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Simple Prediction Model of Axillary Lymph Node Positivity After Analyzing Molecular and Clinical Factors in Early Breast Cancer

The aim of this study was to evaluate the association between pretreatment molecular and clinical factors and axillary lymph node metastases in early breast cancer. A total of 367 consecutive breast cancer patients with cT1–2NxM0 who underwent breast conserving surgery and axillary lymph node dissec...

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Autores principales: Chung, Mi Joo, Lee, Jong Hoon, Kim, Sung Hwan, Suh, Young Jin, Choi, Hyun Joo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4902419/
https://www.ncbi.nlm.nih.gov/pubmed/27196477
http://dx.doi.org/10.1097/MD.0000000000003689
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author Chung, Mi Joo
Lee, Jong Hoon
Kim, Sung Hwan
Suh, Young Jin
Choi, Hyun Joo
author_facet Chung, Mi Joo
Lee, Jong Hoon
Kim, Sung Hwan
Suh, Young Jin
Choi, Hyun Joo
author_sort Chung, Mi Joo
collection PubMed
description The aim of this study was to evaluate the association between pretreatment molecular and clinical factors and axillary lymph node metastases in early breast cancer. A total of 367 consecutive breast cancer patients with cT1–2NxM0 who underwent breast conserving surgery and axillary lymph node dissection followed by whole breast irradiation were enrolled. We evaluated the pathologic tumor and node status, tumor differentiation, calcification, and lymphovascular invasion, the status of estrogen receptor (ER), progesterone receptor (PR), epidermal growth factor receptor 1 (EGFR1), and human epidermal growth factor receptor 2 (HER2), the expression of E-cadherin, P53, and Ki-67 index. Totally, 108 (29.4%) of the 367 patients had positive axillary lymph nodes. An increased tumor size (P = 0.024), the presence of lymphovascular invasion (P < 0.001), and Ki-67 index of >20% (P = 0.038) were significantly associated with axillary lymph node metastases on the multivariate analysis. In our study, 86.2% of the patients with all the unfavorable factors had an involvement of axillary nodal metastases, and only 12.2% of the patients with all the favorable predictors had positive axillary nodes. The predictive power was significant on the receiver operating curve (P < 0.001). We found that several factors, such as tumor size, lymphovascular invasion, and the Ki-67 index, are independent factors that predict positive ALNM on multivariate analysis for the patients with cT1–2 breast cancer. Clinicians simply could predict the probability of ALNM after verifying the molecular and clinical factors in early breast cancer.
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spelling pubmed-49024192016-06-23 Simple Prediction Model of Axillary Lymph Node Positivity After Analyzing Molecular and Clinical Factors in Early Breast Cancer Chung, Mi Joo Lee, Jong Hoon Kim, Sung Hwan Suh, Young Jin Choi, Hyun Joo Medicine (Baltimore) 5700 The aim of this study was to evaluate the association between pretreatment molecular and clinical factors and axillary lymph node metastases in early breast cancer. A total of 367 consecutive breast cancer patients with cT1–2NxM0 who underwent breast conserving surgery and axillary lymph node dissection followed by whole breast irradiation were enrolled. We evaluated the pathologic tumor and node status, tumor differentiation, calcification, and lymphovascular invasion, the status of estrogen receptor (ER), progesterone receptor (PR), epidermal growth factor receptor 1 (EGFR1), and human epidermal growth factor receptor 2 (HER2), the expression of E-cadherin, P53, and Ki-67 index. Totally, 108 (29.4%) of the 367 patients had positive axillary lymph nodes. An increased tumor size (P = 0.024), the presence of lymphovascular invasion (P < 0.001), and Ki-67 index of >20% (P = 0.038) were significantly associated with axillary lymph node metastases on the multivariate analysis. In our study, 86.2% of the patients with all the unfavorable factors had an involvement of axillary nodal metastases, and only 12.2% of the patients with all the favorable predictors had positive axillary nodes. The predictive power was significant on the receiver operating curve (P < 0.001). We found that several factors, such as tumor size, lymphovascular invasion, and the Ki-67 index, are independent factors that predict positive ALNM on multivariate analysis for the patients with cT1–2 breast cancer. Clinicians simply could predict the probability of ALNM after verifying the molecular and clinical factors in early breast cancer. Wolters Kluwer Health 2016-05-20 /pmc/articles/PMC4902419/ /pubmed/27196477 http://dx.doi.org/10.1097/MD.0000000000003689 Text en Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved. http://creativecommons.org/licenses/by/4.0 This is an open access article distributed under the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0
spellingShingle 5700
Chung, Mi Joo
Lee, Jong Hoon
Kim, Sung Hwan
Suh, Young Jin
Choi, Hyun Joo
Simple Prediction Model of Axillary Lymph Node Positivity After Analyzing Molecular and Clinical Factors in Early Breast Cancer
title Simple Prediction Model of Axillary Lymph Node Positivity After Analyzing Molecular and Clinical Factors in Early Breast Cancer
title_full Simple Prediction Model of Axillary Lymph Node Positivity After Analyzing Molecular and Clinical Factors in Early Breast Cancer
title_fullStr Simple Prediction Model of Axillary Lymph Node Positivity After Analyzing Molecular and Clinical Factors in Early Breast Cancer
title_full_unstemmed Simple Prediction Model of Axillary Lymph Node Positivity After Analyzing Molecular and Clinical Factors in Early Breast Cancer
title_short Simple Prediction Model of Axillary Lymph Node Positivity After Analyzing Molecular and Clinical Factors in Early Breast Cancer
title_sort simple prediction model of axillary lymph node positivity after analyzing molecular and clinical factors in early breast cancer
topic 5700
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4902419/
https://www.ncbi.nlm.nih.gov/pubmed/27196477
http://dx.doi.org/10.1097/MD.0000000000003689
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