Development and validation of a point-based scoring system for predicting axillary lymph node metastasis and disease outcome in breast cancer using clinicopathological and multiparametric MRI features

Cancer Imaging

Research Article

Yue Li¹  Weixiong Fan¹  Zhiqi Yang²  Xiangguang Chen²  Xiaofeng Chen²  Zhuozhi Dai³  Ruibin Huang⁴  Yuting Liao⁵  Guijin Li⁶  Mengzhu Wang⁷ 

[1] Department of Radiology, Meizhou People’s Hospital, 514031, Meizhou, China;Department of Radiology, Meizhou People’s Hospital, 514031, Meizhou, China;Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, 514031, Meizhou, People’s Republic of China;Department of Radiology, Shantou Central Hospital, 515041, Shantou, Guangdong, People’s Republic of China;Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 510120, Guangzhou, Guangdong, China;Department of Radiology, The First Affiliated Hospital of Shantou University Medical College, 515000, Shantou, People’s Republic of China;GE Healthcare, 510623, Guangzhou, China;MR Application, Siemens Healthineers, 201318, Shanghai, China;MR Scientific Marketing, Siemens Healthineers, 510620, Guangzhou, China;

关键词: Lymphatic metastasis;    Prognosis;    Breast neoplasms;    Multiparametric magnetic resonance imaging;    Risk factors;   

DOI  :  10.1186/s40644-023-00564-9

 received in 2022-10-20, accepted in 2023-05-01,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundAxillary lymph node (ALN) metastasis is used to select treatment strategies and define the prognosis in breast cancer (BC) patients and is typically assessed using an invasive procedure. Noninvasive, simple, and reliable tools to accurately predict ALN status are desirable. We aimed to develop and validate a point-based scoring system (PSS) for stratifying the ALN metastasis risk of BC based on clinicopathological and quantitative MRI features and to explore its prognostic significance.MethodsA total of 219 BC patients were evaluated. The clinicopathological and quantitative MRI features of the tumors were collected. A multivariate logistic regression analysis was used to create the PSS. The performance of the models was evaluated using receiver operating characteristic curves, and the area under the curve (AUC) of the models was calculated. Kaplan–Meier curves were used to analyze the survival outcomes.ResultsClinical features, including the American Joint Committee on Cancer (AJCC) stage, T stage, human epidermal growth factor receptor-2, estrogen receptor, and quantitative MRI features, including maximum tumor diameter, Kep, Ve, and TTP, were identified as risk factors for ALN metastasis and were assigned scores for the PSS. The PSS achieved an AUC of 0.799 in the primary cohort and 0.713 in the validation cohort. The recurrence-free survival (RFS) and overall survival (OS) of the high-risk (> 19.5 points) groups were significantly shorter than those of the low-risk (≤ 19.5 points) groups in the PSS.ConclusionPSS could predict the ALN metastasis risk of BC. A PSS greater than 19.5 was demonstrated to be a predictor of short RFS and OS.

【 授权许可】

CC BY   
© The Author(s) 2023

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