsDMARDs-Jaki) have shown great efficacy when used as monotherapy. The rationale for this study is based on the fact that the frequency has increased with the appearance of the Jaki. Objectives To estimate the frequency and reason of the use of biological drugs (bDMARDs) or tsDMARDs in monotherapy since 2013 (Year the Jaki were available in Argentina). To describe the frequency of monotherapy by treatment class and analyze the differential characteristics. Methods Retrospective and cross-sectional multicenter study (10 reference centers from Argentina). Consecutive patients, ≥18 years, diagnosis of RA (ACR / EULAR 2010), who were under treatment with bDMARDs or tsDMARDs, started after 2013. Socio-demographic, disease and therapeutic data were collected. Statistical analysis descriptive statistics, Chi2 test, Fisher’s exact test, Student’s T test and Mann Whitney were performed, according to the nature of the variables. A p <0.05 was considered significant. Results Total 505 patients were included, 87.7% women, with a mean age 58 years (SD ± 13.5) and disease duration of 13 years (SD ± 7.8). Treatment: TNF blocker 42.1%, JAKi 30.3%, IL-6 blocker 10.9% and other treatments 16.8%. Since 2013, the frequency of monotherapy was 49% (95% CI: 45-53), in the last visit the current frequency was 41% (95% CI 37-45),of this 40% received JAKi. JAKi and IL-6 blocker were the treatments that were used more frequently in monotherapy vs combination modality (Figure 1). Figure 1. The main causes of monotherapy were intolerance (39.9%), adverse event (22%), physician’s decision (20.2%) and lack of adherence (17.7%) to DMARDs. Patients who were active workers (64% vs 55%, p <0.05), with higher socioeconomic status (31.4% vs 17.2% p <0.01), better mean HAQ at diagnosis (1.1 vs 1.3, p <0.05) an association was observed with monotherapy. In addition, an association was observed with the use of monotherapy in patients in the 2nd biological line or higher vs 1st line (53% vs 33%, p <0.01), lower polypharmacy (45.6% vs 60%, p <0.02) and a shorter mean time of biological treatment (47 months vs 39 months, p <0.01). These variables were entered in a logistic regression model, the results of the independently associated variables are shown in Table 1. Table 1. Variable p OR CI 95% Employment status (active). 0,191 1,327 0,868 2,029 Socioeconomic level (medium-high stratum ) 0,002 2,15 1,323 3,494 HAQ at diagnosis, M (SD ) 0,019 0,704 0,524 0,944 First Line of biological treatment or Jaki (yes ) 0,02 0,459 0,3 0,7 Polypharmacy (>4 drugs) (yes ) 0,018 0,603 0,395 0,918 bDMARDs or tsDMARDs exposure time (months) 0,054 0,994 0,987 1 Conclusion The frequency of monotherapy, since the Jaki’s emergence, was 49% (all follow-up) and 41% (current-last visit). Intolerance to cDMARDs doctor and the patient decision were the main cause. The monotherapy use pattern was greater in those who received JAKi and anti IL6. The use of monotherapy was associated with work activity, socioeconomic status, and functional capacity at diagnosis. An association was also observed with less polypharmacy. References [1]Smolen JS, et al. Ann Rheum Dis 2020;79:685–699. [2]Emery P, Sebba A, Huizinga TW. Ann Rheum Dis.2013;72(12):1897–904. [3]F. Sommerfleck et al. Rev Arg Reumatol. 2013;24(4): 30-36 [4]Aletaha D, Neogi T, Silman AJ,et al. Arthritis Rheum 2010. 2010;62(9):2569–81. Disclosure of Interests Rodrigo Garcia Salinas Speakers bureau: Abbvie, Lilly, BMS, Jassen, Novartis, boehringer ingelheim, Consultant of: Lilly, Jassen, Grant/research support from: Abbvie, Fernando Sommerfleck Speakers bureau: Abbvie, Janssen, Novartis, Grant/research support from: Abbvie, Alfredo Vargas Caselles: None declared, Luis Palomino Romero: None declared, Javier Rosa: None declared, Mariana Benegas: None declared, Etel Saturansky: None declared, Pamela Giorgis: None declared, Florencia Martinez: None declared, Marcelo Abdala: None declared, Jimena Sanchez Alcover: None declared, Emma Estela Civit De Garignani: None declared, Gabriela Vanesa Espasa: None declared, Verónica Inés Bellomio: None declared, Juan Manuel Bande: None declared, Silvia Papasidero: None declared, Veronica Saurit: None declared, Leticia Ibañez Zurlo: None declared, Emilio Buschiazzo: None declared

