POS0239 RISK OF VENOUS THROMBOEMBOLIC EVENTS IN PATIENTS WITH RHEUMATOID ARTHRITIS AGED ≥50 YEARS WITH ≥1 CARDIOVASCULAR RISK FACTOR: RESULTS FROM A PHASE 3b/4 RANDOMISED STUDY OF TOFACITINIB VS TUMOUR NECROSIS FACTOR INHIBITORS

Background

ORAL Surveillance (NCT02092467) was a randomised, open-label, non-inferiority, Phase 3b/4 study assessing the relative risk of major adverse cardiovascular (CV) events (MACE) and malignancies with tofacitinib vs TNF inhibitors (TNFi) in patients (pts) with moderate to severe rheumatoid arthritis despite methotrexate (MTX) and a high risk of MACE (aged ≥50 yrs; ≥1 additional CV risk factor).

Objectives

To assess risk of venous thromboembolic events (VTE; including deep vein thrombosis [DVT] and pulmonary embolism [PE]) in ORAL Surveillance.

Methods

Pts on stable MTX received tofacitinib 5 or 10 mg twice daily (BID) or a TNFi (etanercept 50 mg weekly or adalimumab 40 mg once every 2 weeks). Incidence rates (IRs; pts with first events/100 pt-yrs [PY]) and 95% CIs were calculated for adjudicated VTE, DVT and PE (overall by 6-month interval and for pts with/without history of VTE). For overall VTE, DVT and PE, numbers needed to harm (NNH; tofacitinib 5 or 10 mg BID vs TNFi) were calculated post hoc. Multivariate Cox models were used post hoc to identify overall independent baseline (BL) risk factors for PE. Censoring time was a 28-day on-treatment period (minimum of last contact date or last study treatment dose date +28 days).

Results

Analysis included 1455, 1456 and 1451 pts receiving tofacitinib 5 mg BID, 10 mg BID and TNFi, respectively. Generally, across 6-month intervals to >54 months, VTE, DVT and PE IRs were numerically higher with both tofacitinib doses vs TNFi, and with tofacitinib 10 vs 5 mg BID; IRs were consistent across time (data not shown). Across treatments, VTE, DVT and PE IRs were higher in pts with vs without history of VTE; however, only a small number of pts per treatment had history of VTE (Figure 1). NNH for tofacitinib 5 and 10 mg BID, respectively, vs TNFi were 763 and 198 PY for VTE, 1347 and 589 PY for DVT, and 870 and 229 PY for PE, or, over 5 yrs, 153 and 40 pts for VTE, 269 and 118 pts for DVT, and 174 and 46 pts for PE. Identified BL risk factors for PE across treatments included history of VTE, antidepressant use, body mass index ≥30 kg/m2, corticosteroid use, male sex, age ≥65 yrs, oral contraceptives/hormone-replacement therapy (HRT) use, and history of hypertension (Table 1).

Table 1.

Multivariate Cox analyses to identify overall independent BL risk factors for PE across treatments

HR (95% CI)p valueBL covariateHistory of VTE7.06 (2.46, 20.25)0.0003Antidepressant usea2.94 (1.44, 6.02)0.0032Body mass index ≥30 kg/m22.97 (1.40, 6.32)0.0047Corticosteroid useb3.01 (1.40, 6.46)0.0047Proton pump inhibitor use0.32 (0.15, 0.71)0.0052Male sexc2.18 (1.06, 4.48)0.0340Age ≥65 yrs2.00 (1.03, 3.88)0.0401Oral contraceptives/HRT use3.56 (1.05, 12.10)0.0422History of hypertension2.57 (0.98, 6.76)0.0554

aBL antidepressant use was an indicator of an underlying condition of depression, and subgroup analysis did not identify the difference in HRs for depression across treatments

bProxy for elevated BL disease activity; HRs for BL corticosteroid use were similar between all tofacitinib doses combined and TNFi; includes any BL corticosteroid use

cImpact of sex on PE risk considered inconclusive

Multivariate Cox model using backward selection included treatment effects (not subject to model selection) and overall potential independent risk factors (those affecting PE IRs equally across treatments; subject to model selection) identified from a prior set of Cox regression analyses (which included treatment and a single candidate risk factor in each model fitting, cycling through a predetermined set of risk factors); cut-off for risk factor to stay in multivariate model was p<0.10; nominal p value and HR (95% CI) based on this model

HR, hazard ratio

Conclusion

Generally, in ORAL Surveillance, VTE, DVT and PE IRs were numerically higher for tofacitinib (10 > 5 mg BID) vs TNFi across 6-month intervals, and for pts with vs without history of VTE. Multivariate Cox models identified BL risk factors for PE that may help support future treatment decisions.

Acknowledgements

Study sponsored by Pfizer Inc. Medical writing support was provided by Emma Mitchell, CMC Connect, and funded by Pfizer Inc.

Disclosure of Interests

Christina Charles-Schoeman Consultant of: AbbVie, Gilead Sciences, Pfizer Inc and Regeneron-Sanofi, Grant/research support from: AbbVie, Bristol-Myers Squibb and Pfizer Inc, Roy M. Fleischmann Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, Galvani, Gilead Sciences, GSK, Janssen, Novartis, Pfizer Inc, Sanofi-Aventis and UCB, Grant/research support from: AbbVie, Amgen, AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Flexion, Galapagos, Galvani, Genentech, Gilead Sciences, GSK, Horizon, Janssen, Novartis, Noven, Pfizer Inc, Samumed, Sanofi Aventis, SciSelecta, Teva Pharmaceuticals, UCB, Viela and Vorso, Eduardo Mysler Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly, Janssen, Pfizer Inc, Roche and Sanofi, Grant/research support from: Eli Lilly, Pfizer Inc and Roche, Maria Greenwald Grant/research support from: AbbVie, Eli Lilly, Galapagos, Gilead Sciences, Novartis and Pfizer Inc, Cunshan Wang Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, All-shine Chen Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Carol A. Connell Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, John Woolcott Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Sujatha Menon Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Yan Chen Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Kristen Lee Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Zoltán Szekanecz Speakers bureau: AbbVie, Eli Lilly, Novartis, Pfizer Inc, Roche and Sanofi, Paid instructor for: AbbVie, Eli Lilly, Gedeon Richter, Novartis, Pfizer Inc and Roche, Consultant of: AbbVie, Eli Lilly, Novartis, Pfizer Inc, Roche and Sanofi, Grant/research support from: Pfizer Inc

AB0062 ANGIOTENSIN CONVERTING ENZYME ACTIVITY IN ANTI-TNF-TREATED RHEUMATOID ARTHRITIS AND ANKYLOSING SPONDYLITIS PATIENTS

Background

Angiotensin-converting enzyme (ACE) and ACE2 have been implicated in the regulation of vascular physiology. Elevated synovial and decreased or normal ACE or ACE2 levels have been found in rheumatoid arthritis (RA). Very little is known about the effects of tumour necrosis factor α (TNF-α) inhibition on ACE or ACE2 homeostasis.

Objectives

In this study, we assessed the effects of one-year anti-TNF therapy on ACE and ACE2 production in RA and ankylosing spondylitis (AS) in association with other biomarkers.

Methods

Forty patients including 24 RA patients treated with either etanercept (ETN) or certolizumab pegol (CZP) and 16 AS patients treated with ETN were included in a 12-month follow-up study. Serum ACE levels were determined by commercial ELISA, while serum ACE2 activity was assessed using a specific quenched fluorescent substrate. Ultrasonography was performed to determine flow-mediated vasodilation (FMD), common carotid intima-media thickness (ccIMT) and arterial pulse-wave velocity (PWV) in all patients. In addition, CRP, rheumatoid factor (RF) and ACPA were also measured. All assessments were performed at baseline and 6 and 12 months after treatment initiation.

Results

Anti-TNF therapy increased ACE levels in the full cohort, as well as in the RA and AS subsets. ACE2 activity increased in the full cohort, while the ACE/ACE2 ratio increased in the full cohort and in the RA subset (p<0.05). Uni- and multivariable regression analyses determined associations between ACE or ACE/ACE2 ratios at different time points and disease duration, CRP, RF, FMD and IMT (p<0.05). ACE2 activity correlated with CRP. The changes of ACE or ACE2 over 12 months were determined by treatment together with either RF or FMD (p<0.05).

Conclusion

Anti-TNF treatment may increase ACE and ACE2 in the sera of RA and AS patients. ACE and ACE2 may be associated with disease duration, markers of inflammation and vascular pathophysiology. The effects of TNF inhibition on ACE and ACE2 may reflect, in part, the effects of these biologics on the cardiovascular system.

Disclosure of Interests

Boglárka Soós: None declared, Miklós Fagyas: None declared, Ágnes Horváth: None declared, Edit Végh: None declared, Anita Pusztai: None declared, Monika Czókolyová: None declared, Alexandra Csongrádi: None declared, Attila Hamar: None declared, Zsófia Pethö: None declared, Nóra Bodnár: None declared, György Kerekes: None declared, Katalin Hodosi: None declared, ​Éva Szekanecz​: None declared, Szilvia Szamosi Speakers bureau: Roche, Sager, Amgen, Sándor Szántó Speakers bureau: AbbVie, Novartis, Lilly, MSD, UCB, Consultant of: AbbVie, Novartis, UCB, Gabriella Szücs Speakers bureau: Roche, Lilly, Actelion, Zoltán Papp: None declared, Zoltán Szekanecz Speakers bureau: AbbVie, Pfizer, Roche, MSD, Novartis, Lilly, Richter, Consultant of: Pfizer, Novartis, Richter, Grant/research support from: Pfizer, UCB

OP0269 BIOMARKERS TO PREDICT RISK OF VENOUS THROMBOEMBOLISM IN PATIENTS WITH RHEUMATOID ARTHRITIS RECEIVING TOFACITINIB OR TUMOUR NECROSIS FACTOR INHIBITORS

Background

In the ORAL Surveillance study of patients (pts) aged ≥50 yrs with moderate to severe rheumatoid arthritis (RA) and ≥1 additional cardiovascular risk factor (NCT02092467), the incidence of pulmonary embolism was higher with tofacitinib than with tumour necrosis factor inhibitors (TNFi).1

Objectives

To explore whether biomarkers explained the associations of tofacitinib vs TNFi with venous thromboembolism (VTE) in ORAL Surveillance.

Methods

ORAL Surveillance was a prospective, open-label, event-driven, noninferiority, post-authorisation safety study. Pts were randomised 1:1:1 to receive tofacitinib 5 or 10 mg twice daily or a TNFi (adalimumab 40 mg every 2 weeks or etanercept 50 mg once weekly). For this exploratory post hoc analysis, 294 soluble, proteomic, genetic and antibody biomarkers were assessed (of which 79 have a known role in inflammation, coagulation, vascular biology and/or Janus kinase signalling). Biomarkers were quantified in serum collected at baseline (BL) and Month (M)12 in VTE cases and 4:1 matched controls. D-dimer was analysed with a larger control group (all eligible pts without VTE) and final adjudicated data from BL, M12 and study end.

Results

Of the 4362 randomised and treated pts, D-dimer was quantified in 3732 pts (54 with VTE; 3678 without) and the remaining biomarkers were analysed in 285 pts (57 VTE cases; 228 matched controls). BL characteristics were generally similar in those with or without VTE and between treatment groups. At BL, D-dimer levels were ≥2×upper limit of normal for ~50% of controls and 67% of VTE cases. Mean D-dimer levels decreased from BL to M12 in controls across treatment groups (Figure 1). Key findings from the biomarker analyses are shown in the Table 1. No biomarker showed a clear mechanistic association with the increased risk of VTE for tofacitinib vs TNFi, or demonstrated adequate performance for prognostic use in pts with RA.

Table 1.

Summary of results from biomarker analyses

BiomarkerKey resultsTier 1C-reactive protein•No association with VTE in any treatment arm at BL or M12D-dimer Thrombopoietin•Higher M12 levels were prospectively associated with greater risk of subsequent VTE with tofacitinib 10 mg BID ◦ For D-dimer, the same effect was observed with tofacitinib 5 mg BID •Treatment specificity of effects could not be establishedTier 2Factor VIII Thrombin–antithrombin complex Tissue factor pathway inhibitor Plasminogen activator inhibitor-1 Protein C Antithrombin Apolipoprotein C-III Leptin•No clinically meaningful differences across treatment armsTiers 3 & 4Exploratory proteomic assays (276 markers from multiplex panels)•Two biomarkers with no known relationship to VTE (angiogenin and TNFSF13B) showed significant associations with pulmonary embolism in the tofacitinib 10 mg BID arm ◦ Treatment specificity of effects could not be established for either analyteGenetic biomarkersFactor V Leiden R506Q, prothrombin G20210A and JAK2 V617F mutations•Factor V Leiden and prothrombin risk alleles, individually or combined, were associated with increased incidence of VTE but did not explain excess events with tofacitinib •No VTE cases or matched controls had the JAK2 mutationAntibody biomarkersACA IgG and IgM, anti-β2GP1 IgG and IgM•No statistical differences were observed between treatment arms or between VTE cases and matched controls

ACA, anticardiolipin antibody; β2GP1, beta-2-glycoprotein 1; IgG, immunoglobulin G; IgM, immunoglobulin M; JAK2, Janus kinase 2; TNFSF13B, tumour necrosis factor ligand superfamily member 13B

Conclusion

This post hoc exploratory analysis did not identify biomarkers at BL or M12 that explain the increased VTE risk for tofacitinib vs TNFi. Notably, ORAL Surveillance was neither designed nor powered to compare the risk of VTE across treatments or to identify biomarkers with a mechanistic relationship to VTE. Individual VTE risk should be considered when making decisions about initiation or maintenance of tofacitinib treatment.

References

[1]Ytterberg et al. N Engl J Med 2022; 386: 316-326.

Acknowledgements

Study sponsored by Pfizer Inc. Medical writing support was provided by Julia King, CMC Connect, and funded by Pfizer Inc.

Disclosure of Interests

Zoltán Szekanecz Speakers bureau: AbbVie, Eli Lilly, Novartis, Pfizer Inc, Roche and Sanofi, Paid instructor for: AbbVie, Eli Lilly, Gedeon Richter, Novartis, Pfizer Inc and Roche, Consultant of: AbbVie, Eli Lilly, Novartis, Pfizer Inc, Roche and Sanofi, Grant/research support from: Pfizer Inc, Christina Charles-Schoeman Consultant of: AbbVie, Gilead Sciences, Pfizer Inc and Sanofi-Regeneron, Grant/research support from: AbbVie, Bristol-Myers Squibb and Pfizer Inc, Ivana Vranic Shareholder of: Pfizer Inc, Employee of: Pfizer Ltd, Burak Sahin Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Sara A Paciga Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Zhenyu Wang Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Craig Hyde Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, David Martin Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Jeffrey I Weitz Speakers bureau: Anthos, Bayer AG, Boehringer Ingelheim, Bristol-Myers Squibb, Daiichi Sankyo, Ionis, Janssen, Novartis, Pfizer Inc, PhaseBio, Portola and Servier Pharmaceuticals, Grant/research support from: Bayer AG and Boehringer Ingelheim

POS0677 CONSISTENCY IN TIME TO RESPONSE WITH UPADACITINIB AS MONOTHERAPY OR COMBINATION THERAPY AND ACROSS PATIENT POPULATIONS WITH RHEUMATOID ARTHRITIS

Background

Upadacitinib (UPA) has demonstrated efficacy in patients with moderate-to-severe rheumatoid arthritis (RA) across various patient populations.1–4

Objectives

This post hoc analysis aimed to evaluate the consistency in time to achieving meaningful clinical response with UPA 15 mg + conventional synthetic (cs) DMARDs in biologic (b) DMARD-inadequate responder (IR) versus csDMARD-IR patients with RA as well as with UPA 15 mg monotherapy versus UPA 15 mg + csDMARDs in csDMARD-IR patients.

Methods

Patients originally randomized to UPA 15 mg once daily from four Phase 3 trials were included in this analysis: SELECT-BEYOND1 and SELECT-CHOICE2 (UPA 15 mg + csDMARDs in bDMARD-IR patients), SELECT-NEXT3 (UPA 15 mg + csDMARDs in csDMARD-IR patients), and SELECT-MONOTHERAPY4 (UPA 15 mg monotherapy in methotrexate-IR patients). Time to response was estimated using the Kaplan–Meier method for clinical outcomes over 24 weeks (26 weeks in SELECT-MONOTHERAPY). Clinical outcomes included achievement of 28-joint Disease Activity Score with C-reactive protein (DAS28[CRP]) ≤3.2; low disease activity (LDA) defined as Clinical Disease Activity Index (CDAI) ≤10 and Simple Disease Activity Index (SDAI) ≤11; and 50% improvement in American College of Rheumatology (ACR) core components and morning stiffness (MS) duration/severity. Data presented were as observed.

