Identification of PsA phenotypes with machine learning analytics using data from two phase III clinical trials of guselkumab in a bio-naïve population of patients with PsA.

Psoriatic arthritis (PsA) phenotypes are typically defined by their clinical components, which may not reflect patients' overlapping symptoms. This post hoc analysis aimed to identify hypothesis-free PsA phenotype clusters using machine learning to analyse data from the phase III DISCOVER-1/DISCOVER-2 clinical trials. Pooled data from bio-naïve patients with active PsA receiving guselkumab 100 mg every 8/4 weeks were retrospectively analysed. Non-negative matrix factorisation was applied as an unsupervised machine learning technique to identify PsA phenotype clusters; baseline patient characteristics and clinical observations were input features. Minimal disease activity (MDA), disease activity index for psoriatic arthritis (DAPSA) low disease activity (LDA) and DAPSA remission at weeks 24 and 52 were evaluated. Eight clusters (n=661) were identified: cluster 1 (feet dominant), cluster 2 (male, overweight, psoriasis dominant), cluster 3 (hand dominant), cluster 4 (dactylitis dominant), cluster 5 (enthesitis, large joints), cluster 6 (enthesitis, small joints), cluster 7 (axial dominant) and cluster 8 (female, obese, large joints). At week 24, MDA response was highest in cluster 2 and lowest in clusters 3, 5 and 6; at week 52, it was highest in cluster 2 and lowest in cluster 5. At weeks 24 and 52, DAPSA LDA and remission were highest in cluster 2 and lowest in clusters 4 and 6, respectively. All clusters improved with guselkumab treatment over 52 weeks. Unsupervised machine learning identified eight PsA phenotype clusters with significant differences in demographics, clinical features and treatment responses. In the future, such data could help support individualised treatment decisions.

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Competing interests: PR has received fees from AbbVie, Amgen, Celgene, Janssen, Eli Lilly, MSD, Novartis, Pfizer and UCB. MV has received research grants, consulting or speaker fees from AbbVie, Amgen, the Dutch Arthritis Foundation, Eli Lilly, Janssen, Novartis, Pfizer and UCB. SO has received fees from AbbVie, BMS, Janssen, Mylan, Novartis and Pfizer. WT has received research grants, consulting or speaker fees from AbbVie, Amgen, Celgene, Eli Lilly, GlaxoSmithKline, Janssen, MSD, Novartis, Pfizer and UCB. JR has received consulting or speaker fees from AbbVie, Amgen, Eli Lilly, Janssen, Novartis, Pfizer and UCB. MN is a former employee of Janssen and is now an employee of Takeda Pharmaceuticals International AG. ET is a former employee of Janssen. MZ, MvS, WN and MS are employees of Janssen and own stock in Johnson & Johnson. AK is an employee of Janssen Global Services, R&D, and owns stock in Johnson & Johnson. AZ has received research grants from Novartis, and speaker fees from AbbVie, Amgen, Eli Lilly, Janssen, Novartis and UCB.