利用多态性和临床信息通过机器学习方法预测颌骨药物相关性骨坏死

Prediction of medication-related osteonecrosis of the jaws using machine learning methods from polymorphisms and clinical information.

作者信息

Choi Seo-Yong, Kim Jin-Woo, Oh Sang-Hyeon, Cheon Seunghyun, Yee Jeong, Kim Sun-Jong, Gwak Hye Sun, Chung Jee-Eun

机构信息

College of Pharmacy and Institute of Pharmaceutical Science and Technology, Hanyang University, Ansan, Republic of Korea.

Department of Oral and Maxillofacial Surgery, School of Medicine, Ewha Womans University, Seoul, Republic of Korea.

出版信息

Front Med (Lausanne). 2023 Jun 21;10:1140620. doi: 10.3389/fmed.2023.1140620. eCollection 2023.

DOI:10.3389/fmed.2023.1140620

PMID:37415765

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10321771/

Abstract

OBJECTIVE

The purpose of this study was to evaluate the effect of () polymorphisms on the development of medication-related osteonecrosis of the jaws (MRONJ) in women with osteoporosis.

METHODS

A total of 125 patients taking bisphosphonates was evaluated the relationship between MRONJ occurrence and single nucleotide polymorphisms (SNPs) of . Clinical information was collected, including current age, treatment duration, and comorbidity. Univariate and Multivariable regression analyzes were performed to evaluate the independent predictive factors for MRONJ occurrence. Predictive models were constructed using machine learning methods such as Lasso regression, Random forest (RF), and Support vector machine (SVM). The area under the receiver-operating curve (AUROC) was used to evaluate the performance of a binary classifier.

RESULT

Two SNPs of (rs4870056 and rs78177662) were significantly associated with MRONJ development. Patients with variant allele (A) of rs4870056 showed 2.45 times (95% CI, 1.03-5.87) the odds of MRONJ occurrence compared to those with wild-type homozygote (GG) after adjusting covariates. Additionally, carriers with variant allele (T) of rs78177662 had higher odds than those with wild-type homozygote (CC) (adjusted odds ratio (aOR), 2.64, 95% CI, 1.00-6.94). Among demographic variables, age ≥ 72 years (aOR, 3.98, 95% CI, 1.60-9.87) and bisphosphonate exposure ≥48 months (aOR, 3.16, 95% CI, 1.26-7.93) were also significant risk factors for MRONJ occurrence. AUROC values of machine learning methods ranged between 0.756-0.806 in the study.

CONCLUSION

Our study showed that the MRONJ occurrence was associated with polymorphisms in osteoporotic women.

摘要

目的

本研究旨在评估（）基因多态性对骨质疏松症女性颌骨药物相关性骨坏死（MRONJ）发生发展的影响。

方法

共评估了125例服用双膦酸盐的患者，分析MRONJ发生与（）单核苷酸多态性（SNP）之间的关系。收集临床信息，包括当前年龄、治疗持续时间和合并症。进行单因素和多因素回归分析，以评估MRONJ发生的独立预测因素。使用Lasso回归、随机森林（RF）和支持向量机（SVM）等机器学习方法构建预测模型。采用受试者操作特征曲线下面积（AUROC）评估二元分类器的性能。

结果

（）的两个SNP（rs4870056和rs78177662）与MRONJ的发生显著相关。在校正协变量后，rs4870056变异等位基因（A）的患者发生MRONJ的几率是野生型纯合子（GG）患者的2.45倍（95%CI，1.03 - 5.87）。此外，rs78177662变异等位基因（T）的携带者发生MRONJ的几率高于野生型纯合子（CC）携带者（调整后的优势比（aOR）为2.64，95%CI，1.00 - 6.94）。在人口统计学变量中，年龄≥72岁（aOR，3.98，95%CI，1.60 - 9.87）和双膦酸盐暴露≥48个月（aOR，3.16，95%CI，1.26 - 7.93）也是MRONJ发生的显著危险因素。本研究中机器学习方法的AUROC值在0.756 - 0.806之间。