Differences in trajectory of disease activity according to biologic and targeted synthetic disease-modifying anti-rheumatic drug treatment in patients with rheumatoid arthritis
Abstract Background The purpose of this study was to stratify patients with rheumatoid arthritis (RA) according to the trend of disease activity by trajectory-based clustering and to identify contributing factors for treatment response to biologic and targeted synthetic disease-modifying anti-rheuma...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-10-01
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| Series: | Arthritis Research & Therapy |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13075-022-02918-3 |
| _version_ | 1817983874151481344 |
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| author | Bon San Koo Seongho Eun Kichul Shin Seokchan Hong Yong-Gil Kim Chang-Keun Lee Bin Yoo Ji Seon Oh |
| author_facet | Bon San Koo Seongho Eun Kichul Shin Seokchan Hong Yong-Gil Kim Chang-Keun Lee Bin Yoo Ji Seon Oh |
| author_sort | Bon San Koo |
| collection | DOAJ |
| description | Abstract Background The purpose of this study was to stratify patients with rheumatoid arthritis (RA) according to the trend of disease activity by trajectory-based clustering and to identify contributing factors for treatment response to biologic and targeted synthetic disease-modifying anti-rheumatic drugs (DMARDs) according to trajectory groups. Methods We analyzed the data from a nationwide RA cohort from the Korean College of Rheumatology Biologics and Targeted Therapy registry. Patients treated with second-line biologic and targeted synthetic DMARDs were included. Trajectory modeling for clustering was used to group the disease activity trend. The contributing factors using the machine learning model of SHAP (SHapley Additive exPlanations) values for each trajectory were investigated. Results The trends in the disease activity of 688 RA patients were clustered into 4 groups: rapid decrease and stable disease activity (group 1, n = 319), rapid decrease followed by an increase (group 2, n = 36), slow and continued decrease (group 3, n = 290), and no decrease in disease activity (group 4, n = 43). SHAP plots indicated that the most important features of group 2 compared to group 1 were the baseline erythrocyte sedimentation rate (ESR), prednisolone dose, and disease activity score with 28-joint assessment (DAS28) (SHAP value 0.308, 0.157, and 0.103, respectively). The most important features of group 3 compared to group 1 were the baseline ESR, DAS28, and estimated glomerular filtration rate (eGFR) (SHAP value 0.175, 0.164, 0.042, respectively). The most important features of group 4 compared to group 1 were the baseline DAS28, ESR, and blood urea nitrogen (BUN) (SHAP value 0.387, 0.153, 0.144, respectively). Conclusions The trajectory-based approach was useful for clustering the treatment response of biologic and targeted synthetic DMARDs in patients with RA. In addition, baseline DAS28, ESR, prednisolone dose, eGFR, and BUN were important contributing factors for 4-year trajectories. |
| first_indexed | 2024-04-13T23:38:21Z |
| format | Article |
| id | doaj.art-d84cbeeea08a4286a11033a99d4fe7c7 |
| institution | Directory Open Access Journal |
| issn | 1478-6362 |
| language | English |
| last_indexed | 2024-04-13T23:38:21Z |
| publishDate | 2022-10-01 |
| publisher | BMC |
| record_format | Article |
| series | Arthritis Research & Therapy |
| spelling | doaj.art-d84cbeeea08a4286a11033a99d4fe7c72022-12-22T02:24:38ZengBMCArthritis Research & Therapy1478-63622022-10-012411910.1186/s13075-022-02918-3Differences in trajectory of disease activity according to biologic and targeted synthetic disease-modifying anti-rheumatic drug treatment in patients with rheumatoid arthritisBon San Koo0Seongho Eun1Kichul Shin2Seokchan Hong3Yong-Gil Kim4Chang-Keun Lee5Bin Yoo6Ji Seon Oh7Department of Internal Medicine, Inje University Seoul Paik Hospital, Inje University College of MedicineDepartment of Management Engineering, College of Business, KAISTDivision of Rheumatology, Seoul Metropolitan Government-Seoul National University Hospital Boramae Medical CenterDivision of Rheumatology, Department of Internal Medicine, Asan Medical Center, University of Ulsan College of MedicineDivision of Rheumatology, Department of