{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T06:13:45Z","timestamp":1776147225680,"version":"3.50.1"},"reference-count":57,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T00:00:00Z","timestamp":1776124800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>This study aims to explore the application of machine learning techniques in assessing macrophage activation syndrome (MAS) in Still\u2019s disease.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A multicenter, observational, prospective study was conducted, including patients with Still\u2019s disease enrolled in the Gruppo Italiano di Ricerca in Reumatologia Clinica e Sperimentale (GIRRCS) AOSD Study Group and the AutoInflammatory Disease Alliance (AIDA) Network Still\u2019s Disease Registry.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 737 patients (age: 35.5 \u00b1 17.8, male sex: 44.7%) with Still\u2019s disease were assessed; 11.4% were affected by MAS, and 3% had a poor prognosis. First, random forest imputation was applied to the original dataset. Subsequently, a machine-learning-driven assessment was developed to explore MAS occurrence. Collectively, regression models, an exploration decision tree, and a random forest were applied, suggesting the importance of ferritin, age, C-reactive protein (CRP), and systemic score. A logistic regression model accounting for data leakage concerns was then generated using these variables, and missing values were imputed using random forest imputation. This analysis supported the role of the selected variables, which were further combined across different clinical scenarios to estimate the probability of MAS. The highest risk of MAS was estimated for patients simultaneously characterized by age \u2265 45 years, ferritin \u2265 4,178.10 ng\/mL, CRP \u2265 27.15 mg\/L, and a systemic score \u2265 7, corresponding to a 34.7% probability of MAS, as well as for those characterized by ferritin \u2265 4,178.10 ng\/mL, CRP \u2265 27.15 mg\/L, and systemic score \u2265 7, corresponding to a 33.5% probability of MAS.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>A machine-learning-driven prediction of MAS was explored in Still\u2019s disease, highlighting the importance of age of onset, hyperferritinaemia, increased CRP, and multiorgan involvement. A combination of these features may suggest a clinician-friendly algorithm for stratifying the probability of MAS during Still\u2019s disease.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2026.1811317","type":"journal-article","created":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T05:39:08Z","timestamp":1776145148000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Application of machine learning techniques to explore the occurrence of macrophage activation syndrome in Still\u2019s disease: results from the GIRRCS AOSD Study Group and the AIDA Network Still\u2019s Disease Registry"],"prefix":"10.3389","volume":"17","author":[{"given":"Piero","family":"Ruscitti","sequence":"first","affiliation":[{"name":"Department of Biotechnological and Applied Clinical Sciences, University of L\u2019Aquila","place":["L\u2019Aquila, Italy"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesco","family":"Masedu","sequence":"additional","affiliation":[{"name":"Department of Biotechnological and Applied Clinical Sciences, University of L\u2019Aquila","place":["L\u2019Aquila, Italy"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antonio","family":"Vitale","sequence":"additional","affiliation":[{"name":"Department of Medical Sciences, Surgery and Neurosciences, Research Center of Systemic Autoinflammatory Diseases and Beh\u00e7et\u2019s Disease Clinic University of Siena","place":["Siena, Italy"]},{"name":"Azienda Ospedaliero-Universitaria Senese, European Reference Network (ERN) for Rare Immunodeficiency, Autoinflammatory and Autoimmune Diseases (RITA) Center","place":["Siena, Italy"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Valeria","family":"Caggiano","sequence":"additional","affiliation":[{"name":"Department of Medical Sciences, Surgery and Neurosciences, Research Center of Systemic Autoinflammatory Diseases and Beh\u00e7et\u2019s Disease Clinic University of Siena","place":["Siena, Italy"]},{"name":"Azienda Ospedaliero-Universitaria Senese, European Reference Network (ERN) for Rare Immunodeficiency, Autoinflammatory and Autoimmune Diseases (RITA) Center","place":["Siena, Italy"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ilenia","family":"Di Cola","sequence":"additional","affiliation":[{"name":"Department of Biotechnological and Applied Clinical Sciences, University of L\u2019Aquila","place":["L\u2019Aquila, Italy"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fabiola","family":"Atzeni","sequence":"additional","affiliation":[{"name":"Rheumatology Unit, Department of Experimental and Internal Medicine, University of Messina","place":["Messina, Italy"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jessica","family":"Sbalchiero","sequence":"additional","affiliation":[{"name":"Department of Medical Sciences, Surgery and Neurosciences, Research Center of Systemic Autoinflammatory Diseases and Beh\u00e7et\u2019s Disease Clinic University of Siena","place":["Siena, Italy"]},{"name":"Azienda Ospedaliero-Universitaria Senese, European Reference Network (ERN) for Rare Immunodeficiency, Autoinflammatory and Autoimmune Diseases (RITA) Center","place":["Siena, Italy"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giuseppe","family":"Lopalco","sequence":"additional","affiliation":[{"name":"Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J) Policlinic Hospital, University of Bari","place":["Bari, Italy"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Florenzo","family":"Iannone","sequence":"additional","affiliation":[{"name":"Department of Precision and 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