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A Predictive Model for Nonsentinel Node Status after Sentinel Lymph Node Biopsy in Sentinel Lymph Node-Positive Chinese Women with Early Breast Cancer

BACKGROUND: Axial lymph node dissection (ALND) is needed in patients with positive sentinel lymph node (SLN). ALND is easy to cause upper limb edema. Therefore, accurate prediction of nonsentinel lymph nodes (non-SLN) which may not need ALND can avoid excessive dissection and reduce complications. W...

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Autores principales: He, Lifang, Liang, Peide, Zeng, Huancheng, Huang, Guangsheng, Wu, Jundong, Zhang, Yiwen, Cui, Yukun, Huang, Wenhe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8894031/
https://www.ncbi.nlm.nih.gov/pubmed/35251176
http://dx.doi.org/10.1155/2022/7704686
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author He, Lifang
Liang, Peide
Zeng, Huancheng
Huang, Guangsheng
Wu, Jundong
Zhang, Yiwen
Cui, Yukun
Huang, Wenhe
author_facet He, Lifang
Liang, Peide
Zeng, Huancheng
Huang, Guangsheng
Wu, Jundong
Zhang, Yiwen
Cui, Yukun
Huang, Wenhe
author_sort He, Lifang
collection PubMed
description BACKGROUND: Axial lymph node dissection (ALND) is needed in patients with positive sentinel lymph node (SLN). ALND is easy to cause upper limb edema. Therefore, accurate prediction of nonsentinel lymph nodes (non-SLN) which may not need ALND can avoid excessive dissection and reduce complications. We constructed a new prognostic model to predict the non-SLN metastasis of Chinese breast cancer patients. METHODS: We enrolled 736 patients who underwent sentinel lymph node biopsy (SLNB); 228 (30.98%) were diagnosed with SLNB metastasis which was determined by intraoperative pathological detection and further accepted ALND. We constructed a prediction model by univariate analysis, multivariate analysis, “R” language, and binary logistic regression in the abovementioned 228 patients and verified this prediction model in 60 patients. RESULTS: Based on univariate analysis using α = 0.05 as the significance level for type I error, we found that age (P=0.045), tumor size (P=0.006), multifocality (P=0.011), lymphovascular invasion (P=0.003), positive SLN number (P=0.009), and negative SLN number (P=0.034) were statistically significant. Age was excluded in multivariate analysis, and we constructed a predictive equation to assess the risk of non-SLN metastasis: Logit(P)=Ln(P/1 − P)=0.267∗a+1.443∗b+1.078∗c+0.471∗d − 0.618∗e − 2.541 (where “a” represents tumor size, “b” represents multifocality, “c” represents lymphovascular invasion, “d” represents the number of metastasis of SLN, and “e” represents the number of SLNs without metastasis). AUCs for the training group and validation group were 0.715 and 0.744, respectively. When setting the risk value below 22.3%, as per the prediction equation's low-risk interval, our model predicted that about 4% of patients could avoid ALND. CONCLUSIONS: This study established a model which demonstrated good prognostic performance in assessing the risk of non-SLN metastasis in Chinese patients with positive SLNs.
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spelling pubmed-88940312022-03-04 A Predictive Model for Nonsentinel Node Status after Sentinel Lymph Node Biopsy in Sentinel Lymph Node-Positive Chinese Women with Early Breast Cancer He, Lifang Liang, Peide Zeng, Huancheng Huang, Guangsheng Wu, Jundong Zhang, Yiwen Cui, Yukun Huang, Wenhe J Oncol Research Article BACKGROUND: Axial lymph node dissection (ALND) is needed in patients with positive sentinel lymph node (SLN). ALND is easy to cause upper limb edema. Therefore, accurate prediction of nonsentinel lymph nodes (non-SLN) which may not need ALND can avoid excessive dissection and reduce complications. We constructed a new prognostic model to predict the non-SLN metastasis of Chinese breast cancer patients. METHODS: We enrolled 736 patients who underwent sentinel lymph node biopsy (SLNB); 228 (30.98%) were diagnosed with SLNB metastasis which was determined by intraoperative pathological detection and further accepted ALND. We constructed a prediction model by univariate analysis, multivariate analysis, “R” language, and binary logistic regression in the abovementioned 228 patients and verified this prediction model in 60 patients. RESULTS: Based on univariate analysis using α = 0.05 as the significance level for type I error, we found that age (P=0.045), tumor size (P=0.006), multifocality (P=0.011), lymphovascular invasion (P=0.003), positive SLN number (P=0.009), and negative SLN number (P=0.034) were statistically significant. Age was excluded in multivariate analysis, and we constructed a predictive equation to assess the risk of non-SLN metastasis: Logit(P)=Ln(P/1 − P)=0.267∗a+1.443∗b+1.078∗c+0.471∗d − 0.618∗e − 2.541 (where “a” represents tumor size, “b” represents multifocality, “c” represents lymphovascular invasion, “d” represents the number of metastasis of SLN, and “e” represents the number of SLNs without metastasis). AUCs for the training group and validation group were 0.715 and 0.744, respectively. When setting the risk value below 22.3%, as per the prediction equation's low-risk interval, our model predicted that about 4% of patients could avoid ALND. CONCLUSIONS: This study established a model which demonstrated good prognostic performance in assessing the risk of non-SLN metastasis in Chinese patients with positive SLNs. Hindawi 2022-02-24 /pmc/articles/PMC8894031/ /pubmed/35251176 http://dx.doi.org/10.1155/2022/7704686 Text en Copyright © 2022 Lifang He et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
He, Lifang
Liang, Peide
Zeng, Huancheng
Huang, Guangsheng
Wu, Jundong
Zhang, Yiwen
Cui, Yukun
Huang, Wenhe
A Predictive Model for Nonsentinel Node Status after Sentinel Lymph Node Biopsy in Sentinel Lymph Node-Positive Chinese Women with Early Breast Cancer
title A Predictive Model for Nonsentinel Node Status after Sentinel Lymph Node Biopsy in Sentinel Lymph Node-Positive Chinese Women with Early Breast Cancer
title_full A Predictive Model for Nonsentinel Node Status after Sentinel Lymph Node Biopsy in Sentinel Lymph Node-Positive Chinese Women with Early Breast Cancer
title_fullStr A Predictive Model for Nonsentinel Node Status after Sentinel Lymph Node Biopsy in Sentinel Lymph Node-Positive Chinese Women with Early Breast Cancer
title_full_unstemmed A Predictive Model for Nonsentinel Node Status after Sentinel Lymph Node Biopsy in Sentinel Lymph Node-Positive Chinese Women with Early Breast Cancer
title_short A Predictive Model for Nonsentinel Node Status after Sentinel Lymph Node Biopsy in Sentinel Lymph Node-Positive Chinese Women with Early Breast Cancer
title_sort predictive model for nonsentinel node status after sentinel lymph node biopsy in sentinel lymph node-positive chinese women with early breast cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8894031/
https://www.ncbi.nlm.nih.gov/pubmed/35251176
http://dx.doi.org/10.1155/2022/7704686
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