Internal Medicine, Asan Medical Center, University of Ulsan College of MedicineDivision of Rheumatology, Department of Internal Medicine, Asan Medical Center, University of Ulsan College of MedicineDivision of Rheumatology, Department of Internal Medicine, Asan Medical Center, University of Ulsan College of MedicineDepartment of Information Medicine, Big Data Research Center, Asan Medical CenterAbstract Background The purpose of this study was to stratify patients with rheumatoid arthritis (RA) according to the trend of disease activity by trajectory-based clustering and to identify contributing factors for treatment response to biologic and targeted synthetic disease-modifying anti-rheumatic drugs (DMARDs) according to trajectory groups. Methods We analyzed the data from a nationwide RA cohort from the Korean College of Rheumatology Biologics and Targeted Therapy registry. Patients treated with second-line biologic and targeted synthetic DMARDs were included. Trajectory modeling for clustering was used to group the disease activity trend. The contributing factors using the machine learning model of SHAP (SHapley Additive exPlanations) values for each trajectory were investigated. Results The trends in the disease activity of 688 RA patients were clustered into 4 groups: rapid decrease and stable disease activity (group 1, n = 319), rapid decrease followed by an increase (group 2, n = 36), slow and continued decrease (group 3, n = 290), and no decrease in disease activity (group 4, n = 43). SHAP plots indicated that the most important features of group 2 compared to group 1 were the baseline erythrocyte sedimentation rate (ESR), prednisolone dose, and disease activity score with 28-joint assessment (DAS28) (SHAP value 0.308, 0.157, and 0.103, respectively). The most important features of group 3 compared to group 1 were the baseline ESR, DAS28, and estimated glomerular filtration rate (eGFR) (SHAP value 0.175, 0.164, 0.042, respectively). The most important features of group 4 compared to group 1 were the baseline DAS28, ESR, and blood urea nitrogen (BUN) (SHAP value 0.387, 0.153, 0.144, respectively). Conclusions The trajectory-based approach was useful for clustering the treatment response of biologic and targeted synthetic DMARDs in patients with RA. In addition, baseline DAS28, ESR, prednisolone dose, eGFR, and BUN were important contributing factors for 4-year trajectories.https://doi.org/10.1186/s13075-022-02918-3Rheumatoid arthritisBiologicsTrajectory clustering/trajectory modelingTreatment response |
| spellingShingle | Bon San Koo Seongho Eun Kichul Shin Seokchan Hong Yong-Gil Kim Chang-Keun Lee Bin Yoo Ji Seon Oh Differences in trajectory of disease activity according to biologic and targeted synthetic disease-modifying anti-rheumatic drug treatment in patients with rheumatoid arthritis Arthritis Research & Therapy Rheumatoid arthritis Biologics Trajectory clustering/trajectory modeling Treatment response |
| title | Differences in trajectory of disease activity according to biologic and targeted synthetic disease-modifying anti-rheumatic drug treatment in patients with rheumatoid arthritis |
| title_full | Differences in trajectory of disease activity according to biologic and targeted synthetic disease-modifying anti-rheumatic drug treatment in patients with rheumatoid arthritis |
| title_fullStr | Differences in trajectory of disease activity according to biologic and targeted synthetic disease-modifying anti-rheumatic drug treatment in patients with rheumatoid arthritis |
| title_full_unstemmed | Differences in trajectory of disease activity according to biologic and targeted synthetic disease-modifying anti-rheumatic drug treatment in patients with rheumatoid arthritis |
| title_short | Differences in trajectory of disease activity according to biologic and targeted synthetic disease-modifying anti-rheumatic drug treatment in patients with rheumatoid arthritis |
| title_sort | differences in trajectory of disease activity according to biologic and targeted synthetic disease modifying anti rheumatic drug treatment in patients with rheumatoid arthritis |
| topic | Rheumatoid arthritis Biologics Trajectory clustering/trajectory modeling Treatment response |
| url | https://doi.org/10.1186/s13075-022-02918-3 |
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