A negative binomial regression model for risk estimation of 0–2 axillary lymph node metastases in breast cancer patients

Abstract Extensive clinical trials indicate that patients with negative sentinel lymph node biopsy do not need axillary lymph node dissection (ALND). However, the ACOSOG Z0011 trial indicates that patients with clinically negative axillary lymph nodes (ALNs) and 1–2 positive sentinel lymph nodes hav...

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Autores principales:	De Zeng, Hao-Yu Lin, Yu-Ling Zhang, Jun-Dong Wu, Kun Lin, Ya Xu, Chun-Fa Chen
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3a7c45db41e544efa00cbce9103b0624
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spelling	oai:doaj.org-article:3a7c45db41e544efa00cbce9103b06242021-12-02T13:58:25ZA negative binomial regression model for risk estimation of 0–2 axillary lymph node metastases in breast cancer patients10.1038/s41598-020-79016-42045-2322https://doaj.org/article/3a7c45db41e544efa00cbce9103b06242020-12-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-79016-4https://doaj.org/toc/2045-2322Abstract Extensive clinical trials indicate that patients with negative sentinel lymph node biopsy do not need axillary lymph node dissection (ALND). However, the ACOSOG Z0011 trial indicates that patients with clinically negative axillary lymph nodes (ALNs) and 1–2 positive sentinel lymph nodes having breast conserving surgery with whole breast radiotherapy do not benefit from ALND. The aim of this study is therefore to identify those patients with 0–2 positive nodes who might avoid ALND. A total of 486 patients were eligible for the study with 212 patients in the modeling group and 274 patients in the validation group, respectively. Clinical lymph node status, histologic grade, estrogen receptor status, and human epidermal growth factor receptor 2 status were found to be significantly associated with ALN metastasis. A negative binomial regression (NBR) model was developed to predict the probability of having 0–2 ALN metastases with the area under the curve of 0.881 (95% confidence interval 0.829–0.921, P < 0.001) in the modeling group and 0.758 (95% confidence interval 0.702–0.807, P < 0.001) in the validation group. Decision curve analysis demonstrated that the model was clinically useful. The NBR model demonstrated adequate discriminative ability and clinical utility for predicting 0–2 ALN metastases.De ZengHao-Yu LinYu-Ling ZhangJun-Dong WuKun LinYa XuChun-Fa ChenNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-11 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q De Zeng Hao-Yu Lin Yu-Ling Zhang Jun-Dong Wu Kun Lin Ya Xu Chun-Fa Chen A negative binomial regression model for risk estimation of 0–2 axillary lymph node metastases in breast cancer patients
description	Abstract Extensive clinical trials indicate that patients with negative sentinel lymph node biopsy do not need axillary lymph node dissection (ALND). However, the ACOSOG Z0011 trial indicates that patients with clinically negative axillary lymph nodes (ALNs) and 1–2 positive sentinel lymph nodes having breast conserving surgery with whole breast radiotherapy do not benefit from ALND. The aim of this study is therefore to identify those patients with 0–2 positive nodes who might avoid ALND. A total of 486 patients were eligible for the study with 212 patients in the modeling group and 274 patients in the validation group, respectively. Clinical lymph node status, histologic grade, estrogen receptor status, and human epidermal growth factor receptor 2 status were found to be significantly associated with ALN metastasis. A negative binomial regression (NBR) model was developed to predict the probability of having 0–2 ALN metastases with the area under the curve of 0.881 (95% confidence interval 0.829–0.921, P < 0.001) in the modeling group and 0.758 (95% confidence interval 0.702–0.807, P < 0.001) in the validation group. Decision curve analysis demonstrated that the model was clinically useful. The NBR model demonstrated adequate discriminative ability and clinical utility for predicting 0–2 ALN metastases.
format	article
author	De Zeng Hao-Yu Lin Yu-Ling Zhang Jun-Dong Wu Kun Lin Ya Xu Chun-Fa Chen
author_facet	De Zeng Hao-Yu Lin Yu-Ling Zhang Jun-Dong Wu Kun Lin Ya Xu Chun-Fa Chen
author_sort	De Zeng
title	A negative binomial regression model for risk estimation of 0–2 axillary lymph node metastases in breast cancer patients
title_short	A negative binomial regression model for risk estimation of 0–2 axillary lymph node metastases in breast cancer patients
title_full	A negative binomial regression model for risk estimation of 0–2 axillary lymph node metastases in breast cancer patients
title_fullStr	A negative binomial regression model for risk estimation of 0–2 axillary lymph node metastases in breast cancer patients
title_full_unstemmed	A negative binomial regression model for risk estimation of 0–2 axillary lymph node metastases in breast cancer patients
title_sort	negative binomial regression model for risk estimation of 0–2 axillary lymph node metastases in breast cancer patients
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/3a7c45db41e544efa00cbce9103b0624
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A negative binomial regression model for risk estimation of 0–2 axillary lymph node metastases in breast cancer patients

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