Application of preoperative ultrasound features combined with clinical factors in predicting HER2-positive subtype (non-luminal) breast cancer

Abstract Background Human epidermal growth factor receptor2+ subtype breast cancer has a high degree of malignancy and a poor prognosis. The aim of this study is to develop a prediction model for the human epidermal growth factor receptor2+ subtype (non-luminal) of breast cancer based on the clinica...

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Autores principales:	Jin Zhou, An-qi Jin, Shi-chong Zhou, Jia-wei Li, Wen-xiang Zhi, Yun-xia Huang, Qian Zhu, Lang Qian, Jiong Wu, Cai Chang
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Breast cancer Estrogen receptor Progesterone receptor Human epidermal growth factor receptor-2 Ultrasound Medical technology R855-855.5
Acceso en línea:	https://doaj.org/article/2746eeb5d92b4c16be817ad27acfb313
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spelling	oai:doaj.org-article:2746eeb5d92b4c16be817ad27acfb3132021-12-05T12:21:26ZApplication of preoperative ultrasound features combined with clinical factors in predicting HER2-positive subtype (non-luminal) breast cancer10.1186/s12880-021-00714-01471-2342https://doaj.org/article/2746eeb5d92b4c16be817ad27acfb3132021-12-01T00:00:00Zhttps://doi.org/10.1186/s12880-021-00714-0https://doaj.org/toc/1471-2342Abstract Background Human epidermal growth factor receptor2+ subtype breast cancer has a high degree of malignancy and a poor prognosis. The aim of this study is to develop a prediction model for the human epidermal growth factor receptor2+ subtype (non-luminal) of breast cancer based on the clinical and ultrasound features related with estrogen receptor, progesterone receptor, and human epidermal growth factor receptor2. Methods We collected clinical data and reviewed preoperative ultrasound images of enrolled breast cancers from September 2017 to August 2020. We divided the data into in three groups as follows. Group I: estrogen receptor ± , Group II: progesterone receptor ± and Group III: human epidermal growth factor receptor2 ± . Univariate and multivariate logistic regression analyses were used to analyze the clinical and ultrasound features related with biomarkers among these groups. A model to predict human epidermal growth factor receptor2+ subtype was then developed based on the results of multivariate regression analyses, and the efficacy was evaluated using the area under receiver operating characteristic curve, accuracy, sensitivity, specificity. Results The human epidermal growth factor receptor2+ subtype accounted for 138 cases (11.8%) in the training set and 51 cases (10.1%) in the test set. In the multivariate regression analysis, age ≤ 50 years was an independent predictor of progesterone receptor + (p = 0.007), and posterior enhancement was a negative predictor of progesterone receptor + (p = 0.013) in Group II; palpable axillary lymph node, round, irregular shape and calcifications were independent predictors of the positivity for human epidermal growth factor receptor-2 in Group III (p = 0.001, p = 0.007, p = 0.010, p < 0.001, respectively). In Group I, shape was the only factor related to estrogen receptor status in the univariate analysis (p < 0.05). The area under receiver operating characteristic curve, accuracy, sensitivity, specificity of the model to predict human epidermal growth factor receptor2+ subtype breast cancer was 0.697, 60.14%, 72.46%, 58.49% and 0.725, 72.06%, 64.71%, 72.89% in the training and test sets, respectively. Conclusions Our study established a model to predict the human epidermal growth factor receptor2-positive subtype with moderate performance. And the results demonstrated that clinical and ultrasound features were significantly associated with biomarkers.Jin ZhouAn-qi JinShi-chong ZhouJia-wei LiWen-xiang ZhiYun-xia HuangQian ZhuLang QianJiong WuCai ChangBMCarticleBreast cancerEstrogen receptorProgesterone receptorHuman epidermal growth factor receptor-2UltrasoundMedical technologyR855-855.5ENBMC Medical Imaging, Vol 21, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Breast cancer Estrogen receptor Progesterone receptor Human epidermal growth factor receptor-2 Ultrasound Medical technology R855-855.5
