Risk prediction mode of breast cancer in patients with pathological nipple discharge based on decision tree method
10.3969/j.issn.1009-9905.2025.03.002
- VernacularTitle:基于决策树法构建病理性乳头溢液患者并发乳腺癌风险的预测模型
- Author:
Guang-dong SHAO
1
;
Ming-ming SHI
1
;
Yi-ning SONG
1
;
Chun-hong XU
1
;
Xiao-dong MA
1
;
Xiao-liang HAO
1
Author Information
1. 山东第二医科大学附属中医院(潍坊市中医院)甲状腺乳腺外科(山东 潍坊 261000)
- Publication Type:Journal Article
- Keywords:
Pathological nipple discharge;
Logistic regression analysis;
Decision tree model;
Breast neoplasms
- From:
Chinese Journal of Current Advances in General Surgery
2025;28(3):175-179
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To construct a decision tree model to predict the risk of breast cancer in patients with pathological nipple discharge.Methods:A total of 157 patients with pathological nipple discharge,who were diagnosed and treated at Weifang Municipal Hospital of Traditional Chinese Medicine from January 2019 to April 2024 and met the inclusion criteria,were selected.A risk prediction model for concurrent breast cancer in patients with pathological nipple discharge was developed using Logistic regression analysis.A decision tree was then constructed,and the predictive performance of the model was assessed based on the area under the receiver operating characteristic curve(AUC).Re-sults:The incidence of concurrent breast cancer among patients with pathological nipple discharge was 24.2%.Accord-ing to the results of binary Logistic regression analysis,elevated CEA and CA 153 levels in nipple discharge,as well as bloody discharge,emerged as independent risk factors for the development of breast cancer in such patients(P<0.05).Based on these findings,a decision tree model was constructed to predict the risk of concurrent breast cancer in patients with pathological nipple discharge.The validation results showed that the Logistic regression model had an AUC value of 0.800,while the decision tree model achieved an AUC value of 0.889.Conclusions:The decision tree model,built upon the identified influencing factors,exhibits strong predictive power for the risk of developing concurrent breast can-cer in patients with pathological nipple discharge,thus facilitating more precise preoperative diagnoses by clinicians for these patients.