2022ANNALS OF THE RHEUMATIC DISEASES（2022）

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14POS1204 SARS-CoV-2 INFECTION AFTER VACCINATION IN PATIENTS WITH RHEUMATIC DISEASES FROM ARGENTINA

M. Cosatti,M.E. D´ Angelo,I.E. Petkovic,M.D.L.A. Correa,D. Zelaya,M.S. Gálvez Elkin,A.K. Cogo,C. Retamozo,R. Nieto,E.D. Mussano, E.M. Cavillon,V. Savio,

Background Patients with rheumatic diseases (RD) have been excluded from SARS-CoV-2 vaccine trials. Though data appear to show safety and efficacy, mostly evidence remains in mRNA vaccines. However in our country, adenovirus and inactivated vaccines, as well as heterologous schemes are frequently used. Objectives To describe clinical characteristics and outcomes of SARS-CoV-2 infection after vaccination in patients with RD from de the SAR-CoVAC registry and to compare them with patients who got infected before vaccination. Additionally, factors associated with COVID-19 unfavorable outcome were assessed. Methods Adult patients with RD who have been vaccinated for SARS-CoV-2 were consecutively included between June 1st and December 21st, 2021. Confirmed SARS-CoV-2 infection (RT-PCR o serology) was reported by the treated physician. Infection after an incomplete scheme was defined when the event was diagnosed at least 14 days after first dose; and after a complete scheme when it occurred > 14 days after second dose. Homologous scheme is defined by two same doses of vaccine and heterologous by two different doses. Patients with previous SARS-CoV-2 infection were excluded. To compare SARS-CoV-2 infection characteristics in not vaccinated patients, subjects from the SAR-COVID registry, which includes patients with RD and SARS-CoV-2 infection, were matched 2:1 by gender, age and RD. WHO-Ordinal Scale ≥5 was used to define unfavorable infection outcome. Descriptive statics, Chi2 test, Fischer test, T test and ANOVA were used. Results A total of 1350 patients from the SAR COVAC registry were included, 67 (5%) presented SARS-CoV-2 infection after vaccination. The later were mostly (72%) females with a mean age of 57 (SD 15) years old. The most frequent RD were rheumatoid arthritis (41%), psoriatic arthritis (12%) and systemic lupus erythematosus (10%). At vaccination, most of them (75%) had low disease activity or remission, 19% were taking steroids, 39% methotrexate, 27% bDMARDs and 6% JAK inhibitors. A total of 11 (16%) patients had SARS-CoV-2 infection <14 days after the first vaccine dose, 39 (58%) after an incomplete scheme and 17 (25 %) following a complete one. In the incomplete scheme group, 59% received Gam-COVID-Vac, 31% ChAdOx1 nCov-19 and 10% BBIBP-CorV; and in patients with complete scheme 47%, 24% and 29%, respectively. No event was reported after a complete heterologous scheme. No significant differences regarding sociodemoghraphic characteristics, RD, disease treatment, type of vaccine and regimen was found between in those with infection and those without it. After vaccination only 8 (12%) of the patients who got infected had an unfavorable course, 88% of them following an incomplete scheme (5 received Gam-COVID-Vac, 1 ChAdOx1 nCov-19 and 1 BBIBP-CorV) and one subject after a complete homologous Gam-COVID-Vac scheme. Having an unfavorable outcome of SARS-CoV-2 infection was associated to: male gender [63% vs 24%, p=0.036], older age [mean 70 years (SD 7) vs 55 years (SD 15), p=0.005], being Caucasian [100% vs 54%, p=0.018], higher education [mean 17 years (SD 4) vs 12 years (SD 4), p=0.010], the presence of comorbidities [100% vs 39%, p=0.001, having pulmonary disease [37% vs 5%, p=0.019], dyslipidemia [63% vs 17%, p=0.011] and arterial hypertension [63% vs 24%, p=0.036], RD, treatments, disease activity and types of vaccines received were comparable between groups. When comparing patients with and without vaccination prior SARS-CoV-2 infection, those who received at least one dose of vaccine had less frequently severe COVID-19 (12% vs 24%, p=0.067) and presented lower mortality due to COVID-19 (3% vs 6%, p=0.498). However these differences did not reach statistical significance. Conclusion In the SAR-CoVAC registry 5% of the patients had SARS-CoV-2 infection after vaccination, most of them mild and 25% after a complete scheme. Any vaccine was associated with severe COVID-19. When comparing with non-vaccinated patients, those with at least one dose, had less frequently severe disease and died due COVID-19. Disclosure of Interests None declared

