Cargando…
A New Model for Predicting Nonsentinel Lymph Node Metastasis in Early-Stage Breast Cancer Using MMP15
BACKGROUND: In early-stage breast cancer (BC) patients, 40–70% of lymph node metastases are limited to the sentinel lymph nodes (SLNs). Patients at low risk for nonsentinel lymph node (NSLN) metastasis should be exempt from axillary lymph node dissection (ALND) or regional lymph node radiotherapy (R...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9410952/ https://www.ncbi.nlm.nih.gov/pubmed/36035312 http://dx.doi.org/10.1155/2022/8675705 |
_version_ | 1784775211947655168 |
---|---|
author | Zeng, Xue Li, Yubing Sun, Chaonan Liu, Zhuang Zhao, Jiaming Ma, Xinchi Zhang, Yanyu Zhang, Na |
author_facet | Zeng, Xue Li, Yubing Sun, Chaonan Liu, Zhuang Zhao, Jiaming Ma, Xinchi Zhang, Yanyu Zhang, Na |
author_sort | Zeng, Xue |
collection | PubMed |
description | BACKGROUND: In early-stage breast cancer (BC) patients, 40–70% of lymph node metastases are limited to the sentinel lymph nodes (SLNs). Patients at low risk for nonsentinel lymph node (NSLN) metastasis should be exempt from axillary lymph node dissection (ALND) or regional lymph node radiotherapy (RNI). METHODS: The present study included 237 female early-stage BC patients with positive SLNs who received ALND. Based on the clinicopathological factors of the 158 patients in the training cohort, multivariate analysis was used to determine the independent risk factors for NSLN metastasis, which were used to establish the NSLN metastasis prediction model. The calibration and discrimination of this model were tested with the training and validation cohorts and compared to the Memorial Sloan Kettering Cancer Center (MSKCC) model. RESULTS: Tumor size, neural invasion, lymphovascular invasion, expression of matrix metalloproteinase 15 (MMP15) in the cytoplasm, and the number of positive SLNs were statistically significant by multivariate analysis (P < 0.05), which were used to establish the new model. The MSKCC model was verified by the training cohort, and the area under the receiver-operating characteristic (ROC) curve was 0.733 (95% CI: 0.650–0.816), which was less than that of the new model (0.824; 95% CI: 0.760–0.889). The area under the ROC curve in the validation cohort for the new model was 0.773 (95% CI: 0.669–0.877), and the calibration performed well. The false-negative rates were 3.2%, 6.5%, and 14.5% for the predicted probability cut-offs of 50%, 60%, and 70%, respectively. CONCLUSIONS: The new model included five variables: tumor size, neural invasion, lymphovascular invasion, cytoplasmic MMP15 expression, and the number of positive SLNs. The model with a cut-off of 60% could accurately identify low-risk patients with NSLN metastasis. |
format | Online Article Text |
id | pubmed-9410952 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-94109522022-08-26 A New Model for Predicting Nonsentinel Lymph Node Metastasis in Early-Stage Breast Cancer Using MMP15 Zeng, Xue Li, Yubing Sun, Chaonan Liu, Zhuang Zhao, Jiaming Ma, Xinchi Zhang, Yanyu Zhang, Na J Oncol Research Article BACKGROUND: In early-stage breast cancer (BC) patients, 40–70% of lymph node metastases are limited to the sentinel lymph nodes (SLNs). Patients at low risk for nonsentinel lymph node (NSLN) metastasis should be exempt from axillary lymph node dissection (ALND) or regional lymph node radiotherapy (RNI). METHODS: The present study included 237 female early-stage BC patients with positive SLNs who received ALND. Based on the clinicopathological factors of the 158 patients in the training cohort, multivariate analysis was used to determine the independent risk factors for NSLN metastasis, which were used to establish the NSLN metastasis prediction model. The calibration and discrimination of this model were tested with the training and validation cohorts and compared to the Memorial Sloan Kettering