Predictors Of Axillary Lymph Node Metastasis Research Articles

Breast Cancer in Elderly Women: Role of Tumor Characteristics in Predicting Axillary Lymph Node Metastasis

Background: The number of elderly women with breast cancer is increasing and becoming a major health concern. Worldwide. Nearly a third of breast cancer cases occurs in eldery women. Differences in the pathologic features of breast tumors in aging women have been described. Axillary lymph node metastasis (ALNM) is one of the most important prognostic factors in breast cancer patients. Some studies reported that tumor characteristics were related to an increased axillary lymph node metastasis. The aim of this study was to identify tumor characteristics associated with axillary lymph node metastasis.

Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Carcinoma Using Radiomics Features Based on the Fat-Suppressed T2 Sequence

To investigate the value of radiomics method based on the fat-suppressed T2 sequence for preoperative predicting axillary lymph node (ALN) metastasis in breast carcinoma. The data of 329 invasive breast cancer patients were divided into the primary cohort (n = 269) and validation cohort (n = 60). Radiomics features were extracted from the fat-suppressed T2-weighted images on breast MRI, and ALN metastasis-related radiomics feature selection was performed using Mann-Whitney U-test and support vector machines with recursive feature elimination; then a radiomics signature was constructed by linear support vector machine. The predictive models were constructed using a linear regression model based on the clinicopathologic factors and radiomics signature, and nomogram was used for a visual prediction of the combined model. The predictive performances are evaluated with the sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve. A total of 647 radiomics features were extracted from each patient. About 23 ALN metastasis-related radiomics features were selected to construct the radiomics signature, including 17 texture features, 5 first-order statistical features, and one shape feature; patient age, tumor size, HER2 status, and vascular cancer thrombus accompanied or not were selected to construct the cilinicopathologic feature model. The sensitivity, specificity, accuracy, and are under the curve value of radiomics signature, clinicopathologic feature model, and the nomogram were 65.22%, 81.08%, 75.00%, and 0.819 (95% confidence interval [CI]: 0.776-0.861), 30.44%, 81.08%, 61.67%, and 0.605 (95% CI: 0.571-0.624) and 60.87%, 89.19%, 78.33%, and 0.810 (95% CI: 0.761-0.855), respectively. Radiomics methods based on the fat-suppressed T2 sequence and the nomogram are helpful for preoperative accurate predicting ALN metastasis.

Construction of an immune-related genes nomogram for the preoperative prediction of axillary lymph node metastasis in triple-negative breast cancer

Immune system disorder is associated with metastasis of triple-negative breast cancers (TNBCs). A robust, individualized immune-related genes (IRGs)-based classifier was aimed to develop and validate in our study to precisely estimate the axillary lymph node (ALN) status preoperatively in patients with early-stage TNBC. We first analyzed RNA sequencing profiles in TNBC patients from The Cancer Genome Atlas database by using bioinformatics approaches, and screened 23 differentially expressed IRGs. A 9-gene panel was generated with an area under the curve (AUC) of 0.77 [95% confidence interval (95% CI), 0.68–0.87]. We detected the 9 ALN-status-related IRGs in the training set (n = 133) and developed a reduced and optimized five-IRGs signature, which effectively distinguished TNBC patients with ALN metastasis (AUC, 0.80; 95% CI, 0.65–0.86), and was superior to preoperative ultrasound-based ALN status (AUC, 0.73; 95% CI, 0.53–0.93). Predictive efficiency (AUC, 0.77; 95% CI 0.61–0.93) of this five-IRGs signature was validated in the validation set (n = 81). Furthermore, IRGs nomogram incorporated IRGs signature with US-based ALN status showed higher ALN status prediction efficacy than US-based ALN status and five-IRGs signature alone in both training and validation sets. IRGs nomogram may aid in identifying patients who can be exempted from axillary surgery. Novelty and impact: An immune-related genes (IRGs) nomogram was first developed and externally validated in our study, which incorporated the IRGs signature with ultrasound (US)-based axillary lymph nodes (ALN) status. IRGs nomogram is superior to IRGs signature alone for preoperative estimation of ALN metastasis in patients with triple-negative breast cancer (TNBC). It is a favourable biomarker for preoperatively predicting ALN metastasis risk and may aid in clinical decision-making in early-stage TNBCs.

