Josef S Smolen's research while affiliated with Hospital for Special Surgery and other places

Background In patients (pts) with rheumatoid arthritis (RA), high rheumatoid factor (RF) levels are a poor prognostic factor and associated with higher disease activity, risk of progression, and decreased response to monoclonal antibodies (mAbs) targeting tumour necrosis factor (TNF).1,2,3 Recent data suggest pts with RA and high RF levels have better clinical responses to TNF inhibitors (TNFis) without a fragment crystallisable (Fc) portion, such as certolizumab pegol (CZP), compared to TNFis with an Fc.4,5 However, in pts with RA and high RF levels who have had previous inadequate responses or intolerance to TNFis, data on response to CZP are limited. These pts have poorer responses to subsequent biologic or targeted synthetic disease-modifying anti-rheumatic drugs (DMARDs).⁶ Objectives To assess impact of RF levels and previous therapies on CZP efficacy outcomes in pts with RA, in a post hoc analysis of the REALISTIC trial. Methods REALISTIC (NCT00717236) was double-blind and placebo-controlled to Week (Wk) 12.⁷ Pts with inadequately controlled RA were randomised 4:1 to receive either CZP (400 mg subcutaneous [sc] at Wks 0, 2 and 4, followed by 200 mg sc every 2 weeks) or placebo (PBO) for a 12-wk period, after which all pts received open-label CZP. We report the following outcomes to Wk 36: Disease Activity Score 28 C-reactive protein (DAS28-CRP) score, DAS28-CRP <2.6, Clinical Disease Activity Index (CDAI) score, and CDAI remission (CDAI ≤2.8). Results are stratified by baseline RF level (≤ quartile 3 [Q3] vs >Q3) and prior TNFi use; data are reported as observed case. Results Overall, 751 CZP-randomised pts (RF ≤Q3 [<180 kU/L]: n=560, RF >Q3 [≥180 kU/L]: n=191) and 179 PBO-randomised pts (RF ≤Q3: n=135, RF >Q3: n=44) were included. Baseline demographics were similar between pts with RF ≤Q3 and >Q3, including number of previous DMARDs (Table 1).At Wk 12, TNFi-naïve pts treated with CZP had lower DAS28-CRP scores than PBO-receiving pts regardless of RF levels (CZP, mean [SD]: RF ≤Q3: 3.9 [1.3], RF >Q3: 3.8 [1.3], PBO: RF ≤Q3: 4.9 [1.4], RF >Q3: 4.9 [1.2] PBO), indicating no effect of RF on response to CZP. Interestingly, in pts with prior TNFi use (TNFi-IR), larger differences between DAS28-CRP scores were seen in pts with RF >Q3 than RF ≤Q3 for PBO-randomized pts (RF ≤Q3 4.7 [1.4], RF >Q3, 5.7 [1.4]) compared with CZP (RF ≤Q3: 4.2 [1.4], RF >Q3: 4.2 [1.5]). Responses increased to Wk 36 in all CZP-randomised groups. At Wk 36, the proportion of CZP-randomised pts who achieved DAS28-CRP<2.6 was similar across RF levels and prior TNFi use (Figure 1). At Wk 12, TNFi-naïve CZP-randomised pts also had lower CDAI scores than PBO-randomised pts, regardless of RF levels (RF ≤Q3: 18.6 [13.9] CZP vs 27.3 [15.5] PBO; RF >Q3: 16.7 [12.1] CZP vs 26.9 [12.9] PBO). In TNFi-IR pts, larger differences between CDAI scores for CZP vs PBO were seen in pts with RF >Q3 compared with RF ≤Q3 (RF ≤Q3, mean [SD]: 21.6 [15.4] CZP vs 26.0 [15.8] PBO; RF >Q3, 20.4 [14.9] CZP vs 35.4 [18.2] PBO). Responses increased to Wk 36 in all CZP-randomised groups. The proportion of pts who achieved CDAI remission at Wk 36 was similar in CZP-randomised pts across RF levels and prior TNFi use (Figure 1). Conclusion In PBO-randomised TNF-IR pts responses were lower in the high RF group, compared with low RF (≤Q3). In contrast, pts with RA and high RF levels who were treated with CZP had similar clinical responses to those with low RF levels, indicating that RF does not influence the response to CZP. These data expand previous notions⁵ to a TNFi-IR population. Results may have treatment choice implications in pts with RA and high RF levels who have had inadequate responses to previous TNFi treatment. REFERENCES [1] Vastesaeger N. et al, Rheum 2009;48:1114–21. 