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Record W7117551759 · doi:10.1016/j.ero.2025.12.008

Understanding the transition from psoriasis to psoriatic arthritis: the role of targeted therapy

2025· article· en· W7117551759 on OpenAlexafffund
Fadi Kharouf, Matthew Anacleto-Dabarno, Richard J. Cook, Vinod Chandran, Denis Poddubnyy

Bibliographic record

VenueEULAR Rheumatology Open · 2025
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsUniversity of WaterlooMontreal General HospitalArthritis SocietyUniversity of Toronto
FundersKrembil FoundationUniversity of TorontoUniversity Health Network FoundationUniversity Health Network
KeywordsPsoriatic arthritisPsoriasisSubclinical infectionTargeted therapyDiseaseClinical trialMechanism (biology)Antirheumatic drugs

Abstract

fetched live from OpenAlex

Most individuals who develop psoriatic arthritis (PsA) first present with psoriasis (PsC), often years before musculoskeletal symptoms emerge. Progression from PsC to PsA is multifactorial, shaped by genetic and environmental influences, and may involve at-risk stages and subclinical stages before culminating in clinically overt arthritis. Consistently identified risk factors include greater PsC severity, nail involvement, arthralgia, and elevated body mass index. In this Viewpoint, we review and critically appraise current evidence on PsC-to-PsA transition, focusing on how the mechanism of action of biologic disease-modifying antirheumatic drugs may influence this trajectory. Emerging data suggest that therapies targeting the interleukin (IL)-23/IL-17 axis may provide greater protection against PsA development than tumour necrosis factor inhibitors, underscoring the central role of this pathway in psoriatic disease pathogenesis. However, existing studies are limited by confounding, protopathic bias, and heterogeneous cohorts. By integrating mechanistic insights with clinical data, we emphasise the urgent need for rigorously designed multinational randomised controlled trials to determine whether, and how, biologic therapy can modify the natural history of psoriatic disease.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

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

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 head0.032
GPT teacher head0.285
Teacher spread0.253 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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