POS1548 ENTHESITIS OUTCOMES IN PATIENTS WITH PSORIATIC ARTHRITIS INITIATING A TUMOUR NECROSIS FACTOR INHIBITOR IN A REAL-WORLD SETTING: DATA FROM THE EuroSpA COLLABORATION NETWORK
Bibliographic record
Abstract
Background Enthesitis in patients with psoriatic arthritis (PsA) can be a therapeutic challenge. Objectives To explore the impact of tumor necrosis factor inhibitors (TNFi) on enthesitis in patients with PsA in the EuroSpA collaboration network [1]. Methods Prospectively collected data from biologic-naïve PsA patients ≥18 years at diagnosis, who initiated a TNFi between 2010-2020 and had available baseline data on enthesitis (defined as tenderness at any enthesis included in the Maastricht Ankylosing Spondylitis Enthesitis Score (MASES, mainly axial entheses) and/or Spondyloarthritis Research Consortium of Canada score (SPARCC, peripheral entheses) were pooled from European countries in the EuroSpA collaboration. Changes from baseline to follow-up (6-24 months) in enthesitis scores were calculated both for the first (TNFi-1) and second TNFi (TNFi-2), as were the percentage of sites with complete resolution of enthesitis. Results Demographics and clinical variables of the 723 patients who had a baseline evaluation by MASES (N=549) and/or SPARCC (N=358) are detailed in Table 1. Of these, 192 (35%) and 239 (66.8%) had enthesitis by MASES (3.1±2.4, mean±standard deviation) and SPARCC (3.9±3.4) scores, respectively. The patterns of involvement are shown in Figure 1. MASES/SPARCC baseline and follow-up scores for TNFi-1 were available for 93/85 patients, respectively. Corresponding values were 27/38 patients for TNFi-2. Following TNFi-1, 58 (62.4%) patients (MASES) and 43 (50.9%) patients (SPARCC) achieved complete resolution of enthesitis. These proportions were lower following TNFi-2. SPARCC sites observed an overall lower site-specific enthesitis resolution as compared to MASES sites (61.1% vs 76.2% for TNFi-1). Conclusion Real-life registry data on enthesitis from several European countries are presented. Enthesitis resolution was observed in a substantial proportion of patients with PsA following TNFi-1. Reference [1]Brahe CH, Ørnbjerg LM, Jacobsson L, et al. Retention and response rates in 14261 PsA patients starting TNF-inhibitor treatment – results from 12 countries in EuroSpA. Rheumatology (Oxford) 2020;59:1640-50 Acknowledgements Novartis Pharma AG for supporting the EuroSpA collaboration. Disclosure of Interests Ashish Jacob Mathew Speakers bureau: Novartis, IPCA Laboratories, CIPLA, Grant/research support from: Novartis, IPCA Laboratories, Lykke Midtbøll Ørnbjerg Speakers bureau: Abbvie, Eli-Lilly, Sandoz, Novartis, Egis, UCB, Consultant of: Abbvie, Eli-Lilly, Sandoz, Novartis, Egis, UCB, Grant/research support from: Novartis, Jakub Zavada, Mads Pedersen: None declared, Stylianos Georgiadis: None declared, Bente Glintborg Grant/research support from: Pfizer, Abbvie, BMS, Anne Gitte Loft Speakers bureau: Abbvie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Grant/research support from: Novartis, Michael J. Nissen Speakers bureau: AbbVie, Eli Lilly, Janssens, Novartis, Pfizer, Burkhard Moeller Speakers bureau: Eli-Lilly, Janssen, Novartis, Pfizer, Grant/research support from: Amgen, Ana Maria Rodrigues Speakers bureau: Abbvie and Amgen, Grant/research support from: Novartis, Pfizer and Amgen, Fernando M Pimentel-Santos Speakers bureau: Abbvie, UCB, Janssen, Novartis, MSD, Tecnimed, Eli Lilly, Pfizer, Grant/research support from: Abbvie, Novartis and Janssen, Ziga Rotar Speakers bureau: Abbvie, Novartis, MSD, Medis, Biogen, Eli Lilly, Pfizer, Sanofi, Lek, Janssen, Consultant of: Abbvie, Novartis, MSD, Medis, Biogen, Eli Lilly, Pfizer, Sanofi, Lek, Janssen, Matija Tomšič Speakers bureau: Abbvie, Amgen, Biogen, Eli Lilly, Janssen, Medis, MSD, Novartis, Pfizer, Sanofi, Sandoz, Lek, Heikki Relas Speakers bureau: Abbvie, Celgene, Pfizer, UCB and Viatris, Ritva Peltomaa Speakers bureau: UCB, Lilly, Celtrion, Boehringer Ingelheim, Abbvie, Janssen, Consultant of: Janssen, UCB, Boehringer Ingelheim, Lilly, Sanofi, Björn Gudbjornsson Speakers bureau: Novartis and Nordic Pharma, Thorvardur Jon Löve Speakers bureau: Abbvie, Celgene, Sinem Burcu Kocaer: None declared, Aydan Köken Avşar: None declared, Merete Lund Hetland Speakers bureau: Pfizer, Medac, Sandoz, Grant/research support from: AbbVie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Medac, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis, Mikkel Østergaard Speakers bureau: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, UCB, Consultant of: Abbvie, Amgen, Biogen, Eli Lilly, Janssen, Medis, MSD, Novartis, Pfizer, Sanofi, Sandoz, Lek.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".