Development of a novel clinimetric tool: PAtient Reported Disease Activity Index in Rheumatoid Arthritis (PARDAI-RA) by PANLAR, for the assessment of patients living with rheumatoid arthritis

BACKGROUND

Clinical experience has shown that a single measure is not sufficient to assess disease activity in rheumatoid arthritis (RA). Various clinimetric tools are necessary to address the many clinical situations that can arise.

METHODS

In order to develop a comprehensive measurement tool, the Pan American League of Associations for Rheumatology searched for the most frequent measures of disease activity applied in RA by means of a semi-systematic review of the available literature.

RESULTS

We found that the most frequently reported measures of disease activity were the 28-joint Disease Activity Score, C-reactive protein, and the erythrocyte sedimentation rate, followed by patient-reported measures of pain and stiffness and many other composite indices and patient-reported outcome measures. The most frequent physician-reported sign of disease was the swollen joint count, and the most frequently self-reported feature was the increase in disease activity or flares.

CONCLUSION

In this article, we present a new clinimetric tool developed based on expert consensus and on data retrieved from our search. Disease activity can be better assessed by combining various data sources, such as clinical, laboratory, and self-reported outcomes. These variables were included in our novel clinimetric tool. Key Points • The goal of treatment of RA is to achieve the best possible control of inflammation, or even remission; therefore, disease management should include systematic and regular evaluation of inflammation and health status. • Clinimetric tools evaluate a series of variables (e.g., symptoms, functional capacity, disease severity, quality of life, disease progression) and can reveal substantial prognostic and therapeutic differences between patients. • Our clinimetric tool, which is based on a combination of data (e.g., clinical variables, laboratory results, PROMs), can play a relevant role in patient assessment and care.

Burden of lupus activity on health care resources utilization in Buenos Aires, Argentina

OBJECTIVE

The aim is to analyze health care resource utilization (HCRU) of patients with lupus (SLE) from a health management organization (HMO) in Buenos Aires, Argentina, compared with matched controls and comparing periods of flare, low disease activity, and remission.

METHODS

This is a retrospective observational study including all SLE incident cases (ACR 1997/SLICC 2012 criteria) between 2000 and 2020 and 5 matched controls. Clinical data and HCRU (medical and nonmedical consultations, lab and imaging tests performed, emergency room visits, hospitalizations, and drugs prescribed) were obtained from administrative databases and electronic medical records. For each patient with SLE, an activity state was determined in every month of follow-up: flare (BILAG A or 2 BILAG B); low disease activity (LLDAS); remission (DORIS definition); or intermediate activity (not fulfilling any of previous). Incidence rates for each HCRU item and incidence rate ratios between SLE and control patients were and between remission and flare periods were calculated. Multivariate negative binomial logistic regression analyses were performed for identification of variables associated with major resource use.

RESULTS

A total of 62 SLE and 310 control patients were included, 88.7% were women, the median age at diagnosis was 46 years, and were followed for more than 8 years. Patients with SLE contributed with 537.2 patient-years (CI 95% 461.1-613.3) and controls with 2761.9 patient-years (CI 95% 2600.9-2922.8). HCRU in patients with SLE was significantly higher than in controls in all items, even in remission periods. Patients with SLE remained 74.4% of the time in remission, 12.1% in LLDAS, 12.2% in intermediate activity, and 1.3% in flare (there were 64 flares in 36 patients). HCRU was significantly higher during flare periods compared with remission periods. Number of flares was independently associated with emergency department consultations, lab tests and X-ray performed, number of drugs prescribed, and hospitalizations.

CONCLUSION

Significantly more HCRU was observed in patients with SLE in flare compared to remission periods.

Application of Blended Learning to Veterinary Gross Anatomy Practical Sessions: Students' Perceptions of Their Learning Experience and Academic Outcomes

The use of blended learning strategies is increasingly common in health sciences, including veterinary medicine; however, there are very few descriptions of these methods being applied to practicals. We describe here the application of blended learning based on the implementation of flipped classrooms with collaborative learning and gamification to the 2020-2021 veterinary medicine gross anatomy practicals at CEU Cardenal Herrera University (Spain). Students prepared for the sessions by pre-viewing videos and taking a quiz before the start. The sessions were conducted in small groups where students learned through collaborative work and reviewed their learning with a card game. A small but significant increase was observed when comparing the scores of practical exams of the locomotor apparatus with those of 2018-2019 (6.79 ± 2.22 vs. 6.38 ± 2.24, p < 0.05), while the scores were similar (7.76 ± 1.99 vs. 7.64 ± 1.92) for the organ system exams. Students' responses in a satisfaction survey were mostly positive (>80%) regarding the motivating and learning-facilitating effect of this educational method. Our work shows that the application of blended learning in anatomy practicals based on a flipped classroom and with elements of gamification and collaborative work can be an effective way to improve the learning experience of students.

Learning veterinary anatomy playing cards

Gamification is a dynamic tool for educational transformation useful to encourage student interest and enhance learning. Here we present a study conducted to investigate the effectiveness of an educational card game developed by us in veterinary anatomy practicals to reinforce knowledge acquisition in veterinary students. A total of four sets of cards were designed, each one with different anatomical topics (structure identification, articulation and positioning, clinical anatomy, and comparative anatomy); students were arranged in small groups (7-10 students per group) and played the game at the end of each anatomy practical session, discussing the corresponding questions, randomly chosen, as a team. This activity was highly valued by students, most of whom (>80%) expressed that the game was enjoyable, challenging, helpful to improve their knowledge and understanding in clinical anatomy, and effective for anatomy exam preparation. Thus, the use of educational games in practical sessions seems to improve student engagement in the learning process individually and as a team.NEW & NOTEWORTHY The development and implementation of a card game as a training resource that allows learning veterinary anatomy in a motivating and cooperative environment, promoting teamwork, relationships, and trust and communication between colleagues, is described. Stimulating the ability to solve problems as a team has provided help to students preparing for their exams in a more dynamic and enjoyable way.

Advanced interatrial block predicts recurrence of embolic stroke of undetermined source

BACKGROUND

Advanced interatrial block (IAB) is an independent risk factor for ischaemic stroke. This study aimed to analyse whether advanced IAB predicts recurrence of embolic stroke of undetermined source (ESUS).

METHODS

104 patients with a confirmed diagnosis of ESUS were followed up for a median period of 15 months (interquartile range, 10-48). We recorded data on clinical variables, P-wave characteristics, and presence of IAB on the electrocardiogram. Electrocardiogram findings were interpreted by a blinded, centralised rater at (XXXX2). ESUS recurrence was the primary outcome variable.

RESULTS

Median age was 47 years (range, 19-85); 50% of patients were women. IAB was detected in 36 patients (34.6%); IAB was partial in 29 cases (27.9%) and advanced in 7 (6.7%). Sixteen patients (15.4%) presented stroke recurrence; of these, 5 had partial and 4 had advanced IAB (P = .01; odds ratio [OR] = 9.44; 95% confidence interval [CI], 1.88-47.46; relative risk [RR] = 4.62; 95% CI, 2.01-10.61). Median P-wave duration was longer in patients with stroke recurrence (P = .009). The multivariate logistic regression analysis identified the following independent risk factors for stroke recurrence: advanced IAB (P < .001; OR = 10.86; 95% CI, 3.07-38.46), male sex (P = .028; OR = 4.6; 95% CI, 1.18-17.96), and age older than 50 years (P = .039; OR = 3.84; 95% CI, 1.06-13.88). In the Cox proportional hazards model, the risk variables identified were age older than 50 years (P = .002; hazard ratio, 7.04; 95% CI, 2.06-23.8) and P-wave duration (per ms) (P = .007; hazard ratio, 1.02; 95% CI, 1.01-1.04).

CONCLUSIONS

Advanced IAB and age older than 50 years predict ESUS recurrence.

POS0508 PREDICTORS OF PERSISTENT DISEASE IN EARLY ARTHRITIS: 12 MONTHS RESULTS

Background

Early arthritis is an inflammatory disease with the potential to progress to persistent arthritis, such as established Rheumatoid Arthritis (RA) or other articular disease, to resolve spontaneously or remain undifferentiated for indefinite periods of time.

Objectives

To identify predictors of persistent RA after 12 months follow up in the Argentinean early arthritis clinic (CONAART).

Methods

We conducted an observational, prospective longitudinal study, including patients with early arthritis (at least 1 swollen joint with <2 years of evolution) who had at least one year of follow-up.

Sociodemographic and clinical data and characteristics of the disease were recorded at baseline, at 3, 6 and 12 months. After 1 year of follow-up, each patient was classified according to diagnosis: self-limited arthritis, persistent non-erosive arthritis, or persistent erosive arthritis.

The association between the different predictors of diagnosis at 12 months was evaluated using multiple logistic regression, adjusted by potential confounders. Rheumatoid Factor (RF) and Anti Citrullinated Peptide Antibodies (ACPA) were included in separate models in order to avoid multicollinearity. A value of p<0.05 was considered significant.

Results

We included 839 patients, 83% females, mean age of 57±14 years and mean disease duration of 8.2±6.2 months; 67.5% were rheumatoid factor positive and 59% ACPA positive. Disease characteristics at baseline were DAS28 5.1±1.4, swollen joints 6±5, erythrocyte sedimentation rate (ESR) 34±25 mm/h, C Reactive Protein (CRP) 4±6 and Health Assessment Questionnaire-Argentinean (HAQ-A) 1.2±0.8.

After 12 months follow up, 11% of the patients were diagnosed as self-limited disease, whereas 89% were diagnosed as persistent disease. For the persistent disease, 34% presented radiograph erosions and therefore were catalogued as persistent erosive disease.

The seropositivity for both, RF and ACPA, together with baseline DAS28, were the variables independently associated with the development of persistent disease at 12 months. [Model 1a: RF OR 2.33 (95% CI 1.44, 3.78) and DAS28 1.27 (1.06, 1.52); Model 2a: ACPA 2.61 (1.38, 4.93) and DAS28 1.59 (1.24, 2.04)]. (Table 1).

Table 1.

Predictors of Persistent Rheumatoid Arthritis at 12 months

OutcomesPersistent RAPersistent RAPersistent RAPersistent RAOR (95 IC)OR (95 IC)OR (95 IC)OR (95 IC)Model 1aModel 1bModel 2aModel 2bn708708507507Age (years)0.99 (0.98, 1.01)0.99 (0.98, 1.01)0.99 (0.97, 1.01)0.99 (0.97, 1.01)Female gender1.06 (0.57, 2.00)1.06 (0.56, 1.99)0.72 (0.30, 1.71)0.72 (0.30, 1.70)RF positive2.33 (1.44, 3.78)***2.45 (1.52, 3.98)***--ACPA positive--2.61 (1.38, 4.93)**2.63 (1.39, 4.98)**DAS28 at baseline1.27 (1.06, 1.52)**1.59 (1.24, 2.04)***Categorical DAS28  MDA (vs LDA)-1.81 (0.85, 3.86)^-2.86 (1.68, 6.99)*  HDA (vs LDA)-2.83 (1.30, 6.15)^-6.39 (2.42, 16.82)***

^ p<0.1, * p<0.05, ** p<0.01, *** p<0.001

RF, Rheumatoid Factor; ACPA, Anti Citrullinates Protein Antigen; DAS28, Disease activity Score-28; LDA, low disease activity; MDA, moderate disease activity; HDA, high disease activity.

In the patient prediction model, it can be observed that a patient with female gender, ACPA negative, and a low activity at baseline (DAS28 <3.1) presents a 62.3% of likelihood of developing persistent arthritis after 12 months, while a male patient, ACPA positive, with a high baseline activity level, the probability of having persistent disease rises to 97.5%. (Figure 1)

Figure 1.

Matrix prediction model. Probability of diagnosis of Persistent Rheumatoid Arthritis after 12 months of follow-up. Colors represents predictive probability of achieving the outcome as follow: grey: 0-69.9%; blue: 70.0-89.9%; purple: 90.0-100%.

DAS28, Disease Activity Score 28; LDA, low disease activity; MDA, Moderate Disease Activity; HDA, High Disease Activity.

Conclusion

Predictors of persistent arthritis after 12 months of follow up since AT diagnosis were RF and ACPA seropositivity and higher baseline disease activity level.

Disclosure of Interests

None declared.

POS1030 PAIN RESPONSE IN PSORIATIC ARTHRITIS PATIENTS TREATED WITH GUSELKUMAB IS DRIVEN PREDOMINANTLY BY INFLAMMATION-INDEPENDENT EFFECTS

Background

Although reducing inflammation has been associated with pain improvement, the two do not always correlate. Recent studies have suggested that, in addition to its role in inflammation pathogenesis, IL-23 may be involved in pain regulation in a lymphocyte-independent manner1. Guselkumab (GUS), a fully human monoclonal antibody that selectively inhibits IL-23, has demonstrated safety and efficacy in treating multiple domains of active PsA in the DISCOVER-1&2 (D1&D2) trials2,3.

Objectives

To quantify the role of reducing inflammation on the observed relationship between GUS and pain response in PsA patients (pts) using mediation modelling.

Methods

Pooled data from the D1&D2 studies were analyzed. Pts in D1 had ≥3 swollen and ≥3 tender joints (SJC/TJC) and C-reactive protein (CRP)≥0.3 mg/dL; in D2, pts had ≥5 SJC and ≥5 TJC and CRP≥0.6 mg/dL. 31% of D1 pts received 1-2 prior tumor necrosis factor inhibitors (TNFi); D2 pts were bio-naïve. Pts were randomized 1:1:1 to GUS 100 mg every 4 weeks (Q4W); GUS 100 mg at W0, W4, then every 8 weeks (Q8W); or placebo (PBO); PBO pts crossed over to GUS 100 mg Q4W at W24. Pts with history of fibromyalgia were excluded from the analysis. Least square mean changes in pt-reported pain (0-100 VAS) through W52 were estimated with a repeated measures linear mixed model adjusting for known pain determinants. Mediation modelling was performed separately for Q4W & Q8W, W4 & W24, and TNFi-naïve & -experienced (exp) pts. In each model, change in pt-reported pain was the dependent variable; treatment regimen was the independent variable; inflammation, measured by change in SJC or CRP, was the designated mediator; covariates were: age; sex; and baseline (BL) pain score, BMI, SF-36 MCS score, and NSAID use.

Results

Mean (SD) BL pain levels in the GUS Q4W, GUS Q8W, and PBO groups were 60.4 (19.8), 62.0 (20.2), and 61.1 (19.6), respectively. Treatment with GUS was associated with significantly greater pain improvement compared with PBO as early as W4 (ΔQ4W-PBO [95%CI]: -4.9 [-7.6, -2.2]; ΔQ8W-PBO [95%CI]: -5.2 [-7.9, -2.5] (Figure 1). These between-group differences were further enhanced by W24 (ΔQ4W-PBO [95%CI]: -14.6 [-17.6, -11.5]; ΔQ8W-PBO [95%CI]: -14.3 [-17.3, -11.2]); by W52, GUS-randomized pts exhibited an approximate 30-point (̴50%) decrease in pain. Similar results were observed for TNFi-naïve and TNFi-exp pts.

Figure 1.

Mediation analyses demonstrated that the majority of GUS effect on pain at W4 was not attributable to SJC (direct effect), specifically ≤6% was mediated by inflammation as assessed by changes in SJC (indirect effect; Table 1). Similarly, at W24, the indirect effect via SJC improvement represented ≤10% of the GUS treatment effect. No differences were observed between TNFi-naïve and -exp pts at either timepoint.

Consistent results were obtained when using CRP as the mediator variable instead of SJC, whereby ≤2-9%% of GUS effect on pan was mediated by inflammation and 91-98% was direct (Table 1).

Table 1.