2 Cuchacovich M. et al, Clin Rheumatol 2014;33(12):1707–14. 3 Takeuchi T. et al, Arthritis Res 2017;19:194. 4 Nakayama Y. Rheumatol Int 2022;42:1227–1234. 5 Smolen J. Arthritis Rheumatol 2023;75(suppl 9). 6 Pappas D.A. et al, Rheumatol Int 2021;41:585–593; 7 Weinblatt M.E. et al, Rheum 2012;51:2204–14. • Download figure • Open in new tab • Download powerpoint • Download figure • Open in new tab • Download powerpoint Acknowledgements Funded by UCB Pharma. Medical writing support provided by Costello Medical and funded by UCB Pharma. Disclosure of Interests Josef S. Smolen Honoraria from: AbbVie, Amgen, AstraZeneca, Astro, Bristol-Myers Squibb, Celgene, Celltrion, Chugai, Gilead, ILTOO, Janssen, Eli Lilly, Merck Sharp & Dohme, Novartis-Sandoz, Pfizer, R-Pharma, Roche, Samsung, Sanofi and UCB Pharma, Research grants from: Abbvie, AstraZeneca, Eli Lilly, Novartis and Roche, Ted Mikuls Consultant for: Horizon Therapeutics; Pfizer, Sanofi and UCB Pharma. Royalties from: Wolters Kluwer Health (UpToDate) and Elsevier., Research support from: Horizon Therapeutics, James Galloway Abbvie, Galapagos, Janssen, Eli Lilly, Pfizer and UCB Pharma, GSK, Pfizer, Ulf Müller-Ladner UCB Pharma, Jeffrey R Curtis Grant/research and consultancy fees: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Crescendo, Genentech, Janssen, Pfizer, Roche and UCB Pharma., Grant/research and consultancy fees from: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Crescendo, Genentech, Janssen, Pfizer, Roche and UCB Pharma., Motomu Hashimoto Speaker fees from Bristol Myers, Chugai, Eisai, Eli Lilly, Tanabe and Mitsubishi., Research grants from Abbvie, Asahi Kasei, Astellas, Bristol-Myers Squibb, Eisai, Daiichi Sankyo, Eli Lilly, Novartis and Taisho Toyama., Tsutomu Takeuchi Received honoraria from AbbVie, Asahikasei, Astellas, Bristol-Myers Squibb, Chugai, Daiichi Sankyo, Eisai, Janssen, Mitsubishi-Tanabe and Pfizer Japan., Received grants from AbbVie, Asahikasei, AYUMI, Chugai and Mitsubishi-Tanabe., Ernest Choy Speaker fees from Abbvie, Amgen, Bristol-Myers Squibb, Chugai Pharma, Eli Lilly, Fresenius Kai, Galapagos, Gilead, Janssen, Novartis, Pfizer, Regeneron, RPharm, Roche, Sanofi and UCB Pharma., Consultancy fees from Abbvie, Amgen, Biogen, Biocon, Chugai, Eli Lilly, Fresenius Kabi, Gilead, Janssen, Novartis, Pfizer, Regeneron, Roche, RPharm and Sanofi., Research grants from Bio-Cancer, Biogen, Novartis, Pfizer and Sanofi., Yoshiya Tanaka Speaker fees and/or honoraria from: AbbVie, AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, Chugai, Eisai, Eli Lilly, Gilead, GLAXOSMITHKLINE, Pfizer, Taiho Pharmaceutical and Taisho, Received grants from: Chugai, Eisai, Mitsubishi-Tanabe and Taisho, Carlos Cara UCB Pharma, UCB Pharma, Bernard Lauwerys UCB Pharma, UCB Pharma, Nicola Tilt UCB Pharma, UCB Pharma, Baran Ufuktepe UCB Pharma, Peter C. Taylor Consultancy fees from: AbbVie, Eli Lilly, UCB Pharma, Pfizer, Biogen, Janssen, Fresenius, Galapagos, Gilead, GlaxoSmithKline, Nordic Pharma, Acelyrin Inc. Participation on a Data Safety Monitoring Board/Advisory Board for Immunovant, Sanofi and Kymab., Galapagos.

