Prediction of nonsentinel lymph node metastasis in breast cancer patients based on machine learning

World Journal of Surgical Oncology

Research

Kun Qiao¹  Cong Jiang¹  Yuting Xiu¹  Shiyuan Zhang¹  Yuanxi Huang¹  Xiao Yu¹ 

[1] Department of Breast Surgery, Harbin Medical University Cancer Hospital, 150086, Harbin, China;

关键词: Machine learning;    Nomogram;    Breast cancer;    Nonsentinel lymph node metastasis;   

DOI  :  10.1186/s12957-023-03109-3

 received in 2023-02-11, accepted in 2023-07-12,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundDevelop the best machine learning (ML) model to predict nonsentinel lymph node metastases (NSLNM) in breast cancer patients.MethodsFrom June 2016 to August 2022, 1005 breast cancer patients were included in this retrospective study. Univariate and multivariate analyses were performed using logistic regression. Six ML models were introduced, and their performance was compared.ResultsNSLNM occurred in 338 (33.6%) of 1005 patients. The best ML model was XGBoost, whose average area under the curve (AUC) based on 10-fold cross-verification was 0.722. It performed better than the nomogram, which was based on logistic regression (AUC: 0.764 vs. 0.706).ConclusionsThe ML model XGBoost can well predict NSLNM in breast cancer patients.

【 授权许可】

CC BY   
© BioMed Central Ltd., part of Springer Nature 2023

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