Direct (D) Treatment Effect vs. Indirect (IND) Effect via Inflammation Markers on Pain Improvement

MediatorWeekPt GroupEffectGUS Q4WGUS Q8WSJC4AllD96.7%*97.0%*IND†3.3%3%TNFi-NaiveD93.7%*98.5%*IND†6.3%1.5%TNFi-ExpD100%*100%*IND†0%0%24AllD94.8%*92.0%*IND†5.2%*8.0%*TNFi-NaiveD89.6%*90.1%*IND†10.4%*9.9%*TNFi-ExpD99.8%*95.7%*IND†0.2%4.3%CRP4AllD97.6%*95.0%*IND‡2.4%5.0%TNFi-NaiveD98.2%*95.4%*IND‡1.8%4.6%TNFi-ExpD97.6%*95.3%*IND‡2.4%4.7%24AllD97.2%*94.2%*IND‡2.8%5.8%*TNFi-NaiveD98.1%*95.9%*IND‡1.9%4.1%TNFi-ExpD96.5%*91.4%*IND‡3.5%8.6%

*p<0.05; †via SJC; ‡via CRP

Conclusion

GUS induced significant improvement in pt-reported pain as early as W4 of treatment, which was continuously enhanced through W52. While the known mediation effect of SJC and CRP, as markers of inflammation, on pain was confirmed, the majority of GUS’s effect on pain reduction was independent of its effect on these markers, regardless of dosing regimen or prior TNFi experience.

References

[1]Arthritis Res Ther. 2020;22:123

[2]Lancet. 2020;395:1115

[3]Lancet. 2020;395:1126

Disclosure of Interests

Philip J Mease Speakers bureau: AbbVie, Amgen, Eli Lilly, Janssen, Novartis, Pfizer, Sun Pharma, and UCB, Consultant of: AbbVie, Aclaris, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Inmagene, Janssen, Novartis, Pfizer, Sun Pharma, and UCB, Grant/research support from: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, Sun Pharma, and UCB, Enrique Soriano Speakers bureau: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB, Consultant of: AbbVie, Janssen, Novartis, and Roche, Grant/research support from: AbbVie, Janssen, Novartis, Pfizer, Roche, and UCB, Soumya D Chakravarty Shareholder of: Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC and Drexel University College of Medicine, Emmanouil Rampakakis Consultant of: Janssen, Employee of: JSS Medical Research, May Shawi Shareholder of: Johnson & Johnson, Employee of: Janssen Pharmaceutical Companies of Johnson & Johnson, Peter Nash Speakers bureau: Janssen, Abbvie, Pfizer, Novartis, Lilly, Gilead, Roche, Sandoz, Celgene, Sun, Boehringer, and Bristol Myers Squibb, Consultant of: Janssen, Abbvie, Pfizer, Novartis, Lilly, Gilead, Roche, Sandoz, Celgene, Sun, Boehringer, and Bristol Myers Squibb, Grant/research support from: Janssen, Abbvie, Pfizer, Novartis, Lilly, Gilead, Roche, Sandoz, Celgene, Sun, Boehringer, and Bristol Myers Squibb, Proton Rahman Speakers bureau: Janssen, Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, and UCB, Grant/research support from: Janssen and Novartis

POS1070 BASELINE DETERMINANTS OF PAIN RESPONSE IN PATIENTS WITH PSORIATIC ARTHRITIS RECEIVING GUSELKUMAB

Background

Pain in patients (pts) with psoriatic arthritis (PsA) has multifaceted origins; sustained improvement is difficult to achieve.1 Guselkumab (GUS), a fully human monoclonal antibody that selectively inhibits IL-23, is effective in treating multiple domains of PsA including joint, skin, and entheseal symptoms, and also elicits long-lasting improvements in pt-reported pain in the DISCOVER-1&2 trials of pts with active PsA.2

Objectives

These post hoc analyses were conducted to identify determinants of changes in pt-reported pain in PsA pts using pooled data through 1 year of DISCOVER-1&2.

Methods

Enrolled adult pts had active PsA despite standard therapies. DISCOVER-1 pts had ≥3 swollen and ≥3 tender joints and C-reactive protein (CRP) ≥0.3 mg/dL; DISCOVER-2 pts had ≥5 swollen and ≥5 tender joints and CRP ≥0.6 mg/dL. 31% of DISCOVER-1 pts received 1-2 prior tumor necrosis factor inhibitors; DISCOVER-2 pts were biologic-naïve. Pts were randomized 1:1:1 to GUS 100 mg every 4 weeks (wks) (Q4W); GUS 100 mg at W0, W4, then every 8 wks (Q8W); or placebo (PBO); PBO pts crossed over to GUS 100 mg Q4W at W24. Determinants with a statistically important effect (p<0.15) on pain (0-100 mm Visual Analogue Scale) in univariate Repeated Measures Generalized Linear Mixed Effects Models were included in a multivariate model employing backward stepwise selection (Pout=0.1) to identify independent determinants of pain improvement over 24 wks; the model was then tested separately in pts treated with PBO (through W24) and with GUS (through W24 and through W52).

Results

GUS was associated with significantly greater improvement in pain compared to PBO as early as 2 wks post-treatment; there was a significant interaction between treatment group and time, with effect of GUS on pain continuously enhanced through W24. Higher baseline (BL) pain score, worse mental health (assessed with the Short-Form-36 Mental Component Summary [SF-36 MCS] score), and lower fatigue level and lower tender joint count [TJC] were also associated with significantly greater pain improvements at W24, while background use of NSAIDs was a negative predictor of pain improvement (Table 1). Treatment effect on pain was independent of PsA duration, gender, PsA subtype, prior TNFi exposure, BL skin disease, and BL swollen joint count (SJC). Continuous significant improvement from BL in pain with GUS extended through W52 even after adjustment for the identified determinants of pain improvement through W24 (Figure 1). At W52, predictors of change in pain remained significant with the exception of SF-36 MCS score (Table 1). Results did not exclude a small number of enrolled pts with fibromyalgia (FM: nGUS=8; nPBO=4). According to these exploratory findings, medical history of FM was associated with lower pain improvement through W24 (p=0.066); in the models run separately in pts with GUS and PBO, pts with FM treated with GUS had a mean (95% CI) pain improvement (-9.1 [-19.5, 1.2]) while pts treated with PBO had a mean worsening (0.7 [-12.5, 13.9]). Pain improvement through 52 wks was significant regardless of FM: pts with FM had a mean (95% CI) improvement of -14.7

Table 1.

Significant Predictors of Change in Pain (W24 and W52)

BL DeterminantW24W52Estimate (95% CL)Estimate (95% CL)Pain score-0.62 (-0.69:-0.55) ‡-0.75 (-0.83:-0.67) ‡Fatigue-0.38 (-0.50:-0.27) ‡-0.37 (-0.53:-0.22) ‡SF-36 MCS0.20 (0.11:0.30)‡0.11 (-0.02:0.24)TJC0.13 (0.06:0.19) †0.12 (0.04:0.21) †NSAID use (Y vs N)2.29 (0.62:3.96) †2.76 (0.55:4.98) *

* p <0.05; †p <0.01; ‡p ≤0.0001

(-25.9, -3.6) comparable to non-FM pts at W24, while pain improvement in pts with no FM was -22.2 (-24.0, -20.4).

Conclusion

Early significant effects of GUS on pain were enhanced through 1 year. Significant predictors of change in pain were consistent at W24 and W52, with the exception of mental health measures. The impact of mental status on pt-reported pain and the potential for GUS to improve pain in pts with FM warrant further consideration.

References

[1]Gudu T et al. Expert Rev Clin Immunol 2018;14(5):405-17.

[2]Nash P et al. ACR Convergence 2021;Nov 5-9 (Poster 21-1368).

Disclosure of Interests

Peter Nash Grant/research support from: Janssen, Abbvie, Pfizer, Novartis, Lilly, Gilead, Roche, Sandoz, Celgene, Sun, Boehringer, and Bristol Myers Squibb, Christopher T. Ritchlin Consultant of: UCB Pharma, Amgen, AbbVie, Lilly, Pfizer, Novartis, Gilead, Janssen, Grant/research support from: UCB Pharma, AbbVie, Amgen, Proton Rahman Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, and UCB, Grant/research support from: Janssen and Novartis, May Shawi Shareholder of: Johnson & Johnson, Employee of: Janssen Pharmaceutical Companies of Johnson & Johnson, Emmanouil Rampakakis Consultant of: Janssen, Employee of: JSS Medical Research, YoungJa Lee Shareholder of: Johnson & Johnson, Employee of: Janssen Asia Pacific, Alexa Kollmeier Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Xie L Xu Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Jonathan Sherlock Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Daniel Cua Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Saakshi Khattri Speakers bureau: AbbVie, Eli Lilly, Glenmark, Ichnos Sciences, Janssen, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Eli Lilly, Glenmark, Ichnos Sciences, Janssen, Novartis, Pfizer, and UCB, Enrique Soriano Speakers bureau: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB, Consultant of: AbbVie, Janssen, Novartis, and Roche, Grant/research support from: AbbVie, Janssen, Novartis, Pfizer, Roche, and UCB, Dennis McGonagle Grant/research support from: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, and UCB

POS0082 A NOVEL PSORIATIC ARTHRITIS COMPOSITE ENDPOINT COMBINING TREATMENT TARGETS FOR SKIN AND JOINTS: POOLED RESULTS FROM THE GUSELKUMAB DISCOVER-1 AND DISCOVER-2 STUDIES

Background

Psoriatic arthritis (PsA) is characterized by a range of musculoskeletal and extra-articular disease manifestations. Composite indices are valuable tools to assess the multidimensional nature of PsA. The Psoriatic Arthritis Disease Activity Score (PASDAS)1 provides robust assessment of both joint and skin domains but is cumbersome to use in clinical practice. The Disease Activity Index for Psoriatic Arthritis (DAPSA)2 is relatively easy to use but does not assess skin disease.

Objectives

Using pooled data from the phase 3 DISCOVER-1 and DISCOVER-2 studies of guselkumab (GUS) for the treatment of active PsA:3,4 (1) Describe the rate of achievement of a new composite endpoint combining DAPSA low disease activity (LDA; score ≤14, including remission) and Investigator Global Assessment (IGA) of psoriasis score ≤1 (range=0 [clear] to 4 [severe]); (2) Determine whether earlier (Week [W] 16) DAPSA LDA + IGA ≤1 is predictive of future achievement of minimal disease activity (MDA) or American College of Rheumatology (ACR) 50 response criteria; and (3) Contrast the performance of DAPSA LDA + IGA ≤1 with that of PASDAS LDA (score ≤3.2).

Methods

Patients (pts) with active PsA despite standard therapies (DISCOVER-1: ≥3 swollen + ≥3 tender joints; CRP ≥0.3 mg/dL; ~30% had prior use of up to 2 TNF inhibitors; DISCOVER-2: ≥5 swollen + ≥5 tender joints; CRP ≥0.6 mg/dL; all pts were biologic-naïve) were randomized 1:1:1 to GUS 100 mg at W0, W4, then Q4W or Q8W; or placebo (PBO) with crossover to GUS Q4W at W24. In both studies, efficacy of GUS vs PBO was compared at W24 (primary endpoint). The number (%) of pts with DAPSA LDA + IGA ≤1 was determined at W24 for pts randomized to GUS or PBO. For all GUS-randomized pts, baseline variables associated with DAPSA LDA + IGA ≤1 and PASDAS LDA at W16 and the predictive value of W16 DAPSA LDA + IGA ≤1 or PASDAS LDA for achieving ACR50, MDA, and DAPSA LDA at W52 were assessed using logistic regression models.

Results

At W24, DAPSA LDA + IGA ≤1 was met by 37% (277/748) of GUS-treated pts vs 13% (48/372) in the PBO group. At W16, 27% (203/748) of GUS-randomized pts had DAPSA LDA + IGA ≤1, and 22% (164/748) had PASDAS LDA. Among the 73% (545/748) of pts who did not have DAPSA LDA + IGA ≤1 at W16, most (77% [418/545]) had IGA ≤1 but not DAPSA LDA; 4% (23/545) had DAPSA LDA but not IGA ≤1, and 19% (104/545) had neither component. Baseline predictors of DAPSA LDA + IGA ≤1 at W16 were male gender, lower dactylitis score, lower Health Assessment Questionnaire-Disability Index (HAQ-DI) score, lower tender joint count (TJC), and higher Psoriasis Area and Severity Index (PASI) score. Baseline predictors of PASDAS LDA at W16 were younger age, lower dactylitis score, lower HAQ-DI score, lower TJC, and higher PASI score. As shown (Figure 1), pts who had DAPSA LDA + IGA ≤1 and PASDAS LDA at W16 were significantly more likely to achieve ACR50, MDA, and DAPSA LDA at W52 than pts without W16 responses; odds ratios (ORs) for achievement of ACR50, MDA, and DAPSA LDA responses at W52 were similar for pts who had DAPSA LDA + IGA ≤1 and for pts who had PASDAS LDA at W16. ORs for achievement of ACR50 and MDA at W52 were higher for pts who had both DAPSA LDA and IGA ≤1 at W16 (9.5 and 10.7) than for pts who had DAPSA LDA but not IGA ≤1 (6.5 and 3.5) or IGA ≤1 but not DAPSA LDA (1.6 and 1.5).

Conclusion

DAPSA LDA at W16 predicted future (W52) achievement of the stringent treatment targets of ACR50 and MDA; associations with W52 response were greater when W16 IGA ≤1 was added to DAPSA LDA. DAPSA LDA + IGA ≤1 at W16 as a predictor of W52 ACR50 and MDA response performed similarly to PASDAS LDA. The novel composite of DAPSA LDA + IGA ≤1 may be a reliable predictor of long-term PsA skin and joint response that is more practical to implement than the PASDAS.

References

[1]Helliwell PS et al. Ann Rheum Dis. 2013;72:986-91.

[2]Schoels M et al. Ann Rheum Dis 2010;69:1441-47.

[3]Deodhar A et al. Lancet 2020;395:1115-25.

[4]Mease PJ et al. Lancet 2020;395:1126-36.

Disclosure of Interests

Wolf-Henning Boehncke Speakers bureau: AbbVie, Almirall, Janssen, Leo, Lilly, Novartis, and UCB, Consultant of: AbbVie, Almirall, Janssen, Leo, Lilly, Novartis, and UCB, Alice B Gottlieb Consultant of: AnaptsysBio, Avotres Therapeutics, Beiersdorf, Boehringer Ingelheim, Bristol-Myers Squibb Co., Incyte, GSK, Janssen, LEO Pharma, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical Industries, Inc., UCB, and Dermavant, Grant/research support from: Boehringer Ingelheim, Incyte, Janssen, Novartis, UCB, Xbiotech, and Sun Pharma, Enrique Soriano Speakers bureau: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB, Consultant of: AbbVie, Janssen, Novartis, and Roche, Grant/research support from: AbbVie, Janssen, Novartis, Pfizer, Roche, and UCB, Alexis Ogdie Consultant of: Abbvie, Amgen, BMS, Celgene, CorEvitas, Gilead, Happify Health, Janssen, Lilly, Novartis, Pfizer, and UCB, Grant/research support from: Abbvie, Pfizer and Novartis and to Forward from Amgen, Olga Ziouzina Consultant of: AbbVie, Amgen, Janssen, Novartis, Eli Lilly, Pfizer, UCB, Celltrion, and Fresenius-Kabi, Emmanouil Rampakakis Consultant of: Janssen, Employee of: JSS Medical Research, Xie L Xu Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Soumya D Chakravarty Shareholder of: Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC, May Shawi Shareholder of: Johnson & Johnson, Employee of: Janssen Pharmaceutical Companies of Johnson & Johnson, Marilise Marrache Shareholder of: Johnson & Johnson, Employee of: Janssen Inc, Alexa Kollmeier Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Atul Deodhar Speakers bureau: AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Amgen, Aurinia, Bristol Myers Squibb, Celgene, Eli Lilly, GlaxoSmithKline, Janssen, MoonLake, Novartis, Pfizer, and UCB, Grant/research support from: AbbVie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer, and UCB

AB0894 Efficacy and Safety of Guselkumab in Biologic-Naïve Patients With Active Axial Psoriatic Arthritis: Study Design of a Phase 4, Randomized, Double-Blind, Placebo-Controlled Trial

Background

Established criteria for classifying axial psoriatic arthritis (PsA) are lacking, and assessments of disease activity often rely on measures developed for ankylosing spondylitis (AS). There is an unmet need to systematically identify and measure efficacy of treatments for axial PsA patients (pts). Guselkumab (GUS), a selective interleukin (IL)-23p19 inhibitor, was efficacious in improving signs and symptoms of active PsA in 2 phase 3, randomized, placebo (PBO)-controlled studies: DISCOVER-1 and DISCOVER-2. In a post-hoc pooled analysis of DISCOVER-1&2 pts with investigator-confirmed sacroiliitis, GUS-treated pts had greater improvements in axial symptoms compared with PBO.1 Imaging in DISCOVER-1&2 was restricted to the sacroiliac (SI) joints, occurring prior to/at screening as confirmed by the investigator, and locally read.