Background Therapeutic advances of the recent past have led to significant changes in clinical practice when treating patients with rheumatoid arthritis (RA). Since the advent of biological disease modifying anti-rheumatic drugs (DMARD), double-blind randomized controlled trials (RCT) have been the mainstay of drug development. Over time, a significant increase in placebo response rates has been observed in these trials. We hypothesized that one element contributing to these increasing placebo responses are changing recruitment patterns with an increasing move towards geographic areas with less affluent health care systems. Objectives To determine the contribution of changes in geographic recruiting patterns to placebo response rates in RA. Methods We analysed the placebo arms of all available trials with reports on ACR response rates at week 12 and/or week 24. To ensure completeness of trial acquisition, we identified all placebo controlled RCTs investigating biological or targeted synthetic DMARDs in RA patients with established csDMARD background therapy through a systematic literature search covering the time from database inception until December 2nd, 2021. To assess geographic distribution, we extracted the numbers of recruiting centres per country from the original articles or from clinicaltrials.gov. We then used data published from the world bank on the per capita gross national product (GNP) of each recruiting country to calculate a weighted GNP per study, calculated as: weighted GNP=sum[(number of centres per country)*(GNP of respective country at study start)]/(total number of centres of that study). We performed linear mixed model regression with a random effect on study level (to control for study heterogeneity), weighted by the number of patients per study, and adjusted for the global trend of rising GNPs over time. Statistics were conducted using R (version 4.3.1). Results For complete trial evaluation, two independent researchers screened in total 12.793 articles, of which 522 were assessed in detail, with 122 articles finally fulfilling the criteria for trial analysis. Of the included studies the year of study start ranged from 1994 to 2019. All studies had low risk of bias using the version 2 of the Cochrane risk-of-bias tool for randomized trials. A significant positive association of placebo response rates with the study start year was found (estimate: 0.95; SE: 0.21; p<0.001). Recruitment areas have expanded from initially covering only North America and Western Europe to an increasing global recruitment over time (Figure 1), with more recent studies being conducted in less affluent countries. We identified a strong and significant negative association of the weighted and normalised GNP per study and placebo response rates in a study, with an estimate of -3.81% ACR20 response (SE 1.07; p<0.001; Figure 2) per 10.000 international Dollar. • Download figure • Open in new tab • Download powerpoint Figure 1. Patterns of recruiting centers (per country) from 1994 to 2019 (study start). • Download figure • Open in new tab • Download powerpoint Figure 2. Association of placebo response rates with the weighted gross national product (GNP) per study. The size of the bubbles represents the number of patients in each placebo arm analysed. Conclusion Placebo response rates are rising over time, in parallel to the change of geographic recruiting patterns, with more recent RCTs recruiting increasingly in less effluent countries. Our data support the hypothesis that these geographic recruitment changes are a significant contributor to the higher placebo rates observed in more recent clinical trials. One explanation may be the more limited access to health care and innovative therapies in less affluent countries, leading to preferential incentives for inclusion in clinical trials and subsequently also higher regression to the mean, which will be considered as placebo response. These effects should have implications for sponsors, investigators, patients, health care providers and political stakeholders. REFERENCES NIL Acknowledgements We thank the expert librarians, Mag.a Brigitte Wildner and Dr. Eva Chwala, for their assistance with the database searches. The authors also thank B. Bierbaumer, MSc for his assistance in building the underlying database for this project. Disclosure of Interests Andreas Kerschbaumer AbbVie, Amgen, Galapagos, Janssen, Eli Lilly, MSD, Novartis, Pfizer and UCB, AbbVie, Amgen, Galapagos, Janssen, Eli Lilly, MSD, Novartis, Pfizer and UCB, Marlene Steiner: None declared, Pascale Pruckner: None declared, Josef S. Smolen Samsung, Lilly, R-Pharma, Chugai, MSD Janssen, Novartis-Sandoz, Abbvie, Galapagos/Gilead, Novartis-Sandoz, BMS, Samsung, Sanofi, Chugai, R-Pharma, Lilly, Astra-Zeneca, Abbvie, Astra-Zeneca, Lilly, Galapagos, Daniel Aletaha Abbvie, Gilead, Janssen, Lilly, Merck, Novartis, Sanofi, Galapagos, Lilly.