Results

Overall, 905 patients were included (SELECT-BEYOND: n=164; SELECT-CHOICE: n=303; SELECT-NEXT: n=221; SELECT-MONOTHERAPY: n=217). csDMARD-IR patients had a mean disease duration of 7.3 (SELECT-NEXT) or 7.5 years (SELECT-MONOTHERAPY); bDMARD-IR patients had a mean disease duration of 12.4 years, with a more refractory population (≥3 prior bDMARDs) in SELECT-BEYOND (23%) than SELECT-CHOICE (10%). In general, the median time to DAS28(CRP) ≤3.2, CDAI LDA, 50% improvement in ACR core components, and 50% improvement in MS duration/severity were consistent across the studies in bDMARD-IR and csDMARD-IR patients. For SELECT-BEYOND, SELECT-CHOICE, SELECT-NEXT, and SELECT-MONOTHERAPY, the median (95% CI) time to achieve DAS28(CRP) ≤3.2 was 12 (12, 16), 12 (8, 12), 12 (8, 12), and 14 (8, 14) weeks, respectively (Figure 1), and the median time to achieve CDAI LDA was 20 (12, 24), 16 (12, 16), 16 (12, 16), and 20 (14, 20) weeks, respectively (Figure 2). A longer median (95% CI) time to achieve SDAI LDA was observed with UPA monotherapy (20 [14, 20] weeks) versus UPA + csDMARDs (12 [12, 16] weeks) in csDMARD-IR patients. Among bDMARD-IR patients, the median (95% CI) time to 50% improvement in pain was longer in SELECT-BEYOND versus SELECT-CHOICE (16 [12, 20] versus 8 [8, 12] weeks).

Conclusion

In diverse patient populations with RA, patients treated with UPA 15 mg, as monotherapy or with csDMARDs, generally demonstrated consistent time to achieving DAS28(CRP) ≤3.2, CDAI LDA, and 50% improvement in clinical outcomes.

References

[1]Genovese MC, et al. Lancet 2018;391:2513–24.

[2]Rubbert-Roth A, et al. N Engl J Med 2020;383:1511–21.

[3]Burmester GR, et al. Lancet 2018;391:2503–12.

[4]Smolen JS, et al. Lancet 2019;393:2303–11.

Acknowledgements

AbbVie funded this study; contributed to its design; participated in data collection, analysis, and interpretation of the data. No honoraria or payments were made for authorship. Medical writing support was provided by Amy Wilson, MSc, of 2 the Nth (Cheshire, UK), and was funded by AbbVie.

Disclosure of Interests

Andrea Rubbert-Roth Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Chugai, Eli Lilly, Gilead, Janssen, Novartis, Roche, and Sanofi, Bernard Combe Speakers bureau: AbbVie, Bristol-Myers Squibb, Celltrion, Eli Lilly, Gilead/Galapagos, Janssen, Merck, Novartis, Pfizer, Roche/Chugai, and Sanofi, Consultant of: AbbVie, Bristol-Myers Squibb, Celltrion, Eli Lilly, Gilead/Galapagos, Janssen, Merck, Novartis, Pfizer, Roche/Chugai, and Sanofi, Zoltán Szekanecz Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, Gedeon Richter, MSD, Pfizer, Roche, Sanofi, and UCB, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, Gedeon Richter, MSD, Pfizer, Roche, Sanofi, and UCB, Stephen Hall Speakers bureau: Eli Lilly, Janssen, Merck, Novartis, Pfizer, and UCB; and research grants from AbbVie, Janssen, Merck, and UCB, Consultant of: Eli Lilly, Janssen, Merck, Novartis, Pfizer, and UCB; and research grants from AbbVie, Janssen, Merck, and UCB, Boulos Haraoui Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, and UCB, Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, and UCB, Suzan Attar: None declared, Anna-Karin H Ekwall Consultant of: AbbVie and Pfizer, Yanna Song Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Tim Shaw Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Orsolya Nagy Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Ricardo Xavier Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, Janssen, Novartis, Pfizer, and UCB

OP0263 FAVORABLE BALANCE OF BENEFIT AND HARM OF LONG-TERM, LOW-DOSE PREDNISOLONE ADDED TO STANDARD TREATMENT IN RHEUMATOID ARTHRITIS PATIENTS AGED 65+: THE PRAGMATIC, MULTICENTER, PLACEBO- CONTROLLED GLORIA TRIAL

Background

Low-dose glucocorticoid (GC) therapy is widely used in RA but the true balance of benefit and harm is still unknown.

Objectives

We studied the effects of prednisolone (5 mg/day, 2 years) in RA patients aged 65+, requiring adjustment of antirheumatic therapy (DAS28≥2.60).

Methods

Pragmatic double-blind placebo-controlled randomized trial; all co-treatments and changes therein were allowed during the trial except long-term open label GC; Ca/D supplementation was advised in all patients. Minimal exclusion criteria were tailored to seniors.

Harm outcome: the number of patients with ≥1 serious adverse event (SAE), or ≥1 ‘other adverse event of special interest’ (other AESI). Other AESI comprised any AE (except worsening of RA) causing study discontinuation, and GC-specific events (Table 1).

Table 1.

Adverse events of special interest (AESI).*

prednisolone (n=224)placebo (n=225)Events by protocol-defined categorySAEother AESISAEother AESI Infection261241691  Urinary tract449429  Pneumonia217213  Other20581049 Cardiovascular8260 Symptomatic fracture21146 New onset  Hypertension1407  Diabetes mellitus0201  Cataract0726  Glaucoma0103 Other†43433526Total8019463140

*AESI: Comprises serious adverse events (SAE) and other AESI, defined by protocol.

†‘Other’ other AESI: non-serious AE outside of the above predefined categories, but associated with premature discontinuation.

Benefit outcomes: improvement in disease activity (DAS28) and joint damage progression (Sharp/van der Heijde).

Longitudinal mixed models analyzed the data. Given prior knowledge we report one-sided 95% confidence limit (95%CL) and statistical tests, performed only for the main outcomes.

Results

We randomized 451 RA patients in 7 EU countries, 449 received the intervention; of these 63% prednisolone vs 61% placebo patients completed 2 years of follow up. Discontinuations were similar in both groups: for AE (14%) and active disease (4%); the remainder mostly for ‘trial fatigue’ and covid-related access issues (20%). Mean time on study drug was 19 (SD 8) months.

70% of patients were female, mean age was 72 (max 88) years, RA duration 11 years; 67% were RF+, 56% ACPA+, 96% had joint damage on radiographs: mean score 20, median 8. Mean DAS28 was 4.5. Most patients (79%) were on current DMARD treatment, including 14% on biologics; 47% had previously used GC, 14% changed DMARD therapy at baseline. Patients had mean 2.1 active comorbidities, and used median 7 drugs.

Benefit: Disease activity rapidly declined to stabilize after 1 year (Figure 1), and was lower on prednisolone (adjusted mean difference in DAS28 over 2 years: 0.37, 95%CL 0.23, p<0.0001). The contrast in early (3-month) response was larger in 331 patients adherent to protocol on stable treatment: mean difference in DAS28 0.62 (95%CL 0.44), more responders on prednisolone (Figure 1). Significant time-treatment interaction in secondary analyses suggested a decrease in contrast after the first year, most likely caused by significantly more changes in DMARD treatment on placebo. Joint damage progression over 2 years was significantly lower on prednisolone: mean 0.6 (SD 1.9) v 1.8 (6.4) score points on placebo, difference 1.2 (95%CL 0.2, p=0.02).

Harm: 60% prednisolone vs 49% placebo patients experienced the harm outcome: adjusted RR 1.24, 95%CL 1.04, p=0.02; number needed to harm 9.5 (Table 1). During the study 1 vs 2 patients died, and 3 vs 0 died within 5 months of discontinuation. Per 100 patient-years, AE totaled 278 in prednisolone vs 206 in placebo patients, and the difference was most marked for infections (Table 1); these were mostly mild or moderately severe. Other GC-specific AESI were rare without relevant differences.

Conclusion

Add-on low dose prednisolone has beneficial long-term effects on disease activity and damage progression in senior RA patients on standard treatment. The tradeoff is a 24% increase in patients with mostly mild to moderate AE, suggesting a favorable balance of benefit and harm.

Acknowledgements

Trial registration: NCT02585258 (clinicaltrials.gov).

The trial is part of a larger project funded by the European Union’s Horizon 2020 research and innovation program under grant agreement No. 634886.

Apart from the listed authors and centers, the GLORIA Trial Consortium comprises:

L.M. Middelink, Middelinc BV The Netherlands, Operational Lead;

V. Dekker, Amsterdam UMC, Vrije Universiteit, Financial Lead;

Partners:

Trial operations: N. van den Bulk, CR2O BV, The Netherlands;

Study Medication (Development, Manufacturing & Supply): R.M.A. Pinto,

Bluepharma – Indústria Farmacêutica, S.A., Portugal;

Data management: L. Doerwald, Linical Netherlands BV, The Netherlands; S. Manger, Department of Epidemiology & Data Science, Amsterdam UMC, Vrije Universiteit, The Netherlands.

Adherence monitoring: J. Redol, BeyonDevices LDA, Portugal;

Safety monitoring: K. Prinsen, Clinfidence BV, The Netherlands;

Patient partner: M. Scholte-Voshaar, Stichting Tools (Tools2Use), The Netherlands.

Investigators (other recruiting centers):

T.L.T.A. Jansen, VieCuri – location Venlo, The Netherlands;

C. Codreanu, Clinical Center for Rheumatic Diseases, Bucarest, Rumania;

R.M.Zandhuis-Mooij, MSc, Gelre Ziekenhuis, Apeldoorn, The Netherlands;

E. Molenaar, Groene Hart Ziekenhuis, Gouda, The Netherlands;

J.M. van Laar, UMC Utrecht, The Netherlands;

Y.P.M. Ruiterman, Haga Ziekenhuis, Den Haag, The Netherlands;

A.E.R.C.H. Boonen, MUMC, Maastricht, The Netherlands;

M. Micaelo, Instituto Português de Reumatologia, Lisboa, Portugal;

J. Costa, Hospital de Ponte Lima, Portugal;

M. Sieburg, Rheumatologische Facharztpraxis Magdeburg, Germany;

J.P.L. Spoorenberg, UMC Groningen, The Netherlands;

U. Prothmann, Knappschaftsklinikum Saar GbmH, Puettlingen, Germany;

M.J. Saavedra, Hospital de Santa Maria, Lisboa, Portugal;

I. Silva, Hospital de Egas Moniz, Lisboa, Portugal;

M.T. Nurmohamed, Reade, Amsterdam, The Netherlands;

J.W.G. Jacobs, UMC Utrecht, The Netherlands; and

S.W. Tas, Amsterdam UMC, University of Amsterdam, The Netherlands.

Scientific Advisory Committee:

J.W.J. Bijlsma, UMC Utrecht, The Netherlands;

R. Christensen, The Parker Institute, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark;

Y.M. Smulders, Amsterdam UMC, VU University, The Netherlands; and

S.H. Ralston, University of Edinburgh, Edinburgh, UK.

Radiographic assessment:

D.M.F.M. van der Heijde (Imaging Rheumatology BV, the Netherlands)

coordinated the reading of the hand and foot x-rays.

A.F. Marsman and W.F. Lems scored the spine X-rays.

Patient panel:

C. Rusthoven and M. Bakkers, The Netherlands

E. Frazão Mateus, and G. Mendes, Portugal

C. Elling-Audersch and D. Borucki, Germany

A. Cardone, Italy

P. Corduta and O. Constantinescu, Romania

P. Richards, United Kingdom

G. Aanerud, Norway

Disclosure of Interests

Maarten Boers Consultant of: Novartis, Linda Hartman: None declared, Daniela Opris-Belinski Consultant of: Abbvie, Pfizer, MSD, Novartis, Eli Lilly, Ewo Pharma, UCB, Reinhard Bos: None declared, Marc R Kok: None declared, José Antonio P. da Silva: None declared, Eduard N. Griep: None declared, Ruth Klaasen: None declared, Cornelia Allaart: None declared, Paul Baudoin: None declared, Hennie Raterman Consultant of: Abbvie, Pfizer, MSD, Novartis, Eli Lilly, Ewo Pharma, UCB, Zoltán Szekanecz: None declared, Frank Buttgereit Consultant of: Abbvie, AstraZeneca, Gruenenthal, Horizon Therapeutics, Mundipharma, Pfizer, Roche, Pavol MASARYK: None declared, Thomas Klausch: None declared, Sabrina Paolino: None declared, Annemarie M. Schilder Consultant of: Eli Lilly, Novartis, Genzyme, WIllem Lems Consultant of: Pfizer, Galapagos, Lilly, Amgen, UCB., Maurizio Cutolo: None declared

AB1137 USE OF TOCILIZUMAB IN CRITICALLY ILL SARS-COV-2 PATIENTS CARE- PROGNOSTIC FACTORS OF TREATMENT EFFECTIVENESS AND TREATMENT RESULTS

Background

The treatment of COVID-19 caused by SARS-CoV-2 posed serious challenges to health care systems. In 8-10% of patients with severe COVID-19 have a cytokine storm syndrome, highlighting the importance of host immune response in pathogenesis.

Objectives

Our aim was to evaluate the effect of tocilizumab treatment in COVID-19 patients with severe cytokine storm who were refractory to standard of care therapy. To determine the prognostic factors that indicate the success of treatment in these patients.

Methods

Fifty-three patients were treated with tocilizumab during waves 2 and 3 of the pandemic due to a cytokine storm associated with SARS-CoV-2 infection. All patients underwent physical examination, saturation monitoring, laboratory examination, blood gas analysis and chest CT examination. Deteriorating clinical status, elevated IL-6 and other acute phase protein levels observed in patients treated with standard therapy suggest cytokine storm syndrome. The treatment of these patients was supplemented with 8 mg/kg (max. 800 mg) tocilizumab (1 or 2 times within 24 hours). We assessed the clinical and laboratory response of these patients to IL-6-R inhibitor therapy, the need for ventilation, the need for intensive care and mortality.

Results

Immunological consultations were performed in 31 patients, of whom 21 (68%) were successfully treated. Eleven patients of them (22%) died. In the 22 non-consulted patients, this rate was reversed: 7 (22%) were successful and 15 (68%) were treatment failures. The success of the treatment was mainly influenced by the well-established indication, the recognition of contraindications, and the condition that did not require invasive ventilation method. The 29 tocilizumab therapies initiated in the non-intensive care unit avoided intensive care unit treatment in 18 patients. Eleven patients were admitted to the intensive care unit, but 7 patients required temporary respiratory support and recovered, 4 patients required invasive mechanical ventilation and later died (14%). In contrast, 24 treatments initiated in the intensive care unit saved the lives of only 3 patients, and 21 patients were lost (87.5%). The effectiveness of treatment was not affected by age, with survival rates of 40%, 44%, 57% and 55% for the 40-49, 50-59, 60-69, 70-79 age groups, respectively. Interestingly, the extent of lung involvement also did not show a significant difference. Although it was a prerequisite for initiating tocilizumab treatment to have fresh alveolitis on the CT image of the chest.

Conclusion

Use of tocilizumab is most effective in patients with COVID-19 who have high levels of inflammatory activity and IL-6, who are at an early stage of lung involvement and who do not respond to high-dose corticosteroid therapy, who have no bacterial superinfection and require not invasive mechanical ventilation. It is also important that specialist who has immunological approach and routine with biological treatment be also involved in the care of patients with severe COVID-19 disease.

References

[1]Delayed inflammation decrease is associated with mortality in Tocilizumabtreated critically ill SARS-CoV-2 patients: A retrospective matched-cohort analysis. Urbina T. et al. Innate Immun. 2022 Jan 28:17534259211064602.

Disclosure of Interests

None declared

POS0674 RISK FACTORS FOR MAJOR ADVERSE CARDIOVASCULAR EVENTS IN PATIENTS AGED ≥50 YEARS WITH RHEUMATOID ARTHRITIS AND ≥1 ADDITIONAL CARDIOVASCULAR RISK FACTOR: A POST HOC ANALYSIS OF ORAL SURVEILLANCE

Background

ORAL Surveillance (NCT02092467) was a post-approval safety study of tofacitinib vs TNF inhibitors (TNFi) in rheumatoid arthritis (RA) patients (pts) aged ≥50 yrs with ≥1 additional cardiovascular (CV) risk factor and an inadequate response to methotrexate (MTX).

Objectives

To identify independent risk factors for major adverse CV events (MACE) in ORAL Surveillance.

Methods

Pts on stable MTX were randomised 1:1:1 to receive tofacitinib 5 or 10 mg twice daily (BID) or a TNFi (adalimumab 40 mg every 2 weeks or etanercept 50 mg once weekly). Incidence rates (IRs; pts with first events/100 pt-yrs) and hazard ratios (HRs; tofacitinib vs TNFi) were assessed for adjudicated MACE (total/fatal/non-fatal), sudden cardiac death, and total/fatal/non-fatal myocardial infarction (MI) and stroke. Post hoc univariate Cox model analyses identified potentially independent baseline (BL) risk factors for MACE across treatments; those with p<0.10 were entered into a multivariate Cox model using backward selection (p<0.10 stay criteria). MACE HRs were produced for subgroups for BL risk factors with p<0.05 in the final multivariate Cox model.