Ultrasound-based radiomics nomogram: A potential biomarker to predict axillary lymph node metastasis in early-stage invasive breast cancer

PurposeTo establish a radiomics nomogram integrating clinical factors and radiomics features from ultrasound for the preoperative diagnosis axillary lymph node (ALN) status in patients with early-stage invasive breast cancer (EIBC). Materials and methodsBetween September 2016 and December 2018, four hundred twenty-six ultrasound manually segmented images of patients with EIBC were enrolled in our retrospective study, which were divided into a primary cohort (n = 300) and a validation cohort (n = 126). A radiomics signature was built with the least absolute shrinkage and selection operator (LASSO) algorithm in the primary cohort. Multivariable logistic regression analysis was used to establish a radiomics nomogram model based on radiomics signature and clinical variables. The performance of nomogram was quantified with respect to discrimination and calibration. The radiomics model was further evaluated in the internal validation cohort. ResultsThe radiomics signature, consisted of fourteen selected ALN-status-related features, achieved moderate prediction efficacy with an area under the curve (AUC) of 0.78 and 0.71 in the primary and validation cohorts respectively. The radiomics nomogram, comprising tumor size, US-reported LN status and radiomics signature, showed good calibration and favorite performance for ALN detection (AUC 0.84 and 0.81 in the primary and validation cohort). The decision curve which was demonstrated the radiomics nomogram displayed good clinical utility. ConclusionThe radiomics nomogram could hold promise as a non-invasive and reliable tool in predicting ALN metastasis and may facilitate to develop more effective preoperative decision-making.

Usefulness of preoperative breast magnetic resonance imaging with a dedicated axillary sequence for the detection of axillary lymph node metastasis in patients with early ductal breast cancer.

Axillary staging of primary breast cancer is important; however, axillary staging using advanced magnetic resonance imaging (MRI) techniques is very difficult to use. Therefore, we want to evaluate the diagnostic performance of preoperative MRI with a dedicated axillary sequence for axillary lymph node (ALN) metastasis in patients with early ductal breast cancer and determine potential predictors of axillary nodal positivity. We retrospectively reviewed the MRI findings for 74 consecutive patients diagnosed with invasive breast cancer. The diagnostic performances of axial images alone and axial + reconstructed coronal images for the detection of ALN metastasis were evaluated. The clinicopathological and MRI features of the primary breast cancer lesions were determined. The sensitivity (52.9% vs. 47.1%), specificity (89.5% vs. 71.9%), positive predictive value (60% vs. 33.3%), and negative predictive value (86.4% vs. 82%) for the preoperative detection of ALN metastasis were higher for axial + coronal images than for axial images. In addition, the area under the receiver operating characteristic curve value was higher for axial + coronal images than for axial images (0.595 vs. 0.712, p = 0.043). Peritumoral high signal intensity on T2-weighted images (p = 0.015) of the primary tumor was significantly associated with ALN metastasis. Our findings suggest that preoperative axial + reconstructed coronal MR images exhibit good diagnostic performance for ALN metastasis in patients with early ductal breast cancer. In addition, peritumoral high signal intensity on T2-weighted images of the primary tumor can be used as a predictor of ALN metastasis in these patients.