Background CT-P47 which is recombinant humanized monoclonal antibody was developed as a candidate to the reference tocilizumab. Objectives The purpose of this study was to compare the pharmacokinetics (PK), safety, and immunogenicity of CT-P47, EU-approved tocilizumab (EU-tocilizumab) and US-licensed tocilizumab (US-tocilizumab) up to 56 days after a single intravenous infusion of 8 mg/kg in healthy Japanese subjects. Methods 133 subjects aged 18 to 54 years were randomized into 1:1:1 to receive either CT-P47, EU-tocilizumab or US-tocilizumab. The primary PK endpoints included area under the serum concentration-time curve (AUC) from time zero to infinity (AUC0-inf), AUC from time zero to the last quantifiable concentration (AUC0-last), and maximum serum concentration (Cmax). Secondary endpoints were additional PK, safety, and immunogenicity. Results Of the 133 randomized subjects, 132 subjects received the study drug (CT-P47:45; EU-tocilizumab:43; US-tocilizumab:44). The 90% confidence intervals for the geometric least squares mean ratios of each of the primary PK parameters (AUC0-inf, AUC0-last, Cmax) were within the predefined equivalence margin of 80% to 125% (Table 1). Secondary PK variables and mean serum concentrations of tocilizumab were also comparable among all groups (Figure 1). Overall, 24 (53.3%), 24 (55.8%) and 24 (54.5%) subjects reported ≥1 treatment-emergent adverse event (TEAE) in the CT-P47, EU-tocilizumab and US-tocilizumab groups, respectively. Neutrophil count decreased was the most commonly reported TEAE overall (15 [33.3%], 13 [30.2%] and 12 [27.3%] subjects, respectively). No treatment-emergent serious adverse event was reported. Overall, 5 (11.1%), 1 (2.3%) and 2 (4.5%) subjects in the CT-P47, EU-tocilizumab and US-tocilizumab groups, respectively, had ≥1 post-treatment positive result for anti-drug antibodies (ADA) and 2 (4.4%), 0 and 1 (2.3%) subjects, respectively, had ≥1 positive result post-treatment for neutralizing antibody. Primary PK parameters were slightly lower in subjects with any type of ADA compared with ADA negative subjects, at post-dose. Conclusion CT-P47, EU-tocilizumab, and US-tocilizumab were bioequivalent as measured by primary PK endpoints and CT-P47 was determined to be safe and well tolerated in healthy subjects as compared with the comparators. • Download figure • Open in new tab • Download powerpoint • Download figure • Open in new tab • Download powerpoint Figure 1. Mean (± SD) Serum Concentrations of Intravenous Tocilizumab (PK Set) Abbreviations: EU-tocilizumab, European Union-approved tocilizumab; PK, pharmacokinetic; SD, standard deviation; US-tocilizumab, US-licensed tocilizumab. REFERENCES NIL Acknowledgements NIL Disclosure of Interests Miwa Haranaka: None declared, Takashi Eto: None declared, Takanori Tanaka: None declared, Rie Yazawa: None declared, Gerd R. Burmester Chugai, Fresenius, Sanofi., Celltrion, Fresenius, Sanofi., Edward Keystone AbbVie, Celltrion, GSK Pharmaceuticals, Lilly Pharmaceuticals, Pfizer Pharmaceuticals, Sandoz, AbbVie, Celltrion, GSK Pharmaceuticals, Lilly Pharmaceuticals, Pfizer Pharmaceuticals, Sandoz, Samsung Bioepsis, Sung Hyun Kim Celltrion, Inc., YunJu Bae Celltrion, Inc., JeeHye Suh Celltrion, Inc., Yunah Kim Celltrion, Inc., JaeYong Lee Celltrion, Inc., Josef S. Smolen Abbvie, Amgen, Astro, BMS, Celgene, Celltrion, Chugai, Gilead, ILTOO, Janssen, Lilly, MSD, Novartis-Sandoz, Pfizer, Roche, Samsung, Sanofi, UCB, Abbvie, Amgen, Astro, BMS, Celgene, Celltrion, Chugai, Gilead, ILTOO, Janssen, Lilly, MSD, Novartis-Sandoz, Pfizer, Roche, Samsung, Sanofi, UCB, Abbvie, Astra-Zeneca, Janssen, Lilly, Novartis, Roche.

