POS0891 IMPROVED SURVIVAL IN SYSTEMIC SCLEROSIS PATIENTS DURING LAST DECADE: CURRENT FINDINGS AND COMPARISON WITH DIFFERENT PREVIOUS ITALIAN COHORTS

Background:

Systemic Sclerosis (SSc) is a chronic rheumatic disease characterized by an autoimmune disorder with vasculopathy that leads to an excess in collagen and other extracellular matrix proteins deposition. This process results in progressive fibrotic and vascular damage of skin and visceral organs. According to observational studies conducted in last decades, mean survival of SSc patients had improved with significant changes in causes of death.

Objectives:

To assess the 10-years survival in a large Italian multicentre cohort of SSc patients in the last decade compared to previous periods published since the 1980s, and to identify features that can justify any change.

Methods:

We retrospectively analysed all medical records of our longitudinal SSc cohorts, fulfilling 1980 ARA and/or 2013 EULAR/ACR Classification Criteria, with a median (IQR) follow-up of 91.5 (51-120) months from 4 Scleroderma Units since January 2009. All clinical, laboratory and instrumental findings have been recorded and analysed. Survival rate was calculated with Kaplan-Meier curves and log-rank tests, and Cox proportional hazards models were used to identify any predictor. Then, observed SSc survival was compared to those previously published and to that expected in the general population, calculated using official data published on the website United Nation World Population Prospects (www.macrotrends.net/countries/ITA/italy/death-rate).

Results:

Of 912 SSc patients (91.6% female; mean (SD) age at first non-Raynaud symptom (RS) 51 (15.4) years; median (IQR) disease duration from non-RS 24 (0-84.7) months) diffuse cutaneous involvement was defined in 182 (20%) patients. Anti-centromere and anti-topoisomerase-I were detected in 390 (42.8%) and 302 (33.1%) patients, respectively, while 220 (24.1%) presented antibodies for other extractible nuclear antigens. Prevalent non-Raynaud manifestations were interstitial lung disease detected in 459 (50.3%), digital ulcers in 395 (43.3%) and oesophagopathy in 371 (40.7%) patients, respectively, while other gastrointestinal manifestations were reported in 234 (25.7%) patients. Chronic renal failure was observed in 61 (6.7%) patients and pulmonary arterial hypertension (PAH) was confirmed at right heart catheterization in 38 (4.2%) patients. Three hundred twenty-two (35.3%) patients received immunosuppressant, 215 (23.5%) assumed an endothelin receptor antagonist and/or a 5-phosphodiesterase inhibitor, and 72 (7.9%) were treated with a biologic agent. The global 10-years survival was 89.4%; female gender (HR 0.33, CI95% 0.17-0.67), diffuse cutaneous involvement (HR 2.14, CI95% 1.17-3.91), presence of pulmonary hypertension (HR 2.61, CI95%1.31-5.16) and older age at non-RS (HR 1.1, CI95% 1.06-1.12) affected survival. Furthermore, as compared to previous Italian studies, our cohort showed a significant improvement in rate (see Figure 1).

Conclusion:

Survival in SSc patients has improved in last 5 decades but still reduced compared to that expected in general population above all 5 years after diagnosis. Early diagnosis, with reduced renal involvement, along with better screening and innovative therapeutic strategies may explain these achievements.

Figure 1.

Ten-years survival in SSc patients since 2009 (left); comparison of survival across different Italian SSc cohorts (box: current analysis) (right).

References:

[1]Giordano M, et al. The Journal of Rheumatology. 1986; 13:911-916.

[2]Ferri C, et al. Medicine. 2002; 81:139-53.

[3]Vettori S, et al. Reumatismo. 2010; 62(3):202-209.

[4]Ferri C, et al. Autoimmun Rev. 2014; 13(10):1026-34.

Disclosure of Interests:

None declared

OP0220 SECULAR TRENDS IN BASELINE CHARACTERISTICS, TREATMENT RETENTION AND RESPONSE RATES IN 17453 BIONAÏVE PSORIATIC ARTHRITIS PATIENTS INITIATING TNFI – RESULTS FROM THE EUROSPA COLLABORATION

Background:

Knowledge of changes over time in baseline characteristics and tumor necrosis factor inhibitor (TNFi) response in bionaïve psoriatic arthritis (PsA) patients treated in routine care is limited.

Objectives:

To investigate secular trends in baseline characteristics and retention, remission and response rates in PsA patients initiating a first TNFi.

Methods:

Prospectively collected data on bionaïve PsA patients starting TNFi in routine care from 15 European countries were pooled. According to year of TNFi initiation, three groups were defined a priori based on bDMARD availability: Group A (1999–2008), Group B (2009–2014) and Group C (2015–2018).

Retention rates (Kaplan-Meier), crude and LUNDEX adjusted1 remission (Disease Activity Score (DAS28) <2.6, 28-joint Disease Activity index for PsA (DAPSA28) ≤4, Clinical Disease Activity Index (CDAI) ≤2.8) and ACR50 response rates were assessed at 6, 12 and 24 months. No statistical comparisons were made.

Results:

A total of 17453 PsA patients were included (4069, 7551 and 5833 in groups A, B and C).

Patients in group A were older and had longer disease duration compared to B and C. Retention rates at 6, 12 and 24 months were highest in group A (88%/77%/64%) but differed little between B (83%/69%/55%) and C (84%/70%/56%).

Baseline disease activity was higher in group A than in B and C (DAS28: 4.6/4.3/4.0, DAPSA28: 29.9/25.7/24.0, CDAI: 21.8/20.0/18.6), and this persisted at 6 and 12 months. Crude and LUNDEX adjusted remission rates at 6 and 12 months tended to be lowest in group A, although crude/LUNDEX adjusted ACR50 response rates at all time points were highest in group A. At 24 months, disease activity and remission rates were similar in the three groups (Table).

Table 1.

Secular trends in baseline characteristics, treatment retention, remission and response rates in European PsA patients initiating a 1st TNFi

Baseline characteristicsGroup A(1999–2008)Group B(2009–2014)Group C(2015–2018)Age, median (IQR)62 (54–72)58 (49–67)54 (45–62)Male, %514847Years since diagnosis, median (IQR)5 (2–10)3 (1–9)3 (1–8)Smokers, %161717DAS28, median (IQR)4.6 (3.7–5.3)4.3 (3.4–5.1)4.0 (3.2–4.8)DAPSA28, median (IQR)29.9 (19.3–41.8)25.7 (17.2–38.1)24.0 (16.1–35.5)CDAI, median (IQR)21.8 (14.0–31.1)20.0 (13.0–29.0)18.6 (12.7–26.1)TNFi drug, % (Adalimumab / Etanercept / Infliximab / Certolizumab / Golimumab)27 / 43 / 30 / 0 / 036 / 31 / 14 / 5 / 1421 / 40 / 21 / 8 / 10Follow up6 months12 months24 monthsGr AGr BGr CGr AGr BGr CGr AGr BGr CRetention rates, % (95% CI)88 (87–89)83 (82–84)84 (83–85)79 (78–80)72 (71–73)72 (71–73)68 (67–69)60 (59–61)60 (59–62)DAS28, median (IQR)2.7 (1.9–3.6)2.4 (1.7–3.4)2.3 (1.7–3.2)2.5 (1.8–3.4)2.2 (1.6–3.1)2.1 (1.6–2.9)2.1 (1.6–3.1)2.0 (1.6–2.9)1.9 (1.5–2.6)DAPSA28, median (IQR)10.6 (4.8–20.0)9.5 (3.9–18.3)8.7 (3.6–15.9)9.1 (4.1–17.8)7.7 (3.1–15.4)7.6 (2.9–14.4)6.7 (2.7–13.7)6.6 (2.7–13.5)5.9 (2.4–11.8)CDAI, median (IQR)7.8 (3.0–15.2)8.0 (3.0–15.0)6.4 (2.6–12.2)6.4 (2.5–13.0)6.2 (2.5–12.1)5.8 (2.2–11.4)5.0 (2.0–11.0)5.5 (2.0–11.2)5.0 (2.0–9.0)DAS28 remission, %, c/L47 / 4255 / 4661 / 5153 / 4362 / 4566 / 4864 / 4268 / 3775 / 41DAPSA28 remission, %, c/L22 / 1926 / 2228 / 2325 / 2031 / 2232 / 2336 / 2334 / 1938 / 21CDAI remission, %, c/L23 / 2123 / 1926 / 2227 / 2127 / 2029 / 2134 / 2231 / 1735 / 19ACR50 response, %, c/L26 / 2322 / 1824 / 2027 / 2223 / 1721 / 1523 / 1518 / 1014 / 8

Gr, Group; c/L, crude/LUNDEX.

Conclusion:

Over the past 20 years, patient age, disease duration and disease activity level at the start of the first TNFi in PsA patients have decreased. Furthermore, TNFi retention rates have decreased while remission rates have increased, especially remission rates within the first year of treatment. These findings may reflect a greater awareness of early diagnosis in PsA patients, a lowered threshold for initiating TNFi and the possibility for earlier switching in patients with inadequate treatment response.

References:

[1]Arthritis Rheum 2006; 54: 600-6.

Acknowledgements:

Novartis Pharma AG and IQVIA for supporting the EuroSpA Research Collaboration Network.

Disclosure of Interests:

Sara Nysom Christiansen Speakers bureau: BMS and GE, Grant/research support from: Novartis, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Simon Horskjær Rasmussen: None declared, Anne Gitte Loft Speakers bureau: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, UCB, Consultant of: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, UCB, Grant/research support from: Novartis, Johan K Wallman Consultant of: Celgene, Eli Lilly, Novartis, Florenzo Iannone Speakers bureau: Abbvie, MSD, Novartis, Pfizer and BMS, Brigitte Michelsen Consultant of: Novartis, Grant/research support from: Novartis, Michael J. Nissen Speakers bureau: Novartis, Eli Lilly, Celgene, and Pfizer, Consultant of: Novartis, Eli Lilly, Celgene, and Pfizer, Jakub Zavada: None declared, Maria Jose Santos Speakers bureau: AbbVie, Novartis, Pfizer, Manuel Pombo-Suarez: None declared, Kari Eklund: None declared, Matija Tomsic Speakers bureau: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Consultant of: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Björn Gudbjornsson Speakers bureau: Amgen and Novartis, İsmail Sari: None declared, Catalin Codreanu Speakers bureau: AbbVie, Amgen, Egis, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Amgen, Egis, Novartis, Pfizer, UCB, Daniela Di Giuseppe: None declared, Bente Glintborg Grant/research support from: Pfizer, Biogen, AbbVie, Marco Sebastiani: None declared, Karen Minde Fagerli: None declared, Burkhard Moeller: None declared, Karel Pavelka Speakers bureau: AbbVie, Roche, MSD, UCB, Pfizer, Novartis, Egis, Gilead, Eli Lilly, Consultant of: AbbVie, Roche, MSD, UCB, Pfizer, Novartis, Egis, Gilead, Eli Lilly, Anabela Barcelos: None declared, Carlos Sánchez-Piedra: None declared, Heikki Relas: None declared, Ziga Rotar Speakers bureau: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Consultant of: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Thorvardur Love: None declared, Servet Akar: None declared, Ruxandra Ionescu Speakers bureau: Abbvie, Amgen, Boehringer-Ingelheim Eli-Lilly,Novartis, Pfizer, Sandoz, UCB, Gary Macfarlane Grant/research support from: GlaxoSmithKline, Marleen G.H. van de Sande: None declared, Merete L. Hetland Speakers bureau: Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis., Mikkel Østergaard Speakers bureau: AbbVie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Centocor, GSK, Hospira, Janssen, Merck, Mundipharma, Novartis, Novo, Orion, Pfizer, Regeneron, Schering-Plough, Roche, Takeda, UCB and Wyeth, Consultant of: AbbVie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Centocor, GSK, Hospira, Janssen, Merck, Mundipharma, Novartis, Novo, Orion, Pfizer, Regeneron, Schering-Plough, Roche, Takeda, UCB and Wyeth

POS1246 COVID-19 IN ITALIAN PATIENTS WITH RHEUMATIC AUTOIMMUNE SYSTEMIC DISEASES: RESULTS OF A NATIONWIDE SURVEY STUDY

Background:

SARS-CoV-2 infection poses a serious challenge for patients with rheumatic autoimmune systemic diseases (ASD), characterized by marked immune-system dysregulation and frequent visceral organ involvement.

Objectives:

To evaluate the impact of Covid-19 pandemic in a large series of Italian patients with ASD.

Methods:

Our multicenter telephone survey (8-week period, March-April 2020) included a large series of 2,994 patients (584 M, 2,410 F, mean age 58.9±13.4SD years) with ASD followed at 34 tertiary referral centers of 14 regions of northern, central, and southern Italian macro areas, characterized by different prevalence of SARS-CoV-2 infection. According to currently used criteria, Covid-19 was classified as definite Covid-19 (signs or symptoms of Covid-19 confirmed by positive oral/nasopharyngeal swabs at PCR testing) or highly suspected Covid-19 (signs or symptoms highly suggestive of Covid-19, but not confirmed by PCR testing due to limited availability of virological tests in that period). The results were analyzed performing the Odds Ratio by Java-Stat 2-way Contingency Table Analysis.

Results:

The main findings of the survey study revealed a significantly increased prevalence of Covid-19 in:

a.the whole series of ASD patients (definite Covid-19: 22/2994, 0.73%; p=0.0007;

definite Covid-19 plus highly suspected Covid-19: 74/2,994, 2.47%; p<0.0001) when compared to Italian general population of Covid-19 infected individuals (349/100000 = 0.34%; data from Italian Superior Institute of Health;

https://www.epicentro.iss.it/en/coronavirus/sars-cov-2-national-surveillance-system).

b.the subgroup of patients with connective tissue diseases or systemic vasculitis (n = 1,901) compared to the subgroup of inflammatory arthritis (n = 1,093), namely rheumatoid arthritis, psoriatic arthritis, ankylosing spondylitis (definite Covid-19: 19/1,901, 0.99%, vs 3/1,093, 0.27%; p=0.036; definite Covid-19 plus highly suspected Covid-19: 69/1,901, 3.6%, vs 5/1,093, 0.45%; p<0.0001)

c.the subgroup of patients with pre-existing interstitial lung involvement (n = 526) compared to those without (n = 2,468) (definite Covid-19: 10/526, 1.90%, vs 12/2,468, 0.48%; p=0.0015; definite Covid-19 plus highly suspected Covid-19: 33/526, 6.27%, vs 41/2,468, 1.66%; p<0.0001).

