Zhang Yuqi, Du Keqian, Wu Bin, Wang Yongfu, Wei Hua, Feng Xiaoxue, Xu Jia, Xu Peijun, Huang Jianlin
Department of Rheumatology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, People's Republic of China.
Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, People's Republic of China.
Sci Rep. 2025 Apr 21;15(1):13676. doi: 10.1038/s41598-025-97084-2.
Rheumatoid arthritis (RA) is a chronic inflammatory disease requiring early diagnosis and treatment to achieve sustained clinical remission. Achieving a state of remission is associated with favorable outcomes. However, predictive factors for Boolean2.0 remission in RA patients are limited. This retrospective observational study analyzed data from RA patients enrolled in a smart system of disease management group (SSDM) between January 2014 and December 2023. Demographic and clinical characteristics were compared between patients who achieved Boolean2.0 remission and those who did not. Univariate and multivariate logistic regression analyses were performed to identify predictive factors associated with Boolean2.0 remission. Among 5004 patients enrolled for analysis, 541 (10.8%) achieved Boolean2.0 remission. The median (IQR) age at diagnosis of the patients was 51.00 (42.00, 60.00) years, with the majority being female (3978, 79.5%). The median (IQR) disease duration was 26.00 (3.00, 89.00) months. Logistic regression analyses revealed that the likelihood of achieving Boolean2.0 remission was greater in patients who were younger (P = 0.008), had a shorter disease duration (P < 0.001), a lower number of tender joints (P < 0.001), and were prescribed methotrexate (P = 0.012) and leflunomide (P = 0.001). Younger age, shorter disease duration, lower count of tender joints, and treatment with methotrexate and leflunomide were associated with increased likelihood of achieving Boolean2.0 remission. These findings can guide clinicians in identifying high-risk patients and optimizing treatment strategies.
类风湿关节炎(RA)是一种慢性炎症性疾病,需要早期诊断和治疗以实现持续的临床缓解。实现缓解状态与良好的预后相关。然而,RA患者达到Boolean2.0缓解的预测因素有限。这项回顾性观察研究分析了2014年1月至2023年12月期间纳入疾病管理组智能系统(SSDM)的RA患者的数据。比较了达到Boolean2.0缓解的患者和未达到该缓解的患者的人口统计学和临床特征。进行单因素和多因素逻辑回归分析以确定与Boolean2.0缓解相关的预测因素。在纳入分析的5004例患者中,541例(10.8%)达到Boolean2.0缓解。患者诊断时的中位(IQR)年龄为51.00(42.00,60.00)岁,大多数为女性(3978例,79.5%)。中位(IQR)病程为26.00(3.00,89.00)个月。逻辑回归分析显示,年龄较小(P = 0.008)、病程较短(P < 0.001)、压痛关节数量较少(P < 0.001)以及使用甲氨蝶呤(P = 0.012)和来氟米特(P = 0.001)治疗的患者达到Boolean2.0缓解的可能性更大。年龄较小、病程较短、压痛关节计数较低以及使用甲氨蝶呤和来氟米特治疗与达到Boolean2.0缓解的可能性增加相关。这些发现可为临床医生识别高危患者和优化治疗策略提供指导。