Background Dendritic cells are innate immune cells known for their role in antigen presentation and activation of the adaptive immune system. However, their role in the pathogenesis of inflammatory arthritis is poorly defined. Objectives We aimed to elucidate the role of dendritic cells in models of inflammatory arthritis with special emphasis on inflammatory bone destruction. Methods CD11c-diphtheria toxin receptor (CD11cDTR) transgenic mice were treated with diphtheria toxin (DT) or phosphate buffered saline (PBS) during serum transfer arthritis (STA) and human tumour necrosis factor transgenic (hTNFtg) arthritis and scored histologically. We measured cytokines in synovitis by quantitative polymerase chain reaction (qPCR). We performed ovariectomy in CD11cDTR mice treated with PBS or DT. We analysed CD11cDTR and Zbtb46-DTR-treated mice with DT using histomorphometry and OCs of CD11c and Zbtb46 fate reporter mice by fluorescent imaging. We sorted murine and human OC precursors and stimulated them with macrophage colony-stimulating factor (M-CSF) and receptor activator of nuclear factor kappa-B ligand (RANKL) to generate OCs. Results Targeting CD11c⁺ cells in vivo in models of inflammatory arthritis (STA and hTNFtg) ameliorates arthritis by reducing inflammatory bone destruction and OC generation. Targeting CD11c-expressing cells in unchallenged mice removes all OCs in their long bones. We demonstrate that OCs are derived from CD11c⁺ cells and from Zbtb46⁺ conventional dendritic cells (cDCs) as all OCs in CD11c-Tomato and Zbtb46-Tomato fate reporter mice are Tomato⁺. In line, administration of DT in Zbtb46-DTR mice depletes all OCs in long bones. Finally, human CD1c-expressing cDCs readily differentiated into bone resorbing OCs. Conclusion Taken together, we identify DCs as important OC precursors in bone homeostasis and inflammation, and targeting them might open new avenues for therapeutic interventions in OC-mediated diseases. • Download figure • Open in new tab • Download powerpoint Figure 1. Histological analysis of murine paws in a KBxN arthritis model of CD11cDTRtg mice. Mice injected with diphteria toxin (DT) displayed depletion of DCs. Shown is the quantitative analysis of inflammation, bone erosion area and number of synovial osteoclasts (OCs). REFERENCES NIL Acknowledgements NIL Disclosure of Interests Antonia Mazzucato-Puchner: None declared, Elisabeth Simader Lilly, Abbvie, Victoria Saferding Janssen, Melanie Hofmann: None declared, Markus Kieler: None declared, Rene Pfeifle: None declared, Gerhard Krönke: None declared, Josef S. Smolen speakers’ bureau for Samsung, Lilly, R-Pharm, Chugai, MSD, Janssen, Novartis-Sandoz; consulting fees from Abbvie, Galapagos/Gilead, Novartis-Sandoz, BMS, Samsung, Sanofi, Chugai, R-Pharma, Lilly; participation on a data safety monitoring/advisory board for AstraZeneca., grants from AbbVie, Astra-Zeneca, Lilly and Galapagos;, Silvia Hayer: None declared, Günter Steiner reports about speakers’ bureau from Thermo Fisher Scientific, Daniel Aletaha reports about speakers’ bureau from Abbvie, Amgen, Galapagos, Lilly, Janssen, Merck, Novartis, Pfizer, and Sandoz, Abbvie, Amgen, Galapagos, Lilly, Janssen, Merck, Novartis, Pfizer, and Sandoz, grants from Abbvie, Amgen, Galapagos, Lilly, and Sanofi;, Stephan Blüml: None declared.