Of interest, the prevalence of Covid-19 did not correlate with presence/absence of different comorbidities, mainly diabetes, cardio-vascular and/or renal disorders, as well as of ongoing treatments with biological DMARDs; while patients treated with conventional DMARDs showed a significantly lower prevalence of Covid-19 compared to those without. Covid-19 was more frequently observed in the patients’ populations from northern and central compared to southern Italian macro area with lower diffusion of pandemic. Clinical manifestations of Covid-19, observed in 74 patients, were generally mild or moderate; 4/9 individuals requiring hospital admission died for severe pneumonia.

Conclusion:

The prevalence of Covid-19 observed in ASD patients during the first wave of pandemic was significantly higher than that observed in Italian general population; moreover, the actual prevalence of Covid-19 might be underestimated due to the high number of mild variants as well as the possible clinical overlapping between these two conditions. Patients with ASD should be invariably regarded as ‘frail patients’ during the pandemic course, considering the risk of worse outcome in the acute phase of Covid-19, as well as the potential long-term effects of viral infection.

The statistically significant association of Covid-19 with connective tissue diseases/systemic vasculitis, as well as with pre-existing interstitial lung involvement, suggests the presence of distinct clinico-pathological ASD subsets, characterized by markedly different patients’ vulnerability to SARS-CoV-2 infection.

Disclosure of Interests:

None declared

POS0675 THE COMPARATIVE 3-YEAR RETENTION RATE OF TARGETED-SYNTHETIC AND BIOLOGIC DRUGS FOR RHEUMATOID ARTHRITIS: REAL-LIFE DATA FROM THE ITALIAN GISEA REGISTRY

Background:

Long-term observational data on the real-life use of JAK inhibitors (JAKis) for rheumatoid arthritis (RA) and their comparison with biological drugs are still very limited. Large population-based registries have been increasingly used to investigate the performance of targeted drugs in a real-life setting.

Objectives:

The aim of this study is to evaluate and compare the 3-year retention rate of JAKis, TNF inhibitors (TNFis) and biologic drugs with other mechanisms of action (OMAs) in the large cohort of RA patients included in the Italian national GISEA registry.

Methods:

Data of all RA patients treated with targeted synthetic or biologic drugs were prospectively collected in the Italian multicentric GISEA registry. The analysis was limited to patients who started a first- or second-line targeted drug in the period after the first JAKi was marketed in Italy (1st December 2017). The 3-year retention rate was calculated by the Kaplan-Meier method and compared between different drug classes by a log-rank test. A descriptive analysis of reasons for discontinuation was performed.

Results:

The study population included 1027 RA patients (79.8% females, mean age [±SD] 56.9 [±13.5] years, mean disease duration 9.8 [±9] years, mean baseline SDAI 17.5 [±11.9], ACPA positive 67.4%, RF positive 62.7%) who received JAKis (baricitinib or tofacitinib, n=297), TNFis (n=365), or OMAs (n=365) as first or second targeted drug. Main baseline characteristics of study population were overall well balanced between treatment groups. Retention rate was numerically but not statistically higher (p=0.18) in patients treated with JAKis compared with TNFis or OMAs (80.6, 78.9 and 76.4% at 1 year and 73, 56.8 and 63.8% at 3 years, respectively) (Figure 1). Drug survival was significantly higher in patients receiving concomitant methotrexate (MTX) compared with monotherapy only in TNFis (66.8 vs 47.1%, p=0.04) but not in JAKis (76.1 vs 70.1%, p=0.54) and OMAs (66.1 vs 61.9%, p=0.41) group. Therapy was discontinued in a total of 211 patients because of ineffectiveness (n=107), adverse events (n=88), or compliance/other reasons (n=16). The most frequent reason for treatment withdrawal was ineffectiveness in both JAKis (n=30 out of 56) and TNFis (n=45 out of 74) groups, whereas OMAs were discontinued more frequently because of adverse events (n=41 out of 81).

Conclusion:

Our data confirmed in a real-life setting a favorable 3-year retention rate of all available targeted mechanisms of action for RA therapy. As expected, concomitant MTX significantly impacted persistence on therapy of TNFis only. Discontinuations of JAKis for adverse events were infrequent overall, confirming the safety profile observed in randomized clinical trials.

Figure 1.

Three-year retention rate by treatment group

Disclosure of Interests:

None declared

POS0861 EFFECTIVENESS AND SAFETY OF TOCILIZUMAB IN PATIENTS WITH SYSTEMIC SCLEROSIS: A PROPENSITY SCORE CONTROL MATCHED OBSERVATIONAL STUDY OF THE EUSTAR COHORT

Background:

Tocilizumab (TCZ) showed trends for improving skin fibrosis and prevented progression of lung fibrosis in patients with systemic sclerosis (SSc) in placebo-controlled randomised clinical trials (RCTs). However, safety and effectiveness of TCZ beyond these selected and enriched clinical trial populations in SSc is still unknown.

Objectives:

To assess safety and effectiveness of TCZ treatment compared to standard of care in SSc patients from the large, multicentre, observational, real-life EUSTAR network/database using propensity score matching.

Methods:

SSc patients from the EUSTAR network/database, who fulfilled the ACR/EULAR 2013 classification criteria, with a baseline and a follow-up visit at 12±3 months, receiving TCZ or standard of care (controls), were selected. The following variables were used for the propensity score matching (1:1): age at diagnosis, gender, disease subtype, baseline modified Rodnan skin score (mRSS), forced vital capacity (FVC), and diffusing capacity for carbon monoxide (DLCO), co-therapy with immunosuppressives, disease duration, and year of treatment. Primary endpoints were mRSS and FVC at 12±3 months follow-up compared between the groups, using paired t-tests. Secondary endpoints were the percentage of progressive/regressive patients for skin and lung at 12±3 months follow-up according to standard definitions (1,2). Sensitivity analyses assessed pre-processing decisions (selection of most recent vs. random observation for control patients with multiple suitable time intervals), as well as the matching method (optimal vs. exact matching). Missing values were addressed with 100-fold multiple imputation using chained equations. Safety data were analysed in all patients. The study including the statistical analysis plan was pre-registered at www.drks.de (DRKS-ID: DRKS00015537).

Results:

We identified 93 SSc patients treated with TCZ and 2370 SSc patients with standard of care who fulfilled the inclusion criteria. Forty nine (57.7%) of the TCZ treated patients were diffuse, eight patients were not classified, disease duration was (mean±SD) 6.35±5.40 years, their baseline mRSS was 15.05±10.85, and 76 (81.7%) received immunosuppressive therapy in addition to TCZ.Through multiple imputation and propensity score matching, 100 imputed sets of 93 pairs of TCZ/controls were generated. Comparison between groups showed consistent effects of TCZ across all pre-defined primary and secondary endpoints: mRSS was lower in the TCZ group (mean difference (95% confidence interval (CI)) -1.8 (-4.79 to 1.19), p=0.24, Figure 1A). Similarly, FVC % predicted was higher in the TCZ group mean difference (2.25, 95% CI -4.57 to 9.06), p=0.51, Figure 1B). Considering secondary endpoints, the percentage of skin progressors as well as lung progressors at follow up was lower in the TCZ group (odds ratio OR 0.67 (95% CI 0.07 to 6.41), p=0.74 and OR 0.53 (95% CI 0.16 to 1.7); p=0.2, respectively. Consistently, the percentage of regressors for skin (OR 1.6 (95% CI 0.56 to 4.54), p=0.38) and for lung (OR 1.74 (95% CI 0.66 to 4.58), p=0.26) was higher in TCZ. These results were robust regarding the sensitivity analyses. Safety analysis confirmed previously reported adverse event profiles.

Conclusion:

In this large, observational, controlled, real-life EUSTAR study, effectiveness of TCZ did not reach statistical significance compared to standard of care treatment but showed consistent positive effects of TCZ on skin and lung fibrosis across all pre-defined primary and secondary endpoints confirming data from recent RCTs.

References:

[1]Prediction of improvement in skin fibrosis in diffuse cutaneous systemic sclerosis: a EUSTAR analysis. Ann Rheum Dis 2016:1743-8.

[2]Progressive interstitial lung disease in patients with systemic sclerosis-associated interstitial lung disease in the EUSTAR database. Ann Rheum Dis 2021:219-227.

Disclosure of Interests:

Simon Kuster: None declared, Suzana Jordan: None declared, Muriel Daniele Elhai: None declared, Ulrike Held: None declared, Klaus Steigmiller: None declared, Cosimo Bruni: None declared, Florenzo Iannone: None declared, Serena Vettori: None declared, Elise Siegert: None declared, Simona Rednic: None declared, Veronica Codullo: None declared, Paolo Airò Consultant of: Dr. Airo’ reports personal fees (consultancies) from Bristol Myers Squibb, Bohringer Ingelheim, non-financial support from CSL Behring, SOBI, Janssen, Roche, Sanofi, Pfizer, Yolanda Braun-Moscovici: None declared, Nicolas Hunzelmann: None declared, Maria Joao Salvador: None declared, Valeria Riccieri: None declared, Ana Maria Gheorghiu: None declared, Juan Jose Alegre Sancho: None declared, Katarzyna Romanowska-Prochnicka: None declared, Ivan Castellví: None declared, Ina Koetter: None declared, Marie-Elise Truchetet Consultant of: Marie-Elise Truchetet has had consultancy relationships and/or has received research funding from Boehringer Ingelheim, Genentech/Roche, and Sanofi in the area of potential treatments of scleroderma and its complications., Grant/research support from: Marie-Elise Truchetet has had consultancy relationships and/or has received research funding from Boehringer Ingelheim, Genentech/Roche, and Sanofi in the area of potential treatments of scleroderma and its complications., Francisco J López-Longo: None declared, Pavel Novikov: None declared, Alessandro Giollo: None declared, Yuichiro Shirai: None declared, Laura Belloli: None declared, Elisabetta Zanatta: None declared, Eric Hachulla: None declared, Vanessa Smith: None declared, Christopher Denton: None declared, Ruxandra Ionescu: None declared, Tim Schmeiser: None declared, Jörg H.W. Distler: None declared, Armando Gabrielli: None declared, Anna-Maria Hoffmann-Vold Consultant of: AMHV has received research funding and/or consulting fees and/or other remuneration from Actelion, Boehringer Ingelheim, Roche, Bayer, Merck Sharp & Dohme, ARXX, Lilly and Medscape, Grant/research support from: AMHV has received research funding and/or consulting fees and/or other remuneration from Actelion, Boehringer Ingelheim, Roche, Bayer, Merck Sharp & Dohme, ARXX, Lilly and Medscape. Masataka Kuwana: None declared, Yannick Allanore: None declared, Oliver Distler Speakers bureau: Oliver Distler has/had consultancy relationship and/or has received research funding in the area of potential treatments for systemic sclerosis and its complications from (last three years): Abbvie, Acceleron Pharma, Amgen, AnaMar, Arxx Therapeutics, Baecon Discovery, Blade Therapeutics, Bayer, Boehringer Ingelheim, ChemomAb, Corbus Pharmaceuticals, CSL Behring, Galapagos NV, Glenmark Pharmaceuticals, GSK, Horizon (Curzion) Pharmaceuticals, Inventiva, iQvia, Italfarmaco, iQone, Kymera Therapeutics, Lilly, Medac, Medscape, Mitsubishi Tanabe Pharma, MSD, Novartis, Pfizer, Roche, Sanofi, Serodapharm, Topadur, Target Bioscience and UCB. Patent issued “mir-29 for the treatment of systemic sclerosis” (US8247389, EP2331143)., Consultant of: Oliver Distler has/had consultancy relationship and/or has received research funding in the area of potential treatments for systemic sclerosis and its complications from (last three years): Abbvie, Acceleron Pharma, Amgen, AnaMar, Arxx Therapeutics, Baecon Discovery, Blade Therapeutics, Bayer, Boehringer Ingelheim, ChemomAb, Corbus Pharmaceuticals, CSL Behring, Galapagos NV, Glenmark Pharmaceuticals, GSK, Horizon (Curzion) Pharmaceuticals, Inventiva, iQvia, Italfarmaco, iQone, Kymera Therapeutics, Lilly, Medac, Medscape, Mitsubishi Tanabe Pharma, MSD, Novartis, Pfizer, Roche, Sanofi, Serodapharm, Topadur, Target Bioscience and UCB. Patent issued “mir-29 for the treatment of systemic sclerosis” (US8247389, EP2331143)., Grant/research support from: The study was partially supported by a grant from Roche. Roche was not involved in analysis or interpretation of the results.

OP0310 GENDER AND FIBROMYALGIA SEVERITY: REAL LIFE DATA FROM THE ITALIAN REGISTRY

Background:

Fibromyalgia (FM) patients report chronic widespread pain, fatigue, cognitive difficulties and sleep disturbances, often associated with anxiety and/or depression (1). FM syndrome more frequently affects women and many papers describe gender-related differences in the perception, description and expression of pain (2), but up to now, the impact of gender on the clinical severity of FM is still a controversial topic.

Objectives:

The aim of this study was to analyse the data from a web-based registry of FM patients in order to detect a relationship between gender and disease severity.

Methods:

Adult patients with FM, diagnosed on the basis of the 2010/2011 American College of Rheumatology (ACR) diagnostic criteria (3), were recruited at 19 Italian rheumatology centres between November 2018 and April 2019. Those affected by other conditions that could interfere with the assessment of FM, e.g. psychiatric disorders, were excluded from the study. The severity of the disease was evaluated by validated FM-specific questionnaires: the revised Fibromyalgia Impact Questionnaire (FIQR) (4), the modified Fibromyalgia Assessment Status (ModFAS) questionnaire (5), and the Polysymptomatic Distress Scale (PDS) (6). The data obtained were collected in the Italian Fibromyalgia Registry, an online registry created with the support of the Italian Society of Rheumatology (SIR).

Results:

We analyse data from 2.381 patients affected by FM, 2.184 females (91.7%) and 197 males. No significant differences in mean age, disease duration, or BMI between the two genders were reported. The women expressed greater disease burden as indicated by higher scores for each completed test: higher mean ModFAS score (25.23 ± 8.83 Vs 23.37 ± 9.22; p = 0.005), mean FIQR score (58.62 ± 23.22 Vs 51.68 ± 23.06; p <0.001), and mean PDS score (18.77 ± 7.34 Vs 17.19 ± 7.25; p = 0.004). Figure 1 shows the mean scores of each item of the FIQR divided by gender. Women reported significantly higher values on all the items of FIQR except three (feeling overwhelmed, FIQR-11; depression, FIQR-16; and anxiety, FIQR-18). It is interesting to note that men self-reported higher levels of depression (FIQR-16).