Results

4362 pts were included (tofacitinib 5 mg BID, n=1455; tofacitinib 10 mg BID, n=1456; TNFi, n=1451). IRs for total/fatal/non-fatal MACE, sudden cardiac death, and total/non-fatal MI were higher with tofacitinib vs TNFi (Table 1). Fatal MI and stroke (including fatal/non-fatal events) IRs were similar across treatments (Table 1). Total MACE and MI IRs and risk were higher with tofacitinib vs TNFi (HRs >1) and higher for non-fatal MI for tofacitinib 5 mg BID (Table 1). Current smoking, aspirin use, history of chronic lung disease, history of diabetes, male sex and older age were BL risk factors for MACE. While MACE risk was generally higher with tofacitinib vs TNFi across all BL risk factors, increased risk was clearest in current/past smokers (vs never smoked) and aspirin users (vs non-users) (Figure 1). When age and smoking status were considered in combination, pts aged ≥65 yrs or who had ever smoked had a particularly elevated MACE risk vs never smokers aged ≥50–<65 yrs (Figure 1).

Table 1.

MACE, MI and stroke IRs (pts with first events/100 pt-yrs; 95% CI) and HRs (tofacitinib vs TNFi; 95% CI)

Tofacitinib 5 mg BID(N=1455)Tofacitinib 10 mg BID(N=1456)TNFi(N=1451)nIRHRnIRHRnIR(95% CI)(95% CI)(95% CI)(95% CI)(95% CI)MACE470.911.24511.051.43370.73(0.67, 1.21)(0.81, 1.91)(0.78, 1.38)(0.94, 2.18)(0.52, 1.01)Fatal MACE140.271.14190.391.63120.24(0.15, 0.45)(0.53, 2.47)(0.23, 0.60)(0.79, 3.36)(0.12, 0.41)Non-fatal MACE330.641.29320.661.33250.50(0.44, 0.90)(0.77, 2.17)(0.45, 0.93)(0.79, 2.24)(0.32, 0.73)Sudden cardiac death100.191.22130.261.6780.16(0.09, 0.35)(0.48, 3.10)(0.14, 0.45)(0.69, 4.04)(0.07, 0.31)MI190.371.69190.391.80110.22(0.22, 0.57)(0.80, 3.55)(0.23, 0.61)(0.85, 3.77)(0.11, 0.39)Fatal MI00NI30.061.0330.06(0.00, 0.07)(0.01, 0.18)(0.21, 5.11)(0.01, 0.17)Non-fatal MI190.372.32160.332.0880.16(0.22, 0.57)(1.02, 5.30)a(0.19, 0.53)(0.89, 4.86)(0.07, 0.31)Stroke180.351.03180.371.10170.34(0.21, 0.55)(0.53, 2.00)(0.22, 0.58)(0.57, 2.13)(0.20, 0.54)Fatal stroke40.08NI20.04NI00.00(0.02, 0.20)(0.00, 0.15)(0.00, 0.07)Non-fatal stroke140.270.80160.330.97170.34(0.15, 0.45)(0.40, 1.63)(0.19, 0.53)(0.49, 1.93)(0.20, 0.54)

aHR 95% CI excludes 1.

Data collected after pts who were randomised to tofacitinib 10 mg BID had their dose reduced to 5 mg. BID were included in the tofacitinib 10 mg BID group

. HRs (95% CI) were not informative when one of the treatments in the comparison had 0 events.

Risk period was defined as time from first dose to last dose +60 days or to the last contact date, whichever was earlier.

CI, confidence interval; NI, non-informative

Conclusion

MACE IRs and risk were higher with tofacitinib vs TNFi in ORAL Surveillance. BL risk factor findings could aid identification of RA pts with potentially highest risk for MACE, with a view to informing treatment decisions.

Acknowledgements

Study sponsored by Pfizer Inc. Medical writing support was provided by Kirsten Woollcott, CMC Connect, and funded by Pfizer Inc.

Disclosure of Interests

Christina Charles-Schoeman Consultant of: AbbVie, Gilead Sciences, Pfizer Inc and Sanofi-Regeneron, Grant/research support from: AbbVie, Bristol-Myers Squibb and Pfizer Inc, Maya H Buch Speakers bureau: AbbVie, Consultant of: AbbVie, Eli Lilly, Gilead Sciences, MSD, Pfizer Inc and Roche, Grant/research support from: Pfizer Inc, Roche and UCB, Maxime Dougados Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Merck, Novartis, Pfizer Inc, Roche and UCB, Grant/research support from: AbbVie, Bristol-Myers Squibb, Eli Lilly, Merck, Novartis, Pfizer Inc, Roche and UCB, Deepak L Bhatt Grant/research support from: Abbott, Afimmune, Amarin, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Cardax, Chiesi, CSL Behring, Eli Lilly, Eisai, Ethicon, Ferring Pharmaceuticals, Forest Laboratories, Fractyl, HLS Therapeutics, Idorsia, Ironwood, Ischemix, Janssen, Lexicon, Medtronic, MyoKardia, Novo Nordisk, Owkin, Pfizer Inc, PhaseBio, PLx Pharma, Regeneron, Roche, Sanofi, Synaptic and The Medicines Company, Jon T Giles Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Genentech, Gilead Sciences and UCB, Grant/research support from: Pfizer Inc, Steven R. Ytterberg Consultant of: Corbus Pharmaceuticals, Kezar Life Sciences and Pfizer Inc, Gary G Koch Shareholder of: IQVIA, Grant/research support from: AbbVie, Acceleron, Amgen, Arena, AstraZeneca, Cytokinetics, Eli Lilly, Gilead, GSK, Huya Bioscience International, Johnson & Johnson, Landos Biopharma, Merck, Momentum, Novartis, Otsuka, Pfizer Inc, Sanofi and vTv Therapeutics, Employee of: University of North Carolina at Chapel Hill, Ivana Vranic Shareholder of: Pfizer Inc, Employee of: Pfizer Ltd, Joseph Wu Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Cunshan Wang Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Sujatha Menon Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Jose L. Rivas Shareholder of: Pfizer Inc, Employee of: Pfizer SLU, Arne Yndestad Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Carol A. Connell Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Zoltán Szekanecz Speakers bureau: AbbVie, Eli Lilly, Novartis, Pfizer Inc, Roche and Sanofi, Paid instructor for: AbbVie, Eli Lilly, Gedeon Richter, Novartis, Pfizer Inc and Roche, Consultant of: AbbVie, Eli Lilly, Novartis, Pfizer Inc, Roche and Sanofi

OP0264 IMPACT OF BASELINE CARDIOVASCULAR RISK ON THE INCIDENCE OF MAJOR ADVERSE CARDIOVASCULAR EVENTS IN THE TOFACITINIB RHEUMATOID ARTHRITIS CLINICAL PROGRAMME

Background

Results from ORAL Surveillance, a post-authorisation safety study, indicated that patients (pts) with rheumatoid arthritis (RA) aged ≥50 yrs with ≥1 additional cardiovascular (CV) risk factor have an increased risk of major adverse CV events (MACE) with tofacitinib vs tumour necrosis factor inhibitors.1

Objectives

To evaluate the impact of baseline (BL) CV risk on MACE in the wider tofacitinib RA clinical programme.

Methods

Data for pts who received ≥1 tofacitinib dose in 21 Phase 1–3b/4 (excluding ORAL Surveillance) and 2 long-term extension tofacitinib RA studies were pooled and analysed post hoc as two cohorts: (1) overall cohort and (2) CV risk-enriched cohort (pts aged ≥50 yrs with ≥1 additional CV risk factor [current smoker, hypertension, HDL-cholesterol <40 mg/dL, diabetes mellitus, history of myocardial infarction (MI) or coronary heart disease (CHD)]). Data were summarised by average tofacitinib 5 or 10 mg twice daily (BID; average total daily dose of <15 or ≥15 mg, respectively). Incidence rates (IRs; pts with first events/100 pt-yrs) for adjudicated MACE were calculated. MACE IRs were stratified by pts’ BL CV risk profile: pts were first categorised by history of coronary artery disease (HxCAD), then pts without a HxCAD were categorised by 10-yr risk of MACE, per the ASCVD-PCE risk calculator2 with a 1.5 multiplier applied.3

Results

The overall cohort included 7964 pts (average tofacitinib 5 mg BID, n=3969; average tofacitinib 10 mg BID, n=3995); of these, 3125 (39.2%) pts were included in the CV risk-enriched cohort (average tofacitinib 5 mg BID, n=1614; average tofacitinib 10 mg BID, n=1511). In both treatment arms, as expected, higher proportions of pts in the CV risk-enriched cohort had a HxCAD or a high or intermediate 10-yr predicted risk of MACE at BL vs the overall cohort (Table 1). MACE IRs (95% CIs) were lower in the overall cohort (0.38 [0.26, 0.54] and 0.37 [0.27, 0.48] for average tofacitinib 5 and 10 mg BID, respectively) vs the CV risk-enriched cohort (0.72 [0.46, 1.09] and 0.67 [0.46, 0.93], respectively), and were similar between treatment arms. MACE IRs were lower than reported in ORAL Surveillance.1 In the overall cohort, adjudicated MACE most commonly occurred in pts with a HxCAD (IR [95% CI] 0.98 [0.02, 5.47] and 1.05 [0.13, 3.78] for average tofacitinib 5 and 10 mg BID, respectively), or in pts with a high 10-yr risk of MACE at BL (Figure 1). A lower predicted 10-yr MACE risk was associated with lower MACE IRs (Figure 1); trends were similar for the CV risk-enriched cohort (data not shown).

Table 1.

Proportions of pts with a HxCAD and pts without a HxCAD categorised by 10-yr risk of MACE, per ASCVD-PCE risk calculator2 with a 1.5 multiplier applied3

Average tofacitinib 5 mg BIDAverage tofacitinib 10 mg BIDOverall cohort(N=3969)CV risk-enriched cohort(N=1614)Overall cohort(N=3995)CV risk-enriched cohort(N=1511)HxCAD, n (%)61 (1.5)61 (3.8)65 (1.6)60 (4.0)No HxCAD: 10-yr risk of MACE, n (%)High (≥20%)440 (11.1)365 (22.6)337 (8.4)276 (18.3)Intermediate (≥7.5–<20%)853 (21.5)593 (36.7)788 (19.7)530 (35.1)Borderline (≥5–<7.5%)435 (11.0)234 (14.5)404 (10.1)195 (12.9)Low (<5%)2133 (53.7)342 (21.2)2058 (51.5)307 (20.3)Missing data47 (1.2)19 (1.2)343 (8.6)143 (9.5)

CAD is defined as any of MI or CHD.

n, number of pts with specified characteristic; N, number of evaluable pts

Conclusion

In the tofacitinib RA clinical programme, MACE were largely associated with BL CV risk in the overall cohort, consistent with results of ORAL Surveillance, although results should be interpreted with caution due to low pt-yrs of exposure in some pt groups. Noting this limitation, these findings emphasise the importance of assessing and addressing BL CV risk when treating pts with RA.

References

[1]Ytterberg et al. New Engl J Med 2022; 386: 316-326.

[2]American College of Cardiology, American Heart Association. ASCVD risk estimator. https://tools.acc.org/ldl/ascvd_risk_estimator/index.html#!/calulate/estimator/.

[3]Agca et al. Ann Rheum Dis 2017; 76: 17-28.

Acknowledgements

Study sponsored by Pfizer Inc. Medical writing support was provided by Kirsten Woollcott, CMC Connect, and funded by Pfizer Inc.

Disclosure of Interests

Maxime Dougados Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Merck, Novartis, Pfizer Inc, Roche and UCB, Grant/research support from: AbbVie, Bristol-Myers Squibb, Eli Lilly, Merck, Novartis, Pfizer Inc, Roche and UCB, Christina Charles-Schoeman Consultant of: AbbVie, Gilead Sciences, Pfizer Inc and Sanofi-Regeneron, Grant/research support from: AbbVie, Bristol-Myers Squibb and Pfizer Inc, Zoltán Szekanecz Speakers bureau: AbbVie, Eli Lilly, Novartis, Pfizer Inc, Roche and Sanofi, Paid instructor for: AbbVie, Eli Lilly, Gedeon Richter, Novartis, Pfizer Inc and Roche, Consultant of: AbbVie, Eli Lilly, Novartis, Pfizer Inc, Roche and Sanofi, Grant/research support from: Pfizer Inc, Jon T Giles Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Genentech, Gilead Sciences and UCB, Grant/research support from: Pfizer Inc, Steven R. Ytterberg Consultant of: Corbus Pharmaceuticals, Kezar Life Sciences and Pfizer Inc, Deepak L Bhatt Grant/research support from: Abbott, Afimmune, Amarin, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Cardax, Chiesi, CSL Behring, Eisai, Eli Lilly, Ethicon, Ferring Pharmaceuticals, Forest Laboratories, Fractyl, HLS Therapeutics, Idorsia, Ironwood, Ischemix, Janssen, Lexicon, Medtronic, MyoKardia, Novo Nordisk, Owkin, Pfizer Inc, PhaseBio, PLx Pharma, Regeneron, Roche, Sanofi, Synaptic and The Medicines Company, Gary G Koch Grant/research support from: AbbVie, Acceleron, Amgen, Arena, AstraZeneca, Cytokinetics, Eli Lilly, Gilead Sciences, GSK, Huya Bioscience International, Johnson & Johnson, Landos Biopharma, Merck, Momentum, Novartis, Otsuka, Pfizer Inc, Sanofi and vTv Therapeutics, Employee of: University of North Carolina at Chapel Hill, Ivana Vranic Shareholder of: Pfizer Inc, Employee of: Pfizer Ltd, Joseph Wu Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Cunshan Wang Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Kenneth Kwok Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Sujatha Menon Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Carol A. Connell Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Arne Yndestad Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Jose L. Rivas Shareholder of: Pfizer Inc, Employee of: Pfizer SLU, Maya H Buch Speakers bureau: AbbVie, Consultant of: AbbVie, Eli Lilly, Gilead Sciences, MSD, Pfizer Inc and Roche, Grant/research support from: Pfizer Inc, Roche and UCB

POS0520 ASSOCIATION BETWEEN BASELINE STATIN TREATMENT AND MAJOR ADVERSE CARDIOVASCULAR EVENTS IN PATIENTS WITH RHEUMATOID ARTHRITIS: A POST HOC ANALYSIS OF ORAL SURVEILLANCE

Background

ORAL Surveillance (NCT02092467) was a post-authorisation safety study of tofacitinib vs tumour necrosis factor inhibitors (TNFi) in patients (pts) with rheumatoid arthritis (RA) aged ≥50 years (yrs) with ≥1 additional cardiovascular (CV) risk factor and an inadequate response to methotrexate (MTX). Statins are used to treat coronary artery disease (CAD) and are recommended by the American College of Cardiology/American Heart Association (ACC/AHA) for the management of pts at risk of atherosclerotic CV disease (ASCVD),1 such as those with ≥7.5% 10-yr risk of major adverse CV events (MACE) or diabetes mellitus.

Objectives

To examine the association between baseline (BL) statin use and MACE in ORAL Surveillance.

Methods

Pts with RA on stable MTX were randomised 1:1:1 to receive tofacitinib 5 or 10 mg twice daily (BID) or TNFi (adalimumab 40 mg every 2 weeks or etanercept 50 mg once weekly). Pts were stratified post hoc by BL statin use (yes/no). Pts were further categorised by history of CAD (HxCAD), BL CV risk score per ACC/AHA guidelines1 (for pts without HxCAD; 10-yr risk of MACE per the ASCVD-pooled cohort equations risk calculator2 with a 1.5 multiplier applied3), and separately by BL diabetes status. CV risk score/BL diabetes status categories were: high (≥20%)/HxCAD (yes), intermediate (≥7.5–<20%) or low-borderline (<7.5%), and diabetes status (yes). For the overall population and each treatment group, risk of MACE was compared between BL statin use (yes vs no) via Cox analyses for each CV risk category and diabetes status (yes). Incidence rates (IRs; pts with first events/100 pt-yrs) and hazard ratios (HRs; BL statin use: yes vs no) were evaluated for adjudicated MACE.

Results

Of 4362 pts (tofacitinib 5 mg BID, n=1455; tofacitinib 10 mg BID, n=1456; TNFi, n=1451), 497 had a HxCAD, and 3813 without a HxCAD had CV risk scores determined; 789 had BL diabetes. Overall, 1020 (23.4%) pts reported BL statin use. Across CV risk score categories for all treatment groups, <50% of pts received statins at BL, with statin use highest in the high/HxCAD category pts (35.7–40.6%) and pts with diabetes (35.7–44.2%) (Table 1). Across categories, no interpretable associations between BL statin use and MACE were found. However, in the overall population, MACE IRs were lower in pts with vs without BL statin use in the high/HxCAD category, and in pts with diabetes (Figure 1). In pts receiving tofacitinib 5 mg BID and TNFi, MACE IRs were lower in pts with vs without BL statin use across all categories (Figure 1).

Table 1.