Clinical and pathological factors predicting axillary nodal metastasis in breast cancer patients of central Sudan: A single institution experience

Background: Data on factors predicting axillary lymph node (ALN) metastasis among Sudanese patients with breast cancer are rare. Aim: The aim of this study is to provide baseline information of the clinical and pathological factors predicting ALN metastasis in patients who underwent modified radical mastectomy or breast conserving surgery at Wad-Madani Teaching Hospital, Sudan. Materials and Methods: We performed a prospective study to examine the correlation between ALN status and clinicopathological characteristics of 81 patients with breast cancer. Results: The median age at diagnosis was 47 years (range, 25–85 years). The median number of lymph nodes (LNs) retrieved was 14 (range 2–31). ALNs containing metastases were found in 52 patients (64.2%); more than half of them (n = 30) had three or more positive LNs. Factors associated with lower chance of developing LN metastasis were age more than 60 years, postmenopausal status, smaller tumor size, and tumor that were positive for estrogen receptor and/or progesterone receptor. The number of ALNs retrieved was the only factor which showed statistically significant association with ALNs metastases. Conclusions: Our finding reveals a high incidence of ALN metastasis among patients with breast cancer in Sudan, which is likely due to various factors such as young age at diagnosis and large tumor size as a result of late diagnosis.

Pre-operative Conventional Ultrasound and Sonoelastography Evaluation for Predicting Axillary Lymph Node Metastasis in Patients with Malignant Breast Lesions

The objective of our study was to evaluate the association between the sonoelastography features of breast tumor and axillary lymph node metastasis (ALNM) in patients with breast cancer. In a cohort of 106 women with breast cancer, the conventional ultrasound features and elasticity parameters by elasticity imaging and Virtual Touch Tissue Imaging & Quantification (VTIQ) were retrospectively analyzed. Ultrasound and elastography findings were compared with pathologic axillary lymph node status. Receiver operating characteristic curve analysis was used to evaluate diagnostic performance. Pathologically, the overall incidence of ALNM was 39.6% (42/106) in the final analysis. ALNM was significantly more frequent in tumors with elasticity imaging scores >4.5, maximal shear wave velocity values (Smax) >6.42 m/s and mean shear wave velocity values (Smean) >5.66 m/s, respectively. The sensitivity, specificity and accuracy were 78.6%, 54.7% and 64.2% for elasticity imaging score; 85.7%, 54.7% and 67.0% for Smax; and 59.5%, 79.7% and 71.7% for Smean, respectively Elastography features, including elasticity imaging score and VTIQ, can be used to supplement conventional ultrasound to predict ALNM in patients with breast cancers.

Predictive value of primary tumor parameters using 18F-FDG PET/CT for occult lymph node metastasis in breast cancer with clinically negative axillary lymph node.

This study aimed to demonstrate the clinical significance of total lesion glycolysis (TLG) of primary breast cancer using 18F-FDG PET/CT to predict axillary lymph node (ALN) metastasis in invasive ductal breast cancer (IDC) with a clinically negative axillary lymph node (cN-ALN). 135 patients, newly diagnosed with IDC with CN-ALN between July 2016 and October 2017, were retrospectively enrolled. We estimated primary tumor PET/CT parameters including the maximum standard uptake value (SUVmax), metabolic tumor volume (MTV), and TLG, as well as clinicopathologic findings. All patients received breast surgery followed by pathologic axillary lymph node examination. Of the 135 patients, 31 (23.0%) were diagnosed with pathologically proven metastatic ALN. In univariate analysis, SUVmax, MTV, and TLG of the primary breast tumor were correlated with metastatic ALN along with tumor size, lymphovascular invasion, CD34, and D2-40. On multivariate analysis, TLG (> 5.74, p = 0.009) had independent significance for predicting ALN metastasis in IDC with cN-ALN. We demonstrated that TLG of primary tumors can be useful in predicting pathologic ALN metastasis in IDC patients with cN-ALN.

Ultrasound Features of Breast Cancer for Predicting Axillary Lymph Node Metastasis.

The purpose of this study was to assess the clinical value of ultrasound (US) features of breast lesions for predicting the risk of axillary lymph node metastasis in patients with breast cancer. In this retrospective study, 425 patients with breast cancer were recruited, and their preoperative US features and postoperative pathologic results were collected. The association of these US features of breast cancer with axillary lymph node metastasis was determined by univariate and multivariate analyses. Among the 425 patients, 200 (47.1%) had axillary lymph node metastasis, and 225 (52.9%) did not. The parameters of tumor shape, color Doppler flow imaging grades, histologic grade, and E-cadherin level were significantly and independently associated with axillary lymph node metastasis (P < .05 for all). Axillary lymph node metastasis was prone to happen in patients with US features of an irregular tumor shape and higher color Doppler flow imaging grades. Ultrasound imaging provides a promising tool for predicting axillary lymph node metastasis in patients with breast cancer.