Figure 1.

Mean scores for each FIQR item by gender.

Conclusion:

Our findings demonstrate that women with FM are globally more impaired than men (even if some psychological aspects of the disease are comparable), thus reinforcing the idea that gender plays a role in symptoms and functional impairments associated with the disease.

References:

[1]Clauw DJ. Fibromyalgia: a clinical review. JAMA. 2014;311:1547-55.

[2]Nascimento, et al. Gender role in pain perception and expression: an integrative review. BrJP. 2020; 3: 58-62

[3]Wolfe F, et al. Fibromyalgia criteria and severity scales for clinical and epidemiological studies: A modification of the ACR preliminary diagnostic criteria for fibromyalgia. J Rheumatol 2011;38:1113–22.

[4]Burckhardt CS, et al. The fibromyalgia impact questionnaire: development and validation. J Rheumatol 1991;18:728–33.

[5]Salaffi F, et al. Diagnosis of fibromyalgia: comparison of 2011/2016 ACR and AAPT criteria and validation of the modified Fibromyalgia Assessment Status. Rheumatol 2020; 0:1-8.

[6]Wolfe F, et al. Fibromyalgia prevalence, somatic symptom reporting, and the dimensionality of polysymptomatic distress: results from a survey of the general population. Arthritis Care Res. 2013; 65:777–85

Disclosure of Interests:

None declared.

POS0093 HETEROGENEITY IN ADVERSE EVENT ASSESSMENT BETWEEN COUNTRIES PARTICIPATING IN AN INTERNATIONAL COLLABORATION OF REGISTRIES OF RHEUMATOID ARTHRITIS PATIENTS USING JANUS KINASE INHIBITORS (THE JAK-POT STUDY)

Background:

Industry, regulators, and the rheumatology community have recognized the need for observational studies to monitor the safety of new antirheumatic agents. Registries provide a unique opportunity to understand the safety of newer therapies, but pharmacovigilance studies require large number of patients to evaluate rare drug-related adverse-events (AEs). Because JAK-inhibitors (JAKi) have only recently been approved for the treatment of rheumatoid arthritis, it makes sense to combine data from several registries in order to obtain a sufficiently large sample size to promote earlier detection of adverse events.

Objectives:

The purpose of this analysis was to evaluate how AEs are assessed in the various registries in preparation for a collaborative pharmacovigilance analysis, and present preliminary results.

Methods:

The “JAK-pot” collaboration includes 19 RA registries. The principal investigators of the participating registries were sent a structured questionnaire on AE assessment and 18 (94%) provided complete responses on the AE assessment procedures of their registries. We present simple descriptive statistics of the AE assessment procedures employed by the participating registries.

Results:

The 19 registries represent 7186 patients initiating a JAKi (Table 1), who are on average 57 years old, with a mean disease duration 11 years, seropositive (83%), female (82%) and with moderate disease activity at treatment initiation.

Table 1.Country, registryN° of patients on JAKi includedAustria, BIOREG87Belgium, TARDIS2113Canada, RHUMADATA363Czech Republic, ATTRA197Denmark, DANBIO506Finland, ROB-FIN229Germany, RABBIT620Italy, GISEA244Israel, I-RECORD96Netherlands, METEOR4Norway, NOR-DMARD97Portugal, REUMA.PT44Romania, RRBR252Russia, ARBITER428Slovenia, biorx.si141Spain, BIOBADASER139Switzerland, SCQM738Turkey, TURKBIO404UK, BSRBR484

After ineffectiveness, AEs was the second most common reason for JAKi discontinuation (25.5%), with large differences between registries (Figure 1).

Of the participating registries, 2 registries do not collect AEs, while 16 (89%) assess incident AEs, by means of a pre-specified extraction form (3 registries), by free text (5 registries), by a combination of both (6 registries) and/or the use of linkage to external electronic records (3registries). AEs are coded using a predefined coding system by 11 registries (MeDRA (8), other (3)), but nearly all are recording the severity of the AE (15, 94%), AE related-death (15, 94%), or AE-related hospitalisation (15, 94%). AEs of special interest, such as serious infections (15, 94%), thromboembolic events (15, 94%), or shingles (9, 56%), are recorded by most registries. Incident AEs are linked by the treating physician to specific therapies in 11 registries (69%), while the other 5 registries extrapolate potential causal associations based on therapy start and stop dates. A pre-specified adjudication process for AEs is made only by 5 registries (31%).

Conclusion:

Substantial heterogeneity exists among registries regarding AE assessment within the JAK-pot collaboration. These differences must be taken into account when analysing the safety of JAKi across different countries in collaborative studies. For comparative analyses, stratified analyses by country are required to account for differential AE assessment and varying degrees of potential under-reporting.

Disclosure of Interests:

Kim Lauper: None declared, Denis Mongin: None declared, Sytske Anne Bergstra: None declared, Denis Choquette: None declared, Catalin Codreanu: None declared, Diederik De Cock: None declared, Lene Dreyer: None declared, Ori Elkayam: None declared, Kimme Hyrich: None declared, Florenzo Iannone: None declared, Nevsun Inanc: None declared, Eirik kristianslund: None declared, Tore K. Kvien: None declared, Burkhard Leeb: None declared, Galina Lukina: None declared, Dan Nordström: None declared, Karel Pavelka: None declared, Manuel Pombo-Suarez: None declared, Ziga Rotar: None declared, Maria Jose Santos: None declared, Anja Strangfeld: None declared, Delphine Courvoisier: None declared, Axel Finckh Speakers bureau: Eli-Lilly, Pfizer, Consultant of: Eli-Lilly, Pfizer, Grant/research support from: BMS, Pfizer.

AB0380 MACHINE LEARNING CAN PREDICT GIANT CELL ARTERITIS RELAPSE AFTER GLUCOCORTICOID TAPERING

Background:

To date reliable biomarkers and risk factors for relapsing giant cell arteris (GCA) after glucocorticoid (GC) tapering are still lacking.

In an increasing number of social and clinical scenarios, machine learning (ML) is emerging as a promising tool for the implementation of complex multi-parametric decision algorithms. A ML approach allows to handle complex non-linear relationships between patient attributes that are hard to model with traditional statistical methods, merging them to output a forecast or a probability for a given outcome.

Objectives:

To assess whether ML algorithms can predict GCA relapse after glucocorticoid tapering.

Methods:

GC-naïve GCA patients who presented to 4 tertiary care centers between January 2015 and January 2019, who underwent GC therapy and regular follow up visits for at least 12 months were retrospectively analyzed and used for training and validation (through 10-fold cross-validation) of n.2 ML algorithms, namely Decision Trees (DT) and Random Forest (RF).

Test of the algorithms was carried out GCA patients referred to the same centers from March 2019 to September 2020 whose data was longitudinally recorded during the 12 months after presentation.

Demographic, clinical an laboratory characteristics (Erythrocyte Sedimentation Rate (ESR) and C Reactive Protein (CRP) levels) were gathered.

The outcome of interest was the GCA relapse within 12 months after induction of remission, during GC tapering.

The accuracy of the algorithms in both validation and test phases was assessed.

Results:

The training and validation dataset consisted of n.85 GCA patients (59 female, 69.4%) with mean age 73.8 (±8.7) years at presentation. They were treated with 27.1 (±17.4) mg prednisone (PDN) equivalent at first visit. During GC tapering 34 of them (40%) experienced a disease relapse within 12 months. The test dataset consisted of n.22 patients (14 female, 63.4%) with mean age 75.5 (±8.7) years at presentation, who underwent GC induction therapy with a mean dose of 30.3 (±17.3) mg PDN equivalent. Nine of them (40.9%) had a GCA flare during GC tapering, within 12 months. Accuracy of DT and RF in predicting the outcome of interest on the training dataset was 68.3% and 73.4% respectively. On testing datasets DT and RF accuracy was 57.1 and 72.4%, respectively.

As shown in Figure 1, the most important patient attributes for RF forecast were found to be CRP and ESR baseline levels as well as age and symptom duration (months) at first visit.

Conclusion:

RF algorithm can predict GCA relapse after glucocorticoid tapering with fairly good accuracy. To date this is one of the most accurate predictive modeling for such outcome. This ML method represents a reproducible tool executable on computers as well as mobile devices and capable of supporting clinicians in GCA patient management.

References:

[1]Hellmich B., Agueda A., Monti S., et al. 2018 Update of the EULAR recommendations for the management of large vessel vasculitis Annals of the Rheumatic Diseases 2020;79:19-30.

[2]Venerito, V., Angelini, O., Cazzato, G. et al. A convolutional neural network with transfer learning for automatic discrimination between low and high-grade synovitis: a pilot study. Internal and Emergency Medicine 2021.

Disclosure of Interests:

None declared

POS1437 LATENT TUBERCULOSIS INFECTION IN RHEUMATIC DISEASES: A REAL-LIFE STUDY OF THREE APULIAN CENTRES. DATA FROM BIOPURE REGISTRY

Background:

Latent tuberculous infection (LTBI) is very common in the world and screening for it is essential before starting treatment with biotechnological drugs

Objectives:

The aims of our study were to assess the prevalence in Apulia of LTBI among patients affected with rheumatic disease and to record the cases of tuberculosis (TB) infection among patients treated with biologic agents.

Methods:

We analysed data of patients included in BIOPURE registry from 2008 to 2018, who underwent Quantiferon (QTF) test as routinely screening for biologic treatment. Demographic and clinical data were recorded at the time of the first QTF assessment and this time point was considered the “baseline” of the study. Data regarding further QTF tests performed during follow-up was also acquired by electronic charts. Prophylaxis administration and bDMARD treatments were recorded for patients with positive QTF test. All tuberculosis infections were recorded during the entire time of follow-up.

Results:

Three thousand thirty-five patients (female 67.2%, mean age 52 ± 18.3 years) were included in these study, 2692 patients (88.7%) had inflammatory arthritis (28.2% rheumatoid arthritis, 33% psoriatic arthritis and 27.4% spondyloarthritis), 129 (4.2%) patients had connective tissue disease, whereas 214 (7.1%) patients were affected by others rheumatic diseases. The prevalence of LTBI was 10.7% (326 patients) at baseline. Comparisons between positive and negative patients for QTF are reported in Table 1. We acquired data of LTBI prophylaxis of 284 patients; 235 out 265 patients treated with isoniazid completed the treatment, whereas 19 out 19 patients treated with rifampicin completed the prophylaxis regimen. The main cause of isoniazid withdrawal was hypertransaminasemia, but 8 patients then completed prophylaxis with rifampicin. During the entire follow-up (42.6±30.5 months), we recorded 5 (0.02%) cases of primary TB infection in patients on anti-TNFα agents treatment, which had baseline screening negative for LTBI. Data and outcome of these patients are reported in Table 2. The mean time of follow-up of patients on bDMARDs treatment with positive QTF at baseline was 52.7±35.2 months. bDMARD treatment regimens are reported in Table 3. No case of TB reactivation was found among patients with positive baseline QTF. Moreover, of 1563 (51.5%) patients who repeated QTF during follow-up, 62 (4%) of them showed a change in the test result. We observed a change to a positive state in 36 patients with previous negative QTF test, whereas 26 patients with previous positive QTF showed a shift to a negative test during follow-up.

Conclusion:

Our study shows a prevalence of LTBI of 10.7% in Apulian patients affected with rheumatic disease. bDMARDs therapy appears to be safe in patients with positive QTF test treated according to current recommendations1. However, cases of primary TB infections, especially in patients receiving anti-TNFα drugs, have been observed.

References:

[1]Cantini F, et al, Guidance for the management of patients with latent tuberculosis infection requiring biologic therapy in rheumatology and dermatology clinical practice, Autoimmun Rev (2015).

Disclosure of Interests:

None declared

AB0716 FIBROMYALGIA SYNDROME SEVERITY ACCORDING TO AGE CATEGORIES: RESULTS FROM A NATIONAL REGISTER

Background:

Fibromyalgia syndrome (FM) is characterised by a complex symptom spectrum, dominated by the presence of chronic widespread pain, fatigue and unrefreshing sleep. FM affects between 2 and 3% of the general population. It is a condition that mainly involves middle-aged women, although it is increasingly being diagnosed in younger people. The severity of symptoms can vary greatly between individual patients, and is influenced by many factors (e.g. sex, body mass index) [1]. To date, there is little information about changes in severity in accordance with patient age.

Objectives:

The aim of this study was to investigate variations in symptom severity in FM patients according to age categories.

Methods:

A cross-sectional study of adult FM patients diagnosed according to the American College of Rheumatology 2010/2011 criteria was performed. The case series was included from an Italian national registry [2]. Patients were grouped according to five age categories: 18-40 years, 41-50 years, 51-60 years, 61-70 years, over 71 years. Symptom severity was assessed through the revised Fibromyalgia Impact Questionnaire (FIQR) and domains, including FIQR physical function (items 1-9), FIQR health status (items 10-11), and FIQR symptoms (items 12-21). Between-group characteristics were analysed using one-way analysis of variance (ANOVA).

Results:

This study included a total of 2889 patients, 403 aged 18-40 years, 756 aged 40-50 years, 1035 aged 50-60 years, 528 aged 60-70 years, and 167 over 70 years, respectively. The mean (standard deviation [SD]) score of the total FIQR was 52.68 (11.82). Total FIQR and individual domains all showed a normal distribution. Analysing the data by age category, there were statistically significant differences between the categories for the total FIQR (p = 0.030). The age categories with the highest disease severity were those above 71 years (FIQR 62.14, SD 22.45), and between 51-60 years (FIQR 60.31, SD 22.89) (Table 1). Significant differences between age categories were also found for the domains physical function (p = 0.006) and health status (p = 0.012), but not for the domain symptoms (p = 0.164).

Table 1.

Mean values of FIQR total score and domains according to age categories.

FIQR and domains18-40 years41-50 years51-60 years61-70 years≥71 yearsp*FIQR total, mean (SD)57.90 (21.76)59.25 (23.30)60.31 (22.89)57.13 (23.59)62.14 (22.45)0.030FIQR physical function, mean (SD)15.51 (7.56)16.44 (7.77)16.77 (7.51)15.96 (7.82)17.68 (7.26)0.006FIQR health status, mean (SD)11.19 (5.85)11.24 (5.99)11.49 (5.93)10.57 (6.11)12.21 (5.97)0.012FIQR symptoms, mean (SD)31.32 (10.48)31.56 (11.32)32.10 (11.01)30.68 (11.47)32.24 (11.34)0.164

Abbreviations and legend. FIQR = revised Fibromyalgia Impact Questionnaire; SD = standard deviation; * = one-way analysis of variance (ANOVA).

