{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T00:12:00Z","timestamp":1792023120532,"version":"4.4.0"},"reference-count":17,"publisher":"BMJ","issue":"3","license":[{"start":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T00:00:00Z","timestamp":1637107200000},"content-version":"unspecified","delay-in-days":16,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100008792","name":"Novartis Pharma","doi-asserted-by":"publisher","award":["N\/A"],"award-info":[{"award-number":["N\/A"]}],"id":[{"id":"10.13039\/100008792","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["RMD Open"],"accepted":{"date-parts":[[2021,10,29]]},"published-print":{"date-parts":[[2021,11]]},"abstract":"<jats:sec>\n                  <jats:title>Objectives<\/jats:title>\n                  <jats:p>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.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>Pooled baseline data in PsA patients (n=1894) treated with secukinumab across four phase 3 studies (FUTURE 2\u20135) 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.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Seven distinct patient clusters were identified. Cluster 1 (very-high (VH) \u2013 SWO\/TEN (swollen\/tender); n=187) was characterised by VH polyarticular burden for both tenderness and swelling of joints, while cluster 2 (H (high) \u2013 TEN; n=251) was marked by high polyarticular burden in tender joints and cluster 3 (H \u2013 Feet \u2013 Dactylitis; n=175) by high burden in joints of feet and dactylitis. For cluster 4 (L (Low) \u2013 Nails \u2013 Skin; n=209), cluster 5 (L \u2013 skin; n=283), cluster 6 (L \u2013 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.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>PsA clusters identified by ML follow variable response trajectories indicating their potential to predict precise impact on patients\u2019 outcomes.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Trial registration numbers<\/jats:title>\n                  <jats:p>\n                     <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"clintrialgov\" xlink:href=\"NCT01752634\">NCT01752634<\/jats:ext-link>, <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"clintrialgov\" xlink:href=\"NCT01989468\">NCT01989468<\/jats:ext-link>, <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"clintrialgov\" xlink:href=\"NCT02294227\">NCT02294227<\/jats:ext-link>, <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"clintrialgov\" xlink:href=\"NCT02404350\">NCT02404350<\/jats:ext-link>\n                  <\/jats:p>\n               <\/jats:sec>","DOI":"10.1136\/rmdopen-2021-001845","type":"journal-article","created":{"date-parts":[[2021,11,18]],"date-time":"2021-11-18T11:34:22Z","timestamp":1637235262000},"page":"e001845","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":25,"title":["Clinically relevant patient clusters identified by machine learning from the clinical development programme of secukinumab in psoriatic arthritis"],"prefix":"10.1136","volume":"7","clinical-trial-number":[{"clinical-trial-number":"nct01752634","registry":"10.18810\/clinical-trials-gov"},{"clinical-trial-number":"nct01989468","registry":"10.18810\/clinical-trials-gov"},{"clinical-trial-number":"nct02294227","registry":"10.18810\/clinical-trials-gov"},{"clinical-trial-number":"nct02404350","registry":"10.18810\/clinical-trials-gov"}],"author":[{"given":"Effie","family":"Pournara","sequence":"first","affiliation":[{"name":"Immunology, Heptatology and Dermatology, Novartis AG, Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthias","family":"Kormaksson","sequence":"additional","affiliation":[{"name":"Advanced Exploratory Analytics, Novartis Pharmaceuticals Corporation, East Hanover, New Jersey, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2571-788X","authenticated-orcid":false,"given":"Peter","family":"Nash","sequence":"additional","affiliation":[{"name":"School of Medicine, Griffith University School of Medicine, Gold Coast, Queensland, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2602-1219","authenticated-orcid":false,"given":"Christopher T","family":"Ritchlin","sequence":"additional","affiliation":[{"name":"Department of Medicine, Allergy\/Immunology and Rheumatology (SMD), University of Rochester, Rochester, New York, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bruce W","family":"Kirkham","sequence":"additional","affiliation":[{"name":"Rheumatology, Guy's and St Thomas' NHS Foundation Trust, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gregory","family":"Ligozio","sequence":"additional","affiliation":[{"name":"Immunology, Heptatology and Dermatology, Novartis Pharmaceuticals Corporation, East Hanover, New Jersey, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luminita","family":"Pricop","sequence":"additional","affiliation":[{"name":"Immunology, Heptatology and Dermatology, Novartis Pharmaceuticals Corporation, East Hanover, New Jersey, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexis","family":"Ogdie","sequence":"additional","affiliation":[{"name":"Rheumatology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4756-663X","authenticated-orcid":false,"given":"Laura C","family":"Coates","sequence":"additional","affiliation":[{"name":"Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Georg","family":"Schett","sequence":"additional","affiliation":[{"name":"Rheumatology, Friedrich-Alexander-Universitat