2022Annals of the Rheumatic Diseases（2022）

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15POS1200 DIFFERENCES BETWEEN THE FIRST AND THE SECOND WAVE OF SARS-COV-2 INFECTION IN PATIENTS WITH IMMUNE-MEDIATED INFLAMMATORY DISEASES IN ARGENTINA: DATA FROM THE SAR-COVID REGISTRY

A. Bertoli,L. Munoz,M. J. Lopez Perez,L. Sanchez Freytes,M. S. Castano,V. Saurit,G. Berbotto,G. Alle,M. Severina,R. Nieto,F. Maldonado,M. Pera,

BackgroundIn Argentina we have witnessed two COVID 19 waves between 2020 and 2021. The first wave occurred during the spring of 2020 and it was related to the wild type of the virus, the second occurred during the fall/winter of 2021 when the gamma variant showed a clear predominance. During the first wave, patient with rheumatic diseases showed a higher frequency of hospitalization and mortality (4% vs 0.26%) when compared to the general population1; at that time, however, vaccination was not yet available.ObjectivesTo compare sociodemographic and disease characteristics, course and outcomes of SARS-CoV-2 infection in patients with immune-mediated/autoinflammatory diseases (IMADs) during the first and second waves in Argentina.MethodsSAR-COVID is a national, multicenter, longitudinal and observational registry, in which patients ≥18 years of age, with a diagnosis of a rheumatic disease who had confirmed SARS-CoV-2 infection (RT-PCR or positive serology) were consecutively included since August 2020. For the purpose of this report, only patients with IMADs who had SARS-CoV-2 infection during the first wave (defined as cases occurred between March 2020 and March 2021) and the second wave (cases occurred between April and August 2021) were examined. Sociodemographic characteristics, disease diagnosis and activity, comorbidities, immunosuppressive treatment and COVID 19 clinical characteristics, complications and outcomes: hospitalization, intensive care unit (ICU) admission, use of mechanical ventilation and death were compared among groups. Descriptive statistical analysis was performed. Variables were compared with Chi squared test and Student T test or Mann Whitney test. Multivariable logistic regression models with forward and backward selection method, using hospitalization, ICU admission and death as dependent variables were carried out.ResultsA total of 1777 patients were included, 1342 from the first wave and 435 of the second one. Patients had a mean (SD) age of 50.7 (14.2) years and 81% were female. Both groups of patients were similar in terms of socio-demographic features, disease diagnosis, disease activity, the use of glucocorticoids ≥ 10 mg/day and the immunosuppressive drugs (Table 1 below). Patients infected during the first wave have higher frequency of comorbidities (49% vs 41%; p= 0.004). Hospitalizations due to COVID 19 (31% vs 20%; p <0.001) and ICU admissions (9% vs 5%; p= 0.009) were higher during the first wave. No differences in the use of mechanical ventilation (16% vs 16%; p= 0.97) nor in the mortality rate (5% vs 4%; p= 0.41) were observed. In the multivariable analysis, after adjusting for demographics, clinical features and immunosuppressive treatment, patients infected during the second wave were 40% less likely to be hospitalized (OR= 0.6, IC95% 0.4-0.8) and to be admitted to the ICU (OR= 0.6, IC95% 0.3-0.9).Table 1.Variable (% or Mean – SD)First wave(n=1342)Second wave(n=435)p ValueFemale gender81800.7Age (years)51.0 (14.5)50.0 (13.3)0.2Disease diagnosis Rheumatoid arthritis46461 Ankylosing spondylitis10110.8 Systemic lupus erythematosus171850.9 Systemic Scleroderma551 Sjögren´s syndrome650.7 Inflammatory myopathies330.5 Vasculitis430.4Disease activity High430.5Use of immune modulatorsDMARDcs53560.2DMARDts460.1DMARDb82821Use of glucocorticoids ≥10 mg12120.9Comorbidities49410.004ConclusionThe impact of COVID 19 in Argentina, in terms of mortality in patients with IMADs was still higher compared to the general population during the second wave. However, the frequency of hospitalizations and ICU admissions was lower. These findings could be explained by the introduction of the SARS COV 2 vaccination and, probably, by the cumulative knowledge and management improvement of this infection among physicians.References[1]Isnardi CA et al. Epidemiology and outcomes of patients with rheumatic diseases and SARS-COV-2 infection: data from the argentinean SAR-COVID Registry. Ann Rheum Dis, 2021, suppl 1, 887.Disclosure of InterestsNone declared

