Literature DB >> 28629690

Axillary Lymph Node Sonographic Features and Breast Tumor Characteristics as Predictors of Malignancy: A Nomogram to Predict Risk.

Patricia Akissue de Camargo Teixeira1, Luciano F Chala2, Carlos Shimizu2, José R Filassi3, Jonathan Y Maesaka3, Nestor de Barros2.   

Abstract

The purpose of this study was to build a mathematical model to predict the probability of axillary lymph node metastasis based on the ultrasonographic features of axillary lymph nodes and the tumor characteristics. We included 74 patients (75 axillae) with invasive breast cancer who underwent axillary ultrasonography ipsilateral to the tumor and fine-needle aspiration of one selected lymph node. Lymph node pathology results from sentinel lymph node biopsy or surgical dissection were correlated with lymph node ultrasonographic data and with the cytologic findings of fine-needle aspiration. Our mathematical model of prediction risk of lymph node metastasis included only pre-surgical data from logistic regression analysis: lymph node cortical thickness (p = 0.005), pre-surgical tumor size (p = 0.030), menopausal status (p = 0.017), histologic type (p = 0.034) and tumor location (p = 0.011). The area under the receiver operating characteristic curve of the model was 0.848, reflecting an excellent discrimination of the model. This nomogram may assist in the choice of the optimal axillary approach.
Copyright © 2017 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Axillary lymph node metastasis; Axillary ultrasound; Breast cancer; Breast tumor characteristics; Fine-needle aspiration; Lymph node ultrasound features; Nomogram; Statistical model

Mesh:

Year:  2017        PMID: 28629690     DOI: 10.1016/j.ultrasmedbio.2017.05.003

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  8 in total

1.  A Convolutional Neural Network Based on Ultrasound Images of Primary Breast Masses: Prediction of Lymph-Node Metastasis in Collaboration With Classification of Benign and Malignant Tumors.

Authors:  Chunxiao Li; Yuanfan Guo; Liqiong Jia; Minghua Yao; Sihui Shao; Jing Chen; Yi Xu; Rong Wu
Journal:  Front Physiol       Date:  2022-06-02       Impact factor: 4.755

2.  Elaboration and Validation of a Nomogram Based on Axillary Ultrasound and Tumor Clinicopathological Features to Predict Axillary Lymph Node Metastasis in Patients With Breast Cancer.

Authors:  Yubo Liu; Feng Ye; Yun Wang; Xueyi Zheng; Yini Huang; Jianhua Zhou
Journal:  Front Oncol       Date:  2022-05-16       Impact factor: 5.738

Review 3.  Integrating Adjuvant Radiation with Post-Neoadjuvant Therapies in Early Breast Cancer.

Authors:  Max S Mano; Leandro Jonata C Oliveira; Samir A Hanna
Journal:  Curr Oncol Rep       Date:  2021-03-26       Impact factor: 5.075

4.  Nomograms for Predicting Axillary Lymph Node Status Reconciled With Preoperative Breast Ultrasound Images.

Authors:  Dongmei Liu; Yujia Lan; Lei Zhang; Tong Wu; Hao Cui; Ziyao Li; Ping Sun; Peng Tian; Jiawei Tian; Xia Li
Journal:  Front Oncol       Date:  2021-04-07       Impact factor: 6.244

5.  Accuracy of ultrasonographic changes during neoadjuvant chemotherapy to predict axillary lymph node response in clinical node-positive breast cancer patients.

Authors:  Zhuoxuan Li; Yiwei Tong; Xiaosong Chen; Kunwei Shen
Journal:  Front Oncol       Date:  2022-07-22       Impact factor: 5.738

6.  Prediction model of axillary lymph node status using automated breast ultrasound (ABUS) and ki-67 status in early-stage breast cancer.

Authors:  Qiucheng Wang; Bo Li; Zhao Liu; Haitao Shang; Hui Jing; Hua Shao; Kexin Chen; Xiaoshuan Liang; Wen Cheng
Journal:  BMC Cancer       Date:  2022-08-28       Impact factor: 4.638

7.  Preoperative prediction of axillary lymph node metastasis in patients with breast cancer based on radiomics of gray-scale ultrasonography.

Authors:  Wei-Jun Zhou; Yi-Dan Zhang; Wen-Tao Kong; Chao-Xue Zhang; Bing Zhang
Journal:  Gland Surg       Date:  2021-06

8.  Predicting Axillary Lymph Node Status With a Nomogram Based on Breast Lesion Ultrasound Features: Performance in N1 Breast Cancer Patients.

Authors:  Yanwen Luo; Chenyang Zhao; Yuanjing Gao; Mengsu Xiao; Wenbo Li; Jing Zhang; Li Ma; Jing Qin; Yuxin Jiang; Qingli Zhu
Journal:  Front Oncol       Date:  2020-10-27       Impact factor: 6.244

  8 in total

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