Osteoarthritis progression pattern based on patient specific characteristics using machine learning.

Journal: NPJ digital medicine
Published Date: Jul 21, 2025

Abstract

This study aimed to identify key factors associated with different progression patterns of early osteoarthritis (OA) by developing a predictive model using patient-specific characteristics. From 2003 to 2017, data from 833 knees were analyzed. Demographic factors included age, body mass index, bone mineral density (BMD), metabolic diseases, and other comorbidities. Radiographic factors included joint space narrowing (JSN) and osteophyte formation grades. Three classification models were developed using logistic regression and a light gradient boosting machine: unicompartmental/tricompartmental OA, tricompartmental JSN-dominant OA, and tricompartmental osteophyte-dominant OA. Feature importance was evaluated using SHapley Additive exPlanations feature explanations. Patients with osteoporosis were likely to progress to tricompartmental OA with JSN, while those with a high BMD were likely to progress to unicompartmental OA. Metabolic disease-related OA was associated with tricompartmental OA involving large osteophytes. Identifying OA progression patterns and patient information may enable more effective personalized treatment and prevention strategies in the future.

Authors

  • Seong Yun Park
    Department of Orthopedic Surgery, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam-si, Korea.
  • Myeong Ju Kim
    Center for Artificial Intelligence in Healthcare, Seoul National University Bundang Hospital, Healthcare Innovation Park, Seongnam-si, South Korea.
  • Joon Hee Cho
    Department of Orthopedic Surgery, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seoul, South Korea.
  • Hee Seung Nam
    Department of Orthopedic Surgery, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seoul, South Korea.
  • Jade Pei Yuik Ho
    Department of Orthopedic Surgery, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Bundang-gu, Seongnam-si, Gyeonggi-do, South Korea.
  • Yong Seuk Lee
    Department of Orthopedic Surgery, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seoul, South Korea. Electronic address: smcos1@hanmail.net.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals