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Record W4411410168 · doi:10.1016/j.ard.2025.06.1415

ABS0974 EARLY IMPROVEMENTS IN CLINICAL DISEASE ACTIVITY INDEX FOR PSORIATIC ARTHRITIS AND ITS COMPONENTS WITH GUSELKUMAB PREDICT CLINICAL RESPONSE IN TNFi-EXPERIENCED AND BIOLOGIC-NAÏVE PARTICIPANTS WITH ACTIVE PSORIATIC ARTHRITIS: POST HOC ANALYSES OF THREE PHASE 3, RANDOMIZED, CONTROLLED STUDIES

2025· article· en· W4411410168 on OpenAlexaff
L. Gossec, M. Sharaf, Philipp Sewerin, J. H. Galloway, Maria Antonietta D’Agostino, J. Ramírez, E. Rampakakis, K. Lozenski, Suad Hannawi, Andreas Kerschbaumer

Bibliographic record

VenueAnnals of the Rheumatic Diseases · 2025
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicinePsoriatic arthritisPsoriasisDermatologyArthritisClinical trialInternal medicine

Abstract

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Background: Feasibility of an outcome measure is the main criterion for its use in psoriatic arthritis (PsA) disease monitoring and implementation of treat-to-target in routine clinical practice. The Disease Activity Index for PsA (DAPSA), a comprehensive tool for evaluating joint disease activity, includes 66/68 swollen/tender joint counts (SJC/TJC), CRP, and patient-reported outcomes (PROs; global assessment of arthritis [PtGA-Arthritis], and pain [Pt Pain]). Given that routine evaluation of CRP is limited, the clinical DAPSA (cDAPSA) was developed as a simplified tool to assess PsA disease activity, with a performance comparable to DAPSA [1], but omitting CRP. Objectives: To evaluate the utility of cDAPSA in monitoring disease activity in both TNF inhibitor (i)-experienced and biologic-naïve PsA patients, we assessed the predictive value of early improvements in cDAPSA and its components for downstream achieviement of low disease activity (LDA) using a large cohort of participants (pts) pooled from 3 randomized controlled trials (RCTs). Methods: Data were pooled from 3 RCTs (DISCOVER-1 [NCT03162796], DISCOVER-2 [NCT03158285], COSMOS [NCT03796858]) of PsA pts receiving guselkumab (GUS) every 4 weeks (Q4W) or at W0, W4, and Q8W, or placebo (PBO). Only pts with baseline cDAPSA score ≥14 were included in these post hoc analyses. W4 cDAPSA total and item score cutoffs predictive of LDA/remission (REM) achievement at W24 in pooled GUS groups were determined separately in TNF inhibitor (i)-experienced and biologic-naïve cohorts with receiver operator characteristic analyses. Achievement of cDAPSA total and item score cutoffs over 24W was compared between GUS Q8W (regimen common to all 3 studies) and PBO in both cohorts using logistic regression. Nonresponder imputation was used for missing data. Further analyses included logistic regression to determine the association between achievement of early (W4) response (cDAPSA total and item score cutoffs) and achievement of LDA/REM at W24 in GUS Q8W. The proportion of patients achieving LDA/REM at W48 among non-acheivers at W24 was also assessed. Results: Among biologic-naïve (N=995) and TNFi-experienced (N=403) PsA pts pooled across 3 RCTs, baseline patient characteristics were generally comparable across prior treatment cohorts, although more biologic-naïve pts reported NSAID use at baseline. W4 cutoffs for cDAPSA total and PRO item scores predictive of LDA/REM achievement at W24 were similar across prior treatment cohorts, while less stringent W4 joint count cutoffs were observed in biologic-naïve than TNFi-experienced pts (SJC: 5.0 vs 3.0; TJC: 13.0 vs 8.0; Table 1). As early as W4 (after 1 dose), GUS Q8W was associated with higher odds of achieving PRO cutoffs (vs PBO) in the biologic-naïve cohort (odds ratios [OR] for both PtGA-Arthritis