2022ANNALS OF THE RHEUMATIC DISEASES（2022）

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16Cardiovascular and Oncologic Outocomes of Anti-TNF Alfa and JAK Inhibitors in Patients with Rheumatoid and Psoriatic Arthritis. Real World Data and Insights of BIOBADASAR 3.0 Registry

Alejandro Brigante,Rosana Quintana,Carolina Isnardi,Karen Roberts,Gimena Gomez,Maria Haye Salinas,Enrique Soriano,Guillermo Pons-Estel,Maria De la Vega, Osvaldo Kerzberg,Julieta Gamba,Anastasia Secco,

2022ARTHRITIS & RHEUMATOLOGY（2022）

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17POS0660 SURVIVAL AND SAFETY OF BIOLOGICAL AND TARGETED SYNTHETIC THERAPIES. 10 YEARS OF REAL-LIFE DATA. BIOABASAR 3.0 REGISTRY

A. Brigante,C. A. Isnardi,R. Quintana,G. Gomez,K. Roberts,M. Haye,A. C. Costi,N. Perez,P. Astesana, A. M. Smichowski,L. Sorrentino,J. Alcivar Navarrete,

Background The use of biological and targeted synthetic drugs has changed the outcomes of rheumatic diseases. The information on efficacy and safety provided by randomized controlled clinical trials does not always reflect the conditions of patients in real life. Data obtained from prospective registries, over extended periods and with real-world evidence, is a great contribution to the pharmacovigilance of these drugs. Objectives The aim of this study is to describe adverse events (AE) and survival of treatments of patients included in the Argentine Registry of Adverse Events of Biological Therapies and Target Synthetic Drugs (BIOBADASAR 3.0). Methods Observational, prospective and multicenter study of ten years of follow-up in patients with rheumatic diseases treated with original biological drugs, biosimilars or original and generic targeted synthetic therapies in Argentine. Those patients who received biological therapies were considered exposed while non-exposed patients represent the control group. All patients were evaluated at least once a year and whenever they experienced an AE or a change in treatment. Survival of treatments was evaluated by Kaplan Meier curves and the comparison between them was made by Log Rank Test analysis. Results A total of 6010 patients were included and 8810 treatment periods from 56 centers. 79.7% were female, mean age of 43.7 (SD 15.6) years. The most frequently reported rheumatological disease was rheumatoid arthritis (RA) (77.5%), followed by psoriatic arthritis (PsA) (8.2%), systemic lupus erythematosus (SLE) (3.1%), juvenile idiopathic arthritis (JIA) (2.6%) and ankylosing spondylitis (AS) (2.5%). The b-DMARD use frequencies were etanercept in 32.2%, followed by adalimumab in 18.7%, abatacept in 9.7%, certolizumab pegol in 8.7%, tofacitinib in 7.9%, rituximab in 