Objectives

To design a new, dedicated study to evaluate the effects of GUS on axial PsA prospectively.

Methods

Cumulative evidence from DISCOVER-1&2, including exposure–response relationship, covariate adjustment for modest baseline imbalances across treatment groups, subgroup analyses, and comparisons within and across these studies, was considered in designing a new trial. Data from the pivotal registrational studies suggest similar efficacy with GUS every-4-weeks (Q4W) and Q8W regimens in treating PsA signs and symptoms, including symptoms of axial involvement. Power calculations were based on mean changes in Bath AS Disease Activity Index (BASDAI) scores in DISCOVER-1&2.

Results

The phase 4, randomized, PBO-controlled STAR study is specifically designed to prospectively assess efficacy outcomes in PsA pts with magnetic resonance imaging (MRI)-confirmed axial inflammation. Based on observed mean (SD) changes from baseline in BASDAI score from DISCOVER-1&2 (Table 1), 405 pts, randomized (1:1:1) to GUS Q4W, GUS at W0, W4, then Q8W, or PBO →GUS Q8W at W24, are planned for enrollment (Figure 1). STAR eligibility criteria include PsA ≥6 months and active disease (≥3 swollen & ≥3 tender joints, C-reactive protein [CRP] ≥0.3 mg/dL) despite prior non-biologic disease-modifying antirheumatic drugs, apremilast, and/or non-steroidal anti-inflammatory drugs. Pts will be naïve to biologics and Janus kinase inhibitors and have BASDAI ≥4, spinal pain score (visual analog scale [VAS]) ≥4, and screening MRI-confirmed axial disease (positive spine and/or SI joints defined as centrally read Spondyloarthritis Research Consortium of Canada [SPARCC] score ≥3). Follow-up MRIs of spine and SI joints will be obtained at W0, W24, and W52 and also centrally read, with readers blinded to treatment group and timepoint. Spinal/SI joint inflammation will be scored using the SPARCC method, with the former also assessed using the CAN-DEN method. The primary endpoint is mean change in BASDAI at W24; controlled (hierarchical) secondary endpoints, all at W24, include AS Disease Activity Score (ASDAS-CRP), Disease Activity Index for PsA (DAPSA), ≥40% improvement in Assessment in AS criteria (ASAS40), and mean changes in spine/SI joint SPARCC scores.

Table 1.

Power calculations for the primary endpoint in the Phase 4 STAR study.

Historical trial data*Observed mean (SD) change in BASDAI from W0-24Effect sizePower(N=135; α=0.05)**PBO-1.28 (2.24)GUS 100 mg Q4W-2.51 (2.00)1.23>99%GUS 100 mg Q8W-2.61 (2.47)1.33>99%

* From the pooled DISCOVER-1&2 trials

**Power calculations based on N=135 per study group (1:1:1 randomization) and 2-sided significance of 0.05 using a 2-sample T-test assuming equal variances

BASDAI, Bath Ankylosing Spondylitis Disease Activity Index; GUS, guselkumab; PBO, placebo; Q4W, every 4 weeks; Q8W, every 8 weeks; SD, standard deviation; W, week

Conclusion

The phase 4 STAR study will allow for an in-depth, prospective evaluation of the effects of selectively inhibiting the IL-23p19 subunit with GUS in pts with MRI-confirmed axial PsA.

References

[1]Mease, et al. Lancet Rheum. 2021;3(10):e715-e723.

Disclosure of Interests

Dafna D Gladman Consultant of: AbbVie, Amgen, BMS, Celgene, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, and UCB, Grant/research support from: Abbvie, Amgen, BMS, Celgene, Eli Lilly, Janssen, Novartis, Pfizer and UCB, Philip J Mease Speakers bureau: AbbVie, Aclaris, Amgen, BMS, Celgene, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Inmagene, Janssen, Novartis, Pfizer, SUN Pharma, and UCB, Consultant of: AbbVie, Aclaris, Amgen, BMS, Celgene, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Inmagene, Janssen, Novartis, Pfizer, SUN Pharma, and UCB, Grant/research support from: AbbVie, Aclaris, Amgen, BMS, Celgene, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Inmagene, Janssen, Novartis, Pfizer, SUN Pharma, and UCB, Paul Bird Speakers bureau: AbbVie, Eli Lilly, Gilead, Janssen, MSD, Pfizer, and UCB, Consultant of: Eli Lilly, Gilead, Janssen, Novartis, and Pfizer, Enrique Soriano Speakers bureau: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB, Consultant of: AbbVie, Janssen, Novartis, and Roche, Grant/research support from: AbbVie, Janssen, Novartis, Pfizer, Roche, and UCB, Soumya D Chakravarty Shareholder of: Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC, May Shawi Shareholder of: Johnson & Johnson, Employee of: Janssen Global Services, LLC, Stephen Xu Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Sean Quinn Shareholder of: Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC, Cinty Gong Shareholder of: Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC, Evan Leibowitz Shareholder of: Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC, Lai-Shan Tam Consultant of: Janssen, Pfizer, Sanofi, AbbVie, Boehringer Ingelheim, and Lilly, Grant/research support from: Amgen, Boehringer Ingelheim, Janssen, GSK, Novartis, and Pfizer, Philip Helliwell Speakers bureau: AbbVie, Janssen, and Novartis, Consultant of: Galapagos and Janssen, Grant/research support from: AbbVie, Janssen, and Pfizer, Arthur Kavanaugh Consultant of: Abbvie, Amgen, Bristol Myers Squibb, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, and UCB, Atul Deodhar Speakers bureau: AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Eli Lilly, Galapagos, Glaxo Smith & Kline, Janssen, Novartis, Pfizer, and UCB, Grant/research support from: AbbVie, Eli Lilly, Glaxo Smith & Kline, Novartis, Pfizer, and UCB, Mikkel Østergaard Speakers bureau: AbbVie, Boehringer-Ingelheim, Bristol Myers Squibb, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Consultant of: AbbVie, Boehringer-Ingelheim, Bristol Myers Squibb, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Grant/research support from: AbbVie, Bristol Myers Squibb, Celgene, and Novartis, Xenofon Baraliakos Speakers bureau: AbbVie, Biocad, Chugai, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche, and UCB, Consultant of: AbbVie, Biocad, Chugai, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche, and UCB, Grant/research support from: AbbVie, Biocad, Chugai, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche, and UCB

POS0025 PREVALENCE OF ATTENTION DEFICIT HYPERACTIVITY DISORDER AMONG ADULT PATIENTS WITH FIBROMYALGIA

Background

Fibromyalgia (FM) and attention deficit hyperactivity disorder (ADHD) share some clinical features, and a reduced dopamine function has been proposed for both disorders. ADHD is a chronic condition, marked by persistent inattention, impaired concentration, hyperactivity, impulsivity, emotional lability, anxiety and disorganized behaviour. High rates of comorbidity between ADHD and FM have been reported, as well as some evidence that patients with both conditions experience heightened disease severity.

Objectives

Our purpose was to determine the prevalence of ADHD symptoms in patients with FM and to assess the relationship with disease impact.

Methods

Consecutive patients, older than 18 years, with diagnosis of FM (ACR 2016 criteria) without known cognitive impairment, seen at the Rheumatology Unit between April 2018 and December 2019, were included. At inclusion visit the collected data included Revised Fibromyalgia Impact Questionnaire (FIQ-R) and Health Assessment Questionnaire, Argentine version (HAQ-A). During the Neurology visit, the following tests were performed: Montreal Cognitive Assessment (MoCA) test for evaluating the presence of cognitive impairment, Conners Continuous Performance Test II (CPT II) for the assessment of ADHD, and Wender-Utah Rating Scale (WURS) to retrospectively assess childhood ADHD symptoms. Univariate analysis was performed using t-tests for normally distributed continuous variables, and Wilcoxon rank sum test for non-normally distributed continuous variables. A chi-square or Fisher test was used when appropriate for categorical variables. Predictors that were found to be related to ADHD (p ≤ 0.20) were then entered into a multivariable logistic regression model.

Results

60 patients with FM and 71 matched controls without FM or known cognitive impairment were included. FM patients’ characteristics are shown in Table 1. 61.7% (n=37) of the patients with FM tested positive for adult ADHD. In 48.6% (18/37) of them, the diagnosis had been missed in childhood. Participants with both FM and a positive adult ADHD screening test did not score significantly higher on the FIQ-R (52.3, SD= 16.1 vs. 47.9, SD= 12.3; p= 0.2693) and HAQ-A (0.693, SD= 0.455 vs. 0.521, SD= 0.428; p=0.1523) compared with patients without ADHD. Retrospectively assessed childhood ADHD was significantly associated with adult persistence (OR 55.1, CI=3.6 to 842.6, p=0.004).

Table 1.

Clinical and demographic characteristics of patients with FM.

Characteristicsn=60Female, n (%)53 (88.3)Age (years), mean (SD)58.3 (14.2)Time from diagnosis (years), mean (SD)5.2 (5)Scholarity (years), mean (SD)12.9 (3.4)HAQ-A, mean (SD)0.627 (0.449)FIQ-R, mean (SD)50.6 (14.8)Cognitive complaint, n (%)34 (56.7)Depression, n (%)35 (58.3)Anxiety, n (%)27 (45)Concomitant personality disorders39 (65)

Patients with FM had significantly higher prevalence of cognitive impairment (43.3% vs. 16.9%; p<0.0001), childhood ADHD symptoms (31.7% vs. 14.1%; p=0.016) and adult ADHD symptoms (61.7% vs. 23.9%; p<0.0001) than the control group (Figure 1).

Figure 1.

Percentage of FM patients with cognitive impairment, childhood and adult ADHD. Comparison with the control population.

Conclusion

The co-occurrence of adult ADHD in FM was highly prevalent. In nearly half of the patients the diagnosis had been overlooked during childhood and it was associated with adult persistence. The prevalence of cognitive impairment, and childhood and adult ADHD was higher in patients with FM compared with the control group. ADHD was not associated with the FM impact. Evaluation of ADHD symptoms in patients with FM is important for recognition and treatment of this comorbidity.

References

[1]Stefano P et al. J Psychiatr Res. 2021 Apr;136:537-542.

[2]Karas H et a.l Int J Psychiatry Clin Pract. 2020 Sep;24(3):257-263.

[3]Kessler RC et al. Biol Psychiatry. 2005 Jun 1;57(11):1442-51.

Acknowledgements

The authors thank the patients who agreed to participate in

this study.

Disclosure of Interests

None declared

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

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

OP0249 CHARACTERISTICS ASSOCIATED WITH POOR COVID-19 OUTCOMES IN PEOPLE WITH PSORIASIS AND SPONDYLOARTHRITIS: DATA FROM THE COVID-19 PsoProtect AND GLOBAL RHEUMATOLOGY ALLIANCE PHYSICIAN-REPORTED REGISTRIES

Background

Some factors associated with severe COVID-19 outcomes have been identified in patients with psoriasis (PsO) and inflammatory/autoimmune rheumatic diseases, namely older age, male sex, comorbidity burden, higher disease activity, and certain medications such as rituximab. However, information about specificities of patients with PsO, psoriatic arthritis (PsA) and axial spondyloarthritis (axSpA), including disease modifying anti-rheumatic drugs (DMARDs) specifically licensed for these conditions, such as IL-17 inhibitors (IL-17i), IL-23/IL-12 + 23 inhibitors (IL-23/IL-12 + 23i), and apremilast, is lacking.

Objectives

To determine characteristics associated with severe COVID-19 outcomes in people with PsO, PsA and axSpA.

Methods

This study was a pooled analysis of data from two physician-reported registries: the Psoriasis Patient Registry for Outcomes, Therapy and Epidemiology of COVID-19 Infection (PsoProtect), comprising patients with PsO/PsA, and the COVID-19 Global Rheumatology Alliance (GRA) registry, comprising patients with PsA/axSpA. Data from the beginning of the pandemic up to 25 October, 2021 were included. An ordinal severity outcome was defined as: 1) not hospitalised, 2) hospitalised without death, and 3) death. A multivariable ordinal logistic regression model was constructed to assess the relationship between COVID-19 severity and demographic characteristics (age, sex, time period of infection), comorbidities (hypertension, other cardiovascular disease [CVD], chronic obstructive lung disease [COPD], asthma, other chronic lung disease, chronic kidney disease, cancer, smoking, obesity, diabetes mellitus [DM]), rheumatic/skin disease (PsO, PsA, axSpA), physician-reported disease activity, and medication exposure (methotrexate, leflunomide, sulfasalazine, TNFi, IL17i, IL-23/IL-12 + 23i, Janus kinase inhibitors (JAKi), apremilast, glucocorticoids [GC] and NSAIDs). Age-adjustment was performed employing four-knot restricted cubic splines. Country-adjustment was performed using random effects.

Results

A total of 5008 individuals with PsO (n=921), PsA (n=2263) and axSpA (n=1824) were included. Mean age was 50 years (SD 13.5) and 51.8% were male. Hospitalisation (without death) was observed in 14.6% of cases and 1.8% died. In the multivariable model, the following variables were associated with severe COVID-19 outcomes: older age (Figure 1), male sex (OR 1.53, 95%CI 1.29-1.82), CVD (hypertension alone: 1.26, 1.02-1.56; other CVD alone: 1.89, 1.22-2.94; vs no hypertension and no other CVD), COPD or asthma (1.75, 1.32-2.32), other lung disease (2.56, 1.66-3.97), chronic kidney disease (2.32, 1.50-3.59), obesity and DM (obesity alone: 1.36, 1.07-1.71; DM alone: 1.85, 1.39-2.47; obesity and DM: 1.89, 1.34-2.67; vs no obesity and no DM), higher disease activity and GC intake (remission/low disease activity and GC intake: 1.96, 1.36-2.82; moderate/severe disease activity and no GC intake: 1.35, 1.05-1.72; moderate/severe disease activity and GC intake 2.30, 1.41-3.74; vs remission/low disease activity and no GC intake). Conversely, the following variables were associated with less severe COVID-19 outcomes: time period after 15 June 2020 (16 June 2020-31 December 2020: 0.42, 0.34-0.51; 1 January 2021 onwards: 0.52, 0.41-0.67; vs time period until 15 June 2020), a diagnosis of PsO (without arthritis) (0.49, 0.37-0.65; vs PsA), and exposure to TNFi (0.58, 0.45-0.75; vs no DMARDs), IL17i (0.63, 0.45-0.88; vs no DMARDs), IL-23/IL-12 + 23i (0.68, 0.46-0.997; vs no DMARDs) and NSAIDs (0.77, 0.60-0.98; vs no NSAIDs).

Conclusion

More severe COVID-19 outcomes in PsO, PsA and axSpA are largely driven by demographic factors (age, sex), comorbidities, and active disease. None of the DMARDs typically used in PsO, PsA and axSpA, were associated with severe COVID-19 outcomes, including IL-17i, IL-23/IL-12 + 23i, JAKi and apremilast.

Acknowledgements

We thank all the contributors to the COVID-19 PsoProtect, GRA and EULAR Registries.

Disclosure of Interests

None declared

Burnout in Rheumatologists in Latin America

BACKGROUND

Rheumatology is considered a low-risk specialty, but studies have shown a prevalence of burnout between 42% and 51%.

OBJECTIVES

The aim was to determine the prevalence of burnout in rheumatologists in Latin America and the factors associated with it.

METHODS

Cross-sectional study based on a survey completed through Google Forms platform that was sent by the national rheumatology associations of Latin America. Burnout was assessed with the Maslach Burnout Inventory. Data were analyzed using the statistical program SPSS v.22.

RESULTS

Two hundred ninety-seven rheumatologists from 15 countries were included, mainly Argentina (28.3%), Brazil (26.3%), and Mexico (12.8%). The majority were women 62%, 42.4% worked in public hospitals with an average of 40.1 ± 14.2 hours per week; 31.3% did research, 13.1% clinical trials, 56.6% teaching, and 42.8% administrative work; 36% received an annual income less than $25,000; 56.6% had burnout in at least 1 dimension. Only 20.2% thought they had burnout, 9.1% were currently receiving professional help, and 15.8% had sought help in the past; 72.1% said they were willing to participate in a program to reduce burnout. The rheumatologists with burnout were younger than those without burnout (46.5 vs 49.9 years, p = 0.015).