A Risk Model based on Ultrasound, Ultrasound Elastography, and Histologic Parameters for Predicting Axillary Lymph Node Metastasis in Breast Invasive Ductal Carcinoma

To develop a risk model for predicting axillary lymph node metastasis (LNM) in patients with breast invasive ductal carcinoma (IDCs) using ultrasound (US), US elastography of virtual touch tissue imaging (VTI) and virtual touch tissue imaging & quantification (VTIQ), and histologic parameters. This study included 162 breast IDCs in 162 patients. Univariate and multivariate analyses were used to identify the risk factors and a risk model was created. The results found that 64 (39.5%) of 162 patients had axillary LNMs. The risk score (RS) for axillary LNM was defined as following: RS = 1.3 × (if lesion size ≥20 mm) + 2.6 × (if taller than wide shape) + 2.2 × (if VTI score ≥5) + 3.9 × (if histological grade III) + 1.9 × (if positive C-erbB-2). The rating system was divided into 6 stages (i.e. Stage I, Stage II, Stage III, Stage IV, Stage V, and Stage VI) and the associated risk rates in terms of axillary LNM were 0% (0/19), 6.1% (2/33), 7.7% (3/39), 65.5% (19/29), 92.3% (24/26), and 100% (16/16), respectively. The risk model for axillary LNM established in the study may facilitate subsequent treatment planning and management in patients with breast IDCs.

HER2 expression is a strong independent predictor of nodal metastasis in breast cancer

Identification of metastatic potential of breast cancer cells is necessary for proper management of this disease. This work aimed to estimate likelihood of axillary lymph node (ALN) involvement in breast cancer patients based on human epidermal growth factor receptor 2 (HER2) expression. Primary tumors of 317 breast cancer patients were evaluated for estrogen receptor (ER), progesterone receptor (PR) and HER2 expression by immunohistochemistry. The validity of these molecules to predict ALN metastasis was measured statistically and compared to predictive effect of other clinicopathological parameters. ER, PR and HER2 expression was detected in 75.7%, 73.2% and 19.9% of tumors, respectively. Although increased tumor size and grade, ER and PR negativity and HER2 positivity were strong indicators of ALN metastasis on univariate analyses, only tumor size and HER2 expression were independent predictors of ALN involvement on multivariate analysis. ROC curve showed a strong validity of the model using these two parameters to predict ALN status (AUC 0.86; p<0001). HER2-rich, luminal B and triple negative tumors had 6.87, 6.32 and 3.58 times increased risk of metastasis compared to luminal A tumors; respectively. HER2 expression in pT1 and pT2 tumors raised the risk of ALN metastasis by 7.7 and 7.6 times, respectively and grade 1 and 2 tumors that expressed HER2 were 16.0 and 7.8 times more likely to have ALN metastasis, respectively. To conclude, HER2 expression is associated with a significant rise of metastatic potential of breast cancer cells and could be a strong indicator of regional and distant metastasis of breast cancer.

Use of CEA and CA15-3 to Predict Axillary Lymph Node Metastasis in Patients with Breast Cancer.

