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. 2022 Oct 14;24(1):233.
doi: 10.1186/s13075-022-02918-3.

Differences in trajectory of disease activity according to biologic and targeted synthetic disease-modifying anti-rheumatic drug treatment in patients with rheumatoid arthritis

Bon San Koo #  1 , Seongho Eun #  2 , Kichul Shin  3 , Seokchan Hong  4 , Yong-Gil Kim  4 , Chang-Keun Lee  4 , Bin Yoo  4 , Ji Seon Oh  5
Affiliations

Differences in trajectory of disease activity according to biologic and targeted synthetic disease-modifying anti-rheumatic drug treatment in patients with rheumatoid arthritis

Bon San Koo et al. Arthritis Res Ther. .

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.

Keywords: Biologics; Rheumatoid arthritis; Trajectory clustering/trajectory modeling; Treatment response.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Trajectory-based clustering. Trajectory clustered into 4 groups (A) and changes in the disease activities of each individual over 4 years (B). Abbreviation: DAS28, disease activity scores with 28-joints assessment using the erythrocyte sedimentation rate
Fig. 2
Fig. 2
SHAP plots for baseline important features of trajectories. Important features of group 1 compared to groups 2, 3, and 4 (A), group 2 compared to group 1 (B), group 3 compared to group 1 (C), and group 4 compared to group 1 (D). Abbreviations: ACPA, anti-cyclic citrullinated peptide antibody; ALT, alanine aminotransferase; ANA, anti-nuclear antibody; AST, aspartate aminotransferase; BUN, blood urea nitrogen; CRP, C-reactive protein; DAS28, disease activity score with 28-joint assessment; eGFR, estimated glomerular filtration rate; ESR, erythrocyte sedimentation rate; RF, rheumatoid factor
See this image and copyright information in PMC

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