CONCLUSIONS

Burnout affects near half of rheumatologists in Latin America and was associated with younger age, long working hours, low satisfaction, less happiness, higher Patient Health Questionnaire-9, suicidal thoughts, anxiety, income, presence of comorbidities, and low self-esteem.

Advanced interatrial block predicts recurrence of embolic stroke of undetermined source

BACKGROUND

Advanced interatrial block (IAB) is an independent risk factor for ischaemic stroke. This study aimed to analyse whether advanced IAB predicts recurrence of embolic stroke of undetermined source (ESUS).

METHODS

104 patients with a confirmed diagnosis of ESUS were followed up for a median period of 15 months (interquartile range, 10-48). We recorded data on clinical variables, P-wave characteristics, and presence of IAB on the electrocardiogram (ECG). ECG findings were interpreted by a blinded, centralised rater at (XXXX2). ESUS recurrence was the primary outcome variable.

RESULTS

Median age was 47 years (range, 19-85); 50% of patients were women. IAB was detected in 36 patients (34.6%); IAB was partial in 29 cases (27.9%) and advanced in 7 (6.7%). Sixteen patients (15.4%) presented stroke recurrence; of these, 5 had partial and 4 had advanced IAB (P = .01; odds ratio [OR] = 9.44; 95% confidence interval [CI], 1.88-47.46; relative risk [RR] = 4.62; 95% CI, 2.01-10.61). Median P-wave duration was longer in patients with stroke recurrence (P = .009). The multivariate logistic regression analysis identified the following independent risk factors for stroke recurrence: advanced IAB (P < .001; OR = 10.86; 95% CI, 3.07-38.46), male sex (P = .028; OR = 4.6; 95% CI, 1.18-17.96), and age older than 50 years (P = .039; OR = 3.84; 95% CI, 1.06-13.88). In the Cox proportional hazards model, the risk variables identified were age older than 50 years (P = .002; hazard ratio, 7.04; 95% CI, 2.06-23.8) and P-wave duration (per ms) (P = .007; hazard ratio, 1.02; 95% CI, 1.01-1.04).

CONCLUSIONS

Advanced IAB and age older than 50 years predict ESUS recurrence.

POS1188 COVID-19 IN PATIENTS WITH RHEUMATIC DISEASES: COMPARISON OF DATA FROM THE ARGENTINE REGISTRY (SAR-COVID), WITH THE LATIN AMERICAN AND GLOBAL REGISTRY (GLOBAL RHEUMATOLOGY ALLIANCE)

Background:

SARS CoV-2 infection has recently burst onto the global scene, and the knowledge of the course of this infection in patients with rheumatic diseases receiving immunomodulatory treatment is still insufficient. The Argentine Society of Rheumatology (SAR) designed a national registry called SAR-COVID in order to get to assess our reality.

Objectives:

To identify the particular characteristics of patients with rheumatic diseases and COVID-19 in Argentina (SAR-COVID Registry), and to compare them with the data reported at the Latin American and Global level (Global International Alliance Rheum-COVID Registry).

Methods:

A national, multicenter, prospective and observational registry was carried out. Patients older than 18 years, with a diagnosis of rheumatic disease and SARS-CoV-2 infection by PCR or serology, were included between August 13, 2020 and January 17, 2021. Demographic data, underlying rheumatic disease (activity of the disease, current treatment), comorbidities, clinical-laboratory characteristics of the SARS-CoV-2 infection, as well as received treatments (pharmacological, oxygen therapy / ventilatory support) and outcomes (hospitalization, mortality) were recorded. The characteristics of the included patients were compared with the data reported at the Latin American and global level. Descriptive statistics were performed. Comparisons between groups were made using ANOVA, chi2 or Fisher’s test, according to the type of variable.

Results:

Four hundred sixty-five patients from Argentina, 74 patients from Latin America and 583 from the rest of the world were included, mostly women (79.6%, 73% and 71% respectively), with a mean age of 50.2 (SD 15.3), 53.5 (DE 15.6) and 55.8 (15.5), years respectively. The most frequent rheumatic diseases in the three groups were rheumatoid arthritis (43.9%, 35%, and 39%) and systemic lupus erythematosus (16.1%, 22%, and 14%) (Table 1).

In Argentina, fewer patients received specific pharmacological treatment for COVID-19 (40.9%, 68% and 43% respectively, p <0.0001), and there was a lower requirement of NIMV / IMV (Non-Invasive Mechanical Ventilation/Invasive Mechanical Ventilation) than in the rest of Latin America and the world (10.5% vs 31% vs 13%, p <0.0001).

Hospitalization was lower in Argentina than in the rest of Latin America (37.4% vs 61% p 0.0002) and of the world (37.4% vs 45% p 0.0123), and mortality was numerically lower in Argentina, but without statistically significant differences between the three groups (6.9%, 12% and 11%; p 0.6311). Most of the patients, (86.9%) did not present any complications in Argentina, with a statistically significant difference with the rest of the groups (62% and 77%, p <0.0001) (Graph 1).

Conclusion:

The patients with rheumatic diseases and SARS-CoV-2 infection reported in this argentinian registry received less specific pharmacological treatment for COVID-19, presented fewer complications and required less ventilatory support, than those reported in the Latinoamerican and Global registry. However, no statistically significant differences were observed in terms of mortality.

Graph 1.

Main outcomes and evolution of patients with rheumatic disease and COVID-19.

References:

[1]Stokes, Erin K, Zambrano, Laura D, Anderson, Kayla N, et al. Coronavirus Disease 2019 Case Surveillance - United States, January 22-May 30, 2020. MMWR Morb Mortal Wkly Rep; 69(24): 759-765, 2020 Jun 19.

[2]Mehta P, McAuley DF, Brown M, et al. COVID-19: consider cytokine storm síndromes and immunosuppression. Lancet 2020;395:1033–4.

[3]Gianfrancesco M, et al. Characteristics associated with hospitalisation for COVID-19 in people with rheumatic disease: data from the COVID-19 Global Rheumatology Alliance physician-reported registry. Ann Rheum Dis 2020;79:859–866.

[4]Manuel F. Ugarte-Gil, et al. Characteristics associated with Covid-19 in patients with Rheumatic Disease in Latin America. Global Rheumatology. Septiembre 2020.

Disclosure of Interests:

Alvaro Andres Reyes Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Gelsomina Alle Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Romina Tanten Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Marina Scolnik Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Enrique Soriano Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Guillermo Berbotto Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Maria Haye Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, María Julieta Gamba Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Romina Nieto Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Mercedes García Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Veronica Savio Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Luciana Gonzalez Lucero Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Paula Alba Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Lorena Takashima Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, FABIAN RISUEÑO Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Luciana CASALLA Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Natalia Cucchiaro Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Ana Bertoli Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Sabrina POrta Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Carla Maldini Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Rosana Gallo Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Cecilia Goizueta Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Eugenia Picco Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Rosana Quintana Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Karen Roberts Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Carolina Ayelen Isnardi Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”, Guillermo Pons-Estel Grant/research support from: “Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.”

POS0984 PREVALENCE OF AXIAL SPONDYLOARTHRITIS AMONG YOUNG PEOPLE CONSULTING BECAUSE OF CHRONIC LOW BACK PAIN IN A UNIVERSITY HOSPITAL IN ARGENTINA

Background:

Axial spondyloarthritis (SpA) is an umbrella term encompassing a number of inflammatory conditions involving the axial skeleton. A substantial delay between disease onset, diagnosis and treatment often occurs, related in part to under-recognition of SpA symptoms. Although several studies have investigated since the publication of the ASAS classification criteria in 2009, the prevalence and incidence of axial SpA in the general population and in patients with SpA-related conditions, the actual prevalence of SpA in many countries (including Argentina) is unknown.

Objectives:

To estimate the prevalence of axial SpA and the amount of undiagnosed axial SpA in people under 45 years of age that contacted the health care system for chronic low back pain.

Methods:

The setting was a university hospital-based health management organization with a population distribution similary to that of Buenos Aires. All electronic medical records of patients < 45 years of age at the time of onset of symptoms (as per the ASAS 2009 criteria) and chronic low back pain for 3 or more months) seen at the university hospital-based health management organization between 2009 and 2019, were reviewed. If the patient fulfilled the ASAS criteria, was classified as having axial SpA [ankylosing spondylitis (AS) or non-radiographic axial SpA (nr-axSpA)]. Among this group, if the diagnosis was already established in the medical records by the treating physicians, these patients were also classified as diagnosed with axial SpA; if not, they were classified as undiagnosed with axial SpA. We are reporting the results of descriptive analysis.

Results:

A total of 796 patients were included (Table 1), 426 were women (53.52%, 95% CI 50.1-57) with a median age of 34 years (IQR 29-40) at initiation of low back pain with a median follow up of 77.7 months (IQR 35.7-136.4). The prevalence of axial SpA among patients with chronic low back pain was 5.78% (n= 46, 95% CI 4.2-7.4). 22 patients had AS (2.76%, 95% CI 1.6-3.9) with a median lag time between the onset of low back pain and diagnosis of 58.7 months (IQR 33.5 - 92). All AS cases were already diagnosed. 24 patients had nr-axSpA (3.02%, 95% CI 1.8 - 4.2). Of those, 14 were diagnosed by treating physicians with a lag time median of 23.2 months (IQR 13.1 - 36.5) between the onset of low back pain and diagnosis. Ten patients fulfilled the ASAS criteria (41.7%, CI 95% 22 - 61.4) but were not diagnosed by the treating physicians (22%, 95% CI 9.82-33.66) among the patients with axial SpA.

Table 1.

Demographic, clinical features and therapeutic characteristics of patients with chroniclow back pain stratified by diagnosis

Axial spondyloarthritisN=46Ankylosing spondylitisN=22Diagnosednr-axSpAN=14Undiagnosednr-axSpAN=10OtherdiagnosisN=749Female, n (%, CI)18(39.13%, 25.04-53.23)4(18.18%, 2.06-34.29)10(71.42%,47.76-95.09)4(40%, 9.63-70.36)407(54.34,50.77-57.9)Age at chronic LBP initiation, years, median (IQR)36(29.25-40)32(32-40)38(22-36.75)39(35.25-41.5)34(29-40)Follow up, median months (IQR)88(33.43-148.66)33.67(23.38-90.34)16.73(7.64-24.02)64.77(11.21-164.7)77.69(35.83-135.32)Inflammatory chronic LBP by any criteria n (%)44 (95.7)21 (95.5)13 (92.8)10 (100)56 (7.5, 5.6-9.4)Seen by a Rheumatologist, n (%)42 (91.3)22 (100)14 (100)6 (60)36 (5.1)Lag time between first LBP to SpA diagnosis, months, median (IQR)34.6 (22.6-63.2)58.7 (33.5 – 92)23.1 (13.1-36.5)--bDMARDs treatment n, (%, CI)15(33; 19.5–48)10(45; 24.4–67.8)5(36; 13–64.9)--Lag time between NSAIDs failure and first bDMARDs, months, median (IQR)2.66(2.05-4.63)2.76(2.07-11.3).2.66(2.04-3.25)--

CI: 95% confidential interval, IQR: interquartile range, bDMARDs: biologic disease modifying anti-rheumaticdrugs, LBP: low back pain

Conclusion:

In our cohort, 5.78% of the patients < 45 years with chronic low back pain had axial SpA (AS: 2.76%; and nr-axSpA: 3.02%). Approximately, one in every five patients had undiagnosed axial SpA. Original manuscript made in collaboration with Novartis Argentina S.A

Disclosure of Interests:

Mayra Alejandra Tobar Jaramillo: None declared, Nicolas Marin Zucaro: None declared, Javier Rosa: None declared, Josefina Marin: None declared, Maria Laura Acosta Felquer: None declared, LEANDRO FERREYRA: None declared, JOHN FREDY JARAMILLO GALLEGO: None declared, Josefina Marcos Employee of: Novartis, Vanesa Duarte Employee of: Novartis, Enrique Soriano Speakers bureau: AbbVie, Amber, Bristol-Myers Squibb, Eli Lilly, Novartis, Pfizer Inc, Roche, Consultant of: AbbVie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer Inc, Sandoz, Grant/research support from: AbbVie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer Inc, Sandoz.

AB0529 CHARACTERIZATION OF REMISSION IN PATIENTS WITH PSORIATIC ARTHRITIS TREATED WITH UPADACITINIB: POST-HOC ANALYSIS FROM TWO PHASE 3 TRIALS

Background:

For patients (pts) with PsA, several disease activity measures are available including very low/minimal disease activity (VLDA/MDA), cutoffs based on the Disease Activity in PsA (DAPSA) score, and on the Psoriatic Arthritis Disease Activity Score (PASDAS) score.

Objectives:

To assess the rates of pts achieving these remission or low disease activity (LDA) criteria at Wk 24 using data from the SELECT-PsA 1 and SELECT-PsA 2 phase 3 studies;1,2 Additionally, we assessed the distribution of individual MDA components among pts who did or did not achieve MDA criteria at Wk 24.

Methods:

In SELECT-PsA 1 and SELECT-PsA 2, pts with PsA and prior inadequate response (IR) or intolerance to ≥1 non-biologic DMARD (N=1705) or ≥1 biologic DMARD (N=642), respectively, were randomized to once daily upadacitinib (UPA) 15mg, UPA 30mg, adalimumab (ADA) 40mg every other week (SELECT-PsA 1 only), or placebo (PBO). Remission and LDA were assessed using VLDA/MDA, DAPSA scores of ≤4/≤14, and PASDAS scores of ≤1.9/≤3.2, at Wk 24 (Table 1). Non-responder imputation (NRI) was used for handling missing data; pts rescued at Wk 16 were considered non-responders. Pairwise comparisons between UPA doses and PBO or ADA were conducted using the Cochran-Mantel-Haenszel test.

Results:

Overall, 2345 pts were analyzed; mean age 51 years, 53% female. In both studies, higher rates of remission and LDA were observed with both UPA doses vs PBO at Wk 24 (nominal P-values <0.05 for both time points; Table 1). Generally, higher rates of remission and LDA were also observed with UPA30 vs ADA in non-biologic DMARD-IR pts (nominal P-values <0.05). Greater rates of MDA/VLDA were observed at Wk 24 with UPA15 and UPA30 vs PBO in both studies and with UPA30 vs ADA in non-biologic DMARD-IR pts (nominal P-values <0.05 for all comparisons). The proportion of responder or non-responder pts receiving UPA15 or UPA30 was similar for each of the MDA components in both studies. At Wk 24, more responder and non-responder pts in both studies achieved Swollen Joint Count (SJC) 66 ≤1, Psoriasis Area and Severity Index (PASI) ≤1 or Body Surface Area-Psoriasis (BSA-Ps) ≤3%, and Leeds Enthesitis Index (LEI) ≤1 (Figure 1). Conversely, the proportion of pts Achieving Tender Joint Count (TJC) 68 ≤1 and Pt’s Global Assessment of Pain ≤1.5 tended to be lower.

Conclusion:

Regardless of previous biologic DMARD failure, pts treated with UPA15 or UPA30 achieved a higher rate of remission or LDA measured by various disease activity measures vs PBO at Wk 24; higher rates of response were observed in most of the remission and LDA measures with UPA30 vs ADA in non-biologic DMARD-IR pts. Among pts who did or did not achieve MDA criteria at Wk 24, a greater proportion of UPA-treated pts achieved physician derived measures such as SJC ≤1, PASI ≤1 or BSA-Ps ≤3%, and LEI ≤1.

References:

[1]McInnes IB, et al. Ann Rheum Dis, 2020; 79:12.

[2]Genovese MC, et al. Ann Rheum Dis, 2020; 79:139.

Table 1.

Proportion of Patients Achieving Remission and LDA Measures at Week 24

Endpoint, n (%)SELECT-PsA 1SELECT-PsA 2PBON=423ADA 40mg EOWN=429UPA 15mg QDN=429UPA 30mg QDN=423PBON=212UPA 15mg QDN=211UPA 30mg QDN=218MDA52 (12.3)143 (33.3)157 (36.6) *, #192(45.4) *, †, #6 (2.8)53 (25.1) *, #63 (28.9) *, #≥6 VLDA components25 (5.9)90 (21.0)105 (24.5) *134 (31.7) *, †3 (1.4)26 (12.3) *44 (20.2) *VLDA11 (2.6)62 (14.5)55 (12.8) *72 (17.0) *3 (1.4)16 (7.6) *21(9.6) *DAPSA REM9 (2.1)43 (10.0)47 (11.0) *79 (18.7) *, †1 (0.5)15 (7.1) *28 (12.8) *DAPSA LDA70 (16.5)198 (46.2)204 (47.6) *235(55.6) *, †14 (6.6)73 (34.6) *91 (41.7) *PASDAS REM12 (2.8)51 (11.9)60 (14.0) *91 (21.5) *, †4 (1.9)20 (9.5) *31 (14.2) *PASDAS LDA63 (14.9)168 (39.2)195 (45.5) *211 (49.9) *, †9 (4.2)69 (32.7) *82 (37.6) *

*P ≤ 0.05 for UPA15 and UPA30 vs PBO; †P ≤ 0.05 for UPA30 vs ADA; #Statistically significant in the multiplicity-controlled analysis.