Proportion of pts receiving statins at BL, by CV risk category and presence of diabetes

n/N (%)OverallTofacitinibTofacitinibTNFi5 mg BID10 mg BIDHigh (≥20%)/HxCAD525/1370 (38.3)168/435 (38.6)193/475 (40.6)164/460 (35.7)Intermediate (≥7.5–<20%)302/1511 (20.0)110/490 (22.4)94/516 (18.2)98/505 (19.4)Low-borderline (<7.5%)178/1429 (12.5)66/513 (12.9)57/446 (12.8)55/470 (11.7)Diabetes (yes)320/789 (40.6)111/251 (44.2)114/272 (41.9)95/266 (35.7)

N, number of pts in each category; n, number of pts receiving BL statins

Conclusion

In this post hoc analysis of data from ORAL Surveillance, most pts did not receive BL statin treatment. This suggests suboptimal CV risk management, particularly in pts at high risk of CV events. There was no interpretable association between BL statin use and MACE. However, pts in the higher risk categories, particularly those receiving tofacitinib 5 mg BID, had lower MACE IRs with vs without BL statin use. This analysis did not take into account initiation or dose adjustment of statin treatment during the study, and had low yrs of exposure in some categories.

References

[1]Arnett et al. J Am Coll Cardiol 2019; 74: e177-232.

[2]American College of Cardiology, American Heart Association. ASCVD risk estimator. https://tools.acc.org/ldl/ascvd_risk_estimator/index.html#!/calulate/estimator/.

[3]Agca et al. Ann Rheum Dis 2017; 76: 17-28.

Acknowledgements

Study sponsored by Pfizer Inc. Medical writing support was provided by Lauren Hogarth, CMC Connect, and funded by Pfizer Inc.

Disclosure of Interests

Jon T Giles Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Genentech, Gilead Sciences and UCB, Grant/research support from: Pfizer Inc, Christina Charles-Schoeman Consultant of: AbbVie, Gilead Sciences, Pfizer Inc and Sanofi-Regeneron, Grant/research support from: AbbVie, Bristol-Myers Squibb and Pfizer Inc, Maya H Buch Speakers bureau: AbbVie, Consultant of: AbbVie, Eli Lilly, Gilead Sciences, MSD, Pfizer Inc and Roche, Grant/research support from: Pfizer Inc, Roche and UCB, Maxime Dougados Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Merck, Novartis, Pfizer Inc, Roche and UCB, Grant/research support from: AbbVie, Bristol-Myers Squibb, Eli Lilly, Merck, Novartis, Pfizer Inc, Roche and UCB, Zoltán Szekanecz Speakers bureau: AbbVie, Eli Lilly, Novartis, Pfizer Inc, Roche and Sanofi, Paid instructor for: AbbVie, Eli Lilly, Gedeon Richter, Novartis, Pfizer Inc and Roche, Consultant of: AbbVie, Eli Lily, Novartis, Pfizer Inc, Roche and Sanofi, Steven R. Ytterberg Consultant of: Corbus Pharmaceuticals, Kezar Life Sciences and Pfizer Inc, Gary G Koch Shareholder of: IQVIA, Grant/research support from: AbbVie, Acceleron, Amgen, Arena, AstraZeneca, Cytokinetics, Eli Lilly, Gilead Scienes, GlaxoSmithKline, Huya Bioscience International, Johnson & Johnson, Landos Biopharma, Merck, Momentum, Novartis, Otsuka, Pfizer Inc, Sanofi and vTv Therapeutics, Employee of: University of North Carolina at Chapel Hill, Joseph Wu Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Cunshan Wang Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Kenneth Kwok Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Sujatha Menon Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Yan Chen Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Teoman Yusuf Cesur Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Jose L. Rivas Shareholder of: Pfizer Inc, Employee of: Pfizer SLU, Arne Yndestad Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Annette Diehl Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Deepak L Bhatt Grant/research support from: Abbott, Afimmune, Amarin, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Cardax, Chiesi, CSL Behring, Eisai, Ethicon, Ferring Pharmaceuticals, Forest Laboratories, Fractyl, HLS Therapeutics, Idorsia, Ironwood, Ischemix, Janssen, Lexicon, Lilly, Medtronic, MyoKardia, Novo Nordisk, Owkin, Pfizer Inc, PhaseBio, PLx Pharma, Regeneron, Roche, Sanofi, Synaptic and The Medicines Company.

OP0270 TAPERING OF LONG-TERM, LOW-DOSE GLUCOCORTICOIDS IN SENIOR RHEUMATOID ARTHRITIS PATIENTS: FOLLOW-UP OF THE PRAGMATIC, MULTICENTRE, PLACEBO-CONTROLLED GLORIA TRIAL

Background

Guidelines suggest glucocorticoids (GC) should be used as bridge therapy in rheumatoid arthritis (RA), but many patients are treated chronically with low doses. The effects of withdrawal in such patients has not been studied extensively.

Objectives

To study disease activity score (DAS28), disease flares and signs of adrenal insufficiency after withdrawal of blinded trial medication (prednisolone 5 mg/day or placebo for 2 years).

Methods

The 2-year, double-blind GLORIA trial evaluated the long-term benefits and harms of low dose GC added to standard care (see main GLORIA trial abstract). Senior RA patients (≥ 65 years) were randomly assigned to prednisolone 5 mg/day or placebo.

After the final trial visit study medication was linearly tapered to zero in 3 months by adding a stop day every two weeks, and patients were reassessed. Those who successfully completed the trial and did not receive open-label GC during the 4 weeks after the final trial visit were included in this follow-up study.

The primary outcome was change in DAS28 at follow-up compared to the final trial visit. Secondary outcomes included the occurrence of disease flares (DAS28 increase > 0.6 or open-label GC between week 4 and 12 of the taper phase) and signs of adrenal insufficiency, assessed by 9 items selected from the 57-symptom list from the MDHAQ questionnaire (1) and hypotension (systolic RR < 90 or diastolic RR < 60). In a subset of patients from 3 Dutch centres, cortisol and ACTH were measured in spot serum samples during the follow-up visit.

Analysis of covariance assessed the change in DAS28. Linear regression and chi-square test were used for the remaining outcomes.

Results

278 participants completed the GLORIA study, 21 received GC within 4 weeks after the end of the trial, 58 had missing data, leaving 199 patients eligible for this study.

34 patients received open label GC after 4 weeks and were excluded for the primary analysis. In the remaining 165 patients (80 prednisolone, 85 placebo), mean (SD) DAS28 was higher on placebo: 3.14 (1.04) vs 2.92 (1.13) prednisolone at the final trial visit. After tapering, disease activity increased significantly (p=0.02) in the prednisolone group to 3.18 (1.20) but was stable in placebo (3.14). The difference in the increase of DAS28 between the groups was 0.21 (95%CI –0.05;0.47; p=0.11).

For signs of adrenal insufficiency, 33 out of 165 had missing data, leaving 60 in the prednisolone group and 72 in placebo (Table 1). Mean (SD) number of signs for prednisolone was 1.1 (1.1) versus 0.9 (1.3) for placebo at final trial visit and 0.8 (1.2) versus 0.8 (1.0) at follow-up. Difference in the change of the number of signs was –0.1 (95%CI –0.4;0.3; p=0.66).

Table 1.

Adrenal insufficiency signs and symptoms.

prednisolone (n=60)placebo(n=72)end of trialchange after 3 monthsend of trialchange after 3 monthsFatigue (unusual)15113–1Appetite loss5–144Muscle weakness7–26–2Dizziness32101Stomach pain3431Muscle pain19–619–1Nausea5–322Vomiting1001Diarrhoea5–23–2Hypotension*2–14–2Sum**1.1 (1.1)–0.2 (1.3)0.9 (1.3)0.0 (1.3)

* Systolic RR < 90 or diastolic RR < 60.

**Mean (SD)

No differences were seen in ACTH or cortisol levels: mean (SD) ACTH was 5.8 (4.1) in 23 prednisolone patients, and 5.1 (3.7) in 24 placebo patients; cortisol 296 (113) v 310 (166), cortisol/ACTH 67 (40) v 77 (54). Two prednisolone and one placebo patient had cortisol levels below 80. None developed clinical hypoadrenalism during further follow-up.

199 patients qualified for the disease flares sample, 99 prednisolone and 100 placebo; 44 patients flared on prednisolone tapering vs 31 on placebo, relative risk 1.43 (95%CI 0.99; 2.07; p=0.07).

Conclusion

Tapering prednisolone moderately increases disease activity to placebo levels (mean still at low disease activity levels) and numerically increases the risk of flare without any evidence of adrenal insufficiency. This suggests that withdrawal of low dose prednisolone is feasible after 2 years of administration.

References

[1]DeWalt DA et al. Clin Exp Rheumatol. 2004;22:453-61.

Acknowledgements

The GLORIA trial is registered at clinicaltrials.gov under NCT02585258.

The GLORIA project is funded by the European Union’s Horizon 2020 research and innovation programme under the topic ‘’Personalizing Health and Care’’, grant agreement No 634886.

Disclosure of Interests

Abdullah Almayali: None declared, Maarten Boers Consultant of: Novartis, Linda Hartman: None declared, Daniela Opris-Belinski Consultant of: Abbvie, Pfizer, MSD, Novartis, Eli Lilly, Ewo Pharma, UCB, Reinhard Bos: None declared, Marc R Kok: None declared, José Antonio P. da Silva: None declared, Eduard N. Griep: None declared, Ruth Klaasen: None declared, Cornelia Allaart: None declared, Paul Baudoin: None declared, Hennie Raterman Consultant of: AbbVie, Amgen, Celgene, Roche, Sandoz, Sanofi Genzyme and UCB, Zoltán Szekanecz: None declared, Frank Buttgereit Consultant of: Abbvie, AstraZeneca, Gruenenthal, Horizon Therapeutics, Mundipharma, Pfizer, Roche, Pavol MASARYK: None declared, WIllem Lems Consultant of: Pfizer, Galapagos, Lilly, Amgen, UCB., Maurizio Cutolo: None declared, Marieke ter Wee: None declared

POS1402 COST-EFFECTIVENESS AND COST-UTILITY OF ADD-ON, LOW-DOSE PREDNISOLONE IN RA PATIENTS AGED 65+: THE PRAGMATIC, MULTICENTER, PLACEBO-CONTROLLED GLORIA TRIAL

Background

Rheumatoid arthritis (RA) is a disease with substantial impact on quality of life, healthcare and societal costs [1]. Current treatment strategies, especially biologic drugs, result in high costs [2]. Previous studies have already found that a combination treatment strategy of disease-modifying antirheumatic drug(s) with initially medium-to-high doses of prednisolone resulted in better effects and lower costs compared to the treatment strategies without prednisolone [3, 4]. However, to our knowledge the cost-effectiveness of low-dose glucocorticoids (GCs), and that of GC overall in established RA has not been examined separately.

Objectives

To evaluate the cost-effectiveness and cost-utility of low-dose prednisolone in RA patients aged 65+.

Methods

The economic evaluation was performed as part of the placebo-controlled GLORIA trial of RA patients aged 65+ with a disease activity score in 28 joints (DAS28) ≥2.60. Eligible patients were randomized to 2 years 5 mg/day prednisolone or placebo. Patients were recruited from 28 clinical centers in seven European countries. All co-treatment, except for chronic oral GC, was allowed.

The economic evaluation had a societal perspective with a time horizon of two years. Cost data were collected with questionnaires and from recorded events, and valued with unit prices of 2017. The primary effectiveness outcome was the DAS28. For cost-utility, quality-adjusted life years (QALYs) were estimated from the EuroQol-5 Dimension (EQ-5D) questionnaire.

Standard regression models were used to estimate incremental costs and effects between the treatment groups. Bootstrapping assessed the uncertainty around the average differences in costs and health outcomes.

Results

In total, 444 of 451 randomized patients were included in the modified-intention-to-treat analysis (see main GLORIA study abstract). Patients were on average 72 years and had median 4 active comorbidities at baseline. Mean total costs over 2 years were k€10.8 in the prednisolone group, k€0.4 (95% CI –3.7; 1.9) lower than in the placebo group. Total direct medical costs were k€0.5 (95% CI –4.0; 1.5) lower in the prednisolone group. The mean number of QALYs was similar in both groups (difference 0.02 [–0.03; 0.06] in favor of prednisolone). The DAS28 was 0.38 lower in the prednisolone group than in the placebo group (0.19;0.56).

The cost-effectiveness plane shows that the majority of the bootstrapped cost-effect pairs was situated in the southwest quadrant of the plane confirming the larger effects (i.e. decrease in DAS28) and non-significant lower costs in the prednisolone group (Figure 1). The cost-utility plane shows that the number of QALYs was similar for both groups and that the bootstrapped cost-utility pairs were slightly more located in the southeast quadrant confirming a very small increase in QALYs and slightly lower costs in the prednisolone group (Figure 1).

Conclusion

With greater effectiveness at non-significantly lower costs, low-dose, add-on prednisolone is cost-effective for RA compared to placebo over two years. QALYs were equal in both groups, most likely due to the impact of multiple comorbidities.

References

[1]Kobelt G. Elsevier. 2009;83-9.

[2]Souliotis K et al. PLoS One. 2019;14:e0226287.

[3]Ter Wee MM et al. RMD Open. 2017;3:e000502.

[4]Verhoeven AC et al. Br J Rheumatol. 1998;37:1102-9.

Acknowledgements

The GLORIA project is funded by the European Union’s Horizon 2020 research and innovation programme under the topic ‘’Personalizing Health and Care’’, grant agreement No 634886.

Disclosure of Interests

Linda Hartman: None declared, Mohamed El Alili: None declared, Maurizio Cutolo: None declared, Daniela Opris-Belinski Speakers bureau: Abbvie, Pfizer, MSD, Novartis, Eli Lilly, Ewo Pharma, UCB, José Antonio P. da Silva: None declared, Zoltán Szekanecz: None declared, Frank Buttgereit Speakers bureau: Abbvie, AstraZeneca, Gruenenthal, Horizon Therapeutics, Mundipharma, Pfizer, Roche, Pavol MASARYK: None declared, Reinhard Bos: None declared, Marc R Kok: None declared, Sabrina Paolino: None declared, Veerle M. H. Coupé: None declared, WIllem Lems Speakers bureau: Pfizer, Galapagos, Lilly, Amgen, UCB, Maarten Boers Speakers bureau: BMS, Novartis, Pfizer

POS0519 RELATIONSHIP BETWEEN DISEASE ACTIVITY AND MAJOR ADVERSE EVENTS IN PATIENTS WITH RHEUMATOID ARTHRITIS ON TOFACITINIB OR TNF INHIBITORS: A POST HOC ANALYSIS OF ORAL SURVEILLANCE

Background

Uncontrolled rheumatoid arthritis (RA) activity and acute disease flares are associated with higher risk of adverse outcomes such as cardiovascular (CV) disease, venous thromboembolism (VTE), malignancy and infection.1-4

Objectives

To evaluate associations of acute and cumulative Clinical Disease Activity Index (CDAI) measurements with major CV, malignancy, or infectious adverse events (AEs) of special interest in ORAL Surveillance.

Methods

ORAL Surveillance (NCT02092467) was a post-authorisation safety study of tofacitinib vs TNF inhibitors (TNFi) in patients (pts) aged ≥50 yrs with active RA despite methotrexate (MTX), and ≥1 additional CV risk factor. Pts were randomised 1:1:1 to tofacitinib 5 or 10 mg twice daily (BID) or subcutaneous TNFi. Two post hoc analyses were performed: (1) a time-varying multivariate Cox model examined risks of major AEs when pts were in CDAI-defined low (>2.8–≤10; LDA), moderate (>10–≤22; MDA) or high (>22; HDA) disease activity vs remission (≤2.8). The Cox model also included pt demographics, medical history, RA characteristics, prior treatments, baseline (BL) medications and treatment arm, pre-selected using backward selection; (2) area under the curve (AUC) per yr for CDAI prior to event or to study end (pts without event) was calculated and compared using an analysis of variance model with treatment arm, event status and interaction (supportive). Nominal p values <0.10 were considered evidence of associations.

Results

4362 pts were included. Mean RA duration at BL was approximately 10 yrs. All pts were on MTX at BL, and 28% had previously been on one other synthetic disease-modifying antirheumatic drug (DMARD). Overall, 10% of pts had been on one biologic DMARD. Hazard ratios suggested that when pts had LDA, MDA or HDA vs remission, they were potentially at higher risk of developing major adverse CV events (MACE), VTE and non-serious infections (NSIs) excluding herpes zoster (HZ), but not malignancies, serious infections or HZ (Figure 1). Similarly, mean CDAI AUC trended higher for MACE, VTE and NSIs (Table 1).

Table 1.

