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Efficacy of Risankizumab across distinct PsA phenotypes identified with machine learning analytics using data from biologic DMARD-Naïve patients in two phase 3 clinical trials

Abstract Background The development of personalized approaches in psoriatic arthritis (PsA) is challenging due to unclear patient phenotypes and trajectories. Machine learning (ML) could help to identify homogeneous patient groups. The objective of this analysis was to classify patients with PsA int...

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Principais autores: Laure Gossec, Andra Balanescu, Maria Antonietta D’Agostino, Alexis Ogdie, Philipp Sewerin, Yu Deng, Linyu Shi, Yoshiyuki Sugimoto, Sheng Zhong, Yunzhao Xing, Ralph Lippe, Mitsumasa Kishimoto
Format: Artigo
Sprog:Inglês
Udgivet: BMC 2025-11-01
Serier:Arthritis Research & Therapy
Fag:
Biological therapy
Interleukin (IL)-23
KEEPsAKE
Machine learning
Phenotype
Psoriatic arthritis (PsA)
Online adgang:https://doi.org/10.1186/s13075-025-03670-0
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