Erlangen-Nurnberg, Erlangen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4449-8501","authenticated-orcid":false,"given":"Iain B","family":"McInnes","sequence":"additional","affiliation":[{"name":"College of Medical Veterinary and Life Sciences, University of Glasgow, Glasgow, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2021,11,18]]},"reference":[{"key":"2025090313343137000_7.3.e001845.1","doi-asserted-by":"publisher","DOI":"10.7861\/clinmedicine.17-1-65"},{"key":"2025090313343137000_7.3.e001845.2","doi-asserted-by":"crossref","DOI":"10.1093\/rap\/rkaa005","article-title":"Applied machine learning and artificial intelligence in rheumatology","volume":"4","author":"H\u00fcgle","year":"2020","journal-title":"Rheumatol Adv Pract"},{"key":"2025090313343137000_7.3.e001845.3","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.l886"},{"key":"2025090313343137000_7.3.e001845.4","doi-asserted-by":"publisher","DOI":"10.1083\/jcb.201610026"},{"key":"2025090313343137000_7.3.e001845.5","doi-asserted-by":"crossref","first-page":"690","DOI":"10.1002\/art.40428","article-title":"Identification of three rheumatoid arthritis disease subtypes by machine learning integration of synovial histologic features and RNA sequencing data","volume":"70","author":"Orange","year":"2018","journal-title":"Arthritis Rheumatol"},{"key":"2025090313343137000_7.3.e001845.6","doi-asserted-by":"crossref","DOI":"10.1186\/s12967-019-1864-9","article-title":"Are innovation and new technologies in precision medicine paving a new era in patients centric care?","volume":"17","author":"Seyhan","year":"2019","journal-title":"J Transl Med"},{"key":"2025090313343137000_7.3.e001845.7","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(15)61134-5"},{"key":"2025090313343137000_7.3.e001845.8","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1186\/s13075-018-1551-x","article-title":"Efficacy and safety of secukinumab administration by autoinjector in patients with psoriatic arthritis: results from a randomized, placebo-controlled trial (future 3)","volume":"20","author":"Nash","year":"2018","journal-title":"Arthritis Res Ther"},{"key":"2025090313343137000_7.3.e001845.9","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1007\/s40744-019-0163-5","article-title":"Efficacy and Safety of Subcutaneous Secukinumab 150 mg with or Without Loading Regimen in Psoriatic Arthritis: Results from the FUTURE 4 Study","volume":"6","author":"Kivitz","year":"2019","journal-title":"Rheumatol Ther"},{"key":"2025090313343137000_7.3.e001845.10","doi-asserted-by":"crossref","first-page":"annrheumdis-2017-212687","DOI":"10.1136\/annrheumdis-2017-212687","article-title":"Secukinumab improves active psoriatic arthritis symptoms and inhibits radiographic progression: primary results from the randomised, double-blind, phase III future 5 study","volume":"77","author":"Mease","year":"2018","journal-title":"Ann Rheum Dis"},{"key":"2025090313343137000_7.3.e001845.11","unstructured":"McLachlan G , Peel D . Finite mixture models. New York, USA: John Wiley & Sons, 2004."},{"key":"2025090313343137000_7.3.e001845.12","first-page":"309","article-title":"How to find an appropriate clustering for mixed-type variables with application to socio-economic stratification","volume":"62","author":"Hennig","year":"2013","journal-title":"Journal of the Royal Statistical Society: Series C"},{"key":"2025090313343137000_7.3.e001845.13","unstructured":"Hennig C . fpc: flexible procedures for clustering. R package version 2.2-9, 2020. Available: https:\/\/CRAN.R-project.org\/package=fpc"},{"key":"2025090313343137000_7.3.e001845.14","doi-asserted-by":"crossref","unstructured":"McInnes I , Kormaksson M , Pournara E . Clinically Relevant Patient Clusters Identified by Machine Learning Tools in a Large Database from the Secukinumab Psoriatic Arthritis Clinical Development Program [abstract]. Arthritis Rheumatol 2019;71 https:\/\/acrabstracts.org\/abstract\/clinically-relevant-patient-clusters-identified-by-machine-learning-tools-in-a-large-database-from-the-secukinumab-psoriatic-arthritis-clinical-development-program\/","DOI":"10.1136\/annrheumdis-2019-eular.1910"},{"key":"2025090313343137000_7.3.e001845.15","unstructured":"The R project for statistical computing 2020."},{"key":"2025090313343137000_7.3.e001845.16","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1214\/aos\/1176344136","article-title":"Estimating the dimension of a model","volume":"6","author":"Schwarz","year":"1978","journal-title":"Ann Statist"},{"key":"2025090313343137000_7.3.e001845.17","doi-asserted-by":"publisher","DOI":"10.1023\/A:1023949509487"}],"container-title":["RMD Open"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.1136\/rmdopen-2021-001845","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T20:34:41Z","timestamp":1756931681000},"score":1,"resource":{"primary":{"URL":"https:\/\/rmdopen.bmj.com\/lookup\/doi\/10.1136\/rmdopen-2021-001845"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11]]},"references-count":17,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2021,11,18]]},"published-print":{"date-parts":[[2021,11]]}},"alternative-id":["10.1136\/rmdopen-2021-001845"],"URL":"https:\/\/doi.org\/10.1136\/rmdopen-2021-001845","relation":{},"ISSN":["2056-5933"],"issn-type":[{"value":"2056-5933","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11]]}}}