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Predictors of Boolean2.0 remission in rheumatoid arthritis identified using smart disease management system data
Yuqi Zhang1,2, Keqian Du1,2, Bin Wu3
1Department of Rheumatology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, People's Republic of China.
Abstract:
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.
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