군집 알고리즘을 활용한 그레이브스병 환자의 스타틴 용량 궤적 및 갑상선 안병증 위험 연구
Statin Dose Trajectories and Risk of Graves’ Orbitopathy in Patients with Graves’ Disease Using Clustering Algorithm
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초록

Objectives: Graves’ orbitopathy (GO) is an autoimmune condition linked with Graves’ disease (GD). This study focuses on the relationship between statin dose trajectories and the risk of developing GO among GD patients using the data from the National Health Insurance Service (NHIS). Methods: Utilizing the KmL (k-means for longitudinal data) clustering algorithm, we categorized patients with GD and hyperlipidemia into three distinct groups based on their two-year pre-diagnosis statin dosage. A Cox proportional hazards model with inverse probability weighting (IPW) was applied to evaluate the risk of GO across the identified clusters. Results: The findings suggest that patients within the ‘Moderate’ statin dosage cluster are at a statistically lower risk of developing GO compared to those who did not use statins (p =0.048). Conclusions: Moderate statin use significantly reduces the risk of GO in GD patients. These findings support the potential role of statins in GO prevention.

키워드

Cluster algorithmInverse probability weightSurvival analysisGraves’ orbitopathyStatin
제목
군집 알고리즘을 활용한 그레이브스병 환자의 스타틴 용량 궤적 및 갑상선 안병증 위험 연구
제목 (타언어)
Statin Dose Trajectories and Risk of Graves’ Orbitopathy in Patients with Graves’ Disease Using Clustering Algorithm
저자
강진모이정규안화영이주영
DOI
10.21032/jhis.2025.50.1.104
발행일
2025-02
저널명
보건정보통계학회지
50
1
페이지
104 ~ 112

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