Conclusion:

Distinguishing the disease severity in FM patients according to age categories, a bimodal distribution emerges, with the disease severity being greatest in patients over 71 years and in the 51-60 years decade. The main differences in severity, according to what can be detected through the FIQR, are attributable to the domains physical function and health status, which show higher scores in the two classes with higher severity.

References:

[1]Sarzi-Puttini P et al., Fibromyalgia: an update on clinical characteristics, aetiopathogenesis and treatment. Nat Rev Rheumatol 2020; 16: 645–660.

[2]Salaffi F et al., The Italian Fibromyalgia Registry: a new way of using routine real-world data concerning patient-reported disease status in healthcare research and clinical practice. Clin Exp Rheumatol 2020; Suppl 123: 65-71.

Acknowledgements:

Società Italiana di Reumatologia (SIR) and Italian Ministry of Health

Disclosure of Interests:

None declared

POS0631 COMPARATIVE EFFICACY OF COMBINATION THERAPY WITH BIOLOGIC OR TARGET SYNTHETIC DRUGS FOR RHEUMATOID ARTHRITIS: A BAYESIAN NETWORK META-ANALYSIS

Background:

Biologic agents and small molecules have shown long term benefit when added in patients with active RA non-responders to conventional DMARDs treatment (1). In head-to-head trials only adalimumab was compared to other drugs in combination with methotrexate, with some evidence of superiority but no data on multiple comparisons have been reported (2). The availability of biosimilar agents led in clinical practice to prefer mainly the cheaper one, so the choice of the most effective treatment remains a clinical unmet need (3).

Objectives:

To assess the relative efficacy of different therapeutic strategies for achieving ACR50 response at 24 weeks of treatment in patients with active RA, based on direct and indirect evidence.

Methods:

We performed systematic reviews of MEDLINE, EMBASE, and Cochrane Library databases, searching for all published phase 3 Randomised Controlled Trials (RCTs) comparing adalimumab originator to its biosimilars, abatacept, baricitinib, certolizumab pegol, tofacitinib or upadacitinib, combined to MTX, in patients with active RA inadequate responders to previous conventional DMARDs. American College of Rheumatology (ACR) 50% response at 24 weeks of treatment had to be evaluated both in adalimumab branch and in examined drug branch. Bayesian fixed-effect network meta-analysis was performed to combine the direct and indirect evidence using the WinBUGS 1.4 software (MRC Biostatistics Unit, Cambridge, UK).

Results:

Eleven RCTs evaluating 6’004 patients were included in the analysis, namely originator (1) and biosimilars (2) adalimumab, abatacept (3), baricitinib (4), certolizumab pegol (5), tofacitinib (6) and upadacitinib (7). Convergence was reached at n.100’000 iterations. Upadacitinib seems to be more effective than both originator and biosimilar adalimumab in achieving ACR 50 (OR 1.65 95% CI 1.25-2.14 and OR 1.22 95%CI 1.10-2.18; see Figure 1). Similarly, tofacitinib was more effective of originator adalimumab (OR 1.25 95%CI 1.01-155). Upadacitinib was ranked first among treatments with a probability of being the agent more likely to induce ACR 50 response of 86.3%. In this regard tofacitinib had a probability of 4.8%, hence it was ranked second among treatments.

Figure 1.

Caterpillar plot OR for ACR50 at 24 weeks (originator [1] and biosimilars [2] adalimumab; abatacept [3]; baricitinib [4]; certolizumab pegol [5]; tofacitinib [6]; upadacitinib [7]).

Conclusion:

Although patients with active RA and inadequate response to MTX have different therapeutic combination of biologics or small molecules options, the best relative efficacy in terms of ACR50 response after 24 weeks of treatment is for upadacitinib 15 mg/day.

References:

[1]Smolen JS, et al. Annals of the Rheumatic Diseases 2020;79:685-699.

[2]Combe B, Lukas C. Joint Bone Spine, 2020,105004.

[3]Caporali R, et al. Biomed Res Int. 2018 Sep 9;2018:3878953.

Disclosure of Interests:

Fabio Cacciapaglia Speakers bureau: Roche, Pfizer, Eli Lilly, MSD, UCB, BMS, Abbvie, Vincenzo Venerito: None declared, Stefano Stano: None declared, Marco Fornaro: None declared, Giuseppe Lopalco Speakers bureau: Celgene, BMS, Abbvie, Novartis, Florenzo Iannone Speakers bureau: Roche, Pfizer, Eli Lilly, MSD, UCB, BMS, Abbvie, Novartis, Celgene

POS0027 SECULAR TRENDS IN BASELINE CHARACTERISTICS, TREATMENT RETENTION AND RESPONSE RATES IN 27189 BIO-NAÏVE AXIAL SPONDYLOARTHRITIS PATIENTS INITIATING TNFI – RESULTS FROM THE EUROSPA COLLABORATION

Background:

Knowledge of changes over time in baseline characteristics and tumor necrosis factor inhibitor (TNFi) response in bio-naïve axial spondyloarthritis (axSpA) patients treated in routine care is limited.

Objectives:

To investigate secular trends in baseline characteristics and retention, remission and response rates in axSpA patients initiating a first TNFi.

Methods:

Prospectively collected data on bio-naïve axSpA patients starting TNFi in routine care from 15 European countries were pooled. According to year of TNFi initiation, three groups were defined a priori based on bDMARD availability: Group A (1999–2008), Group B (2009–2014) and Group C (2015–2018). Retention rates (Kaplan-Meier), crude and LUNDEX adjusted1 remission (Ankylosing Spondylitis Disease Activity Score (ASDAS) <1.3, Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) <20) and response (ASDAS Major and Clinically Important Improvement (MI/CII), BASDAI 50) rates were assessed at 6, 12 and 24 months. No statistical comparisons were made.

Results:

In total, 27189 axSpA patients were included (5945, 11255 and 9989 in groups A, B and C).

At baseline, patients in group A were older, had longer disease duration and a larger proportion of male and HLA-B27 positive patients compared to B and C, whereas disease activity was similar across groups.

Retention rates at 6, 12 and 24 months were highest in group A (88%/81%/71%) but differed little between B (84%/74%/64%) and C (85%/76%/67%).

In all groups, median ASDAS and BASDAI had decreased markedly at 6 months (Table 1). The ASDAS values at 12 and 24 months and BASDAI at 24 months were higher in group A compared with groups B and C. Similarly, crude remission and response rates were lowest in group A. After adjustments for drug retention (LUNDEX), remission and response rates showed less pronounced between-group differences regarding ASDAS measures and no relevant differences regarding BASDAI measures.

Conclusion:

Nowadays, axSpA patients initiating TNFi are younger with shorter disease duration and more frequently female and HLA-B27 negative than previously, while baseline disease activity is unchanged. Drug retention rates have decreased, whereas crude remission and response rates have increased. This may indicate expanded indication but also a stable disease activity threshold for TNFi initiation over time, an increased focus on targeting disease remission and more available treatment options.

References:

[1]Arthritis Rheum 2006; 54: 600-6.

Table 1.

Secular trends in baseline characteristics, treatment retention, remission and response rates in European axSpA patients initiating a 1st TNFi

Baseline characteristicsGroup A(1999–2008)Group B(2009–2014)Group C(2015–2018)Age, years, median (IQR)57 (49–66)51 (42–60)46 (37–56)Male, %666057HLA-B27, %877772Years since diagnosis, median (IQR)5 (1–12)2 (0–8)2 (0–7)Smokers, %232425ASDAS, median (IQR)3.5 (2.8–4.1)3.4 (2.8–4.1)3.5 (2.8–4.1)BASDAI, median, (IQR)57 (42–71)59 (43–72)57 (41–71)TNFi drug, % (Adalimumab /Etanercept / Infliximab /Certolizumab / Golimumab)22 / 35 / 43 / 0 / 037 / 21 / 20 / 4 / 1827 / 28 / 24 / 8 / 13Follow up6 months12 months24 monthsGr AGr BGr CGr AGr BGr CGr AGr BGr CRetention rates, %, (95% CI)88 (88–89)84 (83–85)85 (84–86)81 (80–82)74 (74–75)76 (75–76)71 (70–72)64 (63–65)67 (66–68)ASDAS, median, (IQR)1.8 (1.2–2.8)1.9 (1.2–2.8)1.8 (1.2–2.6)1.9 (1.3–2.6)1.7 (1.2–2.5)1.6 (1.1–2.4)1.9 (1.4–2.6)1.7 (1.1–2.4)1.5 (1.1–2.2)ASDAS inactive disease, %, c/L28 / 2528 / 2430 / 2624 / 1932 / 2434 / 2623 / 1634 / 2039 / 23ASDAS CII, %, c/L57 / 5159 / 5063 / 5461 / 5063 / 4767 / 5159 / 4168 / 4074 / 45ASDAS MI, %, c/L31 / 2732 / 2737 / 3232 / 2637 / 2741 / 3130 / 2042 / 2546 / 28BASDAI, median, (IQR)23 (10–40)26 (11–48)24 (10–44)21 (10–38)23 (10–42)20 (8–39)22 (9–40)20 (8–39)16 (6–35)BASDAI remission, %, c/L44 / 4040 / 3443 / 3645 / 3645 / 3450 / 3844 / 3048 / 2956 / 34BASDAI 50 response, %, c/L53 / 4750 / 4253 / 4557 / 4656 / 4258 / 4457 / 3960 / 3563 / 38

Gr, Group; c/L, crude/LUNDEX adjusted.

Acknowledgements:

Novartis Pharma AG and IQVIA for supporting the EuroSpA Research Collaboration Network.

Disclosure of Interests:

Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Sara Nysom Christiansen Speakers bureau: BMS and GE, Grant/research support from: Novartis, Simon Horskjær Rasmussen: None declared, Anne Gitte Loft Speakers bureau: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, UCB, Consultant of: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, UCB, Grant/research support from: Novartis, Ulf Lindström: None declared, Jakub Zavada: None declared, Florenzo Iannone: None declared, Fatos Onen: None declared, Michael J. Nissen Speakers bureau: Novartis, Eli Lilly, Celgene, and Pfizer, Consultant of: Novartis, Eli Lilly, Celgene, and Pfizer, Brigitte Michelsen Consultant of: Novartis, Grant/research support from: Novartis, Maria Jose Santos Speakers bureau: AbbVie, Novartis, Pfizer, Gary Macfarlane Grant/research support from: GlaxoSmithKline, Dan Nordström Consultant of: Abbvie, BMS, MSD, Novartis, Pfizer, Roche, UCB, Manuel Pombo-Suarez: None declared, Catalin Codreanu Speakers bureau: AbbVie, Amgen, Egis, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Amgen, Egis, Novartis, Pfizer, UCB, Matija Tomsic Speakers bureau: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Consultant of: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Irene van der Horst-Bruinsma Speakers bureau: Abbvie, BMS, MSD, Novartis, Pfizer, Lilly, UCB, Björn Gudbjornsson Speakers bureau: Amgen and Novartis, Johan Askling: None declared, Bente Glintborg Grant/research support from: Pfizer, Biogen, AbbVie, Karel Pavelka Speakers bureau: AbbVie, Roche, MSD, UCB, Pfizer, Novartis, Egis, Gilead, Eli Lilly, Consultant of: AbbVie, Roche, MSD, UCB, Pfizer, Novartis, Egis, Gilead, Eli Lilly, Elisa Gremese: None declared, Nurullah Akkoc: None declared, Adrian Ciurea Speakers bureau: Abbvie, Eli-Lilly, MSD, Novartis, Pfizer, Eirik kristianslund: None declared, Anabela Barcelos: None declared, Gareth T. Jones Grant/research support from: Pfizer, AbbVie, UCB, Celgene, Amgen, GSK, Anna-Mari Hokkanen Grant/research support from: MSD, Carlos Sánchez-Piedra: None declared, Ruxandra Ionescu Speakers bureau: Abbvie, Amgen, Boehringer-Ingelheim Eli-Lilly,Novartis, Pfizer, Sandoz, UCB, Ziga Rotar Speakers bureau: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Consultant of: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Marleen G.H. van de Sande: None declared, Arni Jon Geirsson: None declared, Mikkel Østergaard Speakers bureau: AbbVie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Centocor, GSK, Hospira, Janssen, Merck, Mundipharma, Novartis, Novo, Orion, Pfizer, Regeneron, Schering-Plough, Roche, Takeda, UCB and Wyeth, Consultant of: AbbVie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Centocor, GSK, Hospira, Janssen, Merck, Mundipharma, Novartis, Novo, Orion, Pfizer, Regeneron, Schering-Plough, Roche, Takeda, UCB and Wyeth, Merete L. Hetland Speakers bureau: Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis.

High disease relapse after bDMARD spacing in psoriatic arthritis compared to rheumatoid arthritis and axial spondyloarthritis patients: real-life data from BIOPURE registry

The objective is to evaluate the effectiveness of a spacing strategy of bDMARDs in a cohort of selected patients in disease remission or low-disease activity (LDA) without glucocorticoids affected with rheumatoid arthritis (RA), psoriatic arthritis (PsA) and axial spondyloarthritis (axSpA). This was a single-centre study carried out on patients prospectively enrolled in the biologic Apulian registry. Patients whose disease was in remission or LDA without taking glucocorticoids during the previous 6 months and who had agreed to increase the time interval between bDMARD doses were included in this study. Demographic and clinical characteristics were recorded at baseline and at 3, 6 and 12 months of follow-up. Endpoint of the study was the survival of spacing doses in the time lag of the study. Failure of spacing was defined as the first flare of disease. Thirty-seven RA, 28 PsA and 20 axSpA patients underwent bDMARD spacing according to a local strategy. During the follow-up, 5 RA, 6 PsA and 4 axSpA patients had a joint flare, but further 5 PsA patients manifested a skin relapse. Global persistence was 86.5% for RA (MST = 41 (95% CI: 37-45) months) and 80% for axSpA patients (MST = 36 (95% CI: 31-42) months). PsA patients showed a lower persistence, being of 60.7% (MST = 30 (95% CI: 23-36) months) (log-rank test, p = 0.03). Dose reduction by spacing bDMARD doses may be a feasible approach in patients with persistent remission/LDA activity. However, PsA patients might have greater odds of spacing failure because of skin psoriasis relapse. Key Points • Spacing of bDMARDs may be a feasible strategy for some patients with rheumatoid arthritis, psoriatic arthritis and axial spondyloarthritis who achieve the target and withdrawn glucocorticoids. • Psoriatic arthritis patients showed lower persistence because of both articular and skin relapses.