spellingShingle	Breast cancer Estrogen receptor Progesterone receptor Human epidermal growth factor receptor-2 Ultrasound Medical technology R855-855.5 Jin Zhou An-qi Jin Shi-chong Zhou Jia-wei Li Wen-xiang Zhi Yun-xia Huang Qian Zhu Lang Qian Jiong Wu Cai Chang Application of preoperative ultrasound features combined with clinical factors in predicting HER2-positive subtype (non-luminal) breast cancer
description	Abstract Background Human epidermal growth factor receptor2+ subtype breast cancer has a high degree of malignancy and a poor prognosis. The aim of this study is to develop a prediction model for the human epidermal growth factor receptor2+ subtype (non-luminal) of breast cancer based on the clinical and ultrasound features related with estrogen receptor, progesterone receptor, and human epidermal growth factor receptor2. Methods We collected clinical data and reviewed preoperative ultrasound images of enrolled breast cancers from September 2017 to August 2020. We divided the data into in three groups as follows. Group I: estrogen receptor ± , Group II: progesterone receptor ± and Group III: human epidermal growth factor receptor2 ± . Univariate and multivariate logistic regression analyses were used to analyze the clinical and ultrasound features related with biomarkers among these groups. A model to predict human epidermal growth factor receptor2+ subtype was then developed based on the results of multivariate regression analyses, and the efficacy was evaluated using the area under receiver operating characteristic curve, accuracy, sensitivity, specificity. Results The human epidermal growth factor receptor2+ subtype accounted for 138 cases (11.8%) in the training set and 51 cases (10.1%) in the test set. In the multivariate regression analysis, age ≤ 50 years was an independent predictor of progesterone receptor + (p = 0.007), and posterior enhancement was a negative predictor of progesterone receptor + (p = 0.013) in Group II; palpable axillary lymph node, round, irregular shape and calcifications were independent predictors of the positivity for human epidermal growth factor receptor-2 in Group III (p = 0.001, p = 0.007, p = 0.010, p < 0.001, respectively). In Group I, shape was the only factor related to estrogen receptor status in the univariate analysis (p < 0.05). The area under receiver operating characteristic curve, accuracy, sensitivity, specificity of the model to predict human epidermal growth factor receptor2+ subtype breast cancer was 0.697, 60.14%, 72.46%, 58.49% and 0.725, 72.06%, 64.71%, 72.89% in the training and test sets, respectively. Conclusions Our study established a model to predict the human epidermal growth factor receptor2-positive subtype with moderate performance. And the results demonstrated that clinical and ultrasound features were significantly associated with biomarkers.
format	article
author	Jin Zhou An-qi Jin Shi-chong Zhou Jia-wei Li Wen-xiang Zhi Yun-xia Huang Qian Zhu Lang Qian Jiong Wu Cai Chang
author_facet	Jin Zhou An-qi Jin Shi-chong Zhou Jia-wei Li Wen-xiang Zhi Yun-xia Huang Qian Zhu Lang Qian Jiong Wu Cai Chang
author_sort	Jin Zhou
title	Application of preoperative ultrasound features combined with clinical factors in predicting HER2-positive subtype (non-luminal) breast cancer
title_short	Application of preoperative ultrasound features combined with clinical factors in predicting HER2-positive subtype (non-luminal) breast cancer
title_full	Application of preoperative ultrasound features combined with clinical factors in predicting HER2-positive subtype (non-luminal) breast cancer
title_fullStr	Application of preoperative ultrasound features combined with clinical factors in predicting HER2-positive subtype (non-luminal) breast cancer
title_full_unstemmed	Application of preoperative ultrasound features combined with clinical factors in predicting HER2-positive subtype (non-luminal) breast cancer
title_sort	application of preoperative ultrasound features combined with clinical factors in predicting her2-positive subtype (non-luminal) breast cancer
publisher	BMC
publishDate	2021
url	https://doaj.org/article/2746eeb5d92b4c16be817ad27acfb313
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Application of preoperative ultrasound features combined with clinical factors in predicting HER2-positive subtype (non-luminal) breast cancer

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