Cancer Center (MSKCC) model. RESULTS: Tumor size, neural invasion, lymphovascular invasion, expression of matrix metalloproteinase 15 (MMP15) in the cytoplasm, and the number of positive SLNs were statistically significant by multivariate analysis (P < 0.05), which were used to establish the new model. The MSKCC model was verified by the training cohort, and the area under the receiver-operating characteristic (ROC) curve was 0.733 (95% CI: 0.650–0.816), which was less than that of the new model (0.824; 95% CI: 0.760–0.889). The area under the ROC curve in the validation cohort for the new model was 0.773 (95% CI: 0.669–0.877), and the calibration performed well. The false-negative rates were 3.2%, 6.5%, and 14.5% for the predicted probability cut-offs of 50%, 60%, and 70%, respectively. CONCLUSIONS: The new model included five variables: tumor size, neural invasion, lymphovascular invasion, cytoplasmic MMP15 expression, and the number of positive SLNs. The model with a cut-off of 60% could accurately identify low-risk patients with NSLN metastasis. Hindawi 2022-08-18 /pmc/articles/PMC9410952/ /pubmed/36035312 http://dx.doi.org/10.1155/2022/8675705 Text en Copyright © 2022 Xue Zeng 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 Zeng, Xue Li, Yubing Sun, Chaonan Liu, Zhuang Zhao, Jiaming Ma, Xinchi Zhang, Yanyu Zhang, Na A New Model for Predicting Nonsentinel Lymph Node Metastasis in Early-Stage Breast Cancer Using MMP15 |
title | A New Model for Predicting Nonsentinel Lymph Node Metastasis in Early-Stage Breast Cancer Using MMP15 |
title_full | A New Model for Predicting Nonsentinel Lymph Node Metastasis in Early-Stage Breast Cancer Using MMP15 |
title_fullStr | A New Model for Predicting Nonsentinel Lymph Node Metastasis in Early-Stage Breast Cancer Using MMP15 |
title_full_unstemmed | A New Model for Predicting Nonsentinel Lymph Node Metastasis in Early-Stage Breast Cancer Using MMP15 |
title_short | A New Model for Predicting Nonsentinel Lymph Node Metastasis in Early-Stage Breast Cancer Using MMP15 |
title_sort | new model for predicting nonsentinel lymph node metastasis in early-stage breast cancer using mmp15 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9410952/ https://www.ncbi.nlm.nih.gov/pubmed/36035312 http://dx.doi.org/10.1155/2022/8675705 |
work_keys_str_mv | AT zengxue anewmodelforpredictingnonsentinellymphnodemetastasisinearlystagebreastcancerusingmmp15 AT liyubing anewmodelforpredictingnonsentinellymphnodemetastasisinearlystagebreastcancerusingmmp15 AT sunchaonan anewmodelforpredictingnonsentinellymphnodemetastasisinearlystagebreastcancerusingmmp15 AT liuzhuang anewmodelforpredictingnonsentinellymphnodemetastasisinearlystagebreastcancerusingmmp15 AT zhaojiaming anewmodelforpredictingnonsentinellymphnodemetastasisinearlystagebreastcancerusingmmp15 AT maxinchi anewmodelforpredictingnonsentinellymphnodemetastasisinearlystagebreastcancerusingmmp15 AT zhangyanyu anewmodelforpredictingnonsentinellymphnodemetastasisinearlystagebreastcancerusingmmp15 AT zhangna anewmodelforpredictingnonsentinellymphnodemetastasisinearlystagebreastcancerusingmmp15 AT zengxue newmodelforpredictingnonsentinellymphnodemetastasisinearlystagebreastcancerusingmmp15 AT liyubing newmodelforpredictingnonsentinellymphnodemetastasisinearlystagebreastcancerusingmmp15 AT sunchaonan newmodelforpredictingnonsentinellymphnodemetastasisinearlystagebreastcancerusingmmp15 AT liuzhuang newmodelforpredictingnonsentinellymphnodemetastasisinearlystagebreastcancerusingmmp15 AT zhaojiaming newmodelforpredictingnonsentinellymphnodemetastasisinearlystagebreastcancerusingmmp15 AT maxinchi newmodelforpredictingnonsentinellymphnodemetastasisinearlystagebreastcancerusingmmp15 AT zhangyanyu newmodelforpredictingnonsentinellymphnodemetastasisinearlystagebreastcancerusingmmp15 AT zhangna newmodelforpredictingnonsentinellymphnodemetastasisinearlystagebreastcancerusingmmp15 |