Pulmonary arterial hypertension: guidelines and unmet clinical needs

The term pulmonary arterial hypertension (PAH) identifies a heterogeneous group of diseases characterized by a progressive increase in pulmonary arterial resistance (PVR), which causes a significant burden in terms of quality of life, right heart failure and premature death. The pathogenesis of PAH is not completely clear: the remodeling of the small pulmonary vessels is crucial, causing an increase in the resistance of the pulmonary circle. Its diagnosis is based on cardiac catheterization of the right heart. According to the present hemodynamic definition of pulmonary hypertension (PH) proposed by the Guidelines of the European Society of Cardiology/European Respiratory Society (ESC-ERS), the mean pulmonary arterial pressure (mPAP) values are ≥25 mmHg. In case of PAH, apart from an mPAP value ≥25 mmHg, patients must have a >3 Wood units increase in PVR and normal pressure values of the left heart. PH is a pathophysiological condition observed in more than 40 different diseases, while PAH is a primary disease of the pulmonary bloodstream potentially treatable with specific drugs. PAH is a severe complication of systemic sclerosis (SSc) affecting about 10% of the patients. Due to the devastating nature of SSc-PAH, there is a clear need to systematically adopt appropriate screening programs. In fact, despite awareness of the negative impact of SSc-PAH on quality of life and survival, as well as on the severity of lung function, at the moment standardized and shared guidelines and/or screening programs for the diagnosis and the subsequent early treatment of PAH in SSc are not available. The aim of the present paper is to highlight the lights and shadows of SSc-PAH, unraveling the unmet clinical needs on this topic with a proposal of clinical-diagnostic and therapeutic guidelines.

OP0231 COMPARATIVE EFFECTIVENESS OF JAK-INHIBITORS, TNF-INHIBITORS, ABATACEPT AND IL-6 INHIBITORS IN AN INTERNATIONAL COLLABORATION OF REGISTERS OF RHEUMATOID ARTHRITIS PATIENTS (THE “JAK-POT” STUDY)

Background:

In many countries, JAK-inhibitors (JAKi) have only recently been approved as treatment for patients with rheumatoid arthritis (RA).

Objectives:

To evaluate the effectiveness of JAKi compared to bDMARDs in RA patients in the real-world population in an international collaboration of registers (the “JAK-pot” collaboration).

Methods:

Patients initiating either JAKi, TNFi, IL-6i or abatacept (ABA) during a time period when JAKi were available in each country (19 registers, Table) were included. We compared the effectiveness of JAKi and bDMARDs in terms of retention using crude and adjusted survival analysis. Missing covariates were imputed using multiple imputation.

Results:

Among 25521 included patients, 6063 initiated a JAKi, 13879 a TNFi, 2348 ABA, and 3231 an IL-6i. Patients were on average 55 years old, with a mean disease duration 10 years, mostly seropositive (67%), female (77%) and with moderate disease activity at treatment initiation. The main reason of stopping treatment was ineffectiveness (49%), followed by adverse events (21%). Patients on JAKi were treated more often as monotherapy, had higher CRP and disease activity at baseline and had experienced more previous ts/bDMARDs. Crude median retention was 1.4 (95% CI 1.2-1.5) years for JAKi, 1.6 (1.6-1.7) for TNFi, 1.5 (1.3-1.7) for IL6i and 1.1 (1.0-1.3) for ABA. After adjustment, the hazard ratio (HR) for discontinuation tended to be lower for JAKi (HR 0.86 (0.65-1.13)) compared to TNFi, but comparable for ABA (1.02 (0.94-1.10)) and IL6i (0.99 (0.88-1.10)) (Figure 1). HRs differed notably between countries (Figure 2).

Table 1.

Registers

Country, registerNJAKi, n (%)Austria, BIOREG*Belgium, TARDIS62882113 (33.6)Canada, RHUMADATA528114 (21.6)Czech Republic, ATTRA374253 (67.6)Denmark, DANBIO4721506 (10.7)Finland, ROB-FIN807234 (29.0)Germany, RABBIT*Italy, GISEA757250 (33.0)Israel, I-RECORD40094 (23.5)Netherlands, METEOR16424 (0.2)Norway, NOR-DMARD50799 (19.5)Portugal, REUMA.PT79744 (5.5)Romania, RRBR593328 (55.3)Russia, ARBITER526483 (91.8)Slovenia, BIORX.SI583146 (25.0)Spain, BIOBADASER781139 (17.8)Switzerland, SCQM2956796 (26.9)Turkey, TURKBIO2150397 (18.5)UK, BSRBR111163 (5.7)

*Registers planning to participate in future studies but not included yet

Conclusion:

The adjusted overall drug retention of JAKi tended to be higher than for TNFi, with large variation between countries. Other measures of effectiveness, such as the evaluation of CDAI remission and low disease activity are planned to shape a more comprehensive picture of JAKi effectiveness in the real world.

Disclosure of Interests:

Kim Lauper: None declared, Denis Mongin: None declared, Sytske Anne Bergstra: None declared, Denis Choquette Grant/research support from: Rhumadata is supported by grants from Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Consultant of: Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Speakers bureau: Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Catalin Codreanu Consultant of: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Speakers bureau: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Diederik De Cock: None declared, Lene Dreyer: None declared, Ori Elkayam Speakers bureau: AbbVie, BMS, Pfizer, Roche, Sanofi-Aventis, Novartis, Jansen, Kimme Hyrich Grant/research support from: Pfizer, UCB, BMS, Speakers bureau: Abbvie, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Nevsun Inanc: None declared, Eirik kristianslund: None declared, Tore K. Kvien Grant/research support from: Received grants from Abbvie, Hospira/Pfizer, MSD and Roche (not relevant for this abstract)., Consultant of: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Paid instructor for: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Speakers bureau: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Burkhard Leeb Grant/research support from: chairman of BioReg, Consultant of: AbbVie, Pfizer, Roche, Lilly, Grünenthal, Gebro,, Paid instructor for: Lilly, Biogen, Speakers bureau: Biogen, Lilly, Pfizer, Grünenthal, Astropharma,, Galina Lukina Speakers bureau: Novartis, Pfizer, UCB, Abbvie, Biocad, MSD, Roche, Dan Nordström Consultant of: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Speakers bureau: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Karel Pavelka Consultant of: Abbvie, MSD, BMS, Egis, Roche, UCB, Medac, Pfizer, Biogen, Speakers bureau: Abbvie, MSD, BMS, Egis, Roche, UCB, Medac, Pfizer, Biogen, Manuel Pombo-Suarez Consultant of: Janssen, Lilly, MSD and Sanofi., Speakers bureau: Janssen, Lilly, MSD and Sanofi., Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Maria Jose Santos Speakers bureau: Novartis and Pfizer, Anja Strangfeld Speakers bureau: AbbVie, BMS, Pfizer, Roche, Sanofi-Aventis, Delphine Courvoisier: None declared, Axel Finckh Grant/research support from: Pfizer: Unrestricted research grant, Eli-Lilly: Unrestricted research grant, Consultant of: Sanofi, AB2BIO, Abbvie, Pfizer, MSD, Speakers bureau: Sanofi, Pfizer, Roche, Thermo Fisher Scientific

THU0628-HPR SSCENTRY: A PERSONAL DISEASE DIARY APP FOR SYSTEMIC SCLEROSIS PATIENTS

Background:

Systemic Sclerosis (SSc) is a connective tissue disease characterized by severe alterations in the microvasculature and progressive fibrosis of the skin and internal organs [1]. Management of SSc is not easy, for both patients and physicians [2]. Symptoms are manifold and have a significant impact on patient’s daily autonomy and psychological well-being.

Objectives:

SScEntry (SSc data Entry tool; Figure 1) is a solution conceived to assist SSc patients in monitoring their disease, as a kind of “sentry”. The core idea is to provide patients with a personal diary to annotate and track the onset, evolution and resolution of symptoms as well as any changes in their general health condition, through an app for iOS and Android smartphones and tablets.

Figure 1.

SScEntry logo.

Methods:

SScEntry is a smartphone/tablet app designed by rheumatology and computer science engineering specialists in close partnership [3]. A carefully designed user interface (UI), inspired to a social network wall, allows annotating the evolution of symptoms by means of standard clinical investigation methods such as scientifically validated questionnaires. The UI facilitates data collection through speech-based interaction as well as touch and gestures optimized for patients with finger skin lesions and joints impairments. User engagement over the course of time is fostered by: follow-up reminders to update information on the evolution of past events and periodic questionnaires for general health assessment; the integration of symptom photos taken with on-device camera and health data collected from wearable devices; gamification features. Privacy and security have been a primary design concern, with app access protection and full on-device data encryption; no personal data transmission occurs without explicit user consent. SScEntry generates a disease activity summary report, for displaying to the physician during visit or emailing/printing.

Results:

SScEntry is ready for Android and iOS smartphones and tablets. All planned features have been implemented (Figure 2). Currently supported languages are English and Italian. Areas of interest include vascular, cutaneous, articular, visceral (gastro-intestinal and cardio-pulmonary) as well as relationship, sexual and working life.

Figure 2.

SScEntry features.

Conclusion:

Novel Narrative-based Medicine approaches are getting increasing attention to enhance the mutual understanding between patient and physician, reinforcing the therapeutic adherence at the core of healthcare. This is particularly important with chronic and disabling diseases like SSc. Involving patients in disease management with SScEntry will increase their compliance and confidence, with benefits on psychological well-being. Expected benefits for rheumatologists include better evaluation of target therapy and outcomes, as no data on disease activity is lost during the patient clinical history.

References:

[1]J. Varga et al. (2017) Pathogenesis of systemic sclerosis: recent insights of molecular and cellular mechanisms and therapeutic opportunities. J Scleroderma Relat Disord 2:137–52.

[2]L. Mouthon et al. (2017) Patients’ views and needs about systemic sclerosis and its management: a qualitative interview study. BMC Musculoskelet Disord 18(1):230.

[3]M. Bradway et al. (2015) Mobile Health: empowering patients and driving change. Trends in Endocrinology & Metabolism, 26(3):114-117.

Disclosure of Interests:

Emanuela Praino: None declared, Floriano Scioscia: None declared, Crescenzio Scioscia: None declared, Giuseppe Loseto: None declared, Filippo Gramegna: None declared, Saverio Ieva: None declared, Agnese Pinto: None declared, Michele Ruta: None declared, Eugenio Di Sciascio: None declared, Giovanni Lapadula: None declared, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD

SAT0430 SECUKINUMAB EFFECTIVENESS IN 1543 PATIENTS WITH PSORIATIC ARTHRITIS TREATED IN ROUTINE CLINICAL PRACTICE IN 13 EUROPEAN COUNTRIES IN THE EuroSpA RESEARCH COLLABORATION NETWORK

Background:

There is a lack of real-life evidence on secukinumab effectiveness in psoriatic arthritis (PsA) patients.

Objectives:

To assess the real-life 6- and 12-month secukinumab retention rates and proportions of patients in remission/low disease activity (LDA) overall, and by prior biologic disease-modifying anti-rheumatic drug (bDMARD)/targeted synthetic (ts)DMARD use.

Methods:

Data from PsA patients treated with secukinumab in routine care from 13 countries in the European Spondyloarthritis (EuroSpA) Research Collaboration Network were pooled. Patients started secukinumab ≥12 months before date of datacut. Crude and LUNDEX adjusted (crude value adjusted for drug retention) 28-joint Disease Activity index for PSoriatic Arthritis (DAPSA28) and 28-joint Disease Activity Score with CRP (DAS28CRP) remission and LDA rates were calculated. Group comparisons between b/tsDMARD naïve, 1 prior and ≥2 prior b/tsDMARD users were done with ANOVA, Kruskal-Wallis, Chi-square or Kaplan-Meier analyses with log-rank test, as appropriate.

Results:

A total of 1543 PsA patients were included (Table 1). b/tsDMARD naïve patients had shorter time since diagnosis, higher baseline disease activity, a higher proportion were men and a higher proportion achieved remission. Overall 6/12-month secukinumab retention rates were 86%/74% and significantly higher in b/tsDMARD naïve patients at 12, but not 6 months (Table 2, Figure). Overall, crude 6- and 12-month DAPSA28≤4/DAS28CRP<2.6 were achieved by 13%/34% and 11%/39% of the patients, respectively.

Table 1.All patients (n=1543)b/tsDMARD naïve (n=287)1 prior b/tsDMARD (n=333)≥2 prior b/tsDMARDs (n=923)p *Age (years), mean (SD)52 (11)49 (12.3)51 (11)53 (11)<0.001Male, %42%49%46%39%0.003Years since diagnosis, mean (SD)9 (8)7 (8)8 (7)10 (8)<0.001Current smokers, %19%21%22%18%0.23CRP (mg/L), median (IQR)5 (2-12)7 (2-19)4 (2-8)5 (2-11)<0.001DAPSA28, median (IQR)26 (18-37)28 (19-38)22 (13-32)27 (19-38)<0.001DAS28CRP, median (IQR)4.2 (3.3-5.0)4.4 (3.5-5.2)3.8 (2.6-4.5)4.2 (3.4-5.0)<0.001

*Comparisons across number of prior b/tsDMARD were done with ANOVA, Kruskal-Wallis or Chi-square test, as appropriate

Table 2.MonthsAll patients (n=1543)b/tsDMARD naïve (n=287)1 prior b/tsDMARD (n=333)≥2 prior b/tsDMARDs (n=923)p *Secukinumab retention rate, % (95%CI)686% (84-87%)89% (86-93%)85% (81-89%)85% (82-87%)0.111274% (72-76%)81% (76-86%)76% (71-80%)72% (69-75%)0.006DAPSA28≤4 Crude613%25%11%11%<0.001 LUNDEX11%22%9%9%<0.001 Crude1211%22%11%8%<0.001 LUNDEX7%17%7%5%0.001DAS28CRP<2.6 Crude634%51%33%30%<0.001 LUNDEX29%45%27%24%<0.001 Crude1239%55%41%34%<0.001 LUNDEX26%41%27%21%<0.001DAPSA28 >4 and ≤14 Crude633%42%32%30%0.04 LUNDEX27%37%27%25%0.02 Crude1235%48%36%32%0.009 LUNDEX24%36%24%20%0.004DAS28CRP ≤3.2 Crude652%69%53%47%<0.001 LUNDEX43%61%45%38%<0.001 Crude1255%72%55%50%<0.001 LUNDEX37%54%37%32%<0.001

*Comparisons across number of prior b/tsDMARDs were done with Kaplan-Meier with log-rank test or Chi-Square test, as appropriate

Conclusion:

In this real-life study of 1543 patients with PsA in 13 European countries 12-month secukinumab retention was high, and significantly higher for b/tsDMARD naïve patients. Overall, a higher proportion of bionaïve than previous b/tsDMARD users achieved remission, regardless of remission criteria.