Cumulative CDAI (from BL to event) for pts with vs without events (AUC/yr)

Major AEPts with eventsPts without eventsLS mean difference in pts with vs without eventsp valueTreatmentnLS mean AUC/yrnLS mean AUC/yrMACETofacitinib 5 mg BID426275.413364607.31668.10.0018*Tofacitinib 10 mg BID505237.413064482.6754.80.1253TNFi365234.513124851.5383.00.5069VTETofacitinib 5 mg BID156546.713634614.41932.30.0293*Tofacitinib 10 mg BID316688.213234458.52229.70.0003*TNFi86423.613394839.41584.10.1907Malignancy excl. NMSCTofacitinib 5 mg BID595249.313194618.9630.40.1655Tofacitinib 10 mg BID554793.713014482.2311.50.5077TNFi395561.413084826.3735.10.1854Serious infectionsTofacitinib 5 mg BID1275710.212424577.51132.70.0004*Tofacitinib 10 mg BID1505425.211974476.4948.80.0013*TNFi1056058.412404807.71250.70.0003*HZTofacitinib 5 mg BID1755184.511994738.1446.40.1101Tofacitinib 10 mg BID1635549.111864481.31067.80.0002*TNFi565667.212914875.5791.80.0930*NSIs excl. HZTofacitinib 5 mg BID7606608.34635122.51485.8<0.0001*Tofacitinib 10 mg BID7506587.84265009.61578.2<0.0001*TNFi7226737.65215217.51520.1<0.0001*

*p<0.10. Data collected after pts who were randomised to tofacitinib 10 mg BID had their dose reduced to 5 mg BID were included in the tofacitinib 10 mg BID group LS, least squares; n, number of pts in analysis of variance model

Conclusion

In ORAL Surveillance, the risk of MACE, VTE and NSIs excluding HZ appeared higher when pts had active disease than when in remission. Greater cumulative RA disease activity was seen in pts who suffered these AEs vs those who did not. Our findings support treat-to-target recommendations for RA.

References

[1]Molander et al. Ann Rheum Dis 2021; 80: 169-175.

[2]Maradit-Kremers et al. Arthritis Rheum 2005; 52: 722-732.

[3]Au et al. Ann Rheum Dis 2011; 70: 785-791.

[4]Baecklund et al. Arthritis Rheum 2006; 54: 692-701.

Acknowledgements

Study sponsored by Pfizer Inc. Medical writing support was provided by Karen Thompson, PhD, CMC Connect, and funded by Pfizer Inc.

Disclosure of Interests

George Karpouzas Speakers bureau: Sanofi-Genzyme-Regeneron, Consultant of: Janssen and Sanofi-Genzyme-Regeneron, Grant/research support from: Pfizer Inc, Zoltán Szekanecz Speakers bureau: AbbVie, Eli Lilly, Novartis, Pfizer Inc, Roche and Sanofi, Paid instructor for: AbbVie, Eli Lilly, Gedeon Richter, Novartis, Pfizer Inc and Roche, Consultant of: AbbVie, Eli Lilly, Novartis, Pfizer Inc, Roche and Sanofi, Eva Baecklund: None declared, Ted Mikuls Paid instructor for: Pfizer Inc, Consultant of: Gilead Sciences, Horizon and Sanofi, Grant/research support from: Bristol-Myers Squibb and Horizon, Deepak L Bhatt Grant/research support from: Abbott, Afimmune, Amarin, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Cardax, Chiesi, CSL Behring, Eisai, Eli Lilly, Ethicon, Ferring Pharmaceuticals, Forest Laboratories, Fractyl, HLS Therapeutics, Idorsia, Ironwood, Ischemix, Janssen, Lexicon, Medtronic, MyoKardia, Novo Nordisk, Owkin, Pfizer Inc, PhaseBio, PLx Pharma, Regeneron, Roche, Sanofi, Synaptic and The Medicines Company, Harry Shi Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Cunshan Wang Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Gosford Sawyerr Consultant of: Pfizer Inc, Employee of: Syneos Health Inc, Yan Chen Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Sujatha Menon Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Carol A. Connell Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Steven R. Ytterberg Consultant of: Corbus Pharmaceuticals, Kezar Life Sciences and Pfizer Inc, Mahta Mortezavi Shareholder of: Pfizer Inc, Employee of: Pfizer Inc.

POS1410 DEVELOPMENT OF PREDICTION MODELS FOR SENIOR PATIENTS WITH RHEUMATOID ARTHRITIS AND COMORBIDITIES TREATED WITH CHRONIC LOW-DOSE GLUCOCORTICOIDS IN THE GLORIA TRIAL

Background

Rheumatoid arthritis (RA) is a systemic, inflammatory disease primarily located in the joints resulting in pain, joint damage, functional disability and reduced quality of life. Treatment of RA is essential to prevent these outcomes, but the treatment itself may also result in adverse events and comorbidity [1]. Although many investigators are working on personalized medicine [2], better models to predict harm and benefit from a certain drug need to be developed before they can be used in daily clinical practice [3].

Objectives

To develop prediction models for individual patient harm and benefit outcomes in senior patients with RA and comorbidities treated with chronic low-dose glucocorticoid therapy or placebo.

Methods

In the GLORIA trial 451 RA patients aged 65+ were randomized to 2 years 5 mg/day prednisolone or placebo. Eight prediction models were developed from the dataset in a stepwise procedure. In preparation, to limit excessive statistical testing and false positive results, possible predictors were grouped into five predictor sets based on prior knowledge (Table 1). The first set of four models disregarded study treatment and examined general predictive factors. The second set of four models was similar but examined the additional role of study treatment, as main factor and as interaction factor with other predictive variables. In each set two models focused on harm (1: occurrence of ≥1 adverse event of special interest (AESI); 2: number of AESIs per year) and two on benefit (3: early clinical response–disease activity; 4: lack of joint damage progression). AESI comprised all serious adverse events, events leading to discontinuation of study treatment, and events related to glucocorticoid exposure (see main GLORIA study abstract). Linear and logistic multivariable regression methods with backward selection were used to develop the models. The final models were assessed and internally validated with bootstrapping techniques, and their performance was evaluated with model fit and discrimination measures.

Table 1.

Predictor sets.

Personal factorsDisease factorsComorbiditiesAgeDAS28Active comorbidity: cont, dich,SexRA durationGC-relatedEducationRFPrior comorbidity: cont, dich,SmokingAnti-CCPGC-relatedAlcoholDamage (cont, dich)# comorbidity medicationsBMICoping RAJoint surgeryBlood pressureImpact RA# patient symptomsMedicationHealth and daily functioning# concomitant medicationsHAQPrevious use DMARD, bDMARD, GCQoLCurrent use bDMARDVAS healthAdherenceSF36 physical, mentalSwitch antirheumatic drugs

cont=continuous; dich=dichotomous; GC=glucocorticoid.

Results

Study treatment (i.e. prednisolone) was highly predictive as a main factor in models 5-8, increasing the risk of both benefit and harm. In addition, a few additional variables were slightly (but not relevantly) predictive for the outcome in one of the models (Figure 1). Their association was much weaker than that of study treatment. In three instances, prednisolone interacted with another predictive factor (see Figure 1). The quality of the prediction models was sufficient, the performance low to moderate: explained variance: 12-15%, AUC 0.67-0.69.

Conclusion

Baseline factors are not helpful to select senior RA patients for treatment with low-dose prednisolone given their low power to predict the chance of benefit or harm.

References

[1]Smolen JS et al. Lancet. 2016;388(10055):2023-38.

[2]Huizinga TWJ. J Intern Med. 2015;277(2):178-87.

[3]De Punder YMRVR et al. Journal of Rheumatology. 2015;42(3):391-7.

Acknowledgements

The GLORIA project is funded by the European Union’s Horizon 2020 research and innovation programme under the topic ‘’Personalizing Health and Care’’, grant agreement No 634886.

Disclosure of Interests

Linda Hartman: None declared, José Antonio P. da Silva: None declared, Frank Buttgereit Speakers bureau: Abbvie, AstraZeneca, Gruenenthal, Horizon Therapeutics, Mundipharma, Pfizer, Roche, Maurizio Cutolo: None declared, Daniela Opris-Belinski Speakers bureau: Abbvie, Pfizer, MSD, Novartis, Eli Lilly, Ewo Pharma, UCB, Zoltán Szekanecz: None declared, Pavol MASARYK: None declared, Marieke Voshaar: None declared, Martijn W. Heijmans: None declared, WIllem Lems Speakers bureau: Pfizer, Galapagos, Lilly, Amgen, UCB, Désirée van der Heijde: None declared, Maarten Boers Speakers bureau: BMS, Novartis, Pfizer

Effects of one-year tofacitinib therapy on bone metabolism in rheumatoid arthritis

Janus kinase (JAK) inhibitors are used to treat rheumatoid arthritis (RA). We assessed the effects of tofacitinib on bone density and bone markers in association with clinical and laboratory parameters in RA. Tofacitinib stabilized bone density and resulted in a positive balance of bone turnover.

INTRODUCTION

Janus kinase (JAK) inhibitors emerged as new therapeutic options in rheumatoid arthritis (RA). We have little information on how it affects areal and volumetric bone mineral density (BMD) and bone turnover markers. The aim of this study was to assess the effects of 1-year tofacitinib therapy on bone metabolism in RA.

METHODS

Thirty RA patients with active disease were treated with either 5 mg bid or 10 mg bid tofacitinib for 12 months. We determined DAS28, CRP, IgM rheumatoid factor (RF), and anti-cyclic citrullinated peptide (CCP) levels, as well as serum levels of sclerostin, osteocalcin (OC), P1NP, DKK-1, OPG, RANKL, and 25-hydroxy-vitamin D3. Areal and volumetric BMD were assessed by DXA and peripheral quantitative CT (QCT), respectively.

RESULTS

Twenty-six patients (13 on each arm) completed the study. Tofacitinib was clinically effective by suppressing DAS28, CRP, and HAQ. This was accompanied by the attenuation of further bone loss. Tofacitinib therapy significantly increased OC, OPG, and vitamin D3, while decreased CTX levels (p < 0.05). Age and multiple bone markers (OC, CTX, P1NP, RANKL) inversely correlated with L2-4 and femoral neck BMD by DXA. CRP, DAS28, and RANKL inversely determined volumetric BMD by QCT. Age, CRP, anti-CCP, and DKK-1 influenced the effects of tofacitinib therapy on BMD changes.

CONCLUSIONS

One-year tofacitinib treatment stabilized BMD in RA patients and resulted in a positive balance of bone turnover as indicated by bone biomarkers. Further studies are needed to evaluate the potential beneficial effects of JAK inhibitors on inflammatory bone loss.

OP0074 A FRAMEWORK OF POTENTIAL INTERVENTIONS TO ACCELERATE GENDER-EQUITABLE CAREER ADVANCEMENT IN ACADEMIC RHEUMATOLOGY

Background:

A growing number of professional societies in clinical and medically related disciplines investigate evidence, make recommendations, and take action to advance gender equity. Evidence on women’s advancement and leadership in the context of the European Alliance of Associations for Rheumatology, EULAR, is limited [1].

Objectives:

The objective of the EULAR Task Force on Gender Equity in Academic Rheumatology was to establish the extent of the unmet need for support of female rheumatologists, health professionals and non-clinical scientists in academic rheumatology and develop a framework to address this through EULAR and Emerging EULAR Network (EMEUNET).

Methods:

Potential interventions to accelerate gender-equitable career advancement in academic rheumatology were gathered from a narrative review of the relevant literature, expert opinion of a multi-disciplinary Task Force (comprised of 23 members from 11 countries), data from the surveys of EULAR scientific member society leaders, EULAR and EMEUNET members, and EULAR Executive Committee members. These interventions were rated by Task Force members, who ranked each according to perceived priority on a five-point numeric scale from 1 = very low to 5 = very high.

Results:

A framework of 29 potential interventions was formulated, which covers six thematic areas, namely, EULAR policies, advocacy and communication, EULAR Congress and associated symposia, training courses, mentoring/peer support, and EULAR funding (Figure 1).

Figure 1.

A framework of potential interventions with the levels of priority, mean and standard deviation (SD)

Conclusion:

The framework provides structured interventions for accelerating gender-equitable career advancement in academic rheumatology.

References:

[1]Andreoli L, Ovseiko PV, Hassan N, et al. Gender equity in clinical practice, research and training: Where do we stand in rheumatology? Joint Bone Spine 2019;86(6):669-72.

Acknowledgements:

The task force is grateful to EULAR for funding this activity under project number EPI 024.

Disclosure of Interests:

None declared

AB0160 HIGH NUMBER OF CONCOMITANT MEDICATIONS AND COMORBIDITIES AT BASELINE IN THE GLUCOCORTICOID LOW-DOSE OUTCOME IN RHEUMATOID ARTHRITIS (GLORIA) STUDY: AN OLDER POPULATION WITH RHEUMATOID ARTHRITIS

Background:

Treatment with low-dose glucocorticoids (GCs) (≤7.5 mg prednisolone) in combination with standard care is highly effective in rheumatoid arthritis (RA), but despite 70 years of clinical experience, evidence-based information on its balance of benefit and harm is incomplete. This leads to an ongoing debate, with under- and over-use of GCs as result. The GLORIA pragmatic trial was developed to assess harm, benefit and costs of low-dose GCs added to the standard treatment of older RA patients.

Objectives:

The objective of this abstract is to document the baseline status and frequency of comorbid conditions in the GLORIA study population. The results of the unblinded data will be submitted as late-breaking abstract.

Methods:

This double-blind, randomized, placebo-controlled, multicenter trial (1) was open for patients with RA according to the 1987 or 2010 (2) criteria, age ≥65 years, and disease activity score of 28 joints (DAS28) of ≥2.6. Patients were recruited from rheumatology clinics in Germany, Hungary, Italy, The Netherlands, Portugal, Romania and Slovakia. Eligible patients were randomized to two years of treatment with daily 5 mg prednisolone or matching placebo. All other medication was allowed, except for GCs. The presented data are blinded because the database is not closed yet.

Results:

The population consists of 451 patients with mean disease duration 10.6 (Q1-Q3: 3-15) years. The majority (70%) is female, mean age is 72.5 (Q1-Q3: 68-76, range: 65-88) years, 66% were positive for rheumatoid factor and 56% for ACPA. Patients had a mean of 4.3 (SD 2.8) comorbidities besides RA (3.4 active) and therefore used multiple concomitant medications (3.9 (SD 3.4)) (Table 1). The most common comorbidities (provisional data of 161 patients with complete coding) in this older population are: vascular disorders (58%), musculoskeletal and connective tissue disorders (57%) and a history of surgical and medical procedures (45%). Patients were most frequently on beta blocking agents (22%, mainly metoprolol) and HMG CoA reductase inhibitors (20%, mainly simvastatin). Most patients also have an extensive history of anti-rheumatic treatment. At the start of the trial most patients (82%) were on cDMARD treatment; 15% were on bDMARDs/tsDMARDs. Almost half of the patients previously had been treated with GCs, with a mean duration of 3.4 years and a mean last dose of 4.6 mg/day.

Conclusion:

The baseline data shows that we have an older study population who have relatively many other comorbidities next to RA and who are almost all treated with multiple concomitant medications in addition to the study medication. Therefore, we expect to report a high adverse event rate. Research among older patients is urgently needed, but the frailty of this population as represented by the multiple comorbidities and concomitant medications have to be taken into account in the analyses and interpretation of the results.

References:

[1]Hartman L, Rasch LA, Klausch T, Bijlsma HWJ, Christensen R, Smulders YM, et al. Harm, benefit and costs associated with low-dose glucocorticoids added to the treatment strategies for rheumatoid arthritis in elderly patients (GLORIA trial): study protocol for a randomised controlled trial. Trials. 2018;19:67.

[2]Aletaha D, Neogi T, Silman AJ, Funovits J, Felson DT, Bingham CO, et al. 2010 Rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Arthritis Rheum. 2010;62:2569-81.

Table 1.

Comorbidities and concomitant medications at baseline in the GLORIA trial.

MeanSDRangeComorbidities 4.32.8 0-15 Active 3.4 Past 1.9Concomitant medications (count) 3.93.4 0-15 Beta blocking agents (%)22 HMG CoA reductase inhibitors (%)20 Platelet aggregation inhibitors (%)16 ACE inhibitors (%)12 Angiotensin II antagonists (%)11DAS28 4.521.05DAS28CRP 4.060.97HAQ (0-3) 1.20.7RA treatmentCurrent (%)Previous (%) cDMARD8492 bDMARD/tsDMARD1522 NSAID5129 Glucocorticoids 049

Acknowledgements:

The GLORIA project is funded by the European Union’s Horizon 2020 research and innovation programme under the topic ‘’Personalizing Health and Care’’, grant agreement No 634886.

Disclosure of Interests:

None declared

POS0222 PREDICTORS OF RESPONSE: BASELINE CHARACTERISTICS AND EARLY TREATMENT RESPONSES ASSOCIATED WITH ACHIEVEMENT OF REMISSION AND LOW DISEASE ACTIVITY AMONG UPADACITINIB-TREATED PATIENTS WITH RHEUMATOID ARTHRITIS

Background:

Upadacitinib (UPA) 15 mg once daily (QD) has demonstrated efficacy in phase 3 studies of patients with rheumatoid arthritis (RA).1–4 Early prediction of response to treatment with UPA could help to optimize therapy.

Objectives:

To identify baseline (BL) characteristics or Week (Wk) 12 disease activity measures that may predict the achievement of remission (REM) or low disease activity (LDA) at 6 months in patients with RA receiving UPA 15 mg.