7.3% and tocilizumab in 5.5%. The frequency of AE was 11.7% in the exposed group and 4.9% in controls (p=0.001). Infections were present in 41% in the exposed group vs 34% in controls (p<0.001). AE-free survival was 23 years [IQR: 18.2] in controls vs 10 years [IQR: 8.8]) in the exposed group p<0.0001). In the multivariate regression model, age (HR: 1.005, 95% CI 1.001-1.009) and corticosteroid treatment (HR: 1.18, 95% CI 1.05-1.34) were associated with a higher risk of AE in exposed patients. Treatment survival was 15 years [IQR: 28] in unexposed group vs 4.7 years [IQR: 10] in exposed patients (p<0.0001). In the multivariate analysis, female sex (HR 1.1, 95% CI 1.09-1.2), older age (HR 1.0, 95% CI: 1.010-1.014), corticosteroid treatment (HR 1.16, 95% CI 1.09-1.2), the diagnosis of systemic lupus erythematosus (HR1.547, CI95%1.3-1.8) and disease duration (HR1.01, CI95%1.008-1.015) were associated with a higher risk of treatment discontinuation while the diagnosis of rheumatoid arthritis (HR 0.83 CI95% 0.75-0.93) was associated with a lower risk of suspension. Conclusion We found that the use of steroids and elderly patients are still being associated with a higher risk of presenting an AE and treatment discontinuing. This could be related to the fact that the use of steroids is frequently associated with active disease or severe conditions. Exposed patients have a lower AE-free survival and a lower treatment survival. This could be since unexposed patients have a longer follow-up time and a longer duration of their disease. This data from real-world Latin American patients of ten years of follow-up are extremely useful for monitoring and pharmacovigilance of biological therapies in patients with rheumatic diseases. References [1]De la Vega M, et al. The importance of rheumatology biologic registries in Latin America. Rheumatol Int. 2013;33(4):827-35. Rocha FA. Latin-American challenges and opportunities in rheumatology. Arthritis Res Ther. 2017;19(1):29. [2]Prior-Español A, et al. Clinical factors associated with discontinuation of ts/bDMARDs in rheumatic patients from the BIOBADASER III registry. Sci Rep. 2021 May 27;11(1):11091. doi: 10.1038/s41598-021-90442-w. PMID: 34045525; PMCID: PMC8159943. Disclosure of Interests None declared

2022ANNALS OF THE RHEUMATIC DISEASES（2022）

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18AB1094 SAFETY AND EFFICACY OF VACCINES FOR SARS-CoV-2 IN PATIENTS WITH RHEUMATIC AND IMMUNE-MEDIATED INFLAMMATORY DISEASES: DATA FROM THE ARGENTINEAN REGISTRY SAR-CoVAC

C. A. Isnardi,K. Roberts,R. Quintana,J. Kreimer,C. Echeverria,P. C. Luna,B. M. Virasoro,I. E. Exeni,N. Kogan,M. D. L. A. Correa,D. A. Pereira,D. Zelaya,