Acknowledgments:

Novartis and IQVIA for supporting the EuroSpA RCN

Disclosure of Interests:

Brigitte Michelsen Grant/research support from: Research support from Novartis, Consultant of: Consulting fees Novartis, Stylianos Georgiadis Grant/research support from: Novartis, Daniela Di Giuseppe: None declared, Anne Gitte Loft Grant/research support from: Novartis, Consultant of: AbbVie, MSD, Novartis, Pfizer and UCB, Speakers bureau: AbbVie, MSD, Novartis, Pfizer and UCB, Michael Nissen Grant/research support from: Abbvie, Consultant of: Novartis, Lilly, Abbvie, Celgene and Pfizer, Speakers bureau: Novartis, Lilly, Abbvie, Celgene and Pfizer, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Manuel Pombo-Suarez Consultant of: Janssen, Lilly, MSD and Sanofi., Speakers bureau: Janssen, Lilly, MSD and Sanofi., Heřman Mann: None declared, Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Kari Eklund Consultant of: Celgene, Lilly, Speakers bureau: Pfizer, Roche, Tore K. Kvien Grant/research support from: Received grants from Abbvie, Hospira/Pfizer, MSD and Roche (not relevant for this abstract)., Consultant of: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Paid instructor for: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Speakers bureau: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Maria Jose Santos Speakers bureau: Novartis and Pfizer, Björn Gudbjornsson Speakers bureau: Novartis and Amgen, Catalin Codreanu Consultant of: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Speakers bureau: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Sema Yilmaz: None declared, Johan K Wallman Consultant of: AbbVie, Celgene, Eli Lilly, Novartis and UCB Pharma, Cecilie Heegaard Brahe Grant/research support from: Novartis, Burkhard Moeller: None declared, Ennio Giulio Favalli Consultant of: Consultant and/or speaker for BMS, Eli-Lilly, MSD, UCB, Pfizer, Sanofi-Genzyme, Novartis, and Abbvie, Speakers bureau: Consultant and/or speaker for BMS, Eli-Lilly, MSD, UCB, Pfizer, Sanofi-Genzyme, Novartis, and Abbvie, Carlos Sánchez-Piedra: None declared, Lucie Nekvindova: None declared, Matija Tomsic: None declared, Nina Trokovic: None declared, Eirik kristianslund: None declared, Helena Santos Speakers bureau: AbbVie, Eli-Lilly, Janssen, Pfizer, Novartis, Thorvardur Love: None declared, Ruxandra Ionescu Consultant of: Consulting fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Speakers bureau: Consulting and speaker fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Yavuz Pehlivan: None declared, Gareth T. Jones Grant/research support from: Pfizer, AbbVie, UCB, Celgene and GSK., 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, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, 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, Merete L. Hetland Grant/research support from: BMS, MSD, AbbVie, Roche, Novartis, Biogen and Pfizer, Consultant of: Eli Lilly, Speakers bureau: Orion Pharma, Biogen, Pfizer, CellTrion, Merck and Samsung Bioepis

AB0296 EFFECTIVENESS OF CERTOLIZUMAB IN 506 PATIENTS WITH RHEUMATOID ARTHRITIS, PSORIATIC ARTHRITIS, AND SPONDYLOARTHRITIS FROM THE APULIAN REGISTRY BIOPURE

Background:

Little is known about effectiveness of certolizumab (CTZ) in clinical practice, especially in patients with inadequate response to prior biologics.

Objectives:

To estimate the survival rate of CTZ in RA, PsA or SpA cohorts from the registry BIOPURE. Secondary endpoint was the changes of clinical outcomes from baseline at 6 and 12 months for each disease.

Methods:

We analyzed longitudinal data of consecutive patients, affected with RA, PsA or SpA starting a treatment with CTZ recorded into the web-based Apulian registry BIOPURE. Demographic and disease related characteristics were collected at baseline, 6 and 12 months. Drug survival was evaluated by Kaplan-Meier life table analysis. Estimates hazard ratios (HRs, 95% confidence intervals (CI)) of drug discontinuation adjusted for patient’s demographics, disease characteristics and prior biologic treatments were computed by Cox-regression models. Differences of DAS28, DAPSA and BASDAI among baseline, 6 and 12 months were estimated by T-test.

Results:

506 patients were included in this analysis (table 1). Global mean survival time (95% CI) was 58 (52-64) months. Drug survival rate was significantly higher in RA (71.1%) than in PsA (63.5%, p=0.001), while SpA showed 67.5% (Figure 1). Naïve-CTZ patients showed higher survival rates than biologic-inadequate responder (Bio-IR) patients in PsA (naïve 78.4% vs 56.9%, p=0.02), but not in RA (76.9% vs 64.1%, p=0.08), or SpA (73.7% vs 64.8%, p=0.84). The only weak predictor of drug discontinuation was age at baseline for SpA patients (HR 1.04 (95% CI:1.005-1.007) p=0.02) (Figure 1). No baseline covariate, including sex, cDMARDs co-therapy and biologic-naïve status, was found to be associated with CTZ discontinuation for RA and PsA cohorts. A significant improvement of clinical outcomes from baseline was seen at 6 and 12 months, regardless prior biologic therapies. In RA DAS28 dropped from 3.95 ±1.5 to 2.77 ±1.3 at 6 months (p=0.0001) and 2.55 ±1.3 at 12 months (p= 0.0001). In PsA DAPSA decreased from 19.1 ±10 to 10.8 ±8 at 6 months (p=0.0001) and 9.6 ±7 at 12 months (p=0.0001). In SpA DAS28 reduced from 3.66 ±1.4 to 2.85 ±1.3 at 6 months (p=0.0001) and 2.55 ±1.1 at 12 months (p=0.0001). Additionally, in SpA BASDAI dropped from 5.3 ±1.6 to 3.8 ±2.3 at 6 months (p=0.0001) and 2.8 ±1.8 at 12 months (p=0.0001).

Conclusion:

In real-life settings CTZ has shown a good effectiveness also in Bio-IR patients. Unlike other TNF-inhibitors, the clinical response and the survival rate were also meaningful in RA patients.

Table:

RA(nr. 180)PsA(nr.189)SpA(nr.137)Age (mean ± SD)54.5 ±1250.6 ±1252.0 ±11Female82.9 %74.6 %56.3 %BMI (mean)25.9 ± 528.4 ± 526.7 ± 5Dis Durat months (mean ± SD)46 ± 14106 ± 8297 ± 92Naive53.9 %32.8 %28.5 %Prior biologics52.9 %75.0 %71.1 %Glucocorticoids55.9 %39.7 %39.4 %DMARDs72.4 %52.4 %43.8 %DAS28 (mean ± SD)4.8 ± 1.53.6 ± 1.23.7 ± 1.3BASDAI (mean ± SD)5.2 ± 2DAPSA (mean ± SD)19.7 ±10HAQ (mean ± SD)1.2 ± 0.71.1 ± 0.61.2 ± 0.7RF/ACPA +72.4 %

Disclosure of Interests:

Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Nicola Maruotti Speakers bureau: Pfizer, Angelo Semeraro Speakers bureau: Sanofi, Roche, AbbVie, BMS, MSD, Novartis, Romano Bucci Speakers bureau: Pfizer, Sanofi, MSD, BMS, Giorgio Carlino Speakers bureau: Pfizer, Janssen, AbbVie, MSD, BMS., Leonardo Santo Consultant of: AbbVie, MSD, Novartis UCB outside this work, Speakers bureau: AbbVie, MSD, Novartis UCB outside this work, Laura Quarta: None declared, Carmelo Zuccaro Consultant of: MSD, AbbVie, Novartis, Pfizer, Janssen outside this work, Speakers bureau: MSD, AbbVie, Novartis, Pfizer, Janssen outside this work, Giuseppina Santacesaria: None declared, Marco Fornaro: None declared, Francesco Paolo Cantatore: None declared

SAT0348 CLINICAL SPECTRUM TIME COURSE OF ANTISYNTHETASE SYNDROME PATIENTS POSITIVE FOR ANTICENTROMERE ANTIBODIES

Background:

ASSD is characterized by antisynthetase antibodies (ARS) and the triad arthritis/myositis/Interstitial Lung Disease (ILD). ASSD and systemic sclerosis (SSc) may share features, like Raynaud’s phenomenon (RP), capillaroscopic alterations, and also some SSc specific autoantibodies.

Objectives:

To evaluate the characteristics of ASSD + for anticentromere antibodies (ACA).

Methods:

Retrospective analysis of clinical and laboratory characteristics of ACA + ASSD. Patients were identified in an established international cohort, randomly matched 1:1 for sex, age, disease duration and ARS positivity with a group of ACA - ASSD.

Results:

18 ACA + ASSD (15 females, 83%, 15 anti-Jo1, 2 anti-PL7, 1 anti-PL12 ARS) patients were identified. In comparison to ACA - group, no differences were observed in disease clinical presentation and evolution. Though, 9 ACA + patients (50%) satisfied the ACR/EULAR 2013 classification criteria for SSc and only 1 in ACA - group (p=0.007) (Table 1).

An incomplete ASSD (lack of at least one triad finding) was observed in 15 patients in both ACA + and – group (p=1). Among these patients, 13 ACA + and 11 ACA – developed de-novo triad finding during disease course (p=0.651). In ACA + group, a de-novo arthritis was observed in 4 patients (vs 1, p=0.565), a de-novo myositis in 8 (vs 5, p=1), and a de-novo ILD in 7 (vs 10, p=1). The prevalence of complete forms was similar between ACA + and – group at both disease onset (3 vs 3, 17%, p=1) and last follow-up, (10 vs 11, 56% vs 61%, p=1). Of note, only 1 patient (6%) for each group died (p=1).

Conclusion:

The clinical spectrum time course of ACA+ and - ASSD is similar, even when ACA + patients could be classified as SSc. By considering the high prevalence of arthritis and myositis we observed, we suggest that ACA+ patients with arthritis and myositis, should be tested for ARS antibodies even when an ASSD is not clearly suspected.

References:

[1]Mirrakhimov AE. Curr Med Chem 2015;22:1963–75

[2]Cavagna L. J Clin Med 2019;8:E2013

[3]Sebastiani M. J Rheum 2019:46:279-84

[4]van den Hoogen F. Ann Rheum Dis 2013;72:1747-55

Table 1.

Patients characteristics. IQR, interquartile range; ILD, interstitial Lung Disease; SSc, systemic sclerosis

ACA+ (18)ACA - (18)pAge (years) at disease onset (median, IQR)47 (37-63)47 (39-63)0.834Disease duration (months) (median, IQR)81 (62-169)77 (58-165)0.486anti Ro52antibody (%)12(67)11 (61)1Arthritis onset10 (56)13 (72)0.489Arthritis last follow-up (%)14 (78)14 (78%)1Myositis onset (%)7 (39)11 (61)0.318Myositis last follow-up (%)15 (83)16 (89)1ILD onset (%)9 (50)6 (33)0.5ILD last follow-up (%)16 (89)16 (89)1Complete form onset (%)3 (17)3 (17)1Complete form last follow-up (%)10 (56)11 (61)1Raynaud phenomenon (%)13 (72)9 (50)0.305Mechanic’s hands (%)6 (33)7 (38)1Teleangectasias (%)2 (11)0 (0)0.486Cutaneous sclerosis (%)510.177Acral ulcers (%)1 (6)0 (0)1Scleroderma pattern at NVC8 (44)7 (39)1Pulmonary arterial hypertension (%)3 (17)2 (11)12013 ACR/EULAR SSc classification criteria9 (50)1 (6)0.007

Disclosure of Interests:

Giovanni Zanframundo: None declared, Gianluca Sambataro: None declared, Veronica Codullo: None declared, Alessandro Biglia: None declared, Emanuele Bozzalla Cassione: None declared, Elena Bravi: None declared, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Marco Fornaro: None declared, Konstantinos Triantafyllias: None declared, Alberto Pesci: None declared, Paola Tomietto: None declared, Øyvind Molberg: None declared, Salvatore Scarpato: None declared, Reinhard Voll: None declared, Marco Matucci-Cerinic Grant/research support from: Actelion, MSD, Bristol-Myers Squibb, Speakers bureau: Acetelion, Lilly, Boehringer Ingelheim, Miguel A González-Gay Grant/research support from: Pfizer, Abbvie, MSD, Speakers bureau: Pfizer, Abbvie, MSD, Carlomaurizio Montecucco: None declared, Lorenzo Cavagna: None declared

OP0199 POINTS TO CONSIDER WHEN ANALYSING AND REPORTING COMPARATIVE EFFECTIVENESS RESEARCH WITH OBSERVATIONAL DATA IN RHEUMATOLOGY

Background:

Comparing drug effectiveness in observational settings is hampered by several major threats, among them confounding and attrition bias bias (patients who stop treatment no longer contribute information, which may overestimate true drug effectiveness).

Objectives:

To present points to consider (PtC) when analysing and reporting comparative effectiveness with observational data in rheumatology (EULAR-funded taskforce).

Methods:

The task force comprises 18 experts: epidemiologists, statisticians, rheumatologists, patients, and health professionals.

Results:

A systematic literature review of methods currently used for comparative effectiveness research in rheumatology and a statistical simulation study were used to inform the PtC (table). Overarching principles focused on defining treatment effectiveness and promoting robust and transparent epidemiological and statistical methods increase the trustworthiness of the results.

Points to consider

Reporting of comparative effectiveness observational studies must follow the STROBE guidelinesAuthors should prepare a statistical analysis plan in advanceTo provide a more complete picture of effectiveness, several outcomes across multiple health domains should be comparedLost to follow-up from the study sample must be reported by the exposure of interestThe proportion of patients who stop and/or change therapy over time, as well as the reasons for treatment discontinuation must be reportedCovariates should be chosen based on subject matter knowledge and model selection should be justifiedThe study baseline should be at treatment initiation and a description of how covariate measurements relate to baseline should be includedThe analysis should be based on all patients starting a treatment and not limited to patients remaining on treatment at a certain time pointWhen treatment discontinuation occurs before the time of outcome assessment, this attrition should be taken into account in the analysis.Sensitivity analyses should be undertaken to explore the influence of assumptions related to missingness, particularly in case of attrition

Conclusion:

The increased use of real-world comparative effectiveness studies makes it imperative to reduce divergent or contradictory results due to biases. Having clear recommendations for the analysis and reporting of these studies should promote agreement of observational studies, and improve studies’ trustworthiness, which may also facilitate meta-analysis of observational data.