Methods:

This ad hoc analysis included patients who were randomized to UPA 15 mg QD, as monotherapy in methotrexate (MTX)-naïve patients (SELECT-EARLY) or in combination with conventional synthetic disease-modifying antirheumatic drugs (csDMARDs), in patients with an inadequate response (IR) to MTX (SELECT-COMPARE) or ≥1 tumor necrosis factor inhibitors (TNFis) (SELECT-BEYOND and SELECT-CHOICE). The association of BL characteristics (including age, disease duration, prior/concomitant treatments, C-reactive protein [CRP], seropositivity, and disease activity) and Wk 12 disease activity parameters with the achievement of Clinical Disease Activity Index (CDAI) REM (≤2.8) or LDA (≤10) at Wk 24 (or Wk 26 in SELECT-COMPARE) was assessed by concordance statistics (C-statistics), or area under the receiver operator characteristic curve. C-index values and 95% confidence intervals were calculated by fitting a univariate logistic regression model for: demographic and BL characteristics, Wk 12 disease activity measures, and change from BL at Wk 12 in disease activity measures. A multivariate logistic regression with stepwise model selection was also performed. The proportion of patients achieving Wk 24/26 CDAI REM/LDA was stratified by ≥50% improvement from BL in swollen and/or tender joint count in 66/68 joints (SJC66/TJC68).

Results:

A total of 1377 patients were included in the analysis. Across the 4 studies, CDAI REM and LDA were achieved in 11.0–28.4% and 50.0–58.6% of patients, respectively (Table 1). BL demographics and disease characteristics were weakly predictive (C-index <0.70) of Wk 24/26 CDAI REM (C-index 0.49–0.69) or LDA (C-index 0.47–0.65), with the exception of BL Health Assessment Questionnaire-Disability Index in SELECT-BEYOND, which was moderately predictive of CDAI REM (C-index 0.73). Changes from BL in disease activity measures at Wk 12 were weakly or moderately predictive of Wk 24/26 CDAI REM (Figure 1) or LDA. CDAI value at Wk 12 was strongly predictive (C-index >0.80) of Wk 24/26 CDAI REM or LDA. Disease Activity Score in 28 joints using CRP and pain at Wk 12 were strongly predictive of Wk 24/26 CDAI REM (except in SELECT-CHOICE). Physician’s global assessment at Wk 12 was the only common predictor in the multivariate regression models for CDAI REM/LDA at Wk 24/26 across the 4 studies. A greater proportion of patients achieving ≥50% improvement in SJC66 and TJC68 at Wk 12 achieved CDAI REM (16.5–37.8% vs 0–9.4%) or LDA (66.0–72.8% vs 20.9–35.7%) at Wk 24/26 than those who did not.

Table 1.

Achievement of CDAI LDA and REM at Wk 24/26a

SELECT-EARLYSELECT-COMPARESELECT-BEYONDSELECT-CHOICEPatient populationMTX-naïveMTX-IRTNFi-IRTNFi-IRTreatmentUPA 15 mg monotherapy (n=317)UPA 15 mg + MTX(n=651)UPA 15 mg + csDMARD(n=146)UPA 15 mg + csDMARD(n=263)Efficacy at Wk 24/26a, n (%)CDAI REM (≤2.8)90 (28.4)150 (23.0)16 (11.0)60 (22.8)CDAI LDA (≤10)178 (56.2)343 (52.7)73 (50.0)154 (58.6)

a Wk 26 for SELECT-COMPARE only

Conclusion:

BL characteristics did not strongly predict response to UPA, but composite disease activity scores at Wk 12 predicted Wk 24/26 REM/LDA with UPA 15 mg QD across MTX-naïve, MTX-IR, and TNFi-IR patients. ≥50% improvement in SJC/TJC at Wk 12 was also associated with Wk 24/26 REM/LDA.

References:

[1]van Vollenhoven R, et al. Arthritis Rheumatol 2020;72:1607–20; 2. Genovese MC, et al. Lancet 2018;391:2513–24; 3. Fleischmann R, et al. Arthritis Rheumatol 2019;71:1788–800; 4. Rubbert-Roth A, et al. N Engl J Med 2020;383:1511–21.

Acknowledgements:

AbbVie funded this study; contributed to its design; participated in data collection, analysis, and interpretation of the data; and participated in the writing, review, and approval of the abstract. No honoraria or payments were made for authorship. Medical writing support was provided by Laura Chalmers, PhD, of 2 the Nth (Cheshire, UK), and was funded by AbbVie.

Disclosure of Interests:

Arthur Kavanaugh Consultant of: Janssen, Grant/research support from: Janssen, Zoltán Szekanecz: None declared, Edward C. Keystone Speakers bureau: Abbott, Amgen, AstraZeneca, Biotest, Bristol-Myers Squibb, Eli Lilly, Genentech, Janssen, MSD, Novartis, Pfizer, Roche, Sanofi, and UCB, Consultant of: Abbott, Amgen, AstraZeneca, Biotest, Bristol-Myers Squibb, Eli Lilly, Genentech, Janssen, MSD, Novartis, Pfizer, Roche, Sanofi, and UCB, Grant/research support from: Abbott, Amgen, AstraZeneca, Biotest, Bristol-Myers Squibb, Eli Lilly, Genentech, Janssen, MSD, Novartis, Pfizer, Roche, Sanofi, and UCB, Andrea Rubbert-Roth Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Chugai, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and Sanofi, Stephen Hall Grant/research support from: Pfizer, Ricardo Xavier: None declared, Joaquim Polido-Pereira: None declared, In-Ho Song Shareholder of: May own stock or options in AbbVie, Employee of: AbbVie, Naomi Martin Shareholder of: May own stock or options in AbbVie, Employee of: AbbVie, Yanna Song Shareholder of: May own stock or options in AbbVie, Employee of: AbbVie, Samuel Anyanwu Shareholder of: May own stock or options in AbbVie, Employee of: AbbVie, Peter Nash Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Gilead, Janssen, MSD, Novartis, Pfizer, Roche, Sanofi, and UCB.

POS0390 SIMULTANEOUS ASSESSMENT OF JOINT AND VASCULAR INFLAMMATION BY PET-CT IN TOFACITINIB-TREATED PATIENTS WITH RHEUMATOID ARTHRITIS: A PROSPECTIVE STUDY

Background:

Rheumatoid arthritis (RA) has bene associated with atherosclerosis and cardiovascular (CV) disease. 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18FDG-PET/CT) is suitable to detect synovial and vascular inflammation. Tofacitinib has been used to effectively treat RA.

Objectives:

We wished to assess the effects of tofacitinib treatment on synovitis and vascular inflammation simultaneously by 18FDG-PET/CT.

Methods:

Thirty RA patients with active disease were treated with either 5 mg bid or 10 mg bid tofacitinib and evaluated at baseline and after 6 and 12 months. We determined DAS28, CRP, IgM rheumatoid factor (RF) and anti-cyclic citrullinated peptide (aCCP) levels. All patients underwent 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) in order to determine vascular and synovial inflammation in five aortic segments and five articular regions, respectively. In the joints, mean (SUVmean) and maximum standard uptake values (SUVmax), while in the aorta, mean (TBRmean) and maximum target-to-background ratios (TBRmax) were determined. Carotid intima-media thickness (IMT), arterial stiffness (PWV) and endothelial dysfunction (FMD) were determined by ultrasound.

Results:

One-year tofacitinib treatment significantly attenuated vascular and synovial inflammation as visualized by PET/CT. Articular SUVmean (p=0.010), SUVmax (p=0.001), as well as aorta TBRmax (p<0.001) significantly decreased over time. Synovial inflammation as determined by PET/CT variably and positively associated with aCCP, RF, CRP, ApoB, lipoprotein A (LpA), IMT and PWV. Vascular inflammation (TBRmax) inversely correlated with HAQ and positively with ESR, ApoA, and PWV. Uni- and multivariable analyses suggested that articular SUV values were independently associated with CRP, ApoB, LpA, IMT and PWV, while aortic TBRmax was determined by HAQ and PWV.

Conclusion:

18F-PET/CT is suitable to simultaneously assess synovial and vascular inflammation in RA. One-year tofacitinib treatment dampened inflammation. PET/CT changes were associated with markers of systemic inflammation, atherogenic lipids, carotid atherosclerosis and arterial stiffness.

References:

[1]Gotthardt M, Bleeker-Rovers CP, Boerman OC, Oyen WJ. Imaging of inflammation by PET, conventional scintigraphy, and other imaging techniques. J Nucl Med. 2010;51(12):1937-49.

[2]Bucerius J, Hyafil F, Verberne HJ, Slart RH, Lindner O, Sciagra R, et al. Position paper of the Cardiovascular Committee of the European Association of Nuclear Medicine (EANM) on PET imaging of atherosclerosis. Eur J Nucl Med Mol Imaging. 2016;43(4):780-92.

Acknowledgements:

This research was supported by the European Union and the State of Hungary and co-financed by the European Social Fund in the framework of TAMOP-4.2.4.A/2-11/1-2012-0001 ‘National Excellence Program’ (Z.S.); by the European Union grant GINOP-2.3.2-15-2016-00015 (G.P., G.T. and Z.S.) and by the Pfizer Investigator Initiated Research Grant no. WI188341 (Z.S.).

Disclosure of Interests:

Attila Hamar: None declared, Zsolt Hascsi: None declared, Anita Pusztai: None declared, Monika Czókolyová: None declared, Edit Végh: None declared, Zsófia Pethö: None declared, Katalin Gulyás: None declared, Boglárka Soós: None declared, György Kerekes: None declared, Éva Szekanecz: None declared, Katalin Hodosi: None declared, Sándor Szántó Speakers bureau: Abbvie, MSD, Novartis, Consultant of: Abbvie, MSD, Novartis, Gabriella Szücs Speakers bureau: Boehringer, Actelion, Roche, Consultant of: Boehringer, Actelion, Roche, Tamas Seres: None declared, Zoltán Szekanecz Speakers bureau: Abbvie, Pfizer, Roche, Novartis, Lilly, Sager, Janssen, Consultant of: Pfizer, Abbvie, Roche, Novartis, Grant/research support from: Pfizer, Szilvia Szamosi Speakers bureau: Roche

POS0043 PERIPHERAL QUANTITATIVE COMPUTED TOMOGRAPHY IN THE ASSESSMENT OF BONE MINERAL DENSITY IN ANTI-TNF-TREATED RHEUMATOID ARTHRITIS AND ANKYLOSING SPONDYLITIS PATIENTS

Background:

Rheumatoid arthritis (RA) and ankylosing spondylitis (AS) have been associated with osteoporosis. There have been very few data on the use of peripheral quantitative computed tomography (QCT) in anti-TNF-treated patients.

Objectives:

We wished to assess volumetric bone mineral density (BMD) by forearm QCT in conjunction with dual-energy X-ray absorptiometry (DXA) and bone biomarkers in RA and AS.

Methods:

Forty RA and AS patients treated with etanercept (ETN) or certolizumab pegol (CZP) were included in a 12-month follow-up study. Peripheral QCT and DXA BMD were determined. Bone biomarkers, such as PTH, osteocalcin, RANKL, 25-hydroxyvitamin D (VITD), P1NP, CTX, sclerostin, DKK-1 and cathepsin K (CATHK) were assessed by ELISA.

Results:

There was no further bone loss during anti-TNF treatment. Volumetric and areal BMD showed significant correlations with each other (p<0.05). Total QCT BMD after 12 months was inversely determined by disease activity at baseline in the full cohort (p=0.030). Cortical BMD was negatively determined by baseline disease activity (p=0.005) and CATHK (p=0.025). In RA, VITD-0 determined QTRABBMD-12 (p=0.005). In the full cohort, the one-year change in QTRABBMD was related to TNF inhibition together with higher VITD-0 (p=0.031). Therapy and lower CATHK determined QCORTBMD changes (p=0.006). In RA, treatment together with VITD-0 (p<0.01) or CATHK-0 (p=0.002), while in AS, treatment together with RANKL-0 (p<0.05) determined QCT BMD changes.

Conclusion:

QCT confirmed that biologics may attenuate bone loss. Disease activity, CATHK, RANKL and VITD may predict the effects of anti-TNF treatment on volumetric BMD changes. There may be differences between RA and AS in this respect.

Acknowledgements:

This research was supported by Hungarian National Scientific Research Fund (OTKA) grant No. K 105073 (H.P.B. and Z.S.); by the European Union and the State of Hungary and co-financed by the European Social Fund in the framework of TAMOP-4.2.4.A/2-11/1-2012-0001 ‘National Excellence Program ’(Z.S.); by the European Union grant GINOP-2.3.2-15-2016-00050 (Z.S.); and by the Pfizer Investigator Initiated Research Grants no. WS1695414 and WS1695450 (Z.S.).

Disclosure of Interests:

Balázs Juhász: None declared, Katalin Gulyás: None declared, Ágnes Horváth: None declared, Edit Végh: None declared, Anita Pusztai: None declared, Agnes Szentpetery: None declared, Zsófia Pethö: None declared, Nóra Bodnár: None declared, Attila Hamar: None declared, Levente Bodoki: None declared, Harjit Pal Bhattoa: None declared, Éva Szekanecz: None declared, Katalin Hodosi: None declared, Andrea Domjan: None declared, Szilvia Szamosi Speakers bureau: Roche, Csaba Horváth: None declared, Sándor Szántó Speakers bureau: Abbvie, MSD, Novartis, Consultant of: Abbvie, Novartis, Gabriella Szücs Speakers bureau: Roche, Boehringer, Actelion, Sager, Consultant of: Actelion, Boehringer, Hennie Raterman: None declared, WIllem Lems Speakers bureau: Pfizer, Amgen, Lilly, UCB, Galapagos, Consultant of: Pfizer, Amgen, Lilly, UCB, Galapagos, Oliver FitzGerald Speakers bureau: AbbVie, Janssen, Pfizer, Consultant of: BMS, Celgene, Eli Lilly, Janssen, Pfizer, Grant/research support from: AbbVie, BMS, Eli Lilly, Novartis, Pfizer, Zoltán Szekanecz Speakers bureau: Pfizer, Roche, Abbvie, Novartis, Lilly, Sanofi, Consultant of: Pfizer, Abbvie, Novartis, Grant/research support from: Pfizer, UCB.

POS0383 EFFECTS OF TOFACITINIB THERAPY ON ARGININE AND METHIONINE METABOLITES IN ASSOCIATION WITH VASCULAR PATHOPHYSIOLOGY IN RHEUMATOID ARTHRITIS: A METABOLOMIC APPROACH

Background:

Rheumatoid arthritis (RA) has been associated with increased cardiovascular (CV) risk and metabolic changes.

Objectives:

We wished to determine how the Janus kinase (JAK) inhibitor tofacitinib influences vascular pathophysiology and metabolites of the arginine and methionine-homocysteine pathways.

Methods:

Thirty RA patients with active disease were treated with either 5 mg bid or 10 mg bid tofacitinib and evaluated at baseline and after 6 and 12 months. We determined DAS28, CRP, IgM rheumatoid factor (RF) and anti-cyclic citrullinated peptide (aCCP) levels. We assessed brachial artery flow-mediated vasodilation (FMD), carotid intima-media thickness (IMT) and pulse-wave velocity (PWV) by ultrasound. We also determined plasma L-arginine, L-citrulline, L-ornithine, inducible nitric oxide synthase (iNOS), asymmetric (ADMA) and symmetric dimethylarginine (SDMA), L-N-monomethyl-arginine (L-NMMA), cysteine, homocysteine, and methionine levels.

Results:

Twenty-six patients completed the study. Tofacitinib treatment maintained FMD and PWV. Ten mg bid tofacitinib significantly increased L-arginine, L-ornithine, iNOS and methionine levels after 12 months. Tofacitinib transiently increased L-citrulline and L-NMMA and decreased homocysteine levels after 12 months. Based on L-citrulline, L-ornithine, ADMA and SDMA levels, L-arginine remained highly available for endothelial NO production. Multivariate analysis indicated variable correlations of L-arginine, L-citrulline, ADMA, L-NMMA, homocysteine and methionine with DAS28, CRP, ESR and RF but not with aCCP. Regarding vascular pathophysiology, only PWV and methionine correlated with each other after 12 months.

Conclusion:

Tofacitinib suppressed systemic inflammation in RA yielding stabilization of vascular function. It may exert CV protective effects in RA, at least in part, by shifting L-arginine metabolism to high arginine availability and decreasing homocysteine levels.

Acknowledgements:

This research was supported by the European Union and the State of Hungary and co-financed by the European Social Fund in the framework of TAMOP-4.2.4.A/2-11/1-2012-0001 ‘National Excellence Program ’(Z.S.); by the European Union grant GINOP-2.3.2-15-2016-00015 (Z.S.) and by the WI188341 investigator-initiated research (IIR) grant obtained from Pfizer US (Z.S.).

