Prediction model of lymphovascular invasion based on clinicopathological factors in Chinese patients with invasive breast cancer

Shen, Sandi; Gui-hua, WU; Xiao, Gaofang; Du, Richang; Hu, Ningdong; Xia, Xu Gang; Zhou, Haibo

doi:10.1097/md.0000000000012973

Cited by 26 publications

(27 citation statements)

References 14 publications

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“…Additionally, calcification was also an independent predictor of LVI, which was similar to the result obtained in the work of Gajdos et al In addition, patients younger than 45 years and suspicious AUS findings had independent value for predicting ALNM and LVI. Similar results have indicated that the positivity of LVI and ALNM drops in younger (<50 years) patients . Since the menstrual status is age related, both a hormonal effect and time‐dependent exposure might be reasonable explanations .…”

Section: Discussionsupporting

confidence: 77%

The Association Between Ultrasound Features and Biological Properties of Invasive Breast Carcinoma Is Modified by Age, Tumor Size, and the Preoperative Axilla Status

Tong

Sun

Zhou

et al. 2019

J of Ultrasound Medicine

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Objectives-To investigate the value of ultrasound (US) feature-based models in predicting the proliferation and invasiveness of invasive breast cancer (IBC) and to compare the performance of models based solely on US features with models that combined US features, patient age, tumor size, and axilla status from US.Methods-With ethical approval, 746 patients with a pathologic diagnosis of IBC were reviewed for preoperative clinical, US, and postoperative pathologic data. The proliferation and invasiveness properties of the IBC included the histologic grade and Ki-67 status and lymphovascular invasion (LVI) and axillary lymph node metastasis (ALNM), respectively. Logistic regression analyses were used to identify independent risk factors for tumor proliferation and invasiveness.Results-Posterior echo enhancement, calcification, a tumor size larger than 2 cm, and suspicion of ALNM from axillary US were independent risk factors for a high histologic grade and high Ki-67 expression of IBC (P < .05). A posterior echo shadow, patient age younger than 45 years, and suspicious findings on axillary US imaging were independent variables for predicting the presence of LVI and ALNM in IBC (P < .05). Calcification was the independent factor for predicting LVI (P = .013). The predictive performance of the combined models was improved compared with the US feature-based models, with a higher accuracy rate and negative predictive value. The area under curve of the combined models was also significantly higher than that of the single models (P < .05).Conclusions-Compared with the US feature-based models, the combined models yielded better predictive performance. This may provide a more robust model to predict the tumor biological properties of IBC before surgery.

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Section: Discussionsupporting

confidence: 77%

The Association Between Ultrasound Features and Biological Properties of Invasive Breast Carcinoma Is Modified by Age, Tumor Size, and the Preoperative Axilla Status

Tong

Sun

Zhou

et al. 2019

J of Ultrasound Medicine

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“…The prognosis of breast cancer is determined by certain clinicopathological factors, including the presence or absence of lymph node metastasis, tumor size, histological grade, estrogen receptor (ER) status, progesterone receptor (PR) status, human epidermal growth factor receptor-2 (HER-2) status, Ki-67 expression, and the presence or absence of lymphovascular invasion (LVI) [ 1 ]. LVI is the main route of lymph node metastasis and is a known independent predictor of lymph node metastasis, disease-free survival (DFS) and overall survival (OS) in breast cancer [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

Predictors of lymphovascular invasion identified from pathological factors in Chinese patients with breast cancer