Disclosure of Interests:

Delphine Courvoisier: None declared, Kim Lauper: None declared, Sytske Anne Bergstra: None declared, Maarten de Wit Grant/research support from: Dr. de Wit reports personal fees from Ely Lilly, 2019, personal fees from Celgene, 2019, personal fees from Pfizer, 2019, personal fees from Janssen-Cilag, 2017, outside the submitted work., Consultant of: Dr. de Wit reports personal fees from Ely Lilly, 2019, personal fees from Celgene, 2019, personal fees from Pfizer, 2019, personal fees from Janssen-Cilag, 2017, outside the submitted work., Speakers bureau: Dr. de Wit reports personal fees from Ely Lilly, 2019, personal fees from Celgene, 2019, personal fees from Pfizer, 2019, personal fees from Janssen-Cilag, 2017, outside the submitted work., 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, Thomas Frisell: None declared, Kimme Hyrich Grant/research support from: Pfizer, UCB, BMS, Speakers bureau: Abbvie, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Joanna KEDRA: None declared, Pedro M Machado Consultant of: PMM: Abbvie, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Speakers bureau: PMM: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Maria Jose Santos Speakers bureau: Novartis and Pfizer, Tanja Stamm Grant/research support from: AbbVie, Roche, Consultant of: AbbVie, Sanofi Genzyme, Speakers bureau: AbbVie, Roche, Sanofi, Simon Stones Consultant of: I have been a paid consultant for Envision Pharma Group and Parexel. This does not relate to this abstract., Speakers bureau: I have been a paid speaker for Actelion and Janssen. These do not relate to this abstract., Anja Strangfeld Speakers bureau: AbbVie, BMS, Pfizer, Roche, Sanofi-Aventis, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Axel Finckh Grant/research support from: Pfizer: Unrestricted research grant, Eli-Lilly: Unrestricted research grant, Consultant of: Sanofi, AB2BIO, Abbvie, Pfizer, MSD, Speakers bureau: Sanofi, Pfizer, Roche, Thermo Fisher Scientific

THU0398 DRUG RETENTION RATES AND TREATMENT OUTCOMES IN 1860 AXIAL SPONDYLOARTHRITIS PATIENTS TREATED WITH SECUKINUMAB IN ROUTINE CLINICAL PRACTICE IN 13 EUROPEAN COUNTRIES IN THE EUROSPA RESEARCH COLLABORATION NETWORK

Background:

To determine the real-life 6- and 12-month secukinumab effectiveness in Europe overall, as well as stratified by prior biologic disease-modifying anti-rheumatic drug (bDMARD)/targeted synthetic (ts)DMARD use.

Objectives:

Real-life data from axSpA patients treated with secukinumab from 13 countries in the European Spondyloarthritis (EuroSpA) Research Collaboration Network were pooled. We calculated proportions of patients achieving Bath Ankylosing Spondylitis Disease Activity Score (BASDAI) <2/<4 and Ankylosing Spondylitis Disease Activity Score (ASDAS) <1.3/<2.1 at 6 and 12 months, including with LUNDEX adjustments (crude value adjusted for drug retention). Retention rates were compared between b/tsDMARD naïve, 1 prior and ≥2 prior b/tsDMARD users with Kaplan-Meier analyses with log rank test and disease states by Chi-square test.

Methods:

A total of 1860 axSpA patients were included (Table 1). Overall 6/12-month secukinumab retention rates were 82%/72% and higher in bionaïve patients (Table 2, Figure). Significant differences in retention rates in-between the registries were found. Inactive disease/low-disease-activity (LDA) were achieved more often in bionaïve patients (Table 2).

Table 1All patients (n=1860)b/tsDMARD naïve (n=414)1 prior b/tsDMARD (n=448)≥2 prior b/tsDMARDs (n=998)Age (years), mean (SD)47 (12)45 (12)47 (12)48 (12)Men, %57%68%58%49%Years since diagnosis, mean (SD)10 (9)8 (9)10 (9)11 (9)Current smokers, %25 %27%25%23%Patient’s global (0-100), median (IQR)70 (50-81)80 (60-90)64 (50-80)70 (50-82)Physician’s global (0-100), median (IQR)45 (25-63)64 (43-78)45 (22-60)40 (20-58)C reactive protein (mg/L), median (IQR)8 (3-25)15 (5-31)7 (3-25)6 (2-22)Erythrocyte sedimentation rate (mm/h), median (IQR)22 (9-44)30 (14-44)24 (8-45)18 (8-42)Pain (0-100), median (IQR)70 (50-81)80 (65-90)65 (49-80)70 (50-80)BASDAI, median (IQR)6.2 (4.6-7.6)6.8 (5.2-8.0)5.9 (4.2-7.2)6.1 (4.4-7.6)BASFI, median (IQR)5.5 (3.2-7.3)6.1 (3.2-7.6)4.8 (2.8-6.8)5.5 (3.3-7.2)ASDAS, median (IQR)3.6 (2.9-4.3)4.2 (3.5-4.8)3.5 (2.7-4.2)3.5 (2.8-4.2)Table 2MonthsAll patients (n=1860)b/tsDMARD naïve (n=414)1 prior b/tsDMARD (n=448)≥2 prior b/tsDMARDs (n=998)p-value*Secukinumab retention rate, % (95%CI)682% (80-84%)90% (87-93%)83% (79-86%)78% (76-81%)0.0011272% (69-74%)84% (81-88%)73% (69-78%)66% (63-69%)<0.001BASDAI <2, % Crude626373518<0.001 LUNDEX adjusted21342813<0.001 Crude1225412918<0.001 LUNDEX adjusted16311811<0.001BASDAI <4, % Crude651716040<0.001 LUNDEX adjusted40654730<0.001 Crude1251765639<0.001 LUNDEX adjusted32573623<0.001ASDAS <1.3, % Crude69131360.001 LUNDEX adjusted712115<0.001 Crude1211181570.002 LUNDEX adjusted713940.002ASDAS <2.1, % Crude6243226200.002 LUNDEX adjusted19292115<0.001 Crude1227442721<0.001 LUNDEX adjusted17331712<0.001

*Comparisons between b/tsDMARD naïve, 1 prior and ≥2 prior b/tsDMARD users were performed with Kaplan-Meier with log-rank test or Chi-Square test, as appropriate

Conclusion:

In this real-life study of 1860 patients with axSpA in 13 European countries secukinumab retention was high and significantly higher for bionaïve patients. Overall, a higher proportion of bionaïve than previous b/tsDMARD users achieved inactive disease/LDA.

Figure

Acknowledgments:

Novartis and IQVIA for supporting the EuroSpA RCN

Disclosure of Interests:

Brigitte Michelsen Grant/research support from: Research support from Novartis, Consultant of: Consulting fees Novartis, Ulf Lindström: None declared, Catalin Codreanu Consultant of: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Speakers bureau: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Adrian Ciurea Consultant of: Consulting and/or speaking fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Merck Sharp & Dohme, Novartis and Pfizer., Jakub Zavada Speakers bureau: Abbvie, UCB, Sanofi, Elli-Lilly, Novartis, Zentiva, Accord, Anne Gitte Loft Grant/research support from: Novartis, Consultant of: AbbVie, MSD, Novartis, Pfizer and UCB, Speakers bureau: AbbVie, MSD, Novartis, Pfizer and UCB, Manuel Pombo-Suarez Consultant of: Janssen, Lilly, MSD and Sanofi., Speakers bureau: Janssen, Lilly, MSD and Sanofi., Fatos Onen: None declared, Tore K. Kvien Grant/research support from: Received grants from Abbvie, Hospira/Pfizer, MSD and Roche (not relevant for this abstract)., Consultant of: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Paid instructor for: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Speakers bureau: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Maria Jose Santos Speakers bureau: Novartis and Pfizer, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Anna-Mari Hokkanen: None declared, Björn Gudbjornsson Speakers bureau: Novartis and Amgen, Johan Askling Grant/research support from: JA acts or has acted as PI for agreements between Karolinska Institutet and the following entities, mainly in the context of the ARTIS national safety monitoring programme of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB Pharma, Ruxandra Ionescu Consultant of: Consulting fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Speakers bureau: Consulting and speaker fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Michael Nissen Grant/research support from: Abbvie, Consultant of: Novartis, Lilly, Abbvie, Celgene and Pfizer, Speakers bureau: Novartis, Lilly, Abbvie, Celgene and Pfizer, Karel Pavelka Consultant of: Abbvie, MSD, BMS, Egis, Roche, UCB, Medac, Pfizer, Biogen, Speakers bureau: Abbvie, MSD, BMS, Egis, Roche, UCB, Medac, Pfizer, Biogen, Carlos Sánchez-Piedra: None declared, Servet Akar: None declared, Joe Sexton: None declared, Matija Tomsic: None declared, Helena Santos Speakers bureau: AbbVie, Eli-Lilly, Janssen, Pfizer, Novartis, Marco Sebastiani: None declared, Jenny Osterlund: None declared, Arni Jon Geirsson: None declared, Gareth T. Jones Grant/research support from: Pfizer, AbbVie, UCB, Celgene and GSK., 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, Stylianos Georgiadis Grant/research support from: Novartis, Cecilie Heegaard Brahe Grant/research support from: Novartis, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Merete L. Hetland Grant/research support from: BMS, MSD, AbbVie, Roche, Novartis, Biogen and Pfizer, Consultant of: Eli Lilly, Speakers bureau: Orion Pharma, Biogen, Pfizer, CellTrion, Merck and Samsung Bioepis, 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

FRI0230 THE 2009-2019 SURVIVAL AND MORTALITY PREDICTORS IN A LARGE MULTICENTRE SYSTEMIC SCLEROSIS COHORT

Background:

Systemic sclerosis (SSc) is one of the connective tissue diseases with the poorer prognosis and disease-related causes, particularly pulmonary fibrosis, PAH and cardiac involvement, accounting the most deaths.

Objectives:

This multicentre study aimed to evaluate the global survival and any predictor of mortality in a large multicentric cohort of SSc patients.

Methods:

We performed a retrospective analysis examining the medical records of our longitudinal SSc cohorts with a median (IQR) follow-up of 11 (6-18) years from 3 Scleroderma Units since January 2009. All clinical, laboratory and instrumental findings have been recorded and analyzed using Chi-squared tests, Kaplan-Meier curves, log-rank tests, and Cox proportional hazards models.

Results:

Data from 750 SSc patients (91.9% female; mean (SD) age at first Non-Raynaud symptom 48.4 (15.3) years, median (IQR) disease duration 3 (0-8) years; diffuse cutaneous involvement 162 (21.6%) patients) fulfilling the 1980 ARA and/or 2013 ACR/EULAR classification criteria, were collected. All patients were positive for ANA, anti-Topo-I Abs were found in 235 (31.3%) and Cenp-B Abs in 300 (40%) patients. 98 (13.1%) patients were positive to other Abs (Anti-RNA polymerase III, anti-Pm/Scl) and anti-ENA were negative/unknown for 117 (15.6%) patients. Interstitial lung disease (ILD) was present in 202 (26.9%), pulmonary arterial hypertension (PAH) was found in 29 (3.9%), and 50/750 (6.7%) patients presented pulmonary hypertension combined with ILD (PH-ILD). The overall 10-years survival was 93.1% and, it was significantly impaired by the presence of ILD, PAH or PH-ILD [Figure]. The univariate analysis showed that female gender, higher age at first Non-Raynaud symptom, earlier referral to a tertiary Scleroderma center, absence of any ENA antibodies, and PH-ILD presence were survival predictors. After multivariate analysis the significance of PH-ILD was lost [Table]. Disease duration, basal Rodnan skin score, smoking, renal or gastrointestinal comorbidities, NYHA functional class, steroid or immune-suppressive treatments did not reach the statistically significance.

Conclusion:

Our study demonstrated a global 10-years survival rate over 93%. Male patients and rapid evolution of Non-Raynaud symptoms represent the main death predictors in our SSc cohort. A rapid referral to a tertiary rheumatological centre and early treatment with effective agents are associated to a better prognosis.

Figure.

Kaplan-Meier curves for 5-years survival in SSc patients (Log-rank 8.96, p=0.03).

Table.

Prognostic factors for 10-years survival at univariate and multivariate analysis.

UNIVARIATE ANALYSISMULTIVARIATE ANALYSISHR95%ICPHR95%ICPFemale gender0.350.15-0.810.010.310.15-0.660.002Age at first Non-Raynaud symptom1.071.04-1.10.0011.081.05-1.110.001Time referral to a tertiary SSc centre0.830.76-0.920.0010.840.77-0.930.001Absence of any ENA antibodies0.080.01-0.620.010.090.01-0.710.02PH-ILD presence2.61.01-6.820.042.40.93-6.10.069

Disclosure of Interests:

Fabio Cacciapaglia Speakers bureau: BMS; Roche; Pfizer; Abbvie, Enrico De Lorenzis: None declared, Addolorata Corrado: None declared, Silvia Laura Bosello Speakers bureau: Abbvie, Pfizer, Boehringer, Marco Fornaro: None declared, Fabio Montini: None declared, Livio Urso: None declared, Lucrezia Verardi: None declared, Alberto Altomare: None declared, Francesco Paolo Cantatore: None declared, Elisa Gremese Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck Sharp & Dohme, Novartis, Sanofi, UCB, Roche, Pfizer, Speakers bureau: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck Sharp & Dohme, Novartis, Sanofi, UCB, Roche, Pfizer, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD

FRI0239 ANTI-NXP2 ANTIBODIES: CLINICAL AND SEROLOGICAL ASSOCIATIONS IN A MULTICENTRIC ITALIAN STUDY

Background:

anti-NXP2 antibodies is considered a serological marker of dermatomyositis (DM), with calcinosis, severe myositis and, in some series, cancer. Historically, these associations have been detected with immunoprecipitation (IP), but in the last few years commercial lineblot (LB) assay have been released.

