Patient Clusters Identified by Machine Learning from a Pooled Analysis of the Clinical Development Programme of Secukinumab in Psoriatic Arthritis, Ankylosing Spondylitis and Psoriatic Arthritis with Axial Manifestations
Clin Exp Rheumatol. 2023 doi: 10.55563/clinexprheumatol/b8co74 Epub ahead of print
Psoriatic arthritis clusters, obtained by machine learning (ML) analysis of pooled data from the FUTURE, MEASURE, and MAXIMISE trials, indicate phenotypical heterogeneity of patients with PsA and axial manifestations and overlapping features across the spondyloarthritis spectrum. Here, Baraliakos, et al. sort to identify distinct clinical clusters, based on patient demographics and baseline clinical indicators, from the secukinumab clinical development programme.
Guselkumab, a Selective Interleukin-23 p19 Subunit Inhibitor, Resolves Dactylitis in Patients With Active Psoriatic Arthritis: Pooled Results Through Week 52 From Two Phase 3 Studies
ACR Open Rheumatol. 2023;5(4):227–240 doi 10.1002/acr2.11537
Post hoc analysis of guselkumab, Phase 3 DISCOVER-1 and -2 studies finds that 75% of guselkumab-randomised patients have complete resolution of dactylitis through one year.
Efficacy of Secukinumab on Dactylitis in Patients with Active Psoriatic Arthritis from the FUTURE 5 study
Clin Exp Rheumatol. 2023 doi: 10.55563/clinexprheumatol/vezf95
The presence of dactylitis was associated with a higher disease burden in patients with PsA compared with those without dactylitis at baseline. The aim of this study was to evaluate the efficacy of secukinumab in patients with dactylitis at baseline over 2 years.