MDA (5/7) and VLDA (7/7): TJC ≤ 1; SJC ≤ 1; PASI ≤ 1 or BSA-Psoriasis ≤ 3%; Patient’s Assessment of Pain NRS ≤ 1.5; PtGA-Disease Activity NRS ≤ 2.0; HAQ-DI score ≤ 0.5; and tender entheseal points ≤ 1.

DAPSA REM ≤ 4; DAPSA LDA ≤ 14.

PASDAS REM ≤ 1.9; PASDAS LDA ≤ 3.2.

Figure 1

Acknowledgements:

AbbVie and the authors thank the patients, study sites, and investigators who participated in this clinical trial. AbbVie, Inc was the study sponsor, contributed to study design, data collection, analysis & interpretation, and to writing, reviewing, and approval of final version. No honoraria or payments were made for authorship. Medical writing support was provided by Ramona Vladea, PhD of AbbVie Inc.

Disclosure of Interests:

Philip J Mease Speakers bureau: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers, Celgene, Galapagos, Gilead, GlaxoSmithKline, Janssen, Lilly, Merck, Novartis, Pfizer, Sun Pharma, and UCB., Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers, Celgene, Galapagos, Gilead, GlaxoSmithKline, Janssen, Lilly, Merck, Novartis, Pfizer, Sun Pharma, and UCB., Grant/research support from: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers, Celgene, Galapagos, Gilead, GlaxoSmithKline, Janssen, Lilly, Merck, Novartis, Pfizer, Sun Pharma, and UCB., Arthur Kavanaugh Consultant of: AbbVie Inc., Amgen, Astra-Zeneca, BMS, Celgene, Centocor-Janssen, Pfizer, Roche, and UCB, Grant/research support from: AbbVie Inc., Amgen, Astra-Zeneca, BMS, Celgene, Centocor-Janssen, Pfizer, Roche, and UCB, Dafna D Gladman Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Celgene Corporation, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer Inc, and UCB, Oliver FitzGerald Speakers bureau: AbbVie, Amgen, BMS, Celgene, Janssen, Lilly, Novartis, Pfizer and UCB, Consultant of: AbbVie, Amgen, BMS, Celgene, Janssen, Lilly, Novartis, Pfizer and UCB, Grant/research support from: AbbVie, Amgen, BMS, Celgene, Janssen, Lilly, Novartis, Pfizer and UCB, Enrique Soriano Speakers bureau: AbbVie, Amgen, Bristol Myers, Celgene, Janssen, Lilly, Novartis, Pfizer, Roche, Sanofi, and UCB, Consultant of: AbbVie, Amgen, Bristol Myers, Celgene, Janssen, Lilly, Novartis, Pfizer, Roche, Sanofi, and UCB, Grant/research support from: AbbVie, Amgen, Bristol Myers, Celgene, Janssen, Lilly, Novartis, Pfizer, Roche, Sanofi, and UCB, Peter Nash Speakers bureau: AbbVie, BMS, Roche, Pfizer, Janssen, Amgen, Sanofi-Aventis, UCB, Eli Lilly, Novartis, and Celgene, Consultant of: AbbVie, BMS, Roche, Pfizer, Janssen, Amgen, Sanofi-Aventis, UCB, Eli Lilly, Novartis, and Celgene, Grant/research support from: AbbVie, BMS, Roche, Pfizer, Janssen, Amgen, Sanofi-Aventis, UCB, Eli Lilly, Novartis, and Celgene, Dai Feng Shareholder of: AbbVie, Employee of: AbbVie, Apinya Lertratanakul Shareholder of: AbbVie, Employee of: AbbVie, Kevin Douglas Shareholder of: AbbVie, Employee of: AbbVie, Ralph Lippe Shareholder of: AbbVie, Employee of: AbbVie, Laure Gossec Consultant of: AbbVie,Amgen, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Samsung, Sanofi, UCB, Grant/research support from: Lilly, Pfizer, and Sandoz.

POS0302 BURNOUT IN RHEUMATOLOGISTS IN LATIN AMERICA

Background:

Rheumatology is considered a low-risk specialty, but studies have shown a prevalence of burnout between 42% to 51%1,2. Factors associated with it include the use of electronic medical records, administrative tasks and prolonged working hours. This has several repercussions such as higher prevalence of depression/anxiety and less productivity.

Objectives:

To determine the prevalence of burnout in rheumatologists in Latin America and the factors associated with it.

Methods:

Cross-sectional study based on a survey completed through Google Forms platform that was sent by the national rheumatology associations of Latin America. Burnout was assessed with the Maslach Burnout Inventory (MBI) with cut off values of ≥27 for emotional exhaustion (EE), ≥10 for depersonalization (DP), and ≤33 for personal accomplishment (PA). Other variables were studied such as demographics, working conditions, satisfaction, comorbidities, depression using PHQ-9 and happiness using the Subjective Happiness Scale. Data was analyzed using the statistical program SPSS v.22.

Results:

297 rheumatologists from 15 countries were included, mainly Argentina (28.3%), Brazil (26.3%) and Mexico (12.8%). The majority were women 62%, 42.4% worked in public hospitals with an average of 40.1 ± 14.2 hours per week. 31.3% did research, 13.1% clinical trials, 56.6% teaching, and 42.8% administrative work. 36% received an annual income less than 25K.

56.6% had burnout in at least 1 dimension. According to the dimensions, 35.7% had burnout in EE, 25.6% in PA and 26.6% in DP. 32.3% had burnout in only 1 dimension, 17.2% in two and 7.1% in all three dimensions. Only 20.2% thought they had burnout, 9.1% were currently with professional help and 15.8% had sought help in the past. 72.1% said they were willing to participate in a program to reduce burnout.

The rheumatologists with burnout were younger than those without burnout (46.5 vs 49.9 years, p = 0.015), mentioned more frequently that they would like to decrease the number of working hours (56.5% vs 36.4%, p = 0.002) and had lower practice satisfaction (5.2 vs 6.2, p <0.001) and income satisfaction (3.4 vs 4.6, p <0.001). Those with burnout were less happy than those without burnout (5.1 vs 5.9, p <0.001) and had higher PHQ-9 (7.7 vs 2.5, p <0.001). In the burnout group, there was a higher percentage with an income less than $ 25K/year (45.7% vs 25.4%, p=0.008), presence of comorbidities (53.6% vs 40.3%, p=0.023), anxiety (11.9 % vs. 2.3%, p=0.002), use of SSRIs/SNRIs (19% vs 8.5%, p=0.011), suicidal thoughts (13.6% vs 1.6%, p <0.001) and low self-esteem (12.5% vs 3.1%, p <0.001). There was a higher percentage of rheumatologists involved in teaching in the group without burnout (66.7% vs 48.8%, p = 0.002). No statistically significant associations were found between burnout and sex, exercise, alcohol consumption, duration of career, main workplace, type of clinical practice, duration of vacation, clinical research, clinical trials and administrative work.

Conclusion:

Burnout affects near half of rheumatologists in Latin America and was associated to younger age, long working hours, low satisfaction, less happiness, higher PHQ-9, suicidal thoughts, anxiety, income, presence of comorbidities and low self-esteem. Most of the rheumatologists were willing to participate in programs to reduce burnout which represents an opportunity for interventions to reduce this syndrome.

References:

[1]Martin K. Medscape Rheumatologist Lifestyle, Happiness & Burnout Report 2020. 2020; Available at: https://www.medscape.com/slideshow/2020-lifestyle-rheumatologist-6012480#4. Accessed July 10, 2020.

[2]Tiwari V, Kavanaugh A, Martin G, Bergman M. High impact of burnout on rheumatology practitioners. Journal of rheumatology 2020:jrheum.191110.

Disclosure of Interests:

None declared

AB0214 SURVIVAL, EFFICACY AND SAFETY OF GOLIMUMAB IN PATIENTS WITH RHEUMATOID ARTHRITIS AND SPONDYLOARTHRITIS: DATA FROM AN ARGENTINEAN COHORT

Background:

Golimumab is a human monoclonal antibody directed against TNFα in its soluble and transmembrane forms. It can be used subcutaneously or intravenously and has shown efficacy for use in patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA) and ankylosing spondylitis (AS).

Objectives:

The aim of this study was to evaluate the efficacy, safety, and cumulative survival of golimumab in patients with RA, PsA and AS from different rheumatology centers in Argentina.

Methods:

We performed a longitudinal study of consecutive adults with RA (ACR/EULAR 2010 criteria), PsA (CASPAR criteria) and AS (ASAS 2009 criteria), who have started treatment with subcutaneous or intravenous golimumab according to medical indication in each center. Data was obtained by review of medical records. Sociodemographic and clinical data, musculoskeletal manifestations, comorbidities, previous treatments were recorded. In reference to golimumab treatment, start date, route of administration and concomitant treatments were identified. Disease activity was assessed using DAS28 for RA patients, DAPSA and MDA for PsA and BASDAI for AS. The presence of adverse events (AE) was recorded. If golimumab was stopped, date and cause was documented. Patients were followed up until golimumab discontinuation, loss of follow-up, or study completion (November 30, 2020). Statistical analysis: Chi2 test or Fischer exact test and T test or Mann Whitney and ANOVA or Kruskal Wallis, as appropriate. The incidence of EA was assessed in events every 100 patient/year. Kaplan-Meier curves and log Rank analysis. Cox proportional regression.

Results:

One hundred eighty two patients were included, 116 with a diagnosis of RA, 30 with PsA and 36 with AS. Most of them (70.9%) were female with a median (m) age of 55 years (IQR 43.8-64) and m disease duration of 7 years (IQR 4-12.7) at treatment initiation. Al least one prior biological DMARD or a small molecule was received by 63 patients (34.6%). The most frequent indication cause was conventional DMARD failure. In 94.8% of the patients Golimumab was administered subcutaneously, and in 80.8% in association with conventional DMARDs, the most frequently used was methotrexate. Total follow-up was 318.1 patients/year.

Golimumab treatment showed clinical improvement in all three groups of patients. In RA patients DAS28 significantly decreased during the first 12 months of follow-up, m 5.9 (IQR 4.9-6.6) at baseline, 3.8 (IQR 2.6-4.6) at 6 months and 2.8 (IQR 2.1-3.6) at 12 months, p <0.0001. In PsA, m DAPSA-ESR value was 32.2 (IQR 24.2-47.7), 10.1 (IQR 5.8-18.3) and 11.2 (IQR 3.4-24) at baseline, 6 and 12 months, respectably (p <0.0001). In AS, m BASDAI was 6.2 (IQR 4.8-7.3), 2.8 (IQR 1.7-4.1) and 2.2 (IQR 1.1-3.2), at baseline, 6 and 12 months respectively (p <0.0001).

The incidence of adverse events was 6.6 per 100 patients/year, being infections the most frequents ones. During follow-up, 50 patients (27.5%) discontinued golimumab, the most frequent cause was treatment failure (68%), followed by lack of health insurance (16%) and adverse events (10%). Golimumab persistence was 79% and 57.6% at 12 and 24 months, respectively. Treatment survival was 50.2 months (95% CI 44.4-55.9). Patients who had received prior treatment with biological DMARDs or small molecules showed lower survival (Figure 1). In the multivariate analysis, adjusting for age, sex and disease duration, those patients showed twice the risk of suspending treatment (HR 2.01, 95% CI 1.1-3.7).

Figure 1.

Golimumab survival according to prior b-DMARD o small molecule treatment.

Conclusion:

Golimumab treatment in real life patients in Argentina has shown good efficacy and safety. Drug survival was over 4 years and almost 80% were still using golimumab after one year. Prior treatment with other b-DMARDs o small molecules was associated with lower treatment survival.

Disclosure of Interests:

Carolina Ayelen Isnardi Speakers bureau: Bristol Myers Squibb, Janssen, Grant/research support from: Pfizer, Emma Estela Civit De Garignani Speakers bureau: Abbvie, Novartis, Agustín García Ciccarelli Speakers bureau: Janssen, Novartis, Consultant of: Novartis, Grant/research support from: Janssen, Novartis, Jimena Sanchez Alcover: None declared, Rodrigo Garcia Salinas Speakers bureau: Abbvie, AMGEN, Bristol-Myers Squibb, Eli Lilly, GSK, Janssen Cilag, Montpellier-UCB, Novartis, Roche – Genentech, Sanofi, Merck Serono., Sebastian Magri Speakers bureau: Abbvie, AMGEN, Bristol-Myers Squibb, Eli Lilly, GSK, Janssen Cilag, Montpellier-UCB, Novartis, Roche – Genentech, Sanofi, Merck Serono., Eduardo Albiero Consultant of: Janssen, Carla Gobbi Speakers bureau: Pfizer, Consultant of: Pfizer, Janssen, Edson Velozo Speakers bureau: Janssen, Novartis, Pfizer, Consultant of: Abbvie, Janssen, Novartis, Grant/research support from: Janssen, Novartis, Pfizer, Enrique Soriano Speakers bureau: AbbVie, Novartis, Bristol MS, Novartis, Eli Lilly, Genzyme, Pfizer, Amgen, and Roche, Consultant of: Novartis, AbbVie, Pfizer, Eli Lilly, Sanofi, Sandoz, Amgen., Grant/research support from: Roche, Novartis, AbbVie, Glaxo Smith Kline, BMS, Martín Brom: None declared, Johana Zacariaz Grant/research support from: Bristol Myers Squibb, Ingrid Strusberg Speakers bureau: Gema Biotech SAU, BMS, Abbvie, Consultant of: Gema Biotech SAU, Abbvie, Janssen, Grant/research support from: Abbvie, Lilly, Galápagos, Servier, GSK, Merck Serono, Marcos BARAVALLE Speakers bureau: Montepellier, Consultant of: Abbvie, Janssen, Grant/research support from: Abbvie, Lilly, Galápagos, Servier, GSK, Merck Serono, Sol Castaños Speakers bureau: Abbvie, Lilly, Galápagos, Servier, GSK, Merck Serono, Liliana Morales Speakers bureau: Lilly, Consultant of: Janssen, Grant/research support from: Abbvie, Lilly, Galápagos, Servier, GSK, Merck Serono, Sergio Paira: None declared, Romina Calvo: None declared, Alberto Ortiz: None declared, Rodolfo Perez Alamino Speakers bureau: Pfizer, Abbvie, Amgen, Bristol-Myers-Squibb, Lilly, Janssen, Novartis, Hernan Maldonado Ficco Speakers bureau: Pfizer, Abbvie, Jansen, Novartis, Bago, Bristol, Eli Lilly., Consultant of: Pfizer, Abbvie, Novartis, Jansen, Bago, Eli Lilly., Gustavo Citera Speakers bureau: Abbvie, BMS, Lilly, Jansen, Gema, Pfizer, Roche, Grant/research support from: Pfizer

OP0229 THE GROUP FOR RESEARCH AND ASSESSMENT OF PSORIASIS AND PSORIATIC ARTHRITIS (GRAPPA) TREATMENT RECOMMENDATIONS 2021

Background:

Since the 2015 GRAPPA treatment recommendations were published, therapeutic options and management strategies for psoriatic arthritis (PsA) have advanced considerably.

Objectives:

The goal of the GRAPPA recommendations update is to develop high quality, evidence-based recommendations for the treatment of PsA, including related conditions and comorbidities.