Disclosure of Interests:

Boglárka Soós: None declared, Attila Hamar: None declared, Anita Pusztai: None declared, Monika Czókolyová: None declared, Edit Végh: None declared, Szilvia Szamosi Speakers bureau: Roche, Zsófia Pethö: None declared, Katalin Gulyás: None declared, György Kerekes: None declared, Éva Szekanecz: None declared, Sándor Szántó Speakers bureau: Abbvie, MSD, Novartis, Consultant of: Abbvie, Novartis, Gabriella Szücs Speakers bureau: Actelion, Roche, Sager, Boehringer, Consultant of: Boehringer, Actelion, Sager, Uwe Christians: None declared, Jelena Klawitter: None declared, Tamas Seres: None declared, Zoltán Szekanecz Speakers bureau: Pfizer, Abbvie, Roche, Lilly, Novartis, Boehringer, Consultant of: Pfizer, Abbvie, Novartis, Grant/research support from: Pfizer

THU0579 “EVOLVING THE MANAGEMENT OF RA” PROGRAMME: EDUCATIONAL TOOLS TO SUPPORT DAILY PRACTICE

Background:

The eRA (evolving the management of RA) programme was initiated in Europe to provide practical educational tools that address unmet needs in the management of rheumatoid arthritis (RA). Several eRA tools – covering early access to care, management of comorbidities, treat-to-target strategies, and patient empowerment – are available to the rheumatology community. Through ongoing activities, the eRA Steering Committee (SC) identified a need for tools on non-pharmacological management of RA.

Objectives:

To improve accessibility to eRA tools for rheumatology professionals; to review the evidence base of non-pharmacological interventions to create new eRA resources that may support management decisions.

Methods:

A web platform providing information on eRA programme and tools was developed in 2019. The platform collects survey-based metrics to quantify perception of eRA and use of eRA tools in clinical practice. Platform and tools are translated to further support access and use across Europe.

To address unmet needs in non-pharmacological patient management, the eRA SC reviewed the core literature on agreed priority interventions, including physical activity, diet, patient education and self-management, psychosocial interventions, occupational therapy and orthotics, hand exercises, and hydrotherapy/balneotherapy. Available evidence for each intervention was assessed and graded according to the Oxford Centre for Evidence-based Medicine Levels of Evidence.

Results:

The eRA web platform is now live in 3 countries (www.evolvingthemanagementofRA.com), hosting translated copies of the eRA tools, with additional countries launching throughout 2020.

From a review of core literature on non-pharmacological interventions, the eRA SC determined that strong evidence exists to support use of physical activity, patient education and self-management, psychosocial interventions, and occupational therapy and orthotics. Evidence was lacking or conflicting for diet and nutrition, hand exercises, and balneotherapy/hydrotherapy. A set of educational slides was produced by the eRA SC to summarise the evidence (Fig. 1) and provide top-line guidance on use of interventions in practice that should engage relevant members of the multi-disciplinary team. These slides are available through eRA dissemination activities.

Conclusion:

The eRA programme content is now freely available to health care professionals in several countries on a web platform, supported by translations of the eRA tools. An additional slide set on non-pharmacological management serves to further increase the practical guidance of this programme’s educational offering.

Acknowledgments:

The eRA programme is funded by Sanofi Genzyme. Programme direction and content creation are driven by an independent Steering Committee

Disclosure of Interests:

Gerd Rüdiger Burmester Consultant of: AbbVie Inc, Eli Lilly, Gilead, Janssen, Merck, Roche, Pfizer, and UCB Pharma, Speakers bureau: AbbVie Inc, Eli Lilly, Gilead, Janssen, Merck, Roche, Pfizer, and UCB Pharma, Jose-Maria Alvaro-Gracia Grant/research support from: Abbvie, Elli-Lilly, MSD, Novartis, Pfizer, Consultant of: Abbvie, BMS, Janssen-Cilag, Elli-Lilly, MSD, Novartis, Pfizer, Sanofi, Tigenix, Roche, UCB, Paid instructor for: Elli-Lilly, Pfizer, Roche, Speakers bureau: Abbvie, BMS, Janssen-Cilag, Elli-Lilly, Gedeon Richter, MSD, Novartis, Pfizer, Sanofi, Tigenix, Roche, UCB, Neil Betteridge Consultant of: Amgen, Eli Lilly and Company, Grunenthal, GSK, Sanofi Genzyme, Jaime Calvo Grant/research support from: Lilly, UCB, Consultant of: Abbvie, Jansen, Celgene, Bernard Combe Grant/research support from: Novartis, Pfizer, Roche-Chugai, Consultant of: AbbVie; Gilead Sciences, Inc.; Janssen; Eli Lilly and Company; Pfizer; Roche-Chugai; Sanofi, Speakers bureau: Bristol-Myers Squibb; Gilead Sciences, Inc.; Eli Lilly and Company; Merck Sharp & Dohme; Pfizer; Roche-Chugai; UCB, Patrick Durez Speakers bureau: AbbVie, Bristol-Myers Squibb, Celltrion, Eli Lilly, Pfizer, Sanofi, Ricardo J. O. Ferreira Grant/research support from: Abbvie, Consultant of: Sanofi Genzyme, Amgen, MSD, Paid instructor for: UCB, Bruno Fautrel Grant/research support from: AbbVie, Lilly, MSD, Pfizer, Consultant of: AbbVie, Biogen, BMS, Boehringer Ingelheim, Celgene, Lilly, Janssen, Medac MSD France, Nordic Pharma, Novartis, Pfizer, Roche, Sanofi Aventis, SOBI and UCB, Annamaria Iagnocco Grant/research support from: Abbvie, MSD and Alfasigma, Consultant of: AbbVie, Abiogen, Alfasigma, Biogen, BMS, Celgene, Eli-Lilly, Janssen, MSD, Novartis, Sanofi and Sanofi Genzyme, Speakers bureau: AbbVie, Alfasigma, BMS, Eli-Lilly, Janssen, MSD, Novartis, Sanofi, Carlomaurizio Montecucco: None declared, Mikkel Ǿstergaard Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Merck, and Novartis, Consultant of: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Sofia Ramiro Grant/research support from: MSD, Consultant of: Abbvie, Lilly, Novartis, Sanofi Genzyme, Speakers bureau: Lilly, MSD, Novartis, Andrea Rubbert-Roth Consultant of: Abbvie, BMS, Chugai, Pfizer, Roche, Janssen, Lilly, Sanofi, Amgen, Novartis, Tanja Stamm Grant/research support from: AbbVie, Roche, Consultant of: AbbVie, Sanofi Genzyme, Speakers bureau: AbbVie, Roche, Sanofi, Zoltán Szekanecz Grant/research support from: Pfizer, UCB, Consultant of: Sanofi, MSD, Abbvie, Pfizer, Roche, Novertis, Lilly, Gedeon Richter, Amgen, Peter C. Taylor Grant/research support from: Celgene, Eli Lilly and Company, Galapagos, and Gilead, Consultant of: AbbVie, Biogen, Eli Lilly and Company, Fresenius, Galapagos, Gilead, GlaxoSmithKline, Janssen, Nordic Pharma, Pfizer Roche, and UCB, Mart van de Laar Consultant of: Sanofi Genzyme, Speakers bureau: Sanofi Genzyme

FRI0373 ASSOCIATIONS OF VASCULAR PATHOPHYSIOLOGY AND BONE METABOLISM IN ANTI-TNF- TREATED RHEUMATOID ARTHRITIS AND ANKYLOSING SPONDYLITIS PATIENTS

Background:

Cardiovascular (CV) disease and osteoporosis (OP) have become increasing challenges in the ageing population, even more in patients with inflammatory rheumatic diseases, such as rheumatoid arthritis (RA) and spondyloarthropathies. Both RA and ankylosing spondylitis (AS) have been associated with generalized and localized bone loss, accelerated atherosclerosis, increased CV morbidity and mortality.

Objectives:

Bone and vascular biomarkers and parameters along with the effect of one-year anti-TNF therapy on these markers were assessed in order to determine correlations between vascular pathophysiology and bone metabolism in RA and AS.

Methods:

Fifty-three patients including 36 RA patients treated with etanercept (ETN) or certolizumab pegol (CZP) and 17 AS patients treated with ETN were included in a 12-month follow-up study. Bone and vascular markers were assessed by ELISA. Bone density was assessed by DXA and quantitative CT (QCT). Flow-mediated vasodilation (FMD), common carotid intima-media thickness (ccIMT) and pulse-wave velocity (PWV) were assessed by ultrasound. The effects of vascular markers on bone and bone effects on vasculature undergone statistical analysis.

Results:

Serum levels of vascular endothelial growth factor (VEGF), PDGF-BB, angiopoietin 2 (Ang2) and cathepsin K (CathK) decreased, procollagen type 1 N-propeptide (P1NP) and sclerostin (SOST) levels increased, soluble receptor activator nuclear kappa B ligand (sRANKL) and osteoprotegerin (OPG) levels showed no differences. When bone and vascular markers were correlated with each other, at baseline, OPG correlated with Ang2 and adiponectin. SOST correlated positively with ccIMT. DXA L2-4 BMD, DXA L1 BMD and DXA femoral neck (FN) BMD correlated with FMD and CRP. QCT trabecular BMD correlated with ccIMT and PON1. According to the univariate analysis, FMD correlated with OPG, ccIMT correlated with SOST and QCT trabecular BMD. Ang1, Ang2 and PDGF-BB showed correlation with Dickkopf-1 (DKK1). Ang2 also correlated with OPG. As suggested by the multivariate analysis, OPG determined FMD; DKK1 was an independent predictor of Ang1, Ang2 and PDGF-BB. OPG was a predictor of Ang2.

Conclusion:

In our study of anti-TNF treated RA and AS patients, vascular and bone parameters showed numerous correlations. The therapy was clinically effective, it halted further bone loss over 1 year and reduced the production of angiogenic markers.

Acknowledgments:

This research was supported by an investigator-initiated research grant from Pfizer.

Disclosure of Interests:

Monika Czókolyová: None declared, Katalin Gulyás: None declared, Ágnes Horváth: None declared, Edit Végh: None declared, Zsófia Pethö: None declared, Szilvia Szamosi: None declared, Attila Hamar: None declared, Anita Pusztai: None declared, Emese Balogh: None declared, Nóra Bodnár: None declared, Levente Bodoki: None declared, Agnes Szentpetery: None declared, Harjit Pal Bhattoa: None declared, György Kerekes: None declared, Katalin Hodosi: None declared, Andrea Domjan: None declared, Sándor Szántó: None declared, Gabriella Szücs: None declared, Hennie Raterman Grant/research support from: UCB, Consultant of: Abbvie, Amgen, Bristol-Myers Sqibb, Cellgene and Sanofi Genzyme, WIllem Lems Grant/research support from: Pfizer, Consultant of: Lilly, Pfizer, Zoltán Szekanecz Grant/research support from: Pfizer, UCB, Consultant of: Sanofi, MSD, Abbvie, Pfizer, Roche, Novertis, Lilly, Gedeon Richter, Amgen

THU0181 SOLUBLE VASCULAR BIOMARKERS IN RHEUMATOID ARTHRITIS AND ANKYLOSING SPONDYLITIS: EFFECTS OF ONE-YEAR ANTI-TNF-Α THERAPY

Background:

Rheumatoid arthritis (RA) and ankylosing spondylitis (AS) have been associated with inflammatory atherosclerosis, increased cardiovascular (CV) morbidity and mortality. Numerous proteins may serve as biomarkers of inflammatory atherosclerosis. The treatment of arthritis by tumour necrosis factor α (TNF-α) inhibitors may decrease the serum concentrations of these biomarkers.

Objectives:

In this study we wished to determine circulating levels of oxidized LDL (oxLDL) - β2 glycoprotein I (β2GPI) complexes (AtherOx), anti-hsp60 antibodies, soluble urokinase plasminogen activator receptor (sUPAR) and N-terminal B-type natriuretic peptide (NT-proBNP) in sera of RA and AS patients. We also wished to assess the effects of anti-TNF treatment on these biomarkers.

Methods:

Altogether 53 arthritis patients including 36 RA patients treated with either etanercept (ETN) or certolizumab pegol (CZP) and 17 AS patients treated with ETN were included in a 12-month follow-up study.Circulating oxLDL/β2gpI complexes, anti-human Hsp60 immunoglobulin G (IgG) levels and BNP8-29fragment levels were assessed by ELISA. suPAR levels were assessed by suPARnostic®Quick Triage test. All laboratory assessments were performed at baseline, as well as 6 and 12 months after treatment initiation. Results were associated with DAS28, BASDAI, CRP.

Results:

In the mixed cohort of 53 arthritis patients, the circulating levels of oxLDL/β2gpI significantly decreased after 12 months of anti-TNF therapy (0.20±0.11 U/ml) compared to baseline (0.24±0.10 U/ml; p=0.014). There was a tendency of non-significant decrease after 6 months (0.23±0.14 U/ml) versus baseline. Anti-Hsp60 antibody levels did not change after 6 months (158.6±138.6 AU/ml) and 12 months (167.3±143.3 AU/ml) compared to baseline (170.3±140.4 AU/ml). Among the patients, 21.2% had low, 36.4% “observe”, 9.1% high and 33.3% critical suPAR levels. suPAR levels showed a tendency of non-significant decrease after 6 months (11.3±17.7 ng/ml) and 12 months (10.3±15.3 ng/ml) versus baseline (11.5±16.4 ng/ml). However, when the four serum level categories described above were considered, suPAR concentrations exerted significant decrease in RA patients with critical suPAR levels (>9ng/ml) (p=0.04). Similarly, BNP fragment levels showed only a tendency of decrease after 6 months (518.2±422.4 pmol/l) and 12 months (484.1±418.2 pmol/l) versus baseline (530.8±441.8 pmol/l). However, serum BNP levels at baseline and after 12 months were significantly increased in CCP positive compared to CCP negative RA patients (baseline: 670.6±323.0 versus 138.0±436.4 pmol/l; p=0.030 and 12 months: 652.9±283.2 versus 456.5±423.1 pmol/l; p=0.021), as well as in RF positive compared to RF negative RA patients (baseline: 680.6±381.6 versus 292.9±198.3 pmol/l; p=0.007 and 12 months: 668.9±346.5 versus 312.2±207.0 pmol/l; p=0.001).

Conclusion:

One-year anti-TNF therapy significantly decreased circulating oxLDL/β2gpI complex levels. This therapy also decreased suPAR levels in patients with critically high suPAR. BNP fragment levels were associated with seropositivity in RA. These vascular biomarkers may reflect the effects of TNF inhibition on endothelial activation.

Acknowledgments:

This study was sponsored by an investigator-initiated grant from Pfizer.

Disclosure of Interests:

Anita Pusztai: None declared, Attila Hamar: None declared, Ágnes Horváth: None declared, Edit Végh: None declared, Nóra Bodnár: None declared, György Kerekes: None declared, Monika Czókolyová: None declared, Szilvia Szamosi: None declared, Levente Bodoki: None declared, Katalin Hodosi: None declared, Andrea Domjan: None declared, Gábor Nagy: None declared, Ibolya Szöllösi: None declared, Luis Lopez Employee of: Retired employee of Corgenix Inc., Eiji Matsuura: None declared, Zoltán Prohászka: None declared, Sándor Szántó: None declared, Zoltán Nagy: None declared, Yehuda Shoenfeld: None declared, Zoltán Szekanecz Grant/research support from: Pfizer, UCB, Consultant of: Sanofi, MSD, Abbvie, Pfizer, Roche, Novertis, Lilly, Gedeon Richter, Amgen, Gabriella Szücs: None declared

THU0580 EULAR TASK FORCE ON GENDER EQUITY IN ACADEMIC RHEUMATOLOGY: PRELIMINARY SURVEY FINDINGS

Background:

Women represent an increasing proportion of the overall rheumatology workforce, but are underrepresented in academic rheumatology, especially in leadership roles [1].

Objectives:

The EULAR Task Force on Gender Equity in Academic Rheumatology has been convened to establish the extent of the unmet need for support of female rheumatologists, health professionals and non-clinical scientists in academic rheumatology and develop a framework to address this through EULAR and EMEUNET.

Methods:

To investigate gender equity in academic rheumatology, an anonymous web-based survey was targeted at the membership of EULAR and Emerging EULAR Network (EMEUNET) and their wider networks. The survey was developed based on a narrative literature review [1], best practice from The Association of Women in Rheumatology, a survey of task force members and face-to-face task force discussions. Personal experiences were explored and 24 potential interventions to aid career advancement were ranked. Statistics were descriptive with significance testing for male/female responses compared using chi-squared/t-tests. The level of significance was set at p<0.001.

Results:

A total of 301 respondents from 24 countries fully completed the survey. By profession, 290 (86.4%) were rheumatologists, 19 (6.3%) health professionals, and 22 (7.3%) non-clinical scientists. By gender, 217 (72.1%) were women, 83 (27.6%) men, and 1 (0.3%) third gender. By age, 203 (67.5%) were 40 or under. By ethnicity, 30 (10.0%) identified themselves as ethnic minority. A high proportion of respondents reported having experienced gender discrimination (47.2% total: 58.1% for women and 18.1% for men) and sexual harassment (26.2%: 31.8% and 10.8% respectively) (Figure 1). Chi-squared tests on the numbers on which these proportions were based showed statistically significant differences between women and men in having experienced gender discrimination (Χ2=36.959 (df=1), p <0.001) and sexual harassment (Χ2=12.633 (df=1), p <0.001). The highest-ranked interventions for career advancement regardless of respondents’ gender included: leadership skills training; speaking/presentation/communication skills training; information on training/career pathways; effective career planning training; support on grant writing applications; and high-impact scientific writing master-classes (Figure 2). Only 8 of 24 proposed interventions showed a significantly higher ranking (p<0.001) by female respondents and these typically related to promotion of female role models and gender-balance in committees, editorial boards and research funding (Figure 2).