Purpose: The clinical significance of preoperative serum levels of carcinoembryonic antigen (CEA) and cancer antigen 15-3 (CA15-3) in breast cancer is controversial. The purpose of this study was to assess the clinical value of preoperative serum levels of CEA and CA 15-3 on the risk of axillary lymph node metastasis (ALNM) in patients with breast cancer.Methods: This retrospective study analyzed 1148 breast cancer patients whose preoperative CEA and CA 15-3 levels were measured. The association of these tumor markers and clinicopathologic parameters with ALNM was determined by univariate and multivariate analysis.Results: A median of 15 lymph nodes were removed. Seven hundred seventy-eight (67.8%) patients had node-negative disease and 370 (32.2%) had ALNM. Univariate analysis showed that tumor location (P = 0.024), stage (P = 0.001), grade (P < 0.001), lymphovascular invasion (LVI) (P < 0.001), CEA level (P < 0.001), CA15-3 level (P < 0.001), and breast cancer subtype (BCS) (P < 0.001) were significantly associated with ALNM. ALNM was present in 4.5% of patients with normal CEA and 11.6% of patients with elevated CEA. ALNM was present in 8.0% of patients with normal CA15-3 and 17.0% of patients with high CA15-3. Multivariate logistic regression analysis showed that tumor location, stage, grade, LVI, CEA, CA15-3, and BCS were significantly and independently associated with ALNM (P < 0.05 for all).Conclusion: The probability of ALNM was greater in patients with elevated preoperative serum levels of CEA and CA15-3. CEA and CA15-3 appear to be independent predictors of ALNM in breast cancer.

Significance of Loss of Heterozygosity in Predicting Axillary Lymph Node Metastasis of Invasive Ductal Carcinoma of the Breast

Invasive ductal carcinoma (IDC) of breast metastatic to axillary lymph node (ALN) is a critical factor in determining stage and is a strong predictor of disease prognosis and survival. We studied ALN metastasis using a combined histopathologic/molecular approach to gain insights into the pathobiology implications. Fourteen patients with IDC with positive ALN and 19 with negative ALN were retrieved. Analysis of 17 polymorphic microsatellite repeat markers targeting 1p34-36, 3p24-26, 5q23, 9p21, 10q23, 17p13, 17q12, 17q21, 21q22, and 22q13 was carried out in DNA isolated from primary tumors and metastatic tumors. ALN metastasis correlated with fractional mutation rate of primary and ALN metastatic tumors, primary tumor size, and nuclear grade, and did not correlate with expression of estrogen receptor, progesterone receptor, and Her2/neu. Loss of heterozygosity (LOH) detected at 1p34-36, 3p24-26, 9p21, 10q23, 17p13, 17q12, 21q22, and 22q13 may play an important role in the development and aggressiveness of IDC, and LOHs at 1p34-36, 17p13, and 22q13 may play an important role in metastasis. None of the LOHs were shared by all the tumors, suggesting that IDC develops through various pathways that have unique and personalized patterns of mutational changes, although they share similar morphology. Detection of LOH in IDC is not only useful in studying oncogenesis, but also predicting aggressiveness and ALN metastasis.

P5-14-21: Predicting the Status of the Axillary Lymph Nodes in 1300 Consecutive Patients with Early Breast Cancer Treated in a Single Institution.

Abstract Purpose. Lymph node involvement is the most important prognostic factor in breast cancer. It is a multifactorial event determined by tumour and patient characteristics. Several predictors of axillary lymph node metastasis (ALNM) in breast cancer have been described. The purpose of this study was to determine clinical and pathological factors predictive for ALNM in patients with early breast cancer and to build a model to portend lymph node involvement. Methods. We evaluated 1300 consecutive patients surgically treated in our institution (2007-2009) for cT1-T2 invasive breast cancer. The patient and tumour characteristics evaluated included: age at diagnosis, number of foci, histologic grade, location, tumour size, histologic subtype, lymphovascular invasion (LVI), estrogen-receptor (ER), progesterone-receptor (PR) and Her2 status. Univariate and multivariate analyses were performed. Factors significantly associated with lymph node metastasis by univariate analysis and histologic subtype were included in the multivariate model. We validated our model with the same 1300 patients on the basis of a multivariable logistic regression model containing the variables, using a correction factor. Results. By univariate analysis, the incidence of ALNM was significantly higher in patients with a tumour with LVI (P &amp;lt; 0.0001), larger tumours (P &amp;lt; 0.0001), tumours with a higher histologic grade (P &amp;lt; 0.0001), tumours located retroareolar or lateral in the breast (P &amp;lt; 0.0001), tumours with multiple foci (P = 0.0002) and in patients who underwent an axillary lymph node dissection. We found no effect of ER/PR nor HER-2 status. By multivariate analysis, lymph node involvement was significantly associated with the presence of lymphovascular invasion (P &amp;lt; 0.0001), larger tumour size (P &amp;lt; 0.0001), axillary lymph node dissection (P = 0.0003), retroareolar and lateral tumour location in the breast (P = 0.0019) and the presence of multiple foci (P = 0.0155). The discrimination of the model, calculated by the area under the curve (AUC), was 0.778. Conclusions. LVI and tumour size emerged as most powerful independent predictors of ALNM. A model with an AUC of 0.50 is equivalent to the toss of a coin, a model with an AUC &amp;gt; 0.70 is considered as good. In conclusion, our result is not perfect in discrimination which raises further questions. It is clear that underlying mechanisms of ALNM remain to be elucidated. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P5-14-21.