Methods:

GRAPPA rheumatologists, dermatologists and patient research partners (PRPs) updated overarching principles for the management of adults with PsA by consensus. Principles considering use of biosimilars and tapering/discontinuing of therapy were added to this update. Systematic literature searches based on data publicly available from three databases (MEDLINE, EMBASE, and Cochrane CENTRAL) were conducted from the end of the previous recommendations’ searches through August 2020. Additional abstract searches were performed for conference presentations in 2017-2020. Searches covered PsA treatments (peripheral arthritis, axial arthritis, enthesitis, dactylitis, skin, and nail disease). Additional searches were performed for related conditions (uveitis and IBD) and comorbidities evaluating their impact on safety and treatment outcomes. Individual groups assessed the risk of bias and applied the GRADE system to generate strong or conditional recommendations for therapies within the domain groups and for the management of comorbidities and related conditions. These recommendations were then incorporated into an overall treatment schema.

Results:

Updated, evidence-based treatment recommendations are shown (Table 1). Since 2015, many new medications have been incorporated. Additional results for older medications, such as methotrexate, have been published across PsA domains. Based on the evidence, the treatment recommendations developed by individual groups were incorporated into the overall schema including principles for management of arthritis, spondylitis, enthesitis, dactylitis, skin, and nail disease in PsA, and associated conditions (Figure 1). Choice of therapy for an individual should ideally address all of the domains that impact on that patient, supporting shared decision making with the patient involved. Additional consideration in the recommendations was given to key associated conditions and comorbidities as these often impact on therapy choice.

Conclusion:

These GRAPPA treatment recommendations provide up to date, evidence-based guidance to providers who manage and treat adult patients with PsA. These recommendations are based on domain-based strategy for PsA and supplemented by overarching principles developed by consensus of GRAPPA members.

IndicationStrongForConditional ForConditionalAgainstStrongAgainstInsufficient evidencePeripheral Arthritis DMARD NaïvecsDMARDs, TNFi, PDE4i, IL-12/23i, IL-17i, IL-23i, JAKiNSAIDs, oral CS, IA CS,IL-6i,Peripheral Arthritis DMARD IRTNFi, IL-12/23i, IL-17i, IL-23i, JAKiPDE4i, other csDMARD, NSAIDs, oral CS, IA CS,IL-6i,Peripheral ArthritisbDMARD IRTNFi, IL-17i, IL-23i, JAKi,NSAIDs, oral CS, IA CS, IL-12/23i, PDE4i, CTLA-4-IgIL-6i,Axial arthritis, Biologic NaïveNSAIDs, Physiotherapy, simple analgesia, TNFi, IL-17i, JAKiCS SIJ injections, bisphosphonatescsDMARDs, IL-6i,IL-12/23i, IL-23iAxial PsA, Biologic IRNSAIDs, Physiotherapy, simple analgesia, TNFi, IL-17i, JAKi csDMARDs, IL-6i,IL-12/23i, IL-23iEnthesitisTNFi, IL-12/23i, IL-17i, PDE4i, IL-23i, JAKiNSAIDs, physiotherapy, CS injections, MTXIL-6i,Other csDMARDsDactylitisTNFi IL-12/23i, IL-17i, IL-23i, JAKi, PDE4iNSAIDs, CS injections, MTXOther csDMARDsPsoriasisTopicals, phototherapy, csDMARDs, TNFi, IL-12/23i, IL-17i, IL-23i, PDE4i, JAKi AcitretinNail psoriasisTNFi, IL12/23i, IL17i, IL23i, PDE4iTopical CS, tacrolimus and calcipotriol combination or individual therapies, Pulsed dye laser, csDMARDs, acitretin, JAKiTopical Cyclosporine / Tazarotene, Fumarate, Fumaric Acid Esters, UVA and UVB Phototherapy, AlitretinoinIBDTNFi (not ETN), IL-12/23i, JAKiIL-17iUveitisTNFi (not ETN)

Disclosure of Interests:

Laura C Coates Speakers bureau: AbbVie, Amgen, Biogen, Celgene, Gilead, Eli Lilly, Janssen, Medac, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, and UCB, Grant/research support from: AbbVie, Amgen, Celgene, Eli Lilly, Pfizer, and Novartis, Enrique Soriano Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb,GSK, Genzyme, Janssen, Lilly, Novartis, Pfizer, Roche, Sandoz, Sanofi, UCB, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb,GSK, Genzyme, Janssen, Lilly, Novartis, Pfizer, Roche, Sandoz, Sanofi, UCB, Grant/research support from: AbbVie, Janssen, Novartis Pharma, Pfizer, Roche, and UCB, Nadia Corp: None declared, Heidi Bertheussen Consultant of: Pfizer, Kristina Callis-Duffin Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Lilly, Janssen, Novartis, Pfizer, Sienna Biopharmaceuticals, Stiefel Laboratories, UCB, Ortho Dermatologics, Inc, Regeneron Pharmaceuticals, Inc., Anaptys Bio, Boehringer Ingelheim., Cristiano Barbosa Campanholo Speakers bureau: AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Janssen, Novartis, Pfizer, and UCB, Jeffrey Chau: None declared, Lihi Eder Consultant of: Abbvie, UCB, Janssen, Eli Lily, Pfizer, Novartis, Grant/research support from: Abbvie, UCB, Janssen, Eli Lily, Pfizer, Novartis, Daniel Fernandez Consultant of: Abbvie, UCB, Roche, Janssen, Pfizer, Amgen and Brystol, Grant/research support from: Abbvie, UCB, Roche, Janssen, Pfizer, Amgen and Brystol, Oliver FitzGerald Speakers bureau: AbbVie, Janssen and Pfizer Inc, Consultant of: BMS, Celgene, Eli Lilly, Janssen and Pfizer Inc, Grant/research support from: AbbVie, BMS, Eli Lilly, Novartis and Pfizer Inc, Amit Garg Consultant of: Abbvie, Amgen, Asana Biosciences, Bristol Myers Squibb, Boehringer Ingelheim, Incyte, InflaRx, Janssen, Pfizer, UCB, Viela Biosciences, Grant/research support from: Abbvie, Dafna D Gladman Consultant of: Abbvie, Amgen, BMS, Eli Lilly, Galapagos, Gilead, Jansen, Novartis, Pfizer and UCB, Grant/research support from: Abbvie, Amgen, Eli Lilly, Jansen, Novartis, Pfizer and UCB, Niti Goel: None declared, Suzanne Grieb: None declared, Philip Helliwell Speakers bureau: Janssen, Novartis, Pfizer, Consultant of: Eli Lilly, M Elaine Husni Consultant of: Abbvie, Amgen, Janssen, Novartis, Lilly, UCB, Regeneron, and Pfizer, Deepak Jadon Speakers bureau: AbbVie, Amgen, Celgene, Eli Lilly, Gilead, Healthcare Celltrion, Janssen, MSD, Novartis, Pfizer, Roche, Sandoz, UCB, Consultant of: AbbVie, Amgen, Celgene, Eli Lilly, Gilead, Healthcare Celltrion, Janssen, MSD, Novartis, Pfizer, Roche, Sandoz, UCB, Grant/research support from: AbbVie, Amgen, Celgene, Eli Lilly, Gilead, Healthcare Celltrion, Janssen, MSD, Novartis, Pfizer, Roche, Sandoz, UCB, Arnon Katz: None declared, Dhruvkumar Laheru: None declared, John Latella: None declared, Ying Ying Leung Speakers bureau: Novartis, AbbVie, Eli Lilly, Janssen, Consultant of: Pfizer and Boehringer Ingelheim, Grant/research support from: Pfizer and conference support from AbbVie, Christine Lindsay Shareholder of: Amgen, Employee of: Aurinia pharmaceuticals, Ennio Lubrano Speakers bureau: Alfa-Sigma, Abbvie, Galapagos, Janssen Cilag, Lilly., Consultant of: Alfa-Sigma, Abbvie, Galapagos, Janssen Cilag, Lilly., Luis Mazzuoccolo Speakers bureau: Abbvie, Amgen, Novartis, Elli Lilly, Jansen, Consultant of: Abbvie, Amgen, Novartis, Elli Lilly, Jansen, Roland McDonald: None declared, Philip J Mease Speakers bureau: AbbVie, Amgen, Eli Lilly, Janssen, Novartis, Pfizer and UCB, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squibb, Eli Lilly, Galapagos, Gilead Sciences, GlaxoSmithKline, Janssen, Novartis, Pfizer, SUN and UCB, Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Galapagos, Gilead Sciences, Janssen, Novartis, Pfizer, SUN and UCB, Denis O’Sullivan: None declared, Alexis Ogdie Consultant of: AbbVie, Amgen, BMS, Celgene, Corrona, Gilead, Janssen, Lilly, Novartis, and Pfizer, Grant/research support from: Novartis and Pfizer and Amgen, Wendy Olsder: None declared, Lori Schick: None declared, Ingrid Steinkoenig: None declared, Maarten de Wit Consultant of: AbbVie, BMS, Celgene, Janssen, Lilly, Novartis, Pfizer, Roche, Danielle van der Windt: None declared, Arthur Kavanaugh Speakers bureau: AbbVie, Amgen, BMS, Eli Lilly, Gilead Janssen, Novartis, Pfizer, UCB, Consultant of: AbbVie, Amgen, BMS, Eli Lilly, Gilead Janssen, Novartis, Pfizer, UCB

P178 The impact of peripheral articular manifestations on the efficacy of ixekizumab in patients with radiographic axial spondyloarthritis

Background/Aims 

Axial spondyloarthritis (axSpA) is characterised by chronic inflammation of the axial skeleton and is commonly associated with peripheral articular manifestations (PA), which further increases disease burden. Ixekizumab (IXE), a high-affinity monoclonal antibody that selectively targets IL-17A, is approved for treating both nonradiographic and radiographic (r-) forms of axSpA. We explored the efficacy of IXE in patients with raxSpA with (PA+) and without (PA−) PA at baseline.

Methods 

Week 16 data from two Phase 3, randomized, double-blind, placebo (PBO)-controlled trials, with patients who fulfilled the Assessment of Spondylo-Arthritis International Society (ASAS) criteria for r-axSpA and were either biologic-naïve (COAST-V, NCT02696785) or TNFi-experienced (COAST-W, NCT02696798), were analysed. Patients were randomly assigned 1:1:1:1 to subcutaneous PBO, 80 mg IXE every 4 (Q4W) or 2 (Q2W) weeks (80 mg or 160 mg starting dose, assigned 1:1) or 40 mg adalimumab (ADA) Q2W in COAST-V or 1:1:1 in COAST-W. We present a post-hoc analysis of data from COAST-V and -W and an integrated dataset, with patients categorized by baseline PA status. Presence of PA was defined as a 44-joint swollen joint count (SJC) ≥1 or a 46-joint tender joint count (TJC) ≥1. Efficacy and health-related quality of life (HRQoL) outcomes were analysed at week 16.

Results 

Data from 656 patients (COAST-V: N = 146 PA−/194 PA+; COAST-W: N = 93 PA−/223 PA+) were analyzed. At baseline, PA+ patients had a higher mean age, more enthesitis (higher Spondyloarthritis Research Consortium of Canada [SPARCC] scores), and higher disease activity (higher CRP levels, Ankylosing Spondylitis Disease Activity Score [ASDAS] and BASDAI). ASAS40, ASDAS &lt;2.1, and BASDAI50 responder rates (Table, section a) were all significantly higher for both IXE dose regimens versus PBO in both PA− and PA+ patients in the integrated dataset and numerically higher in the separate datasets. Furthermore, short-form-36 physical component summary (Table, section b) showed significantly greater improvements from baseline in both IXE groups vs PBO in the separate and integrated datasets, regardless of baseline PA status.

Conclusion 

IXE led to significant improvements versus PBO in all efficacy and HRQoL endpoints at Week 16 in the integrated dataset, irrespective of PA manifestations at baseline. P178 Table 1:a) Responder rates at Week 16 for the intent-to-treat population, number (%)No peripheral articular manifestations at baselinePeripheral articular manifestations at baselinePBOADAQ2WIEQ4WIXEQ2WPBOADAQ2WIXEQ4WIXEQ2WIntegrated datasetaN=71N/AN=63N=66N=119N/AN=132N=115ASAS4011.5N/A29 (46.0)‡28 (42.4)‡18 (15.1)N/A39 (29.5)†45 (39.1)‡ASDAS &lt;2.18 (11.3)N/A24 (38.1)‡23 (34.8)†8 (6.7)N/A31 (23.5)‡28 (24.3)‡BASDAI5010 (14.1)N/A21 (33.3)*26 (39.4)†15 (12.6)N/A38 (28.8)‡33 (28.7)†COAST-VbN=34N=39N=35N=38N=52N=51N=46N=45ASAS408 (23.5)17 (43.6)18 (51.4)*18 (47.4)8 (15.4)15 (29.4)21 (45.7)†25 (55.6)‡ASDAS &lt;2.17 (20.6)18 (46.2)*14 (40.0)17 (44.7)*4 (7.7)16 (31.4)†21 (45.7)†18 (40.0)‡BASDAI507 (20.6)16 (41.0)13 (37.1)16 (42.1)8 (15.4)13 (25.5)21 (45.7)†20 (44.4)†COAST-WbN=37N/AN=28N=28N=67N/AN=86N=70ASAS403 (8.1)N/A11 (39.3)†10 (35.7)*10 (35.7)*N/A18 (20.9)20 (28.6)ASDAS &lt;2.11 (2.7)N/A10 (35.7)‡6 (21.4)*4 (6.0)N/A10 (11.6)10 (14.3)BASDAI503 (8.1)N/A8 (28.6)*10 (35.7)*7 (10.4)N/A17 (19.8)13 (18.6)Non-responder imputation was used for missing responses.P-values vs. PBO (aCochran-Mantel-Haenszel test, adjusted by study;bFisher’s exact test):*P&lt;0.05,†P&lt;0.01,‡P&lt;0.001.b) Change from baseline in SF-36 PCS scores at Week 16 for the intent-to-treat population, LSM (SE)No peripheral articular manifestations at baselinePeripheral articular manifestations at baselinePBOADAQ2WIXEQ4WIXEQ2WPBOADAQ2WIXEQ4WIXEQ2WIntegrated dataseta1.6 (0.90)N/A7.2 (0.95)‡6.1 (0.92)‡3.8 (0.69)N/A7.7 (0.67)‡8.2 (0.71)‡COAST-Vb2.3 (1.15)7.0 (1.10)†6.9 (1.13)†6.4 (1.07)*4.6 (1.00)6.9 (1.01)8.3 (1.07)*9.3 (1.10)†COAST-Wc0.64 (1.57)N/A7.1 (1.75)†5.4 (1.72)*1.9 (0.96)N/A6.4 (0.85)‡6.3 (0.97)‡P-values vs. PBO (MMRM analysis with treatment,a,b,c study,a baseline value,a,b,c visit,a,b,c baseline value-by-visit,a,b,c treatment-by-visit interaction,a,b,c geographic region,b,c baseline CRP status,b,c and number of prior TNF inhibitorsc included as fixed factors):*P &lt; 0.05,†P &lt; 0.01,‡P &lt; 0.001.ADAQ2W = adalimumab every 2 weeks; ASAS = Assessment of Spondyloarthritis International Society criteria; ASDAS = ankylosing spondylitis disease activity score; BASDAI = Bath Ankylosing Spondylitis Disease Activity Index; CRP = c reactive protein; IXEQ2W = ixekizumab every 2 weeks; IXEQ4W = ixekizumab every 4 weeks; MMRM = mixed-effects model of repeated measures; N/A = not applicable; PBO = placebo; PCS = physical component summary; SE = standard error; SF-36 = short-form-36; TNF = tumour necrosis factor.

Disclosure 

R. Sengupta: None. P. Bird: Grants/research support; Pfizer, Eli Lilly, Gilead, Abbvie, Novartis. D. Aletaha: Consultancies; Abbvie, Amgen, Celgene, Eli Lilly, Medac, Merck, Novartis, Pfizer, Roche, Sandoz, Sanofi, Genzyme. Grants/research support; Abbvie, Novartis, Roche. M. Magrey: Consultancies; Novartis, Pfizer, Eli Lilly, Abbvie, UCB. Other; Clinical trials with: Abbvie and UCB. Y. Kadono: Member of speakers’ bureau; Abbie, Lilly, Novartis. E. Soriano: Consultancies; Abbvie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer, Sandoz. Member of speakers’ bureau; Abbvie, Amber, Bristol-Myers Squibb, Eli Lilly, Novartis, Pfizer, Roche, UCB. Grants/research support; Abbvie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer, Sandoz, UCB. A.J. Bradley: Shareholder/stock ownership; Eli Lilly. Other; Employee of Eli Lilly and Company. S. Liu-Leage: Shareholder/stock ownership; Eli Lilly. Other; Employee of Eli Lilly and Company. Y. Schymura: Other; Employee of Eli Lilly and Company. M.J. Nissen: Corporate appointments; Abbvie, Celgene, Lilly, Novartis, Pfizer. Member of speakers’ bureau; Abbvie, Celgene, Novartis, Pfizer. Other; Member of EuroSpA (supported by Novartis).