Objective To evaluate the association of serum biomarkers with baseline psoriatic arthritis (PsA) disease activity, pharmacodynamic effects of deucravacitinib on biomarker levels, and relationship between biomarkers and clinical responses to deucravacitinib. Methods The phase 2 trial (NCT03881059) randomized 203 patients with PsA 1:1:1 to placebo, deucravacitinib 6 mg once daily (QD), or deucravacitinib 12 mg QD. Serum biomarkers associated with the IL‐23 pathway (IL‐17A, BD‐2, and IL‐19), Type I interferon pathway, inflammation, and collagen matrix turnover were measured by immunoassay. Clinical responses (≥75% improvement from baseline in Psoriasis Area and Severity Index [PASI 75] and ≥20% improvement from baseline in American College of Rheumatology [ACR 20] criteria responses) were measured at week 16. Hematologic variables were also assessed. Results IL‐17A, BD‐2, and IL‐19 had a modest association with PASI scores ( r =0.4, r =0.56, and r =0.5, respectively) at baseline. In deucravacitinib groups, IL‐17A, BD‐2, IL‐19, CXCL‐9, CXCL‐10, CRP, MMP3, and C4M levels were significantly reduced at week 16 versus baseline ( P <0.01); higher levels of IL‐23 pathway‐associated biomarkers predicted higher PASI 75 and ACR 20 response rates in deucravacitinib‐treated patients. Significantly higher PASI 75 response rates were seen in patients with high baseline IL‐17A (OR: 15.76) and BD‐2 (OR: 15.41) versus low. Changes in hematologic variables that are characteristic of JAK inhibition were not observed with deucravacitinib. Conclusion Deucravacitinib significantly impacted biomarkers associated with TYK2 signaling pathways of key inflammatory cytokines, including IL‐23 and Type I IFN, and those related to collagen matrix turnover. These biomarkers may predict treatment responses to deucravacitinib. image

Background/Aims In patients with rheumatoid arthritis (RA), high rheumatoid factor (RF) titres are considered a poor prognostic factor and are associated with higher disease activity, risk of radiographic progression and decreased response to TNF inhibitors (TNFis). Recent data suggests that patients with RA and high RF titre may achieve and maintain greater clinical improvement with TNFis without a crystallisable fragment (Fc) compared to TNFis with an Fc. In this analysis of the EXXELERATE trial, we assessed efficacy outcomes of certolizumab pegol (CZP), a PEGylated Fc-free TNFi, versus adalimumab (ADA; Fc-containing TNFi) in patients with RA and high RF titres. Methods The phase 4 EXXELERATE trial (NCT01500278) compared the efficacy and safety of CZP to ADA. Patients were randomised 1:1 to CZP 200 mg every two weeks (Q2W) plus methotrexate (MTX) or ADA 40 mg Q2W plus MTX. At Week 12 (Wk), patients were classified as responders or non-responders; non-responders were switched to the other TNFi with possible follow-up to Wk104. Here, we report drug plasma concentrations, mean disease activity score (DAS)28-CRP score and proportion of patients achieving low disease activity (LDA; threshold: DAS28-CRP ≤2.7) to Wk104. Results are stratified by RF titre quartile (≤Q3: ≤203 IU/mL; >Q3: >203 IU/mL; measured by Roche Tina-quant®) and reported as observed data. Results Baseline data by RF quartile were available for 453 CZP-randomised patients (≤Q3: n = 334; >Q3: n = 119) and 454 ADA-randomised patients (≤Q3: n = 347; >Q3 n = 107). Baseline characteristics were similar between CZP- and ADA-randomised patients across the RF titre quartiles. At Wk12, 66 CZP-treated patients switched to ADA and 59 ADA-treated patients switched to CZP. At Wk104, mean ADA concentrations were 22.9% lower in patients with RF >Q3 (mean [SD] 4.8 [3.0]) vs those with RF ≤Q3 (6.2 [4.0]); in CZP-treated patients, this difference was smaller (13.0%) in patients with RF >Q3 (23.3 [15.4]) vs those with RF ≤Q3 (26.7 [13.1]). For patients in RF ≤Q3, mean DAS28-CRP scores were similar between CZP- and ADA-treated patients through Wks0-104 (mean [SD] DAS28 at Wk104: 2.48 [1.18] CZP vs 2.49 [1.14] ADA). However, for patients in RF >Q3, mean [SD] DAS28-CRP scores were nominally lower in CZP- vs ADA-treated patients (Wk104: 2.50 [1.18] CZP vs 2.93 [1.22] ADA). A similar pattern was observed for