Prediction of medication-related osteonecrosis of the jaw (MRONJ) using automated machine learning in patients with osteoporosis associated with dental extraction and implantation: a retrospective study

• 영문명: Prediction of medication-related osteonecrosis of the jaw (MRONJ) using automated machine learning in patients with osteoporosis associated with dental extraction and implantation: a retrospective study
• 발행기관: 대한구강악안면외과학회
• 저자명: Da Woon Kwack Sung Min Park
• 간행물 정보: 『대한구강악안면외과학회지』제49권 제3호, 135~141쪽, 전체 7쪽
• 주제분류: 의약학 > 내과학
• 파일형태: PDF
• 발행일자: 2023.06.30

영문 초록

Objectives: This study aimed to develop and validate machine learning (ML) models using H2O-AutoML, an automated ML program, for predicting medication-related osteonecrosis of the jaw (MRONJ) in patients with osteoporosis undergoing tooth extraction or implantation. Patients and Methods: We conducted a retrospective chart review of 340 patients who visited Dankook University Dental Hospital between January 2019 and June 2022 who met the following inclusion criteria: female, age ≥55 years, osteoporosis treated with antiresorptive therapy, and recent dental extraction or implantation. We considered medication administration and duration, demographics, and systemic factors (age and medical history). Local factors, such as surgical method, number of operated teeth, and operation area, were also included. Six algorithms were used to generate the MRONJ prediction model. Results: Gradient boosting demonstrated the best diagnostic accuracy, with an area under the receiver operating characteristic curve (AUC) of 0.8283. Validation with the test dataset yielded a stable AUC of 0.7526. Variable importance analysis identified duration of medication as the most important variable, followed by age, number of teeth operated, and operation site. Conclusion: ML models can help predict MRONJ occurrence in patients with osteoporosis undergoing tooth extraction or implantation based on questionnaire data acquired at the first visit.

목차

I. Introduction

II. Patients and Methods

III. Results

IV. Discussion

V. Conclusion

ORCID

Authors’ Contributions

Funding

Ethics Approval and Consent to Participate

Conflict of Interest

References

키워드

Medication-related osteonecrosis of the jaw Bisphosphonate Osteoporosis Machine learning Algorithm