SAT0426 CAN BIOLOGICS “PREVENT” THE DEVELOPMENT OF PSORIATIC ARTHRITIS IN PSORIASIS PATIENTS? DATA FROM A LARGE UNIVERSITY HOSPITAL COHORT IN ARGENTINA

Background:

As psoriasis (Pso) commonly precedes psoriatic arthritis (PsA), an important unanswered question is whether treatment of Pso might influence the development of PsA in patients with psoriasis

Objectives:

The objective of this study was to analyze the incidence of PsA in a large cohort of patients with PsO according to different treatments, with the hypothesis that treatment with biologics might prevent the development of PsA.

Methods:

Patients with PsO without PsA followed at a University Hospital were included in this retrospective cohort study. Data was obtained from the Hospital Electronic Medical Record (EMR). Patients were classified according to their treatment in topics group (topic and phototherapy), conventional DMARDs (cDMARDs) group (Methotrexate (MTX) and cyclosporine (Cyc)), and biologic DMARDs group (bDMARDs) (TNFi, IL17i, and IL12-23i). Patients contributed time since beginning of the corresponding treatment until diagnosis of PsA, lost of follow up, end of treatment or end of study. Incident cases of PsA were attributed to one treatment if developed during the administration of that treatment and up to 6 months after its discontinuation if no other treatment was started. Incident cases that developed more than one year after discontinuation of treatment were disregarded (3 cases). Incidence rate was calculated for the whole population and for each one of the treatment groups and compared with chi2test, and rate ratios were calculated as well. A multivariable logistic model for the development of PsA was analyzed by treatment groups, adjusting by other variables.

Topics, n= 599cDMARDs, n=106bDMARDs, n=92Total group, n=797Mean age at PsO diagnosis (SD)43.6 (20.6)46.2 (20.7)35.1 (18.9)42.9 (20.6)Female, n (%)314 (52)53 (50)36 (39)403 (50.5)Plaque PsO, n/N (%)514/578 (89)93/103 (90)85/90 (94)692/771 (90)BMI, n; Mean (SD)498; 27.6 (5.4)80; 28.5 (5.6)91; 30 (7)659; 28 (5.7)N Developed PsA (%)68 (8.5)3 (0.38)1 (0.13)72 (9)Follow up (patient/years)915331654810017Incidence rate/1000 Patient/ years (95% CI)7.4 (5.8-9.4)9.5 (1.9-27.5)1.81 (0.04-10)7.2 (5.6-9)Median years between PsO and PsA (IQR)10 (2-21)Patient 1: 23Patient 2: 11.7Patient 3: 24.7Patient (1): 9.610.5 (2-20.8)

Results:

797 patients, contributed a total of 10017 patient/years. Patient’s characteristics are shown in table 1. 599 (75%) patients were treated only with topics or phototherapy, 106 (13%) with cDMARDs (81% MTX and 19% Cyc) and 92 (11.5%) with biologics (TNFi: 64: etanercept: 44, adalimumab:23, infliximab:6; IL17i: 43: 14 Ixekizumab, 29 Secukinumab; IL12-23i: (Ustekinumab) 16; some patients received more than one biologic). During follow-up 72 patients developed PsA (68 under topics; 3 under cDMARDs (2 MTX and 1 Cyc) and 1 under biologics (1 Secukinumab): Global incidence rate: 7.2 per 1000 patient/years (table 1). Although numerically the incidence of PsA in PsO patients treated with biologics was lower, the difference was not statistically significant. In Cox regression analysis, after adjusting by sex, age, and BMI, treatment with biologics was significantly associated with a reduced risk of developing PsA: Hazard ratio (95% CI): 0.1 (0.013 – 0.7); p= 0.021.

Conclusion:

Treatment with biologics in patients with PsO seemed to reduce the risk of PsA and preventing its development in this retrospective single center cohort.

Acknowledgments:

This study was awarded with the PANLAR stimulus award 2019

Disclosure of Interests:

Luciano Lo Giudice: None declared, Maria Laura Acosta Felquer: None declared, Maria Laura Galimberti: None declared, Luis Mazzuoccolo: None declared, Enrique Soriano Grant/research support from: AbbVie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer Inc, Sandoz, Consultant of: AbbVie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer Inc, Sandoz, Speakers bureau: AbbVie, Amber, Bristol-Myers Squibb, Eli Lilly, Novartis, Pfizer Inc, Roche

THU0119 COULD SYNOVITIS AND TENOSYNOVITIS DETECTED BY ULTRASOUND BE CONSIDERED A RISK FACTOR FOR SHORT-TERM FLARE IN RA PATIENTS IN CLINICAL REMISSION

Background:

The clinical value of ultrasound (US) detected synovitis and tenosynovitis as predictors of flares in RA patients in clinical remission is not clear.

Objectives:

To investigate the value of US detected synovitis and tenosynovitis as risk factors for short term flare in RA patients in clinical remission.

Methods:

Consecutive RA patients in clinical remission (DAS28 ERS < 2.6) for at least 3 months, underwent Power Doppler ultrasound (PDUS) examination of: 1st to 6th extensor compartments at the wrist, 2nd to 5th flexor, posterior tibial tendons and peroneals. Regarding joints, carpal joints, 1st to 5th MCP and 2nd to 5th interphalangeal proximal (IPP). Synovitis and tenosynovitis were defined according to OMERACT. Patients were followed for one year. Disease flare was defined as any increase of disease activity generating the need of change in therapy by the attending rheumatologist.

Results:

Ninety patients were included. Patients´ characteristics are shown in the table. After one year of follow-up, 26 patients (29%) experienced a flare. At baseline 39%, 23% and 8% had US detected synovitis, tenosynovitis or both respectively. The presence of US detected tenosynovitis (RR: 4.9; 95% CI: 2.2-10.8), but not of US detected synovitis (RR: 1.3; 95% CI: 0.76-2.2), showed an increased risk of having a flare. In the multivariable analysis, and after adjusting by age, gender, disease duration, DAS28, DMARDs and biologics use, and the US detected synovitis, only subclinical tenosynovitis (OR: 9.8 95% CI: 2.5-39.1; p=0.001) and baseline DAS28 (OR: 5.7, 95% CI: 1.1-31.6; p= 0.047) were significantly associated with an increased risk of flare.

Conclusion:

Subclinical tenosynovitis, but not synovitis, was associated with disease flare in patients with RA in clinical remission. This feature might have physio-pathological implications.

References:

[1]Filippou G, et al. The predictive role of ultrasound-detected tenosynovitis and joint synovitis for flare in patients with rheumatoid arthritis in stable remission. Results of an Italian multicentre study of the Italian Society for Rheumatology Group for Ultrasound: the STARTER study. Ann Rheum Dis 2018;0:1–7.doi:10.1136/annrheumdis-2018-213217

[2]Bellis E, et al. Ultrasound-detected tenosynovitis independently associates with patient-reported flare in patients with rheumatoid arthritis in clinical remission: results from the observational study STARTER of the Italian Society for Rheumatology Rheumatology 2016; 55:1826_1836doi:10.1093/rheumatology/kew258. Advance Access publication 27 June 2016

Table 1.

Demographic and clinical features from RA patients in clinical remission

FeaturePatients with flares (n=26)Patients without flares (n= 64)P valueMean age (SD)63.1 (12.6)57.5 (13.2)0.0679Females, n (%)54 (84)24 (92)0.316Mean Disease duration years (SD)5.5 (5.5)8.4 (5.9)0.0344Positive Rheumatoid Factor, n (%)16 (61.5)40 (62.5)0.802Mean Erythrosedimentation rate (ESR)18.3 (8)14.1 (10.4)0.0680Mean DAS28 ESR (SD)1.9 (0.5)2.2 (0.3)0.0091Mean Swollen joint count (SS)0.15 (0.4)0.15 (0.4)0.9806Mean Patient’s Global VAS (0-10) (SD)1.4 (1.3)1.1 (1.1)0.2471Mean tender joint count (SD)0.2 (0.5)0.2 (0.5)0.9653Treatment with DMARDs, n (%)54 (81)26 (100)0.018Treatment with biologics, n (%)19 (30)3 (11)0.069

Disclosure of Interests:

Johana Zacariaz H: None declared, martin brom: None declared, florencia mollerach: None declared, josefina marin: None declared, leandro ferreyra g: None declared, Javier Rosa Speakers bureau: ABBvie, Pfizer, BMS, Novartis, Janssen, Eli Lilly, enrique soriano Speakers bureau: Abbvie, Pfizer, BMS, Novartis, Janssen, Eli Lilly, UCB, Roche

SAT0144 DOES POLYPHARMACY IN RHEUMATOID ARTHRITIS PATIENTS AFFECT THE TREAT TO TARGET STRATEGY?

Background:

Polypharmacy (PP) is an important risk factor for drug toxicity, delirium, falls, hospitalizations and death. Patients with rheumatoid arthritis (RA) often have comorbid conditions and have PP. Treat to target strategy (T2T) implies a drug escalation and rheumatologists may not apply it in patients with PP.

Objectives:

Our objective was to analyze if PP affects T2T in a real-world scenario.

Methods:

Observational, retrospective cohort study. Patients with a new RA diagnosis (ACR/EULAR 2010 criteria) after 2010, over 18 years old, belonging to a Health Management Organization (HMO) from a university tertiary hospital, with a minimum follow-up period of 2 years, were included. PP was defined as consumption greater than or equal to 5 medications at the time of RA diagnosis, regardless of the medication used for RA, administered for a minimum period of 6 months. T2T strategy was defined as accomplished if an escalation in treatment was done when the patient had moderate or high disease activity at medical visit (by DAS28 and/or CDAI), without a significant improvement with respect to the previous visit. Prevalence of PP at RA diagnosis was calculated and RA patients were divided in those with PP at RA diagnosis time and those without. The first 2 years of disease were analyzed and compare between both groups: clinical and demographic characteristics, percentage of visits where T2T was applied, treatments received during that period. A multivariate logistic regression analysis was performed in order to identify factors associated with no T2T compliance.

Results:

147 patients with RA were included, 86% women, with an average age at diagnosis of 60 years (SD: 15.8). The prevalence of PP at RA diagnosis was 12% (17 patients). Table 1 shows the comparison between patients with and without PP. Patients with PP showed a greater frequency of erosions at baseline and after 2 years of disease, a greater use of corticosteroids at 2 years, higher percentage of hospitalizations and a higher mortality. In the multivariate logistic regression analysis, no compliance of the T2T strategy was only associated with the consumption of corticosteroids at 2 years (OR: 0.36, CI95%: 0.15-0.85; p=0.019) and no association was found with PP at the beginning of the disease.

Table 1.

Demographic and clinical characteristics in patients with and without polypharmacy.)

Patients without Polypharmacy(n= 127)Patients with Polypharmacy(n= 17)PMale sex, n (%)18 (13.8)3 (17.6)0.6Mean age at diagnosis (SD)58.5 (15.6)70.6 (12.2)0.9Positive rheumatoid factor, n (%)87 (66.9)12 (70.5)0.7Positive anti CCP, n (%)109 (85.8)13 (81.2)0.6Erosions at baseline, n (%)25 (19.2)7 (41.1)0.03Active smoker, n (%)28 (21.5)3 (17.6)0.2Past smoker, n (%)23 (17.6)7 (35.2)Charlson score, median (IQR)3 (1-4)4 (4-5)<0.0001Polypharmacy at 2 years, n (%)17 (13.0)46.8 (88.2)<0.0001Rheumatological consultations in 2 years, mean (DE), (IC 95%)8.6 (3.3)(8.0-9.2)8.8 (3.1)(7.2-10.5)0.6Corticosteroid therapy at 2 years, n (%)29 (22.3)8 (47.0)0.02cDMARDs therapy at 2 years, n (%)114 (87.6)13 (76.4)0.2Biologic therapy at 2 years, n (%)13 (10)4 (23.5)0.1Erosions at 2 years, n (%)29 (22.3)9 (52.9)0.007No T2T compliance, n (%)65 (50)5 (29.4)0.1Hospitalizations, n (%)12 (9.2)7 (41.1)<0.0001Mortality, n (%)2 (1.5)2 (11.7)0.01

Conclusion:

The prevalence of PP in our patients with a new RA diagnosis was 12% and was associated with more baseline erosions, a higher consumption of steroids, and a higher frequency of hospitalizations and mortality during the first 2 years of the disease. No relationship between PP and adherence to the T2T strategy was demonstrated. In the multivariate logistic regression analysis, no compliance with the T2T strategy was only associated to the consumption of corticosteroids at 2 years, may be reflecting a poorer disease control.

Disclosure of Interests:

JOHN FREDY JARAMILLO GALLEGO: None declared, Javier Rosa: None declared, Marina Scolnik: None declared, Mayra Alejandra Tobar Jaramillo: None declared, LEANDRO FERREYRA: None declared, Enrique Soriano Grant/research support from: AbbVie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer Inc, Sandoz, Consultant of: AbbVie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer Inc, Sandoz, Speakers bureau: AbbVie, Amber, Bristol-Myers Squibb, Eli Lilly, Novartis, Pfizer Inc, Roche

AB0831 COMPARISON OF DIFFERENT REMISSION INDICES IN PATIENTS WITH PSORIATIC ARTHRITIS: A POST HOC ANALYSIS OF DATA FROM PHASE 3 TOFACITINIB STUDIES

Background:

An international task force has agreed that remission and low disease activity (LDA) are treatment targets for patients (pts) with PsA, and recommends the Disease Activity Index in Psoriatic Arthritis (DAPSA) and minimal disease activity (MDA) to assess disease activity states.1Tofacitinib is an oral Janus kinase inhibitor for the treatment of PsA.

Objectives:

In this post hoc analysis, we compared DAPSA LDA with MDA, and DAPSA remission with very low disease activity (VLDA) and DAS28-3(CRP) remission, in pts with PsA receiving tofacitinib.

Methods:

Data were pooled from 2 Phase 3 studies (OPAL Broaden [12 months;NCT01877668]; OPAL Beyond [6 months;NCT01882439]) for pts receiving tofacitinib 5 or 10 mg twice daily (BID) or placebo (PBO). DAPSA was determined by summing: swollen joint count (SJC66); tender/painful joint count (TJC68); Patient’s Global Assessment of Arthritis (PtGA; visual analogue scale [VAS]); pain (VAS); and CRP. Pts were classified as achieving MDA or VLDA when meeting ≥5 (MDA) or 7 (VLDA) of the following criteria: TJC68 ≤1; SJC66 ≤1; Psoriasis Activity and Severity Index ≤1 or body surface area ≤3%; pain (VAS) ≤15; PtGA (VAS) ≤20; HAQ-DI ≤0.5; tender entheseal points (using Leeds Enthesitis Index [LEI]) ≤1. A logistic regression model was used to assess demographic and baseline characteristics as predictors of a trend in DAPSA scores at Month (M)3. DAPSA LDA (≤14), MDA, DAPSA remission (DAPSA ≤4), VLDA and DAS28-3(CRP) remission (DAS28-3[CRP]<2.6) rates were compared at M1, M3 and M6 for pts receiving tofacitinib 5 mg BID and at M6 for pts receiving tofacitinib 5 or 10 mg BID. Agreement between disease activity indices at M6 was evaluated using a kappa test. The percentage of tofacitinib-treated pts who achieved MDA, VLDA and non-response was reported at M6, stratified by achievement of DAPSA LDA, remission or non-response.

Results:

This analysis included 709 pts: tofacitinib 5 mg BID, n=237; tofacitinib 10 mg BID, n=236; PBO, n=236. At M3, older patients treated with tofacitinib, and tofacitinib- or PBO-treated pts with higher baseline SJC66, TJC68, PtGA VAS, HAQ-DI, LEI and Pain VAS, were significantly (p<0.05) more likely to have higher DAPSA. DAPSA LDA, MDA, remission (DAPSA and DAS28-3[CRP]) and VLDA rates generally increased from M1 to M6 for patients receiving tofacitinib 5 mg BID (Figure a). At M6, most tofacitinib-treated pts who achieved MDA, and all who achieved VLDA, were also in DAPSA remission or LDA (Figure b). At least moderate agreement (defined by kappa values 0.41–0.60) was observed between DAPSA LDA and MDA, and between DAPSA remission and VLDA, with both doses of tofacitinib at M6 (Figure c).

Conclusion:

Remission and LDA rates generally increased over time in pts with PsA receiving tofacitinib. DAPSA LDA showed moderate agreement with MDA, and DAPSA remission showed at least moderate agreement with VLDA, confirming that DAPSA and MDA are useful measurement tools to assess disease activity in pts with PsA treated with tofacitinib.

References:

[1]Smolen et al. Ann Rheum Dis 2018;77:3-17.

Acknowledgments:

Study sponsored by Pfizer Inc. Medical writing support was provided by Sarah Piggott of CMC Connect, McCann Health Medical Communications, and funded by Pfizer Inc.

Disclosure of Interests:

Emilce Schneeberger: None declared, Gustavo Citera Grant/research support from: AbbVie, Amgen, Eli Lilly, Gema, Genzyme, Novartis and Pfizer Inc, Consultant of: AbbVie, Amgen, Eli Lilly, Gema, Genzyme, Novartis and Pfizer Inc, Peter Nash Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Gilead, Janssen, MSD, Novartis, Pfizer Inc, Roche, Sanofi, UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Gilead, Janssen, MSD, Novartis, Pfizer Inc, Roche, Sanofi, UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Gilead, Janssen, MSD, Novartis, Pfizer Inc, Roche, Sanofi, UCB, Josef S. Smolen Grant/research support from: AbbVie, AstraZeneca, Celgene, Celltrion, Chugai, Eli Lilly, Gilead, ILTOO, Janssen, Novartis-Sandoz, Pfizer Inc, Samsung, Sanofi, Consultant of: AbbVie, AstraZeneca, Celgene, Celltrion, Chugai, Eli Lilly, Gilead, ILTOO, Janssen, Novartis-Sandoz, Pfizer Inc, Samsung, Sanofi, Philip J Mease Grant/research support from: Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB – grant/research support, Consultant of: Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB – consultant, Speakers bureau: Abbott, Amgen, Biogen Idec, BMS, Eli Lilly, Genentech, Janssen, Pfizer, UCB – speakers bureau, Enrique Soriano Grant/research support from: AbbVie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer Inc, Sandoz, Consultant of: AbbVie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer Inc, Sandoz, Speakers bureau: AbbVie, Amber, Bristol-Myers Squibb, Eli Lilly, Novartis, Pfizer Inc, Roche, Claudia Helling Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Annette E Szumski Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Rajiv Mundayat Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Daniela Graham Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Dario Ponce de Leon Shareholder of: Pfizer Inc, Employee of: Pfizer Inc

FRI0332 EVALUATION OF THE INDIVIDUAL COMPONENTS OF ACR50+PASI100 AND MDA AT WEEK 24 FROM THE SPIRIT-H2H TRIAL COMPARING THE EFFICACY AND SAFETY OF IXE VERSUS ADA IN PATIENTS WITH PSA NAÏVE TO BDMARDS

Background:

Psoriatic arthritis (PsA) is a chronic systemic disease with manifestations affecting musculoskeletal and extra-articular domains. Treatment and assessment of response are therefore major challenges in routine clinical practice. Minimal disease activity (MDA) is a multidimensional endpoint that can define a treatment target1. In SPIRIT-H2H2, a head-to-head clinical trial comparing the efficacy and safety of ixekizumab (IXE) versus) to adalimumab (ADA), the percentage of patients simultaneously achieving American College of Rheumatology 50 (ACR50) and Psoriasis Area and Severity Index 100 (PASI100), was the primary endpoint in order to reflect improvement in two domains of PsA.

Objectives:

To evaluate how individual components of the simultaneous achievement of ACR50 and PASI100 compare with those of MDA at week 24.

Methods:

Patients with active PsA (defined as those with a tender joint count [TJC] ≥ 3/68, a swollen joint count [SJC] ≥ 3/66 and a body surface area [BSA] of active plaque psoriasis ≥ 3%) were randomised 1:1 to approved dosing (according to baseline psoriasis involvement) of IXE or ADA in SPIRIT-H2H, an open label, assessor-blinded study.

The proportion of patients meeting each criterion of the composite endpoints was calculated for the intent-to-treat ([ITT], N=566) population and the population of MDA responders at Week 24 (N=235). Missing individual responses were imputed with non-responder status. Spidergrams were generated using SAS 9.4.

Results:

For both the overall ITT population and the MDA responders population, the use of PASI≤1 or BSA≤3% in the skin-related component of the MDA contributed to the higher response rate relative to the PASI100 response. Thus, the PASI100 response is a more stringent endpoint. Proportions of responders are similar across MDA and ACR50+PASI100 individual components for HAQ and SJC. The high baseline TJC levels (mean TJC: IXE=19.1, ADA=21.3) as opposed to lower levels observed for baseline SJC (mean SJC: IXE=10.1, ADA=10.7) made MDA-TJC criterion (≤1) more difficult to achieve than the equivalent criterion of the ACR50+PASI100 endpoint.

Conclusion:

Despite the differences in criteria definitions, there are consistent response patterns in the individual components of the simultaneous ACR50+PASI100 and MDA endpoints in particular for the peripheral arthritis domain.

References:

[1]Smolen, Josef S et al. “Treating axial spondyloarthritis and peripheral spondyloarthritis, especially psoriatic arthritis, to target: 2017 update of recommendations by an international task force.”Annals of the rheumatic diseasesvol. 77,1 (2018): 3-17.

[2]Mease PJ The SPIRIT H2H study group, et al. “A head-to-head comparison of the efficacy and safety of ixekizumab and adalimumab in biological-naïve patients with active psoriatic arthritis: 24-week results of a randomised, open-label, blinded-assessor trial.”Annals of the Rheumatic Diseases2020;79:123-131.

Disclosure of Interests:

Laura C Coates: None declared, Michael Nissen Grant/research support from: Abbvie, Consultant of: Novartis, Lilly, Abbvie, Celgene and Pfizer, Speakers bureau: Novartis, Lilly, Abbvie, Celgene and Pfizer, Celine El Baou Consultant of: Eli Lilly and Company, Jane Zochling Employee of: Jannssen Cilag, Speakers bureau: Janssen Cilag, AbbVie, Novartis, UCB, BMS, Eli Lilly, Antonio Marchesoni Speakers bureau: Abbvie, Pfizer, UCB, Novartis, Celgene, Eli Lilly, Soyi Liu Leage Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Enrique Soriano Grant/research support from: AbbVie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer Inc, Sandoz, Consultant of: AbbVie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer Inc, Sandoz, Speakers bureau: AbbVie, Amber, Bristol-Myers Squibb, Eli Lilly, Novartis, Pfizer Inc, Roche, Valderilio F Azevedo Grant/research support from: Abbvie, Janssen, Bristol-Myers Squibb, Boehringer-Ingelheim, Lilly and Novartis, Consultant of: Lilly, Novartis, Janssen, Boehringer-Ingelheim, Amgen, Pfizer and Abbvie, Speakers bureau: Sandoz, Celltrion, Lilly, Novartis, Janssen, Boehringer-Ingelheim, Amgen, Pfizer and Abbvie, Klaus Machold Grant/research support from: AbbVie, MSD, UCB, Consultant of: Arsanis, Astro, Baxter, BMS, Celgene, Eli-Lilly, MSD, Pfizer, Roche, Novartis, Sandoz, Speakers bureau: MSD, Pfizer, BMS, Janssen-Cilag, Sandoz, Novartis, Eli-Lilly, Christophe Sapin Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company

AB1270 RHEUMATOLOGY WORKFORCE IN LATIN AMERICA: TRAINING AND CURRENT STATUS

Background:

The demand for rheumatology care has been steadily increasing over the last few years. However, supply seems to be insufficient, according to previous research1. This situation may be at least partly explained by less physicians beginning a rheumatology residency program2.

Objectives:

We aim to identify baseline data, room for change, and to strengthen functional processes associated with the rheumatology workforce in order to improve care offered to patients living with rheumatic diseases.

Methods:

Descriptive cross-sectional study. We obtained data on each country through local PANLAR rheumatologists. They completed an online survey using the RedCap® platform, used for capture and storage of data. The sample was described according to the type of variable.

Results:

19 Latin American countries were included in this study, globally 1 rheumatologist was available per 106,838 inhabitants. The highest rates were found in Uruguay (1 per 23.695 inhabitants) and Argentina (1 per 40.384 inhabitants). The lowest rates were found in Nicaragua (1 per 640.648 inhabitants) and Guatemala (1 per 559.902 inhabitants). The ratio between women and men rheumatologists was 0,99 women per each man. The lowest proportions were found in Peru (0,26:1), and the highest in the Dominican Republic (2.5:1). The average age for rheumatologists was 51,6 (SD12,75). Lowest average ages were found in Paraguay (43,1 SD10,77) and the highest age averages were found in Peru (56,23 SD12.93). The average monthly compensation was USD $2.382,6 (SD$1.462,5). Venezuela had the lowest salary ($197), the highest salary was found in Costa Rica ($4.500). The proportion of rheumatologists trained abroad was 26,7%, ranging between 0% in Uruguay and 90% in Bolivia.

The countries with more rheumatology training programs were Brazil n = 50 and Mexico n = 20, while Ecuador, Honduras and Nicaragua don’t have any. The countries with the greatest amount of active residents were Brazil (n = 252) and Argentina (n = 100). The educational level required to enter the program was postgraduate studies in internal medicine in 42.11% of the programs. Currently, 108 residency programs in Latin America are active. Duration of residency programs is variable: 2 years (79.63% of cases), 3 years (16.67%), 4 years (1.85%), 5 years (0.96%) or 6 years (0.96%). The median monthly compensation for residents was $ 528 USD (IQR $ 774), the country with the highest payment was Costa Rica ($ 2637). Contrarily, in Cuba, Chile and Colombia there is no payment to residents. Finally, in 8 countries (42.11%) residents must not pay for their postgraduate studies, the average annual tuition expense in the rest of countries is $ 1248 (SD $ 2749).

Conclusion:

The rate of rheumatologists per inhabitant is low. The demographic characteristics and the current status of the rheumatology workforce, as well as rheumatology training in Latin-America varies widely among countries. For instance, relevant differences can be found regarding payment to rheumatologists and residents, and tuition fees. The collected information will be useful when planning regional-based strategies, as well as for future research projects in each country and within PANLAR.

References:

[1]Battafarano DF, Ditmyer M, Bolster MB, et al. 2015 American College of Rheumatology Workforce Study: Supply and Demand Projections of Adult Rheumatology Workforce, 2015-2030. Arthritis Care Res.2018;70(4):617-26

[2]Zborovski S, Rohekar G, Rohekar S. Strategies to improve recruitment into rheumatology: results of the Workforce in Rheumatology Issues Study. J Rheumatol. 2010;37:1749-55

Disclosure of Interests:

Daniel G. Fernández-Ávila: None declared, Daniela Patino-Hernandez: None declared, Sergio Kowalski: None declared, Alfredo Vargas-Caselles: None declared, Ana María Sapag Durán: None declared, Antonio Cachafeiro Vilar: None declared, Belia Meléndez: None declared, Carlos Santiago Pastelín: None declared, Cesar Graf: None declared, Chayanne Rossetto: None declared, Daniel Palleiro: None declared, Daniela Trincado: None declared, Diana Fernández-Ávila: None declared, Dina Arrieta: None declared, Gil Reyes: None declared, Jossiell Then: None declared, Manuel F. Ugarte-Gil Grant/research support from: Jannsen, Pfizer, Mario Cardiel: None declared, Nelly Colman: None declared, Nilmo Chávez: None declared, Paula Burgos: None declared, Ruben Montufar: None declared, Sayonara Sandino: None declared, Yurilis Fuentes-Silva: None declared, Enrique Soriano Grant/research support from: AbbVie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer Inc, Sandoz, Consultant of: AbbVie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer Inc, Sandoz, Speakers bureau: AbbVie, Amber, Bristol-Myers Squibb, Eli Lilly, Novartis, Pfizer Inc, Roche

Effectiveness of the use of an algorithm in the diagnostic approach of joint pain patients by primary care physicians

There is a high percentage of error in the approach of patients with joint pain by primary care physicians. An algorithm can help improve this misdiagnosis problem. Our study seeks to determine the effectiveness of an algorithm when used by primary care physicians for the diagnosis of cases of joint pain patients. A randomized clinical experiment was carried out. Primary care physicians from five cities in Colombia developed a series of clinical cases, which were presented to them through a website on their personal cell phones. Half of the doctors developed the cases using the diagnostic algorithm, and the other half developed the cases without the use of the algorithm. Main measures were proportion of correct diagnosis, number, type of laboratory and diagnostic images requested for the diagnostic approach of clinical cases. Two hundred and twenty-four primary care physicians participated. The overall proportion of cases correctly diagnosed was 37.3% higher in the intervention group; we found a greater difference in cases of spondyloarthritis (60.8%), followed by systemic lupus erythematosus with joint involvement (32.2%), rheumatoid arthritis (30.3%) and osteoarthritis (25.9%). The average number of tests requested to develop clinical cases was lower in the intervention group than in the control group, both globally and for each of the four diseases, with statistically significant differences for each of the comparisons. The diagnostic algorithm proved to be an effective tool when used by primary care physicians; the proportion of correct diagnoses increased, and the number of tests requested in the development of the cases decreased.

Separation of Mineral Salts and Lactose Solutions through Nanofiltration Membranes

Whey is a highly polluting by-product obtained from the elaboration of cheese. Its high content in organic matter, mainly proteins and lactose, makes it a valuable candidate for multiple applications in the food industry. However, mineral salts have to be previously eliminated. The main objective of this work was to eliminate mineral salts from model solutions with different nanofiltration membranes: NF200, NF270, Ds-5 DK and Ds-5 DL polyamide. Although all four membranes showed fairly good results in the demineralisation of the used samples, the most promising results in terms of good permeate flux and low solute retention were obtained with the NF200 and Ds-5 DL membranes, respectively. The effect of the salt mixture concentration on permeate flux and solute retention was further evaluated for Ds-5 DL membrane.

Metal-supported carbon-based materials: opportunities and challenges in the synthesis of valuable products

We summarize relevant applications and limitations of metal-supported carbons and nanocarbons in the synthesis of valuable products and the recent advances in this field.

Distinct X-chromosome SNVs from some sporadic AD samples

Sporadic Alzheimer disease (SAD) is the most prevalent neurodegenerative disorder. With the development of new generation DNA sequencing technologies, additional genetic risk factors have been described. Here we used various methods to process DNA sequencing data in order to gain further insight into this important disease. We have sequenced the exomes of brain samples from SAD patients and non-demented controls. Using either method, we found a higher number of single nucleotide variants (SNVs), from SAD patients, in genes present at the X chromosome. Using the most stringent method, we validated these variants by Sanger sequencing. Two of these gene variants, were found in loci related to the ubiquitin pathway (UBE2NL and ATXN3L), previously do not described as genetic risk factors for SAD.

[FIXING DEVICE FOR CLOSING AND COUPLING AN INTRAVENOUS CATHETER]

INTRODUCTION

skin fixing devices in peripheral, central or arterial catheters have several important drawbacks: site infection, stacking of material in the anatomical area which is very annoying for the patient and medical staff risk when fixating stitches are used.

OBJECTIVE

to develop a fixing device that simplifies presently used systems, favoring asepsis and motility.

METHODS

the device herein described is composed by a mechanical fixation, a closing system and coupling for intravenous catheters. The system has a thin circular piece with at least two holes for subcutaneous fixation, one or several conducts for lumina and a hollow cylindrical part in one side, screwed exteriorly and flat inside, with an oriented protuberance. A watertight plug with one or several thin tubes that adapt to the lumina, a positional slot, a handle and a solid screwed tap for perfect closure are available for at home use. An intermediate plug with one or several lumina and a screwed hollow plug are provided for in hospital use.

RESULTS

the above described device is intended to be used in two settings: in hospital and at home. It is supposed to reduce the risk of infection and stacking of the anatomical site where cutaneo us puncture with fixation of peripheral, central or arterial catheters is performed.