the proportion of patients achieving LDA at Wk104 (≤Q3: 64.8% CZP vs 65.1% ADA; >Q3: 65.7% CZP vs 48.3% ADA). Conclusion CZP-treated patients with RA and high titre RF had similar drug concentrations and clinical responses to patients with RA and low titre RF, a pattern not observed in ADA-treated patients. These data, together with previous reports where CZP showed consistent efficacy irrespective of baseline RF titre, suggest CZP may be a suitable therapy for patients with RA and high RF titre. Disclosure J.S. Smolen: Honoraria; AbbVie, Amgen, AstraZeneca, Astro, Bristol-Myers Squibb, Celgene, Celltrion, Chugai, Gilead, ILTOO, Janssen, Lilly, Merck Sharp & Dohme, Novartis-Sandoz, Pfizer, R-Pharma, Roche, Samsung, Sanofi, and UCB Pharma. Grants/research support; AbbVie, AstraZeneca, Eli Lilly, Novartis and Roche. Other; Editor of Annals of the Rheumatic Diseases, Co-editor of Rheumatology 7E/8E, Convenor of EULAR Task Forces and T2T Task Forces. P.C. Taylor: Consultancies; AbbVie, Biogen, Eli Lilly, Fresenius, Galapagos, Gilead, GSK, Janssen, Nordic Pharma, Pfizer, Sanofi and UCB Pharma. Grants/research support; Galapagos. Y. Tanaka: Honoraria; AbbVie, AstraZeneca, BMS, Boehringer Ingelheim, Chugai, Eisai, Eli Lilly, Gilead, GSK, Pfizer, Taiho, Taisho. Member of speakers’ bureau; AbbVie, AstraZeneca, BMS, Boehringer Ingelheim, Chugai, Eisai, Eli Lilly, Gilead, GSK, Pfizer, Taiho and Taisho. Grants/research support; Chugai, Eisai, Mitsubishi-Tanabe, Taisho. C. Cara: Shareholder/stock ownership; UCB Pharma. Other; Employee of UCB Pharma. B. Lauwerys: Shareholder/stock ownership; UCB Pharma. Other; Employee of UCB Pharma. R. Xavier: Consultancies; AbbVie, AstraZeneca, Janssen, Organon, UCB Pharma. Member of speakers’ bureau; AbbVie, AstraZeneca, Janssen, Organon, and UCB Pharma. J.R. Curtis: Consultancies; AbbVie, Amgen, BMS, Corrona, Crescendo, Genentech, Janssen, Pfizer, Roche, UCB Pharma. Grants/research support; AbbVie, Amgen, BMS, Corrona, Crescendo, Genentech, Janssen, Pfizer, Roche, UCB Pharma. T.R. Mikuls: Consultancies; Horizon Therapeutics, Pfizer, Sanofi, UCB Pharma. Royalties; Elsevier, Wolters Kluwer Health (UpToDate). Grants/research support; Horizon Therapeutics. M. Weinblatt: Consultancies; AbbVie, Aclaris, Amgen, Aqtual, BMS, CorEvitas, Eli Lilly, GSK, Gilead, Horizon, Johnson and Johnson, Prometheus, Pfizer, Rani, Revolo, Sanofi, Scipher, Sci Rhom, Set Point, UCB Pharma. Grants/research support; AbbVie, Aqtual, BMS, Janssen.

Objective Subjects with subclinical psoriatic arthritis (PsA), defined as the presence of arthralgia in psoriasis (PsO), are at higher risk of PsA but scant real-world data exist. Our aims were to (1) estimate the probability of PsA development in subclinical PsA, (2) characterise subclinical PsA symptoms and (3) determine the clinical patterns at PsA diagnosis. Methods Patients with PsO, mainly subclinical PsA, were evaluated longitudinally in two European cohorts. The key outcome was new-onset PsA. Musculoskeletal symptoms including inflammatory and non-inflammatory symptoms before PsA diagnosis were collected. Occurrence of PsA was analysed with survival analysis and cumulative incidence functions (CIFs). Results 384 patients with PsO were included with a mean follow-up of 33.0 (±20.9) months. 311 of 384 (80.9%) had subclinical PsA with a PsA incidence rate of 7.7 per 100 patient-years. Subclinical PsA displayed a higher risk of PsA development compared with PsO (HR=11.7 (95% CI 1.57 to 86.7), p=0.016). The probability of new-onset PsA estimated by the CIF was 9.4% (95% CI 4.7% to 10.6%) at month 12 and 22.7% (95% CI 17.2% to 28.6%) at month 36. 58.9% of cases reported inflammatory symptoms in the months immediately prior to PsA diagnosis but prior non-inflammatory symptoms were evident in 83.9% prior to PsA diagnosis. Peripheral joint swelling was the predominant PsA presentation pattern (82.1%). Conclusions The probability of PsA development among subclinical PsA was relatively high, emphasising the importance of emergent musculoskeletal symptoms when aiming for PsA prevention. Joint swelling was the dominant feature in new-onset PsA, likely reflecting clinical confidence in recognising joint swelling.