Shen

Xiao

et al. 2017

Oncotarget

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This study aimed to evaluate correlations between lymphovascular invasion (LVI) and the expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER-2), Ki-67, CK5/6, epidermal growth factor receptor (EGFR), vascular endothelial growth factor (VEGF), E-cadherin, BCL11A and P53 in invasive breast cancer and to identify predictors of LVI based on these pathological factors. In all, 392 paraffin-embedded tissues from consecutive patients with primary operable invasive breast cancer were included. Immunohistochemistry (IHC) was retrospectively performed using a tissue microarray (TMA) of the paraffin-embedded tissues. LVI-positive rates were compared using the χ2 test. Correlations between pathological factors were assessed using Spearman's test. Binary logistic regression was employed in multivariate analyses of statistically significant factors. The results showed that LVI positivity was significantly higher in patients with HER-2-positive expression or high Ki-67 expression. HER-2 expression was weakly positively correlated with Ki-67 expression. HER-2-positive expression and high Ki-67 expression were found to be risk factors for LVI, and associations between LVI and other pathological factors were not significant. Therefore, HER-2-positive expression and high Ki-67 expression are predictors of LVI, whereas the expression of ER, PR, CK5/6, EGFR, VEGF, E-cadherin, BCL11A and P53 is not associated with LVI in invasive breast cancer.

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“…Previous studies have shown that LVI is a feature related to poor prognosis and that it promotes local recurrence and distant metastasis of tumours [20]. Several recent studies have recognized LVI as an independent predictor of NSLN metastasis in patients with 1-2 positive SLNs [21,22].…”

Section: Discussionmentioning

confidence: 99%

Development of a prediction model based on LASSO regression to evaluate the risk of non-sentinel lymph node metastasis in Chinese breast cancer patients with 1-2 positive sentinel lymph nodes

Meng

Tian

Wang

et al. 2020

Preprint

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Background: Our study aimed to investigate the correlative factors influencing non-sentinel lymph node (NSLN) metastasis in Chinese breast cancer patients with 1-2 positive sentinel lymph nodes (SLNs) and to develop an intraoperative prediction model based on the least absolute shrinkage and selection operator (LASSO) algorithm to evaluate the risk of NSLN metastasis.Methods: The factors affecting NSLN status were investigated in a cohort of 714 patients with 1-2 positive SLNs treated at The First Affiliated Hospital of Chongqing Medical University between January 2013 and December 2018. A new mathematical prediction model based on the LASSO algorithm was developed and was validated in a cohort of 131 patients treated between January 2019 and December 2019.Results: In the training cohort, 266/714 (37.3%) patients had NSLN metastasis. In univariate analysis, the histologic grade (P =0.010), number of positive SLNs (P<0.001), number of negative SLNs (P<0.001), number of SLNs dissected (P<0.001), SLN metastasis ratio (P <0.001), lymphovascular invasion (LVI) status (P <0.001), estrogen receptor (ER) status (P =0.011), human epidermal growth factor receptor 2 (HER2) status (P =0.005), molecular subtype (P =0.001), and risk score (P <0.001) were related with NSLN involvement. In multivariate analysis, the histologic grade (P =0.026), LVI status (P =0.005), number of positive SLNs (P=0.001), number of negative SLNs (P=0.005), SLN metastasis ratio (P =0.005), and molecular subtype (P=0.007) were identified as the independent predictors of NSLN metastasis. A LASSO regression-based mathematical prediction model was developed and had an area under the curve (AUC) of 0.764 (95% CI: 0.729-0.798). In the 131-patient validation cohort, the AUC was 0.777 (95% CI: 0.692-0.862).Conclusions: We present a new prediction model to assess the risk of NSLN metastasis in Chinese breast cancer patients with 1-2 positive SLNs. The model was further validated in the validation cohort and showed excellent clinical applicability and diagnostic performance. It can be used as an intraoperative clinical tool for clinicians to predict the risk of NSLN metastasis and make the final decision regarding axillary lymph node dissection (ALND).

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Prediction model of lymphovascular invasion based on clinicopathological factors in Chinese patients with invasive breast cancer

Cited by 26 publications

References 14 publications

The Association Between Ultrasound Features and Biological Properties of Invasive Breast Carcinoma Is Modified by Age, Tumor Size, and the Preoperative Axilla Status

The Association Between Ultrasound Features and Biological Properties of Invasive Breast Carcinoma Is Modified by Age, Tumor Size, and the Preoperative Axilla Status

Predictors of lymphovascular invasion identified from pathological factors in Chinese patients with breast cancer

Development of a prediction model based on LASSO regression to evaluate the risk of non-sentinel lymph node metastasis in Chinese breast cancer patients with 1-2 positive sentinel lymph nodes

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