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Predicting the risk of axillary lymph node metastasis in early breast cancer patients based on ultrasonographic-clinicopathologic features and the use of nomograms: a prospective single-center observational study.
Fong, Wengcheng; Tan, Luyuan; Tan, Cui; Wang, Hongli; Liu, Fengtao; Tian, Huan; Shen, Shiyu; Gu, Ran; Hu, Yue; Jiang, Xiaofang; Mei, Jingsi; Liang, Jing; Hu, Tingting; Chen, Kai; Yu, Fengyan.
Afiliação
  • Fong W; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China.
  • Tan L; Department of Breast Surgery, Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107 Yanjiang West Road, Guangzhou, 510120, China.
  • Tan C; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China.
  • Wang H; Department of Breast Surgery, Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107 Yanjiang West Road, Guangzhou, 510120, China.
  • Liu F; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China.
  • Tian H; Department of Pathology, Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
  • Shen S; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China.
  • Gu R; Diagnostic Department, Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
  • Hu Y; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China.
  • Jiang X; Diagnostic Department, Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
  • Mei J; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China.
  • Liang J; Department of Breast Surgery, Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107 Yanjiang West Road, Guangzhou, 510120, China.
  • Hu T; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China.
  • Chen K; Diagnostic Department, Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
  • Yu F; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China.
Eur Radiol ; 32(12): 8200-8212, 2022 Dec.
Article em En | MEDLINE | ID: mdl-36169686
ABSTRACT

OBJECTIVES:

The purpose of this study was to establish two preoperative nomograms to evaluate the risk for axillary lymph node (ALN) metastasis in early breast cancer patients based on ultrasonographic-clinicopathologic features.

METHODS:

We prospectively evaluated 593 consecutive female participants who were diagnosed with cT1-3N0-1M0 breast cancer between March 2018 and May 2019 at Sun Yat-Sen Memorial Hospital. The participants were randomly classified into training and validation sets in a 41 ratio for the development and validation of the nomograms, respectively. Multivariate logistic regression analysis was performed to identify independent predictors of ALN status. We developed Nomogram A and Nomogram B to predict ALN metastasis (presence vs. absence) and the number of metastatic ALNs (≤ 2 vs. > 2), respectively.

RESULTS:

A total of 528 participants were evaluated in the final analyses. Multivariable analysis revealed that the number of suspicious lymph nodes, long axis, short-to-long axis ratio, cortical thickness, tumor location, and histological grade were independent predictors of ALN status. The AUCs of nomogram A in the training and validation groups were 0.83 and 0.78, respectively. The AUCs of nomogram B in the training and validation groups were 0.87 and 0.87, respectively. Both nomograms were well-calibrated.

CONCLUSION:

We developed two preoperative nomograms that can be used to predict ALN metastasis (presence vs. absence) and the number of metastatic ALNs (≤ 2 vs. > 2) in early breast cancer patients. Both nomograms are useful tools that will help clinicians predict the risk of ALN metastasis and facilitate therapy decision-making about axillary surgery. KEY POINTS • We developed two preoperative nomograms to predict axillary lymph node status based on ultrasonographic-clinicopathologic features. • Nomogram A was used to predict axillary lymph node metastasis (presence vs. absence). The AUCs in the training and validation groups were 0.83 and 0.78, respectively. Nomogram B was used to estimate the number of metastatic lymph nodes ( ≤ 2 vs. > 2). The AUCs in the training and validation group were 0.87 and 0.87, respectively. • Our nomograms may help clinicians weigh the risks and benefits of axillary surgery more appropriately.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Nomogramas Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Revista: Eur Radiol Assunto da revista: RADIOLOGIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Nomogramas Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Revista: Eur Radiol Assunto da revista: RADIOLOGIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China