and Pt Pain: 1.8), and of achieving PtGA-Arthritis (OR: 2.2) and cDAPSA total score (OR: 2.2) cutoffs in TNFi-experienced pts. Odds of achieving all derived cutoffs were consistently higher with GUS Q8W through W24 in both the biologic-naïve and TNFi-experienced cohorts (OR range at W24: 1.8-2.5 and 1.7-2.6, respectively). GUS Q8W pts achieving the derived cutoffs at W4 were more likely to achieve LDA/REM than non-achievers across the biologic-naïve and TNFi-experienced cohorts (OR range: 2.6-5.3 and 4.1-6.6, respectively; Figure 1). Across these cohorts, 32% of GUS Q8W pts who did not achieve LDA/REM at W24 did so at W48. Conclusion: In a PsA population pooled across 3 RCTs, early improvements in cDAPSA total and constituent item scores with GUS Q8W were associated with higher odds of achieving long-term joint disease activity control, regardless of treatment history. The derived cutoffs suggest that TNFi-experienced pts may need to achieve lower SJCs and TJCs to attain sustained control of joint disease activity. These findings support the utility of cDAPSA, and particularly its PRO components, in assessing early improvements in joint disease activity that predict future achievement of low levels of joint disease. REFERENCES: [1] Schoels MM, et al. Ann Rheum Dis. 2016; 75(5):811-8. Acknowledgements: NIL . Disclosure of Interests: Laure Gossec AbbVie, AlfaSigma, Amgen, Bristol Myers Squibb, Celltrion, Janssen, Eli Lilly, MSD, Novartis, Pfizer, Stada, and UCB, AbbVie, Biogen, Eli Lilly, Novartis, UCB, Mohamed Sharaf Johnson & Johnson, EMEA Medical Affairs, Johnson & Johnson Middle East FZ LLC, Dubai, United Arab Emirates, Philipp Sewerin Amgen, AbbVie, Biogen, Bristol Myers Squibb, Celgene, Eli Lilly, Gilead Sciences, Hexal Pharma, Janssen, Novartis Pharma, Pfizer, Roche Pharma, Rheumazentrum Rhein-Ruhr, Sanofi-Genzyme, Swedish Orphan Biovitrum, and UCB Pharma, AXIOM Health, Amgen, AbbVie, Biogen, Bristol Myers Squibb, Celgene, Chugai Pharma Marketing Ltd/Chugai Europe, Deutscher Psoriasis-Bund, Eli Lilly, Gilead Sciences, Hexal Pharma, Janssen, Mediri GmbH, Novartis Pharma, Onkowissen GmbH, Pfizer, Roche Pharma, Rheumazentrum Rhein-Ruhr, Sanofi-Genzyme, Spirit Medical Communication, Swedish Orphan Biovitrum, and UCB Pharma, James Galloway Abbvie, Alfasigma, Galapagos, Janssen, Eli Lilly, Pfizer, and UCB, Abbvie, Alfasigma, Galapagos, Janssen, Eli Lilly, Pfizer, and UCB, Maria Antonietta D'Agostino AbbVie, Bristol Myers Squibb, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, and UCB, Julio Ramírez AbbVie, Angem, Eli Lilly, Janssen, Novartis, Pfizer, UCB, AbbVie, Janssen, Novartis, and UCB, Emmanouil Rampakakis JSS Medical Research, Janssen, Karissa Lozenski Johnson & Johnson, and Bristol Myers Squibb, Immunology Global Medical Affairs, Janssen Pharmaceutical Companies of Johnson & Johnson, Suad Hannawi AbbVie, Amgen, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Janssen, New Bridge, and Novartis, AbbVie, Amgen, AstraZeneca, Eli Lilly, and Janssen, Andreas Kerschbaumer Eli Lilly, Galapagos, Janssen, MSD, Novartis, and Pfizer, AbbVie, Lilly, Gilead, Janssen, and UCB. © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.

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)0.018
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.014
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.011
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.119
GPT teacher head0.457
Teacher spread0.338 · 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 designRandomized trial
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
Published2025
Admission routes1
Has abstractyes

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