ArticleMedicine2018
Prediction model of lymphovascular invasion based on clinicopathological factors in Chinese patients with invasive breast cancer.
Article in Medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 16 citations in OpenAlex.
- Preoperative Prediction of Fat-Suppressed T2-Weighted Imaging-based Breast Edema Scores for Lymphovascular Invasion in Patients with Breast CancerCurrent medical imaging · 2026Article
- Prediction of lymphovascular invasion in esophageal squamous cell carcinoma by computed tomography-based radiomics analysis: 2D or 3D ?Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Noninvasive Staging of Lymph Node Status in Breast Cancer Using Machine Learning: External Validation and Further Model Development.JMIR cancer · 2023Article
- Multiparametric MRI-based radiomics nomogram for preoperative prediction of lymphovascular invasion and clinical outcomes in patients with breast invasive ductal carcinoma.European radiology · 2022Article
- Immunohistochemical Evaluation of FGD3 Expression: A New Strong Prognostic Factor in Invasive Breast Cancer.Cancers · 2021Article
- Lymphovascular invasion in breast cancer is associated with gene expression signatures of cell proliferation but not lymphangiogenesis or immune response.Breast cancer research and treatment · 2020Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this study was to evaluate the correlation between lymphovascular invasion (LVI) and tumor size, histological grade, and the expression statuses of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER-2), Ki67, epidermal growth factor receptor (EGFR), vascular endothelial growth factor (VEGF), E-cadherin, and P53 in invasive breast cancer, then establish a prediction model of LVI based on the associated clinicopathological factors.A total of 392 patients with primary invasive breast cancers were enrolled, and their paraffin-embedded tissues were manufactured into the tissue microarray. We evaluated the expression statuses of ER, PR, HER-2, Ki67, EGFR, VEGF, E-cadherin, and P53 based on immunohistochemistry, histological grade and LVI based on the hematoxylin and eosin stain, and tumor size.The positivity of LVI was significantly higher in the patients with HER-2 positive expression, Ki67 high expression, and tumor size >2 cm by Chi-square test. HER-2, Ki67, and tumor size were risk factors of LVI by multivariate analysis. The areas under the receiver operating curve of HER-2, Ki67, tumor size, and the combination of the 3 clinicopathological factors were 0.614 [P = .001, 95% confidence interval (CI): 0.544-0.683], 0.596 (P = .006, 95% CI: 0.529-0.662), 0.575 (P = .03, 95% CI: 0.510-0.641), and 0.670 (P < .001, 95% CI: 0.607-0.734), respectively.HER-2 positive expression, Ki67 high expression, and tumor size >2 cm were risk factors of LVI, whereas the power of the prediction model of LVI based on the 3 clinicopathological factors in invasive breast cancer was low.
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