BackgroundCurrently there is little information on the efficacy and safety of SARS-CoV-2 vaccination in patients with immune-mediated diseases and/or under immunosuppressive treatment in our country, where different types of vaccines and mix regimens are used. For this reason, the Argentine Society of Rheumatology (SAR) with the Argentine Society of Psoriasis (SOARPSO) set out to develop a national register of patients with rheumatic and immune-mediated inflammatory diseases (IMIDs) who have received a SARS-CoV-2 vaccine in order to assess their efficacy and safety in this population.ObjectivesTo assess SARS-CoV-2 vaccine efficacy and safety in patients with rheumatic and IMIDs.MethodsSAR-CoVAC is a national, multicenter and observational registry. Adult patients with a diagnosis of rheumatic or IMIDs who have been vaccinated for SARS-CoV-2 were consecutively included between June 1st and September 17th, 2021. Sociodemographic data, comorbidities, underlying rheumatic or IMIDs, treatments received and their modification prior to vaccination and history of SARS-CoV-2 infection were recorded. In addition, the date and place of vaccination, type of vaccine applied, scheme and indication will be registered. Finally, adverse events (AE), as well as SARS-CoV-2 infection after the application of the vaccine were documentedResultsA total of 1234 patients were included, 79% were female, with a mean age of 57.8 (SD 14.1) years. The most frequent diseases were rheumatoid arthritis (41.2%), osteoarthritis (14.5%), psoriasis (12.7%) and spondyloarthritis (12.3%). Most of them were in remission (28.5%) and low disease activity (41.4%). At the time of vaccination, 21% were receiving glucocorticoid treatment, 35.7% methotrexate, 29.7% biological (b) Disease Modifying Anti-Rheumatic Drugs (DMARDs) and 5.4% JAK inhibitors. Before vaccine application 16.9% had had a SARS-CoV-2 infection.Regarding the first dose of the vaccine, the most of the patients (51.1%) received Gam-COVID-Vac, followed by ChAdOx1 nCoV-19 (32.8%) and BBIBP-CorV (14.5%). In a lesser proportion, BNT162b2 (0.6%), Ad26.COV2.S (0.2%) and CoronaVac (0.2%) vaccines were used. Almost half of them (48.8%) completed the scheme, 12.5% were mix regimenes, the most frequent being Gam-COVID-Vac / mRNA-1273. The median time between doses was 51days (IQR 53).More than a quarter (25.9%) of the patients reported at least one AE after the first dose and 15.9% after the second. The flu-like syndrome and local hypersensitivity were the most frequent manifestations. There was one case of mild anaphylaxis. No patient was hospitalized. Altogether, the incidence of AE was 246.5 events/1000 doses. BBIBP-CorV presented significantly lower incidence of AE in comparison with the other types of vaccines. (118.5 events/1000 doses, p<0.002 in all cases)Regarding efficacy, 63 events of SARS-CoV-2 infection were reported after vaccination, 19% occurred before 14 days post-vaccination, 57.1% after the first dose (>14 days) and 23.8% after the second. In most cases (85.9%) the infection was asymptomatic or had an outpatient course and 2 died due to COVID-19.ConclusionIn this national cohort of patients with rheumatic and IMIDs vaccinated for SARS-CoV-2, the most widely used vaccines were Gam-COVID-Vac and ChAdOx1 nCoV-19, approximately half completed the schedule and in most cases homologously. A quarter of the patients presented some AE, while 5.1% presented SARS-CoV-2 infection after vaccination, in most cases mild.Disclosure of InterestsNone declared

2022ANNALS OF THE RHEUMATIC DISEASES（2022）

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19SARS-COV-2 INFECTION AFTER VACCINATION IN PATIENTS WITH RHEUMATIC DISEASES FROM ARGENTINA

M. Cosatti,M. E. D'Angelo,I. E. Petkovic,M. D. L. A. Correa,D. Zelaya,M. S. Galvez Elkin,A. K. Cogo,C. Retamozo,R. Nieto,E. D. Mussano, E. M. Cavillon,V. Savio,

2022ANNALS OF THE RHEUMATIC DISEASES（2022）

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20AB0342 OBSTETRIC AND THROMBOTIC ANTIPHOSPHOLIPID SYNDROME: ARE THEY DIFFERENT ENTITIES?