Figure 1.

Perceived gender discrimination and sexual harassment, 301 responses

Figure 2.

Mean perceived utility of potential interventions for career advancement by gender and statistically significant gender differences (p<.001), 300 responses

Conclusion:

The results of the survey will inform the development of task force policy proposals for interventions to support career advancement among EULAR and EMEUNET members. The identified interventions have potential to support career advancement of all rheumatologists, health professionals and non-clinical scientists regardless of gender.

References:

[1]Andreoli L, Ovseiko PV, Hassan N, Kiltz U, van Mens L, Gossec L, et al. Gender equity in clinical practice, research and training: Where do we stand in rheumatology? Joint, Bone, Spine: Revue du Rhumatisme. 2019;86(6):669-672.

Acknowledgments:

We gratefully acknowledge the rheumatologists, health professionals and non-clinical scientists who responded to the survey.

Disclosure of Interests:

Pavel V Ovseiko: None declared, Laure Gossec Grant/research support from: Lilly, Mylan, Pfizer, Sandoz, Consultant of: AbbVie, Amgen, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Sandoz, Sanofi-Aventis, UCB, Laura Andreoli: None declared, Uta Kiltz Grant/research support from: AbbVie, Amgen, Biogen, Novartis, Pfizer, Consultant of: AbbVie, Biocad, Eli Lilly and Company, Grünenthal, Janssen, Novartis, Pfizer, UCB, Speakers bureau: AbbVie, MSD, Novartis, Pfizer, Roche, UCB, Leonieke van Mens: None declared, Neelam Hassan: None declared, Marike van der Leeden: None declared, Heidi J Siddle: None declared, Alessia Alunno: None declared, Iain McInnes Grant/research support from: Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Janssen, and UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Gilead, Janssen, Novartis, Pfizer, and UCB, Nemanja Damjanov Grant/research support from: from AbbVie, Pfizer, and Roche, Consultant of: AbbVie, Gedeon Richter, Merck, Novartis, Pfizer, and Roche, Speakers bureau: AbbVie, Gedeon Richter, Merck, Novartis, Pfizer, and Roche, Florence Apparailly: None declared, Caroline Ospelt Consultant of: Consultancy fees from Gilead Sciences., Irene van der Horst-Bruinsma Grant/research support from: AbbVie, Novartis, Eli Lilly, Bristol-Myers Squibb, MSD, Pfizer, UCB Pharma, Consultant of: AbbVie, Novartis, Eli Lilly, Bristol-Myers Squibb, MSD, Pfizer, UCB Pharma, Elena Nikiphorou: None declared, Katie Druce Speakers bureau: Pfizer and Lilly, Zoltán Szekanecz Grant/research support from: Pfizer, UCB, Consultant of: Sanofi, MSD, Abbvie, Pfizer, Roche, Novertis, Lilly, Gedeon Richter, Amgen, Alexandre Sepriano: None declared, Tadej Avcin: None declared, George Bertsias Grant/research support from: GSK, Consultant of: Novartis, Georg Schett Speakers bureau: AbbVie, BMS, Celgene, Janssen, Eli Lilly, Novartis, Roche and UCB, Anne Maree Keenan: None declared, Laura C Coates: None declared

SAT0471 EFFECTS OF ONE YEAR TOFACITINIB THERAPY ON BONE DENSITY AND BIOMARKERS OF BONE TURNOVER IN RHEUMATOID ARTHRITIS

Background:

Oral JAK inhibitor, tofacitinib appeared as a new therapeutic option, beside biological therapies, which has already proven its safety and effectivity in RA, but we lack of knowledge how it affects density of bone structures and bone turnover markers.

Objectives:

The aim of this study was to assess the effects of one-year tofacitinib therapy on bone metabolism in patients with RA.

Methods:

Altogether 30 RA patients with active disease were recruited and treated with tofacitinib in this 12-months follow-up study. Mean age of patients were 52.8±10.0 years, duration of rheumatoid arthritis were 7.7±5.0 years. Half of the patients haven’t received biological treatment prior tofacitinib therapy, other half of the patients switched to tofacitinib therapy after completing washout. 15 patients received 2x5mg and 15 patients received 2x10mg tofacitinib daily for 12 months. On both arms 2-2 patients have discontinued treatment and excluded from the study. Assessments were performed at baseline, month 6 and 12. Levels of CRP and IgM rheumatoid factor (RF) antibodies were measured by quantitaive nephelometry and levels of anti-CCP, sclerostin, osteocalcin (OC), P1NP were assesed by ELISA. Bone density was assesed by DXA (dual-energy X-ray absorptiometry, Lunar) and pQCT imaging techniques. Levels of DKK-1, OPG, RANKL were measured by multiplex microbead immunoassay (BioLegend LEGENDplex). In addition, disease activity (DAS28), age and disease duration were also measured. Correlations were determined by Spearman’s analysis. Univariate and multiple regression analysis using the stepwise method was applied to investigate independent associations between DXA measurements (dependent variables) and laboratory parameters (independent variables).

Results:

Tofacitinib significantly reduced DAS28 (p<0.001) and HAQ values (p=0.001), also level of CRP (p<0.001) and We (p=0.014). With respect to bone biomarkers we have experienced significant increase in levels of OC (p=0.013), OPG (p=0.006), sclerostin (p=0.026) and vitamin-D (p=0.017) at month 6, also in levels of OPG and vitamin-D (p=0.004, p=0.003) at month 12. We have found decrease in levels of CTX at month 6 (p=0.009) and 12 (p=0.003). When we examined the groups separately, we’ve found significant increase in levels of P1NP (p=0.027, p=0.005), OPG (p=0.005, p=0.002) and vitamin-D (p=0.001, p=0.004) at month 6 and 12, also in OC at month 6 (p=0.027) in Group A (2x5mg). In Group B (2x10mg) we’ve experienced a significant decrease in levels of phosphate and CTX at month 6 and 12 (p=0.012, p=0.021, and p=0.005, p=0.007).

Conclusion:

One year tofacitinib treatment effectively stabilized bone density in patients with rheumatoid arthritis, and led to the increase of bone turnover markers, which is beneficial for ossification in long term.

Acknowledgments:

This research was supported by an investigator-initiated research grant from Pfizer.

Disclosure of Interests:

Attila Hamar: None declared, Anita Pusztai: None declared, Edit Végh: None declared, Ágnes Horváth: None declared, Szilvia Szamosi: None declared, Zsófia Pethö: None declared, Sándor Szántó: None declared, Gabriella Szücs: None declared, Harjit Pal Bhattoa: None declared, Gábor Tajti: None declared, György Panyi: None declared, Katalin Hodosi: None declared, Zoltán Szekanecz Grant/research support from: Pfizer, UCB, Consultant of: Sanofi, MSD, Abbvie, Pfizer, Roche, Novertis, Lilly, Gedeon Richter, Amgen

Microthrombotic renal involvement in an SLE patient with concomitant catastrophic antiphospholipid syndrome: the beneficial effect of rituximab treatment

Antiphospholipid syndrome is characterized by multiple arterial and/or venous thrombotic events, recurrent fetal losses in the presence of antiphospholipid antibodies (aPL). Catastrophic antiphospholipid syndrome is a life-threatening, rare subset of antiphospholipid syndrome when the thrombotic events affect at least three organs, and clinical manifestations develop simultaneously or within a week. Diagnostically, small vessel occlusions can be detected by histopathology in the presence of aPL. Our case report describes an 18-year-old man who has been treated for antiphospholipid syndrome associated with systemic lupus erythematosus (SLE) since 2011. The clinical findings were dominated by recurrent deep vein thrombosis, and severe proteinuria caused by lupus nephritis, accompanied by mild serological and laboratory findings. The patient was hospitalized in March 2014 because of severe thrombocytopenia and infective diarrhoea. At this time the renal functions deteriorated rapidly. Simultaneously, left upper extremity paresis was observed; computed tomography showed ischaemic lesions in the territory of the middle cerebral artery. Abdominal discomfort and pain occurred. On computed tomography scan ischaemic lesions were seen in the spleen, the right kidney and the coeliac trunk. Laboratory and serological findings verified the presence of aPL and anti-DNA antibodies, anaemia and thrombocytopenia. Based on the above-mentioned clinical and laboratory findings, the diagnosis of catastrophic antiphospholipid syndrome was established. Anticoagulation, corticosteroids and plasma exchange treatment, as well as haemodiafiltration were initiated. Although the thrombotic cascade decelerated following these interventions, we could not see an improvement in the renal function. Rituximab treatment was started, leading to a significant improvement in renal function. After 5 weeks of treatment the patient was discharged from hospital.

Comparison of peripheral quantitative computed tomography forearm bone density versus DXA in rheumatoid arthritis patients and controls

Rheumatoid arthritis (RA) has been associated with osteoporosis. Quantitative computed tomography (QCT) is capable of assessing bone density and composition. We found lower bone density in RA compared to controls. Age and RA duration influenced bone density. QCT may be useful to assess bone metabolism in RA.

INTRODUCTION

RA is associated with generalized and periarticular osteoporosis. In addition to DXA that determines areal bone mineral density (BMD), peripheral QCT also detects volumetric BMD. QCT differentiates between total, trabecular, and cortical BMD. Here, we compared DXA and QCT in RA patients and healthy controls.

METHODS

BMD of 57 female RA patients and 32 age-matched healthy female controls were assessed by DXA. QCT of the forearm ultradistal region was also performed. Densitometry data were correlated with age, disease duration, disease activity, serum CRP, and anti-CCP levels.

RESULTS

Total bone density (310.4 ± 79.7 versus 354.0 ± 54.1 mg/cm³; p = 0.007) and attenuation (0.37 ± 0.05 versus 0.40 ± 0.03 1/cm; p = 0.001), trabecular density (157.6 ± 57.0 versus 193.8 ± 48.7 mg/cm³; p = 0.005) and attenuation (0.28 ± 0.03 versus 0.32 ± 0.04 1/cm; p < 0.0001), and cortical density (434.3 ± 115.8 versus 492.5 ± 64.0 mg/cm³; p = 0.006) and attenuation (0.44 ± 0.07 versus 0.47 ± 0.04 1/cm; p = 0.004) were significantly lower in RA. Both lumbar and femoral neck BMD, as well as T-scores, were significantly lower in RA versus controls (p < 0.001 in all cases). In RA, total and cortical QCT attenuation and density were associated with age, the presence of RA, and their combination. In contrast, trabecular density and attenuation were only affected by the presence of the disease but not by age. Also in RA, total trabecular and cortical density as determined by QCT significantly correlated with lumbar and/or femoral neck BMD as measured by DXA. Finally, anti-CCP seropositivity was associated with lower trabecular density and attenuation.

CONCLUSIONS

Both DXA and QCT may be suitable to study bone metabolism in RA. Areal BMD determined by DXA may correlate with volumetric bone density measured by QCT. Moreover, trabecular osteoporosis may be associated by the underlying autoimmune-inflammatory disease, while cortical osteoporosis may rather be age-related.

Lupus and Cardiovascular Disease: The Facts

Accelerated atherosclerosis leading to coronary artery disease (CAD) and other cardiac manifestations have increasing importance for the management and outcome of systemic lupus erythematosus (SLE). There is increased cardiovascular mortality in SLE. Several traditional and disease-related risk factors, as well as corticosteroids are involved in lupus-associated atherosclerosis and its clinical manifestations. Cardiovascular risk is even higher in lupus patients also having secondary antiphospholipid syndrome (APS) due to the additive effects of SLE- and APS-related risk factors. The primary and secondary prevention of atherosclerosis and CAD in these diseases includes drug treatment, such as the use of statins and aspirin, as well as lifestyle modifications. Apart from CAD, other cardiac manifestations may also be present in SLE patients. Among these conditions, pericarditis is the most common, however, myocarditis, endocarditis and valvular disease, conduction abnormalities, impairment of systolic and diastolic function, pulmonary or peripheral arterial hypertension and microcirculatory problems may also occur. Early diagnosis of SLE, active immunosuppressive treatment and close follow-up of lupus patients and prevention may help to minimize cardiovascular risk in these individuals.

EULAR recommendations for cardiovascular disease risk management in patients with rheumatoid arthritis and other forms of inflammatory joint disorders: 2015/2016 update

Patients with rheumatoid arthritis (RA) and other inflammatory joint disorders (IJD) have increased cardiovascular disease (CVD) risk compared with the general population. In 2009, the European League Against Rheumatism (EULAR) taskforce recommended screening, identification of CVD risk factors and CVD risk management largely based on expert opinion. In view of substantial new evidence, an update was conducted with the aim of producing CVD risk management recommendations for patients with IJD that now incorporates an increasing evidence base. A multidisciplinary steering committee (representing 13 European countries) comprised 26 members including patient representatives, rheumatologists, cardiologists, internists, epidemiologists, a health professional and fellows. Systematic literature searches were performed and evidence was categorised according to standard guidelines. The evidence was discussed and summarised by the experts in the course of a consensus finding and voting process. Three overarching principles were defined. First, there is a higher risk for CVD in patients with RA, and this may also apply to ankylosing spondylitis and psoriatic arthritis. Second, the rheumatologist is responsible for CVD risk management in patients with IJD. Third, the use of non-steroidal anti-inflammatory drugs and corticosteroids should be in accordance with treatment-specific recommendations from EULAR and Assessment of Spondyloarthritis International Society. Ten recommendations were defined, of which one is new and six were changed compared with the 2009 recommendations. Each designated an appropriate evidence support level. The present update extends on the evidence that CVD risk in the whole spectrum of IJD is increased. This underscores the need for CVD risk management in these patients. These recommendations are defined to provide assistance in CVD risk management in IJD, based on expert opinion and scientific evidence.

Antiphospholipid antibodies in acute coronary syndrome

Antiphospholipid (aPL) antibodies entailing anticardiolipin (aCL) and anti-β2 glycoprotein I (anti-β2 GPI) antibodies may be involved in a number of vascular diseases including coronary artery diseases (CAD) or stroke. Here we assessed the presence of aPL antibodies in acute coronary syndrome (ACS). The frequency of anti-β2 GPI antibodies was significantly higher (14.4%) in ACS in comparison to control healthy subjects (2%). In addition, serum concentrations of anti-β2 GPI antibodies were also increased in ACS. Anti-β2 GPI antibodies of the IgA isotype might be the most relevant for the onset and outcome of ACS. Regarding subclasses of ACS, anti-β2 GPI IgA antibodies were elevated in unstable angina (UA) and myocardial infarction with ST elevation (STEMI), but not in myocardial infarction without ST elevation (NSTEMI). The involvement of anti-β2 GPI antibodies in ACS was more pronounced in men than women, and in younger rather than older patients. Finally, anti-β2 GPI antibodies in ACS were associated with previous stroke, but not with hypertension or previous myocardial infarction. Thus, anti-β2 GPI antibodies may be involved in the thrombotic events underlying ACS.

Vitamin D status in men with psoriatic arthritis: a case-control study

We determined hypovitaminosis D prevalence in men with psoriatic arthritis. This is a cross-sectional, analyst blinded, age- and sex-matched, case-control study. Men with psoriatic arthritis have significantly lower 25-hydroxyvitamin D levels. Men with psoriatic arthritis are at increased odds of suffering from hypovitaminosis D.

INTRODUCTION

Skeletal manifestations as a result of abrupted bone metabolism may be predominant in psoriatic arthritis (PsA). Vitamin D plays a vital role in maintenance of skeletal health and is known to modulate the immune system in various autoimmune diseases including PsA. The aim of the present study was to determine the prevalence of hypovitaminosis D in a treatment naïve, de novo psoriatic arthritis male cohort in a cross-sectional, analyst blinded, age- and sex-matched, case-control study.

METHODS

25 hydroxyvitamin D (25OHD), parathyroid (PTH), osteocalcin (OC) and C-terminal telopeptides of type-I collagen (CTx) levels, and lumbar spine and femoral neck bone mineral density were compared between 53 PsA and controls.

RESULTS

The prevalence of hypovitaminosis D (25 hydroxyvitamin D (25OHD) levels <75 nmol/L) was 81 and 57 % in the PsA and control groups, respectively. Compared to the healthy controls, 25OHD (67.2 (12-137) nmol/L vs. 51.9 (15-95) nmol/L; p = 0.001) was significantly lower, and osteocalcin (13.6 (5-33) μg/L vs. 18.2 (6-35) μg/L; p = 0.003) and C-terminal telopeptides of type-I collagen (0.20 (0.01-0.71) μg/L vs. 0.28 (0.06-0.69) μg/L; p = 0.008) were significantly higher in the PsA group. A significant association was found between hypovitaminosis D and PsA; the odds for patients with PsA of having hypovitaminosis D was 3.297 (95 % confidence interval 1.372 to 7.922).

CONCLUSION

The results of this study suggest that men with PsA have significantly lower 25-hydroxyvitamin D levels, and furthermore, men with PsA are at statistically significant increased odds of suffering from hypovitaminosis D.