Trial reportArthritis research & therapy2026
Predicting clinical response in psoriatic arthritis through integrative analysis of transcriptomics and proteomics.
Trial report in Arthritis research & therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
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Authors and funding
12 authors.
Funding
Abstract
backgroundThe therapeutic response to disease-modifying antirheumatic drugs (DMARDs) remains relatively low in psoriatic arthritis (PsA), leading to delayed disease control and frequent treatment switches. Predictive biomarkers may enable personalized treatment and earlier disease control. We aimed to identify transcriptomic and proteomic markers for tofacitinib or comparator treatment outcomes and develop a prediction model to support treatment decisions in PsA patients.
methodsBaseline CD4
resultsFifty percent of patients responded to treatment. Eighteen transcriptomic, ten proteomic, and two clinical predictors were selected. The integrated multi-omics model incorporating treatment-predictor interactions achieved the highest performance (AUC = 0.70 ± 0.19; variation (SD) in treatment-effects in patients 15.2% ± 14.8%). The selected proteins were significantly interconnected (p-value = 3.41E-5) and related to immune system processes.
conclusionsIntegrated baseline gene and protein expression profiles combined with clinical variables can predict treatment response and identify differential treatment effects between individual patients. These findings demonstrate the potential of omics-guided personalized treatment for patients with PsA.
trial registrationEU Clinical Trials, 2017-003900-28.
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