Objectives:

to analyze the clinical features associated to anti-NXP2 antibodies, including the onset of concomitant cancers, both with LB and homemade IP

Methods:

clinical and serological data from medical charts of 213 patients with a diagnosis of inflammatory miosidites without anti-NXP2 (NXP2-), followed-up by two third-level Centers, and 61 anti-NXP2+ patients from 10 Rheumatological centers were analyzed. Anti-myositis specific (MSA) and anti-myositis associated antibodies (MAA) were detected in single centers by LB (Euroimmun Autoimmune Inflammatory Myopathies 16 antigens). Anti-NXP2 was confirmed by protein and RNA IP, as previously described (1)

Results:

clinical diagnosis of anti-NXP2+ positive with LB were 42 DM, 11 PM, inclusion body myositis (IBM) 4, necrotizing myositis and overlap (OM) 1 each. Anti-NXP2+ showed a lower age at onset (p<0.0001) more frequent diagnosis of DM (68.8%vs30%,OR5.2) and IBM (6.5%vs0.49%,OR14.8), typical skin manifestations, myositis (93%vs79% OR3.3), concomitant presence of another MSA (12.7%vs2%, OR6.41) and lower rate of features associated with OM or anti-synthetase syndrome. Serum from 49 NXP2+ was available and IP analysis was made with the confirmation of NXP2 in 31 sera (63.2%) with the following diagnosis: DM 27 cases, PM 3, IBM 1. Whilst the majority of the associations were confirmed comparing NXP2LB+/IP+ with the IIM NXP2-, some peculiar associations were found significant only for the double positive patients: dysphagia (53%vs 30%,OR 2.56) and calcinosis (22%vs6.5% OR4) whereas IBM diagnosis and the presence of concomitant MSA antibodies were lost. Survival time from cancer onset is shown in figure.

IP did not confirmed anti-NXP2 antibodies in 18 sera: in 4 cases at least one MSA/MAA was identified by IP; these 18 patients did not show differences when compared with 213 anti-NXP2-.

Conclusion:

Protein IP confirmed anti-NXP2 antibodies in 63% of LB+ sera. Double positive cases showed more typical DM features and rarely occurred in IIM not DM. Anti-NXP2 positivity by LB should be confirmed by other methods in order to correctly diagnose and characterize IIM patients.

References:

[1]Arthritis Res Ther 2012,30;14:R97

Acknowledgments:

Forum Italiano per la Ricerca Malattie Autoimmuni (FIRMA)

Disclosure of Interests:

Micaela Fredi: None declared, Ilaria Cavazzana: None declared, Angela Ceribelli: None declared, Maria Grazia Lazzaroni: None declared, Simone Barsotti: None declared, Maurizio Benucci: None declared, Lorenzo Cavagna: None declared, Ludovico De Stefano: None declared, Andrea Doria Consultant of: GSK, Pfizer, Abbvie, Novartis, Ely Lilly, Speakers bureau: UCB pharma, GSK, Pfizer, Janssen, Abbvie, Novartis, Ely Lilly, BMS, Giacomo Emmi: None declared, Marco Fornaro: None declared, Federica Furini: None declared, Roberto Gerli: None declared, Maria Grazia Giudizi: None declared, Marcello Govoni: None declared, Anna Ghirardello: None declared, Luca Iaccarino Speakers bureau: GSK, Pfizer, Janssen, Novartis, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Maria Infantino: None declared, Alessandro Mathieu: None declared, Emiliano Marasco: None declared, Paola Migliorini: None declared, Boaz Palterer: None declared, paola parronchi: None declared, Matteo Piga: None declared, Federico Pratesi: None declared, Antonella Radice: None declared, Carlo Selmi: None declared, Valeria Riccieri: None declared, Marilin Tampoia: None declared, Giovanni Zanframundo: None declared, Angela Tincani: None declared, Franco Franceschini: None declared

OP0109 CO-MEDICATION WITH A CONVENTIONAL SYNTHETIC DMARD IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS IS ASSOCIATED WITH IMPROVED RETENTION OF TNF INHIBITORS: RESULTS FROM THE EUROSPA COLLABORATION

Background:

Axial spondylarthritis (axSpA) patients treated with a tumour necrosis factor inhibitor (TNFi) may receive a concomitant conventional synthetic disease-modifying anti-rheumatic drug (csDMARD), although the value of combination therapy remains unclear.

Objectives:

Describe the proportion and phenotype of patients with axSpA initiating their first TNFi as monotherapy compared to TNFi+csDMARD combination therapy, and to compare the 1-year TNFi retention between the two groups.

Methods:

Data from 13 European registries was collected. Two exposure treatment groups were defined: TNFi monotherapy at baseline (=TNFi start date) and TNFi+csDMARD combination therapy. TNFi retention rates were assessed with Kaplan-Meier curves for each country and combined. Hazard ratios (HR, 95% CI) for discontinuing the TNFi were obtained with Cox models: (i) crude; adjusted for (ii) country, and (iii) country, sex, age, calendar year, disease duration and BASDAI. Participating countries were dichotomized into two strata, depending on their 1-year retention rate being above (stratum A) or below (stratum B) the average retention rate across all countries.

Results:

22,196 axSpA patients were included with 34% on TNFi+csDMARD combination therapy. Baseline characteristics are presented in table 1. Overall, the crude TNFi retention rate was marginally longer in the combination therapy group (80% (79-81%)) compared to the monotherapy group (78% (77-79%)) and was primarily driven by differences in stratum B (fig. 1). TNFi retention rates varied significantly across countries (range:-11.0% to +11.3%), with a clear distinction between the 2 strata. The HRs for discontinuation over 1-year (reference=TNFi monotherapy) in the 3 models were: (i) 0.88 (0.82-0.93), (ii) 0.87 (0.82-0.92), (iii) 0.88 (0.82-0.93).

Table 1Baseline characteristicsAll patients(n=22196)Country stratum ACountry stratum BTNFi mono(n=4940)csDMARD + TNFi(n=2547)TNFi mono(n=9693)csDMARD + TNFi(n=5016)Age (years), mean (SD)42.6 (12.5)43.4 (12.0)42.8 (12.2)41.6 (12.7)43.7 (12.7)Females, %41.137.738.242.044.2Disease duration (yrs), mean (SD)5.7 (8.0)6.2 (7.7)6.7 (7.4)4.9 (8.2)6.1 (8.2)Enthesitis, %50.316.733.957.859.7SJC-28, median (IQR)0 (0-1)0 (0-0)0 (0-2)0 (0-0)0 (0-2)VAS pain (0-100), mean (SD)60.9 (24.5)63.3 (26.5)67.8 (23.3)60.2 (23.4)57.2 (24.3)CRP (mg/L), median (IQR)8 (3-20)7.8 (2-20)18 (6.7-32.6)6.0 (2.7-15)8.0 (3-22)BASDAI (0-10), mean (SD)5.7 (2.1)5.7 (2.2)6.2 (2.1)5.6 (2.0)5.4 (2.2)BASFI (0-10), mean (SD)4.4 (2.5)4.4 (2.6)4.9 (2.5)4.3 (2.4)4.2 (2.9)ASDAS, mean (SD)3.5 (1.1)3.7 (1.0)4.0 (1.0)3.3 (1.0)3.3 (1.1)On Infliximab, %25.721222436Baseline csDMARD use, %-Methotrexate045063-Sulfasalazine068033-Leflunomide0801

Conclusion:

Considerable differences were observed across countries in the use of combination therapy and TNFi retention in axSpA patients. The overall 1-year TNFi retention was higher with csDMARD co-therapy compared to TNFi monotherapy. TNFi monotherapy had a 12-13% higher risk of treatment discontinuation.

Acknowledgments:

Novartis Pharma AG and IQVIA

MN and BD participated equally

Disclosure of Interests:

Michael Nissen Grant/research support from: Abbvie, Consultant of: Novartis, Lilly, Abbvie, Celgene and Pfizer, Speakers bureau: Novartis, Lilly, Abbvie, Celgene and Pfizer, Bénédicte Delcoigne: None declared, Daniela Di Giuseppe: None declared, Lennart T.H. Jacobsson Consultant of: AbbVie, Eli Lilly, Janssen, Novartis and Pfizer, Karen Fagerli: None declared, Anne Gitte Loft Grant/research support from: Novartis, Consultant of: AbbVie, MSD, Novartis, Pfizer and UCB, Speakers bureau: AbbVie, MSD, Novartis, Pfizer and UCB, Adrian Ciurea Consultant of: Consulting and/or speaking fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Merck Sharp & Dohme, Novartis and Pfizer., Dan Nordström Consultant of: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Speakers bureau: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Maria Jose Santos Speakers bureau: Novartis and Pfizer, Manuel Pombo-Suarez Consultant of: Janssen, Lilly, MSD and Sanofi., Speakers bureau: Janssen, Lilly, MSD and Sanofi., Björn Gudbjornsson Speakers bureau: Novartis and Amgen, Heřman Mann: None declared, Nurullah Akkoc: None declared, Catalin Codreanu Consultant of: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Speakers bureau: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, 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, Brigitte Michelsen: None declared, Gary Macfarlane: None declared, Merete L. Hetland Grant/research support from: BMS, MSD, AbbVie, Roche, Novartis, Biogen and Pfizer, Consultant of: Eli Lilly, Speakers bureau: Orion Pharma, Biogen, Pfizer, CellTrion, Merck and Samsung Bioepis, Matija Tomsic: None declared, Burkhard Moeller: None declared, Pedro Ávila-Ribeiro Grant/research support from: Novartis, Carlos Sánchez-Piedra: None declared, Heikki Relas Grant/research support from: Abbvie., Consultant of: Abbvie, Celgene, and Pfizer., Speakers bureau: Abbvie, Celgene, and Pfizer., Arni Jon Geirsson: None declared, Lucie Nekvindova: None declared, Gozde Yildirim Cetin Speakers bureau: AbbVie, Novartis, Pfizer, Roche, UCB, MSD, Ruxandra Ionescu Consultant of: Consulting fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Speakers bureau: Consulting and speaker fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Niels Steen Krogh: None declared, Johan Askling Grant/research support from: JA acts or has acted as PI for agreements between Karolinska Institutet and the following entities, mainly in the context of the ARTIS national safety monitoring programme of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB Pharma, Bente Glintborg Grant/research support from: Grants from Pfizer, Biogen and Abbvie, Ulf Lindström: None declared

OP0198 A SYSTEMATIC REVIEW TO INFORM THE EULAR POINTS TO CONSIDER WHEN ANALYSING AND REPORTING COMPARATIVE EFFECTIVENESS RESEARCH WITH OBSERVATIONAL DATA IN RHEUMATOLOGY

Background:

Comparative effectiveness studies using observational data are increasingly used. Despite their high potential for bias, there are no detailed recommendations on how these studies should best be analysed and reported in rheumatology.

Objectives:

To conduct a systematic literature review of comparative effectiveness research in rheumatology to inform the EULAR task force developing points to consider when analysing and reporting comparative effectiveness research with observational data.

Methods:

All original articles comparing drug effectiveness in longitudinal observational studies of ≥100 patients published in key rheumatology journals (Scientific Citation Index > 2) between 1.01.2008 and 25.03.2019 available in Ovid MEDLINE® were included. Titles and abstracts were screened by two reviewers for the first 1000 abstracts and independently checked to ensure sufficient agreement has been reached. The main information extracted included the types of outcomes used to assess effectiveness, and the types of analyses performed, focusing particularly on confounding and attrition.

Results:

9969 abstracts were screened, with 218 articles proceeding to full-text extraction (Figure 1), representing a number of rheumatic and musculoskeletal diseases. Agreement between the two reviewers for the first 1000 abstracts was 92.7% with a kappa of 0.6. The majority of the studies used several outcomes to evaluate effectiveness (Figure 2A). Most of the studies did not explain how they addressed missing data on the covariates (70%) (Figure 2B). When addressed (30%), 44% used complete case analysis and 10% last observation carried forward (LOCF). 25% of studies did not adjust for confounding factors and there was no clear correlation between the number of factors used to adjust and the number of participants in the studies. An important number of studies selected covariates using bivariate screening and/or stepwise selection. 86% of the studies did not acknowledge attrition (Figure 2C). When trying to correct for attrition (14%), 38% used non-responder (NR) imputation, 24% used LUNDEX1, a form of NR imputation, and 21% LOCF.

Conclusion:

Most of studies used multiple outcomes. However, the vast majority did not acknowledge missing data and attrition, and a quarter did not adjust for any confounding factors. Moreover, when attempting to account for attrition, several studies used methods which potentially increase bias (LOCF, complete case analysis, bivariate screening…). This systematic review confirms the need for the development of recommendations for the assessment and reporting of comparative drug effectiveness in observational data in rheumatology.

References:

[1]Kristensen et al. A&R. 2006 Feb;54(2):600-6.

Acknowledgments:

Support of the Standing Committee on Epidemiology and Health Services Research

Disclosure of Interests:

Kim Lauper: None declared, Joanna KEDRA: None declared, Maarten de Wit Grant/research support from: Dr. de Wit reports personal fees from Ely Lilly, 2019, personal fees from Celgene, 2019, personal fees from Pfizer, 2019, personal fees from Janssen-Cilag, 2017, outside the submitted work., Consultant of: Dr. de Wit reports personal fees from Ely Lilly, 2019, personal fees from Celgene, 2019, personal fees from Pfizer, 2019, personal fees from Janssen-Cilag, 2017, outside the submitted work., Speakers bureau: Dr. de Wit reports personal fees from Ely Lilly, 2019, personal fees from Celgene, 2019, personal fees from Pfizer, 2019, personal fees from Janssen-Cilag, 2017, outside the submitted work., 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, Thomas Frisell: None declared, Kimme Hyrich Grant/research support from: Pfizer, UCB, BMS, Speakers bureau: Abbvie, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Pedro M Machado Consultant of: PMM: Abbvie, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Speakers bureau: PMM: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Maria Jose Santos Speakers bureau: Novartis and Pfizer, Tanja Stamm Grant/research support from: AbbVie, Roche, Consultant of: AbbVie, Sanofi Genzyme, Speakers bureau: AbbVie, Roche, Sanofi, Simon Stones Consultant of: I have been a paid consultant for Envision Pharma Group and Parexel. This does not relate to this abstract., Speakers bureau: I have been a paid speaker for Actelion and Janssen. These do not relate to this abstract., Anja Strangfeld Speakers bureau: AbbVie, BMS, Pfizer, Roche, Sanofi-Aventis, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Axel Finckh Grant/research support from: Pfizer: Unrestricted research grant, Eli-Lilly: Unrestricted research grant, Consultant of: Sanofi, AB2BIO, Abbvie, Pfizer, MSD, Speakers bureau: Sanofi, Pfizer, Roche, Thermo Fisher Scientific, Sytske Anne Bergstra: None declared, Delphine Courvoisier: None declared