R. Serrano Morales,R. Nieto,S. Porta,K. Roberts,L. Lema,C. Maldini,Y. Tissera,J. A. Albiero,V. Savio,C. Goizueta, V. Lobo, A. Broll,

Background: Several studies showed two main clinical phenotypes of antiphospholipid syndrome (APS): thrombotic (TAPS) and obstetric APS (OAPS). Although they have the same autoantibody profile, one of them developed thrombosis and other one obstetric morbidity. Objectives: To study clinical, demographic and antibody profile in patients with TAPS and OAPS. Methods: we retrospectively evaluated TAPS and OAPS patients who were included in Argentine Antiphospholipid antibodies registry. We studied clinical, demographic and antibody profile in both groups. Results: 238 patients were included in the registry. 201 (84.81%) of them were female. 122 (60.69 %) of them fullfilled APS Sydney classification criteria, 47 (38.52%) TAPS and 52 (42.62%) OAPS. 23 (18.85%) patients had both thrombotic and obstetric events so they were excluded in this analysis. Arterial Hypertension (HBP) and Hyperlipidemia were more frequent in TAPS versus OAPS. Older age was found in TAPS as well as in association with Systemic lupus erythematosus (SLE). There was no difference in antibody profile between the 2 groups, and the Global Antiphospholipid Syndrome Score (aGAPSS) was higher in TAPS than OAPS. 18 (38.3%) of TAPS patients had at least 1 pregnancy. Mean number of pregnancies of TAPS was 2.5 (1.10) and 3.84 (1.86) in OAPS. Thrombotic events were not found in TAPS during pregnancy and puerperium. HBP and gestational diabetes (GD) and other pregnancy related comorbidities were found in TAPS. OAPS (n=52) TAPS (n=47) P OAPS (n=52) TAPS(n=18) SLE, n (% ) 11 (21.2) 28 (59.6) 0.0002 N % (DE) N % (DE) aGAPSS, mean (RIQ ) 4 (5) 8 (5) <0.0001 Abortions (<10 weeks) 33 38.4 (36.2) 8 26.5 (35.3) Age, mean (DE ) 39.3 (6.24) 43.1 (13.5) <0.0001 Live Birth 36 33.5 (28.1) 16 72.2 (34.7) HBP, n (% ) 5 (9.6) 15 (31.9) 0.0121 >37 weeks 21 16.4 (2.38) 16 61.1 (31.7) Hyperlipidemia, n (% ) 4 (7.7) 12(25.5) 0.0267 Prematurity <37 >34 weeks 11 8.76 (1.97) 0 - GD, n (% ) 3(5.8) 2(4.3) 0.9999 Prematurity <34 weeks 9 6.37 (1.49) 1 1.39 (5.89) Obesity, n (% ) 8 (15.4) 4 (8.5) 0.2912 Pre eclampsia >34-<37 weeks 1 0.490 (0.0350) 2 4.6 3 ( 0.138) Smoking, n (% ) 11 (21.1) 13 (27.6) 0.4019 Placental Hematoma 3 1.86 (8.18) 1 2.78 (11.8) Sedentary lifestyle, n (% ) 16 (30.8) 17 (36.2) 0.8486 Abruptio Placentae 2 1.96 (9.80) 2 4.17 (12.9) Triple Positivity 5 9.6 4 8.5 0.8323 Normal delivery 20 17.8 (27.9) 14 47.7 (33.9) Double Positivity 1 1.9 3 6.4 Cesarean section 22 17.2 (21.6) 2 11.1 (32.3) Simple Positivity 29 38.5 19 40.4 Urgent Cesarean section 13 9.80 (20.3) 4 12.5 (24.6) GD 2 1.37 (7.49) 1 2.78 (11.8) HBP 6 3.46 (10.3) 3 10.2 (26.3) Conclusion: Antibody profile was similar in TAPS and OAPS. However, clinical manifestations and cardiovascular risk were different. These results should be evaluated in prospective studies. Disclosure of Interests: None declared

2021ANNALS OF THE RHEUMATIC DISEASES（2021）

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