ORIGINAL RESEARCH article
Front. Pharmacol.
Sec. Ethnopharmacology
Volume 16 - 2025 | doi: 10.3389/fphar.2025.1651557
This article is part of the Research TopicIntegrating Approaches Traditional and Biomedical Therapies in Rheumatological and other Inflammatory Musculoskeletal DiseasesView all 6 articles
Tongue Feature-Based Model for Assessing Disease Activity in Patients with Rheumatoid Arthritis
Provisionally accepted
Yu Xin Han1
Zihan Wang2
Mei Qi Lan1Yu Ting Bian1
Guangyao Chen2Hao Lu Wu1Wei Chao Li1
Qingwen Tao2
YUAN XU2Jian Ming Wang2*- 1Bejing University of Chinese Medicine, Beijing, China
- 2China-Japan Friendship Hospital, Beijing, China
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Introduction: Tongue features, which are emerging imaging-based biomarkers, have been integrated into predictive models for various diseases. However, their role in assessing rheumatoid arthritis (RA) activity remains unexplored. This study aims to develop a clinically applicable model for assessing RA activity by analyzing the relationship between tongue features and laboratory indicators. Methods: We enrolled 227 patients who visited the Department of Traditional Chinese Medicine Rheumatology, China-Japan Friendship Hospital, from April 2021 to March 2023. Patients were stratified into remission/low-activity (n = 75) and moderate/high activity (n = 152) groups. Multivariable logistic regression was used to develop two predictive models: Model 1 (based on laboratory parameters) and Model 2 (Model 1 plus tongue features). Both models were presented as nomograms and web-based calculators. Model discrimination was evaluated using receiver operating characteristic curves, calibrated via calibration plots, and clinical utility was determined using decision curve analysis. Results: Multivariable logistic regression identified white blood cell (WBC), hemoglobin (HGB), platelets (PLT), and IgA as predictors in Model 1, while Model 2 incorporated WBC, HGB, greasy coating and sublingual varicosity. Model 2 outperformed Model 1, achieving an area under the curve of 0.846 (95% confidence interval = 0.740–0.951), with a sensitivity of 0.63 and specificity of 0.826. A nomogram and online calculator were developed from this optimized model for clinical use. Conclusions: We have developed a preliminary RA disease activity assessment model integrating tongue features and laboratory parameters. This model shows high accuracy and considerable potential for clinical utility.
Keywords: disease activity, Rheumatoid arthritis, tongue characteristics, laboratory indexes, Clinical predictive model
Received: 22 Jun 2025; Accepted: 01 Sep 2025.
Copyright: © 2025 Han, Wang, Lan, Bian, Chen, Wu, Li, Tao, XU and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jian Ming Wang, China-Japan Friendship Hospital, Beijing, China
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