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Identification of individuals at high risk of developing rheumatoid arthritis: a balanced random forest model in a cohort of 1544 first-degree relatives.

RMD open - 27 Nov 2025

Aymon Romain, Lamacchia Céline, Gilbert Benoit Thomas P, Grundhuber Maresa, Gehring Isabel, Swiniarski Sascha, Studer Olivia, Salis Zubeyir, Guemara Romain, Spoerl David, Dudler Jean, Möller Burkhard, Dan Diana, Brulhart Laure, Von Mühlenen Ines, Kyburz Diego, Rubbert-Roth Andrea, Ciurea Adrian, Mueller Ruediger, Courvoisier Delphine S, Finckh Axel

Abstract excerpt

OBJECTIVES: To identify in a genetically susceptible population individuals at higher risk of developing rheumatoid arthritis (RA) using a classification approach combining known epidemiological risk factors, serological biomarkers, genetics, clinical signs and symptoms. METHODS: We used data from the prospective SCREEN-RA (Evaluation of a SCREENing strategy for Rheumatoid Arthritis) cohort of 1540 first-degree...

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Arthritis, Rheumatoid
Autoantibodies
Biomarkers

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Genetic Predisposition to Disease

Rheumatoid Factor

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Open in PubMed Open full text

Identifiers

PMID: 41314668
DOI: 10.1136/rmdopen-2025-005773
PMCID: PMC12666099

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