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Characteristics of regional lymph node metastasis in breast cancer and construction of a nomogram model based on ultrasonographic analysis: a retrospective study.
Zhu, Meidi; Xu, Zipeng; Hu, Jing; Hua, Lingling; Zou, Yu; Qin, Fei; Chen, Chaobo.
Afiliação
  • Zhu M; Department of Ultrasound, Xishan People's Hospital of Wuxi City, Wuxi, 214105, China.
  • Xu Z; Department of General Surgery, Xishan People's Hospital of Wuxi City, Wuxi, 214105, China.
  • Hu J; Department of Postpartum Rehabilitation Center, Xishan People's Hospital of Wuxi City, Wuxi, Jiangsu, 214105, China.
  • Hua L; Department of Ultrasound, Xishan People's Hospital of Wuxi City, Wuxi, 214105, China.
  • Zou Y; Department of Ultrasound, Xishan People's Hospital of Wuxi City, Wuxi, 214105, China.
  • Qin F; Department of Ultrasound, Affiliated Wuxi Fifth Hospital of Jiangnan University, Wuxi, Jiangsu, 214011, China. 353397109@qq.com.
  • Chen C; Department of Ultrasound, the Fifth People's Hospital of Wuxi, Wuxi, Jiangsu, 214011, China. 353397109@qq.com.
World J Surg Oncol ; 22(1): 221, 2024 Aug 26.
Article em En | MEDLINE | ID: mdl-39183267
ABSTRACT

OBJECTIVE:

The ultrasonographic characteristics of lymph node metastasis in breast cancer patients were retrospectively analyzed, and a predictive nomogram model was constructed to provide an imaging basis for better clinical evaluation.

METHODS:

B-mode ultrasound was used to retrospectively analyze the imaging characteristics of regional lymph nodes and tumors. Pathological examination confirmed the presence of lymph node metastasis in breast cancer patients. Univariable and multivariable logistic regression analyses were performed to analyze the risk factors for lymph node metastasis. LASSO regression analysis was performed to screen noninvasive indicators, and a nomogram prediction model was constructed for breast cancer patients with lymph node metastasis.

RESULTS:

A total of 187 breast cancer patients were enrolled, including 74 patients with lymph node metastasis in the positive group and 113 patients without lymph node metastasis in the negative group. Multivariate analysis revealed that pathological type (OR = 4.58, 95% CI 1.44-14.6, p = 0.01), tumor diameter (OR = 1.37, 95% CI 1.07-1.74, p = 0.012), spiculated margins (OR = 7.92, 95% CI 3.03-20.67, p < 0.001), mixed echo of the breast tumor (OR = 37.09, 95% CI 3.49-394.1, p = 0.003), and unclear lymphatic hilum structure (OR = 16.07, 95% CI 2.41-107.02, p = 0.004) were independent risk factors for lymph node metastasis. A nomogram model was constructed for predicting breast cancer with lymph node metastasis, incorporating three significantly correlated indicators identified through LASSO regression analysis, namely, tumor spiculated margins, cortical thickness of lymph nodes, and unclear lymphatic hilum structure. The receiver operating characteristic (ROC) curve revealed that the area under the curve (AUC) was 0.717 (95% CI, 0.614-0.820) for the training set and 0.817 (95% CI, 0.738-0.890) for the validation set. The Hosmer-Lemeshow test results for the training set and the validation set were p = 0.9148 and p = 0.1648, respectively. The prediction nomogram has good diagnostic performance.

CONCLUSIONS:

B-mode ultrasound is helpful in the preoperative assessment of breast cancer patients with lymph node metastasis. The predictive nomogram model, which is based on logistic regression and LASSO regression analysis, is clinically safe, reliable, and highly practical.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Nomogramas / Linfonodos / Metástase Linfática Limite: Adult / Aged / Female / Humans / Middle aged Idioma: En Revista: World J Surg Oncol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Nomogramas / Linfonodos / Metástase Linfática Limite: Adult / Aged / Female / Humans / Middle aged Idioma: En Revista: World J Surg Oncol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Reino Unido