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Nomograms for preoperative prediction of axillary nodal status in breast cancer

BACKGROUND: Axillary staging in patients with breast cancer and clinically node‐negative disease is performed by sentinel node biopsy (SLNB). The aim of this study was to integrate feasible preoperative variables into nomograms to guide clinicians in stratifying treatment options into no axillary st...

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Autores principales: Dihge, L., Bendahl, P.‐O., Rydén, L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Ltd 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5601253/
https://www.ncbi.nlm.nih.gov/pubmed/28718896
http://dx.doi.org/10.1002/bjs.10583
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author Dihge, L.
Bendahl, P.‐O.
Rydén, L.
author_facet Dihge, L.
Bendahl, P.‐O.
Rydén, L.
author_sort Dihge, L.
collection PubMed
description BACKGROUND: Axillary staging in patients with breast cancer and clinically node‐negative disease is performed by sentinel node biopsy (SLNB). The aim of this study was to integrate feasible preoperative variables into nomograms to guide clinicians in stratifying treatment options into no axillary staging for patients with non‐metastatic disease (N0), SLNB for those with one or two metastases, and axillary lymph node dissection (ALND) for patients with three or more metastases. METHODS: Patients presenting to Skåne University Hospital, Lund, with breast cancer were included in a prospectively maintained registry between January 2009 and December 2012. Those with a preoperative diagnosis of nodal metastases were excluded. Patients with data on hormone receptor status, human epidermal growth factor receptor 2 and Ki‐67 expression were included to allow grouping into surrogate molecular subtypes. Based on logistic regression analyses, nomograms summarizing the strength of the associations between the predictors and each nodal status endpoint were developed. Predictive performance was assessed using the area under the receiver operating characteristic (ROC) curve. Bootstrap resampling was performed for internal validation. RESULTS: Of the 692 patients eligible for analysis, 248 were diagnosed with node‐positive disease. Molecular subtype, age, mode of detection, tumour size, multifocality and vascular invasion were identified as predictors of any nodal disease. Nomograms that included these predictors demonstrated good predictive abilities, and comparable performances in the internal validation; the area under the ROC curve was 0·74 for N0 versus any lymph node metastasis, 0·70 for one or two involved nodes versus N0, and 0·81 for at least three nodes versus two or fewer metastatic nodes. CONCLUSION: The nomograms presented facilitate preoperative decision‐making regarding the extent of axillary surgery.
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spelling pubmed-56012532017-10-03 Nomograms for preoperative prediction of axillary nodal status in breast cancer Dihge, L. Bendahl, P.‐O. Rydén, L. Br J Surg Original Articles BACKGROUND: Axillary staging in patients with breast cancer and clinically node‐negative disease is performed by sentinel node biopsy (SLNB). The aim of this study was to integrate feasible preoperative variables into nomograms to guide clinicians in stratifying treatment options into no axillary staging for patients with non‐metastatic disease (N0), SLNB for those with one or two metastases, and axillary lymph node dissection (ALND) for patients with three or more metastases. METHODS: Patients presenting to Skåne University Hospital, Lund, with breast cancer were included in a prospectively maintained registry between January 2009 and December 2012. Those with a preoperative diagnosis of nodal metastases were excluded. Patients with data on hormone receptor status, human epidermal growth factor receptor 2 and Ki‐67 expression were included to allow grouping into surrogate molecular subtypes. Based on logistic regression analyses, nomograms summarizing the strength of the associations between the predictors and each nodal status endpoint were developed. Predictive performance was assessed using the area under the receiver operating characteristic (ROC) curve. Bootstrap resampling was performed for internal validation. RESULTS: Of the 692 patients eligible for analysis, 248 were diagnosed with node‐positive disease. Molecular subtype, age, mode of detection, tumour size, multifocality and vascular invasion were identified as predictors of any nodal disease. Nomograms that included these predictors demonstrated good predictive abilities, and comparable performances in the internal validation; the area under the ROC curve was 0·74 for N0 versus any lymph node metastasis, 0·70 for one or two involved nodes versus N0, and 0·81 for at least three nodes versus two or fewer metastatic nodes. CONCLUSION: The nomograms presented facilitate preoperative decision‐making regarding the extent of axillary surgery. John Wiley & Sons, Ltd 2017-07-18 2017-10 /pmc/articles/PMC5601253/ /pubmed/28718896 http://dx.doi.org/10.1002/bjs.10583 Text en © 2017 The Authors. BJS published by John Wiley & Sons Ltd on behalf of BJS Society Ltd. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs (http://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Original Articles
Dihge, L.
Bendahl, P.‐O.
Rydén, L.
Nomograms for preoperative prediction of axillary nodal status in breast cancer
title Nomograms for preoperative prediction of axillary nodal status in breast cancer
title_full Nomograms for preoperative prediction of axillary nodal status in breast cancer
title_fullStr Nomograms for preoperative prediction of axillary nodal status in breast cancer
title_full_unstemmed Nomograms for preoperative prediction of axillary nodal status in breast cancer
title_short Nomograms for preoperative prediction of axillary nodal status in breast cancer
title_sort nomograms for preoperative prediction of axillary nodal status in breast cancer
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5601253/
https://www.ncbi.nlm.nih.gov/pubmed/28718896
http://dx.doi.org/10.1002/bjs.10583
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