Integrating genetic, epigenetic, and clinical signatures via machine learning for robust prediction of leflunomide response in rheumatoid arthritis: a multi-center validation study.
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| Title: | Integrating genetic, epigenetic, and clinical signatures via machine learning for robust prediction of leflunomide response in rheumatoid arthritis: a multi-center validation study. |
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| Authors: | Chen M; Department of Clinical Epidemiology and Evidence-Based Medicine, the First Hospital of China Medical University, Shenyang, China., Liu H; Department of Rheumatology, The First Hospital of China Medical University, Shenyang, China., Jin L; Department of Rheumatology, ShengJing Hospital of China Medical University, Shenyang, China., Feng X; Department of Rheumatology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China., Dai B; Department of Rheumatology and Immunology, Central Hospital of Dalian University of Technology, Dalian, China., Wang F; Department of Rheumatology, The First Hospital of China Medical University, Shenyang, China., Wang Q; Department of Clinical Epidemiology and Evidence-Based Medicine, the First Hospital of China Medical University, Shenyang, China., Chen Y; Department of Clinical Epidemiology and Evidence-Based Medicine, the First Hospital of China Medical University, Shenyang, China., Yi M; Department of Clinical Epidemiology and Evidence-Based Medicine, the First Hospital of China Medical University, Shenyang, China., Jia B; Department of Clinical Epidemiology and Evidence-Based Medicine, the First Hospital of China Medical University, Shenyang, China., Dong K; Department of Clinical Epidemiology and Evidence-Based Medicine, the First Hospital of China Medical University, Shenyang, China., Zhang J; Department of Rheumatology and Immunology, Central Hospital of Dalian University of Technology, Dalian, China., Fan Z; Department of Clinical Epidemiology and Evidence-Based Medicine, the First Hospital of China Medical University, Shenyang, China., Li J; Department of Clinical Epidemiology and Evidence-Based Medicine, the First Hospital of China Medical University, Shenyang, China., Zhao F; Department of Clinical Epidemiology and Evidence-Based Medicine, the First Hospital of China Medical University, Shenyang, China., Jia Y; Department of Clinical Epidemiology and Evidence-Based Medicine, the First Hospital of China Medical University, Shenyang, China., Wang J; Department of Clinical Epidemiology and Evidence-Based Medicine, the First Hospital of China Medical University, Shenyang, China., Liu M; Department of Clinical Epidemiology and Evidence-Based Medicine, the First Hospital of China Medical University, Shenyang, China., Xu J; Department of Clinical Epidemiology and Evidence-Based Medicine, the First Hospital of China Medical University, Shenyang, China., Fu L; Department of Clinical Epidemiology and Evidence-Based Medicine, the First Hospital of China Medical University, Shenyang, China. |
| Source: | Frontiers in immunology [Front Immunol] 2026 Jun 24; Vol. 17, pp. 1804485. Date of Electronic Publication: 2026 Jun 24 (Print Publication: 2026). |
| Publication Type: | Journal Article; Multicenter Study; Validation Study |
| Journal Info: | Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101560960 Publication Model: eCollection Cited Medium: Internet ISSN: 1664-3224 (Electronic) Linking ISSN: 16643224 NLM ISO Abbreviation: Front Immunol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1664-3224 |
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| DOI: | 10.3389/fimmu.2026.1804485 |