Objectives To obtain an overview of recent evidence on efficacy and safety of pharmacological treatments in psoriatic arthritis (PsA). Methods This systematic literature research (SLR) investigated the efficacy and safety of conventional synthetic (cs), biological (b) and targeted synthetic (ts) disease-modifying antirheumatic drugs (DMARDs) in patients with PsA. A systematic database search using Medline, EMBASE, Cochrane CENTRAL was conducted to identify relevant articles published since the previous update in 2019 until 28 December 2022. Efficacy was assessed in trials while for safety observational data were also considered. Adverse events of special interest were infections (including herpes zoster, influenza and tuberculosis), malignancies, major adverse cardiovascular events, venous thromboembolisms, liver disease, laboratory changes and psychiatric adverse events. No meta-analyses were performed. Results For efficacy, of 3946 articles screened, 38 articles (30 trials) were analysed. The compounds investigated included csDMARDs (leflunomide, methotrexate), bDMARDs inhibiting IL17 (bimekizumab, brodalumab, ixekizumab, izokibep, secukinumab,), IL-23 (guselkumab, risankizumab, tildrakizumab), IL-12/23 (ustekinumab) as well as TNF (adalimumab, certolizumab-pegol, etanercept, infliximab, golimumab) and Janus Kinase inhibitors (JAKi) (brepocitinib, deucravacitinib, tofacitinib, upadacitinib). The compounds investigated were efficacious in improving signs and symptoms of PsA, improving physical functioning and quality of life. For safety, 2055 abstracts were screened, and 24 articles analysed: 15 observational studies and 9 long-term follow-ups of trials, assessing glucocorticoids, TNFi, IL-17i, JAKi, IL-12/23i and PDE4i (apremilast). Safety indicators were generally coherent with the previous SLR in 2019. Conclusion The results of this SLR informed the task force responsible for the 2023 update of the European Alliance of Associations for Rheumatology recommendations for pharmacological management of PsA.

Objective New modes of action and more data on the efficacy and safety of existing drugs in psoriatic arthritis (PsA) required an update of the EULAR 2019 recommendations for the pharmacological treatment of PsA. Methods Following EULAR standardised operating procedures, the process included a systematic literature review and a consensus meeting of 36 international experts in April 2023. Levels of evidence and grades of recommendations were determined. Results The updated recommendations comprise 7 overarching principles and 11 recommendations, and provide a treatment strategy for pharmacological therapies. Non-steroidal anti-inflammatory drugs should be used in monotherapy only for mild PsA and in the short term; oral glucocorticoids are not recommended. In patients with peripheral arthritis, rapid initiation of conventional synthetic disease-modifying antirheumatic drugs is recommended and methotrexate preferred. If the treatment target is not achieved with this strategy, a biological disease-modifying antirheumatic drug (bDMARD) should be initiated, without preference among modes of action. Relevant skin psoriasis should orient towards bDMARDs targeting interleukin (IL)-23p40, IL-23p19, IL-17A and IL-17A/F inhibitors. In case of predominant axial or entheseal disease, an algorithm is also proposed. Use of Janus kinase inhibitors is proposed primarily after bDMARD failure, taking relevant risk factors into account, or in case bDMARDs are not an appropriate choice. Inflammatory bowel disease and uveitis, if present, should influence drug choices, with monoclonal tumour necrosis factor inhibitors proposed. Drug switches and tapering in sustained remission are also addressed. Conclusion These updated recommendations integrate all currently available drugs in a practical and progressive approach, which will be helpful in the pharmacological management of PsA.