Pournara, E. et al. (2021) Clinically relevant patient clusters identified by machine learning from the clinical development programme of secukinumab in psoriatic arthritis. RMD Open, 7(3), e001845. (doi: 10.1136/rmdopen-2021-001845)
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Abstract
Objectives: Identify distinct clusters of psoriatic arthritis (PsA) patients based on their baseline articular, entheseal and cutaneous disease manifestations and explore their clinical and therapeutic value. Methods: Pooled baseline data in PsA patients (n=1894) treated with secukinumab across four phase 3 studies (FUTURE 2–5) were analysed to determine phenotypes based on clusters of clinical indicators. Finite mixture models methodology was applied to generate clinical clusters and mean longitudinal responses were compared between secukinumab doses (300 vs 150 mg) across identified clusters and clinical indicators through week 52 using machine learning (ML) techniques. Results: Seven distinct patient clusters were identified. Cluster 1 (very-high (VH) – SWO/TEN (swollen/tender); n=187) was characterised by VH polyarticular burden for both tenderness and swelling of joints, while cluster 2 (H (high) – TEN; n=251) was marked by high polyarticular burden in tender joints and cluster 3 (H – Feet – Dactylitis; n=175) by high burden in joints of feet and dactylitis. For cluster 4 (L (Low) – Nails – Skin; n=209), cluster 5 (L – skin; n=283), cluster 6 (L – Nails; n=294) and cluster 7 (L; n=495) articular burden was low but nail and skin involvement was variable, with cluster 7 marked by mild disease activity across all domains. Greater improvements in the longitudinal responses for enthesitis in cluster 2, enthesitis and Psoriasis Area and Severity Index (PASI) in cluster 4 and PASI in cluster 6 were shown for secukinumab 300 mg compared with 150 mg. Conclusions: PsA clusters identified by ML follow variable response trajectories indicating their potential to predict precise impact on patients’ outcomes. Trial registration numbers: NCT01752634, NCT01989468, NCT02294227, NCT02404350.
Item Type: | Articles |
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Additional Information: | The research study was funded by Novartis Pharma AG, Basel, Switzerland. |
Keywords: | Psoriatic arthritis, 1506, biological therapy, arthritis, psoriatic, tumor necrosis factor inhibitors, inflammation, t-lymphocyte subsets. |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | McInnes, Professor Iain |
Authors: | Pournara, E., Kormaksson, M., Nash, P., Ritchlin, C. T., Kirkham, B. W., Ligozio, G., Pricop, L., Ogdie, A., Coates, L. C., Schett, G., and McInnes, I. B. |
College/School: | College of Medical Veterinary and Life Sciences > School of Infection & Immunity |
Research Centre: | College of Medical Veterinary and Life Sciences > School of Infection & Immunity > Centre for Immunobiology |
Journal Name: | RMD Open |
Publisher: | BMJ Publishing Group |
ISSN: | 2056-5933 |
ISSN (Online): | 2056-5933 |
Published Online: | 18 November 2021 |
Copyright Holders: | Copyright © 2021 The Authors |
First Published: | First published in RMD Open 7(3): e001845 |
Publisher Policy: | Reproduced under a Creative Commons License |
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