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E066 Baseline characteristics of patients initiating ixekizumab, secukinumab or a tumour necrosis factor inhibitor by country in the 24-month Prospective Psoriatic Arthritis Observational Study of Persistence of Treatment - PRO-SPIRIT

2024· article· en· W4395084838 on OpenAlexaffabout
Nicola Gullick, Mohamed Sheesh, Cedric Laedermann, Marcus Ngantcha, Beatrice Gittens, Khai Jing Ng, William Tillett, Jacques Morel, Ennio Lubrano, Rieke Alten, Lars Erik Kristensen, Vinod Chandran, À. Martínez-Ferrer, Bruce Kirkham

Bibliographic record

VenueLara D. Veeken · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersMedacCelgeneTeva Pharmaceutical IndustriesGilead SciencesSanofiAmgenPfizerEli Lilly and CompanyBristol-Myers SquibbBiogenGlaxoSmithKline
KeywordsSecukinumabMedicineIxekizumabPsoriatic arthritisObservational studyInternal medicineArthritisPersistence (discontinuity)DermatologyOncologyPhysical therapy

Abstract

fetched live from OpenAlex

Abstract Background/Aims The Psoriatic Arthritis Observational Study of Persistence of Treatment (PRO-SPIRIT) is the first large-sample, multinational, prospective, observational study to provide real-world evidence for ixekizumab (IXE) in patients with psoriatic arthritis (PsA) who start a new biologic/targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD), with a primary end point of persistence at 24 months. Aims: To describe baseline characteristics of PRO-SPIRIT patients initiating or switching to IXE, secukinumab (SEC) or a tumour necrosis factor inhibitor (TNFi) in Canada (CA), France (FR), Germany (DE), Italy (IT), Spain (ES) and the United Kingdom (UK). Methods PRO-SPIRIT enrolled adults diagnosed with PsA (≥6 months) between December 2019 and June 2022 to be initiated or switched to a new b/tsDMARD, locally approved for the management of PsA. Baseline characteristics, including patient demographics, therapy and disease activity measures, are described here by country for patients initiating IXE, SEC (both IL-17A inhibitors) or a TNFi (adalimumab, etanercept, infliximab or biosimilar) only. Results This analysis included 943 patients (Table 1). The overall proportion of patients with BMI ≥30 mg/kg2 was highest in CA (67.2%) and lowest in IT (24.5%); across countries, higher proportions of patients initiating an IL-17A vs a TNFi had BMI ≥30 mg/kg2 (except IXE groups in IT, ES and UK). Higher proportions of patients initiating an IL-17A vs a TNFi were diagnosed with PsA ≥3 years before baseline (except SEC groups in DE and ES). The highest proportions of b/tsDMARD-naïve patients were observed in the TNFi groups in all countries (range 46.2% [CA] to 81.9% [UK]). Patients in the IL-17A groups were more likely to be on monotherapy than patients in the TNFi groups (except in FR). There were no clear trends in baseline disease activity for patients initiating IL-17As or TNFis, although country-specific differences were observed. Conclusion The PRO-SPIRIT baseline characteristics described offer important insights into country-specific patient demographics and treatment patterns when initiating or switching to a new b/tsDMARD in a real-world setting. Between-country variations observed in PRO-SPIRIT baseline characteristics may be due to differences in healthcare systems and/or the evolution of treatment options for patients with PsA in each country. Disclosure N. Gullick: Consultancies; AbbVie,Novartis, UCB. Honoraria; AbbVie, Eli Lilly, Janssen, Novartis, UCB. Grants/research support; AbbVie, Astra Zeneca, Eli Lilly, Novartis. M. Sheesh: Corporate appointments; Eli Lilly and Company. Shareholder/stock ownership; Eli Lilly and Company. C. Laedermann: Corporate appointments; Eli Lilly and Company. Shareholder/stock ownership; Eli Lilly and Company. M. Ngantcha: Corporate appointments; Eli Lilly and Company. Shareholder/stock ownership; Eli Lilly and Company. B. Gittens: Corporate appointments; Eli Lilly and Company. K. Ng: Corporate appointments; Eli Lilly and Company. Shareholder/stock ownership; Eli Lilly and Company. W. Tillett: Consultancies; Abbvie, Amgen, Eli Lilly and Company, GSK, Janssen, Novartis, Ono Pharma, Pfizer, UCB. Member of speakers’ bureau; AbbVie, Amgen, Eli Lilly and Company, GSK, Janssen, Novartis, Pfizer, UCB. Grants/research support; Janssen, UCB, Pfizer, Eli Lilly and Company. J. Morel: Consultancies; Pfizer, AbbVie, Boerhinger Ingelheim, Galapagos, GSK. Member of speakers’ bureau; Biogen, Amgen, Bristol Myers Squib, Eli Lilly and Company, Novartis, Sanofi, MSD, Mylan, Fresenius Kabi, Roche, Union Chimique Belge, Janssen, Medac, Nordic Pharma. Grants/research support; Fresenius Kabi. E. Lubrano: Member of speakers’ bureau; Abbvie, Janssen Cilag, Lilly, UCB, Pfizer, Novartis. R. Alten: Consultancies; AbbVie, BMS, Celltrion, Galapagos, Eli Lilly and Company, Novartis, Pfizer, Roche, UC. Member of speakers’ bureau; AbbVie, BMS, Celltrion, Galapagos, Eli Lilly and Company, Novartis, Pfizer, Roche, UCB. L. Kristensen: Consultancies; Pfizer, AbbVie, Amgen, UCB, Gilead, Biogen, BMS, MSD, Novartis, Eli Lilly and Company, Janssen. Member of speakers’ bureau; Pfizer, AbbVie, Amgen, UCB, Gilead, Biogen, BMS, MSD, Novartis, Eli Lilly and Company, Janssen. Grants/research support; Pfizer, Abb- Vie, UCB, Gilead, Biogen, Novartis, Eli Lilly and Company, Janssen. V. Chandran: Consultancies; AbbVie, Eli Lilly, Novartis, Amgen, Janssen. Grants/research support; AbbVie. A. Martinez-Ferrer: Grants/research support; Eli Lilly and Company. B. Kirkham: Consultancies; Abbvie, Eli Lilly and Company, Galapagos, Novartis. Member of speakers’ bureau; Abbvie, Eli Lilly and Company, Galapagos, Janssen, Novartis, Pfizer, UCB. Grants/research support; Eli Lilly and Company, Novartis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.043
GPT teacher head0.261
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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