Diagnostic Accuracy of Preoperative MG, US, MRI, and Physical Examination for Predicting Axillary Lymph Node Metastasis

Diagnostic Accuracy of Preoperative MG, US, MRI, and Physical Examination for Predicting Axillary Lymph Node Metastasis

CCR7 and CXCR4 as Novel Biomarkers Predicting Axillary Lymph Node Metastasis in T1 Breast Cancer

The chemokine receptors CCR7 and CXCR4 have been shown to play an important role in cancer metastasis. We therefore studied the differential expression of CCR7 and CXCR4, along with that of the biomarker HER2-neu, to evaluate whether these biomarkers could predict axillary lymph node metastasis in breast cancer. Biomarker expression levels were evaluated using paraffin-embedded tissue sections of lymph node-negative (n = 99) and lymph node-positive (n = 98) T1 breast cancer by immunohistochemical staining. Lymph node-positive tumors showed higher rates of high cytoplasmic CCR7 staining (21.5% versus 8.5%, P = 0.013) and HER2-neu overexpression (21.5% versus 9.3%, P = 0.019) than did lymph node-negative tumors. Similarly, high cytoplasmic CXCR4 expression occurred more commonly in lymph node-positive tumors (11.2% versus 5.1%, P = 0.113). In contrast, predominantly nuclear CXCR4 staining was more likely to be found in lymph node-negative tumors (54.5% versus 37.8%, P = 0.018). Furthermore, cytoplasmic CXCR4 coexpressed with HER2-neu was the only factor associated with involvement of four or more lymph nodes (16.7% versus 1.2%, P = 0.04) among lymph node-positive tumors. When all three biomarkers (CCR7, CXCR4, HER2-neu) were utilized together, 50.0% of lymph node-positive tumors highly expressed one of these biomarkers compared with 18.8% of the lymph node-negative tumors (P < 0.0001). Our results suggest that the chemokine receptor CCR7 is a novel biomarker that can predict lymph node metastases in breast cancer. Utilization of additional markers, such as CXCR4 and HER2-neu, further improves the prediction of the presence and extent of lymph node involvement.

Factors related to axillary lymph node metastasis in T1 breast carcinoma.

The current study was performed on 38 cases of T1 breast cancers ( 2 cm in greatest diameter) to identify the factors related to recognition of axillary lymph node (AxLN) metastasis. Ten patients (26.3%) had lymph node metastases. Comparing the AxLN positive (+) group with the AxLN negative (-) group revealed that tumor size and hormone receptor status as well as age of the patients were not significantly different. However, the Ki-67 labeling index (22.2 +/- 5. 9% vs. 12.5 +/- 2.8%), the microvessel count (43.8 +/- 12.4/0.785 mm2 vs. 27.0 +/- 8.4/0.785 mm2) and bcl-2+ cases (70% vs. 29%) were significantly higher in the AxLN+ cases. These results suggest that the Ki-67 labeling index, microvessel count and Bcl-2 expression, especially when combined, are useful predictors of AxLN metastases in T1 breast cancers.