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Ultrasound and clinicopathological characteristics-based model for prediction of pathologic response to neoadjuvant chemotherapy in HER2-positive breast cancer: a case–control study

BACKGROUND: The objective of this study was to develop a model combining ultrasound (US) and clinicopathological characteristics to predict the pathologic response to neoadjuvant chemotherapy (NACT) in human epidermal growth factor receptor 2 (HER2)-positive breast cancer. MATERIALS AND METHODS: Thi...

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Autores principales: Sui, Lin, Yan, Yuqi, Jiang, Tian, Ou, Di, Chen, Chen, Lai, Min, Ni, Chen, Zhu, Xi, Wang, Liping, Yang, Chen, Li, Wei, Yao, Jincao, Xu, Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10504141/
https://www.ncbi.nlm.nih.gov/pubmed/37639063
http://dx.doi.org/10.1007/s10549-023-07057-0
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author Sui, Lin
Yan, Yuqi
Jiang, Tian
Ou, Di
Chen, Chen
Lai, Min
Ni, Chen
Zhu, Xi
Wang, Liping
Yang, Chen
Li, Wei
Yao, Jincao
Xu, Dong
author_facet Sui, Lin
Yan, Yuqi
Jiang, Tian
Ou, Di
Chen, Chen
Lai, Min
Ni, Chen
Zhu, Xi
Wang, Liping
Yang, Chen
Li, Wei
Yao, Jincao
Xu, Dong
author_sort Sui, Lin
collection PubMed
description BACKGROUND: The objective of this study was to develop a model combining ultrasound (US) and clinicopathological characteristics to predict the pathologic response to neoadjuvant chemotherapy (NACT) in human epidermal growth factor receptor 2 (HER2)-positive breast cancer. MATERIALS AND METHODS: This is a retrospective study that included 248 patients with HER2-positive breast cancer who underwent NACT from March 2018 to March 2022. US and clinicopathological characteristics were collected from all patients in this study, and characteristics obtained using univariate analysis at p < 0.1 were subjected to multivariate analysis and then the conventional US and clinicopathological characteristics independently associated with pathologic complete response (pCR) from the analysis were used to develop US models, clinicopathological models, and their combined models by the area under the receiver operating characteristic (ROC) curve (AUC), accuracy, sensitivity, and specificity to assess their predictive efficacy. RESULTS: The combined model had an AUC of 0.808, a sensitivity of 88.72%, a specificity of 60.87%, and an accuracy of 75.81% in predicting pCR of HER2-positive breast cancer after NACT, which was significantly better than the clinicopathological model (AUC = 0.656) and the US model (AUC = 0.769). In addition, six characteristics were screened as independent predictors, namely the Clinical T stage, Clinical N stage, PR status, posterior acoustic, margin, and calcification. CONCLUSION: The conventional US combined with clinicopathological characteristics to construct a combined model has a good diagnostic effect in predicting pCR in HER2-positive breast cancer and is expected to be a useful tool to assist clinicians in effectively determining the efficacy of NACT in HER2-positive breast cancer patients.
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spelling pubmed-105041412023-09-17 Ultrasound and clinicopathological characteristics-based model for prediction of pathologic response to neoadjuvant chemotherapy in HER2-positive breast cancer: a case–control study Sui, Lin Yan, Yuqi Jiang, Tian Ou, Di Chen, Chen Lai, Min Ni, Chen Zhu, Xi Wang, Liping Yang, Chen Li, Wei Yao, Jincao Xu, Dong Breast Cancer Res Treat Preclinical Study BACKGROUND: The objective of this study was to develop a model combining ultrasound (US) and clinicopathological characteristics to predict the pathologic response to neoadjuvant chemotherapy (NACT) in human epidermal growth factor receptor 2 (HER2)-positive breast cancer. MATERIALS AND METHODS: This is a retrospective study that included 248 patients with HER2-positive breast cancer who underwent NACT from March 2018 to March 2022. US and clinicopathological characteristics were collected from all patients in this study, and characteristics obtained using univariate analysis at p < 0.1 were subjected to multivariate analysis and then the conventional US and clinicopathological characteristics independently associated with pathologic complete response (pCR) from the analysis were used to develop US models, clinicopathological models, and their combined models by the area under the receiver operating characteristic (ROC) curve (AUC), accuracy, sensitivity, and specificity to assess their predictive efficacy. RESULTS: The combined model had an AUC of 0.808, a sensitivity of 88.72%, a specificity of 60.87%, and an accuracy of 75.81% in predicting pCR of HER2-positive breast cancer after NACT, which was significantly better than the clinicopathological model (AUC = 0.656) and the US model (AUC = 0.769). In addition, six characteristics were screened as independent predictors, namely the Clinical T stage, Clinical N stage, PR status, posterior acoustic, margin, and calcification. CONCLUSION: The conventional US combined with clinicopathological characteristics to construct a combined model has a good diagnostic effect in predicting pCR in HER2-positive breast cancer and is expected to be a useful tool to assist clinicians in effectively determining the efficacy of NACT in HER2-positive breast cancer patients. Springer US 2023-08-28 2023 /pmc/articles/PMC10504141/ /pubmed/37639063 http://dx.doi.org/10.1007/s10549-023-07057-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Preclinical Study
Sui, Lin
Yan, Yuqi
Jiang, Tian
Ou, Di
Chen, Chen
Lai, Min
Ni, Chen
Zhu, Xi
Wang, Liping
Yang, Chen
Li, Wei
Yao, Jincao
Xu, Dong
Ultrasound and clinicopathological characteristics-based model for prediction of pathologic response to neoadjuvant chemotherapy in HER2-positive breast cancer: a case–control study
title Ultrasound and clinicopathological characteristics-based model for prediction of pathologic response to neoadjuvant chemotherapy in HER2-positive breast cancer: a case–control study
title_full Ultrasound and clinicopathological characteristics-based model for prediction of pathologic response to neoadjuvant chemotherapy in HER2-positive breast cancer: a case–control study
title_fullStr Ultrasound and clinicopathological characteristics-based model for prediction of pathologic response to neoadjuvant chemotherapy in HER2-positive breast cancer: a case–control study
title_full_unstemmed Ultrasound and clinicopathological characteristics-based model for prediction of pathologic response to neoadjuvant chemotherapy in HER2-positive breast cancer: a case–control study
title_short Ultrasound and clinicopathological characteristics-based model for prediction of pathologic response to neoadjuvant chemotherapy in HER2-positive breast cancer: a case–control study
title_sort ultrasound and clinicopathological characteristics-based model for prediction of pathologic response to neoadjuvant chemotherapy in her2-positive breast cancer: a case–control study
topic Preclinical Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10504141/
https://www.ncbi.nlm.nih.gov/pubmed/37639063
http://dx.doi.org/10.1007/s10549-023-07057-0
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