Comparison of five different popular scoring systems to predict nonsentinel lymph node status in patients with metastatic sentinel lymph nodes: a tertiary care center experience

Association between postoperative pathological results and non-sentinel nodal metastasis in breast cancer patients with sentinel lymph node-positive breast cancer

OBJECTIVE

For patients with 1-2 positive sentinel lymph nodes (SLN) identified by biopsy, the necessity of axillary lymph node dissection (ALND) remains a matter of debate. The primary aim of this study was to investigate the association between postoperative pathological factors and non-sentinel lymph node (NSLN) metastases in Chinese patients diagnosed with sentinel node-positive breast cancer.

METHODS

This research involved a total of 280 individuals with SLN-positive breast cancer. The relationship between postoperative pathological variables and non-sentinel lymph node metastases was scrutinized using univariate, multivariate, and stratified analysis.

RESULTS

Among the 280 patients with a complete count of SLN positives, 126 (45.0%) exhibited NSLN metastasis. Within this group, 45 cases (35.71%) had 1 SLN positive, while 81 cases (64.29%) demonstrated more than 1 SLN positive. Multivariate logistic regression analysis revealed that HER2 expression status (OR 2.25, 95% CI 1.10-4.60, P = 0.0269), LVI (OR 6.08, 95% CI 3.31-11.14, P < 0.0001), and the number of positive SLNs (OR 4.17, 95% CI 2.35-7.42, P < 0.0001) were positively correlated with NSLNM.

CONCLUSION

In our investigation, the risk variables for NSLN metastasis included LVI, HER2 expression, and the quantity of positive sentinel lymph nodes. However, further validation is imperative, including this institution, distinct institutions, and diverse patient populations.

Development and validation of nomograms for predicting axillary non-SLN metastases in breast cancer patients with 1-2 positive sentinel lymph node macro-metastases: a retrospective analysis of two independent cohorts

BACKGROUND

It is reported that appropriately 50% of early breast cancer patients with 1-2 positive sentinel lymph node (SLN) micro-metastases could not benefit from axillary lymph node dissection (ALND) or breast-conserving surgery with whole breast irradiation. However, whether patients with 1-2 positive SLN macro-metastases could benefit from ALND remains unknown. The aim of our study was to develop and validate nomograms for assessing axillary non-SLN metastases in patients with 1-2 positive SLN macro-metastases, using their pathological features alone or in combination with STMs.

METHODS

We retrospectively reviewed pathological features and STMs of 1150 early breast cancer patients from two independent cohorts. Best subset regression was used for feature selection and signature building. The risk score of axillary non-SLN metastases was calculated for each patient as a linear combination of selected predictors that were weighted by their respective coefficients.

RESULTS

The pathology-based nomogram possessed a strong discrimination ability for axillary non-SLN metastases, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.727 (95% CI: 0.682-0.771) in the primary cohort and 0.722 (95% CI: 0.653-0.792) in the validation cohort. The addition of CA 15-3 and CEA can significantly improve the performance of pathology-based nomogram in the primary cohort (AUC: 0.773 (0.732-0.815) vs. 0.727 (0.682-0.771), P < 0.001) and validation cohort (AUC: (0.777 (0.713-0.840) vs. 0.722 (0.653-0.792), P < 0.001). Decision curve analysis demonstrated that the nomograms were clinically useful.

CONCLUSION

The nomograms based on pathological features can be used to identify axillary non-SLN metastases in breast cancer patients with 1-2 positive SLN. In addition, the combination of STMs and pathological features can identify patients with patients with axillary non-SLN metastases more accurately than pathological characteristics alone.

Mode of presentation and skin thickening on ultrasound may predict nodal burden in breast cancer patients with a positive axillary core biopsy

OBJECTIVE

A number of pre-operative factors predicting nodal burden in females with breast cancer have recently been identified. The aim of this study is to assess if these factors independently influence nodal burden in females with a positive axillary core biopsy.

METHODS

All node positive patients detected on axillary core biopsy were identified in our cancer audit database. Mode of presentation, age, core tumour grade, core tumour type, ER and HER2 status were evaluated. Tumours were assessed for ultrasound size, distance of tumour-to-skin, presence of invasion of skin and diffuse skin thickening. Axillary lymph nodes were assessed for cortical thickness and presence of ultrasound replaced nodes. Statistical significance was ascertained using univariate logistic regression. A predictive model was produced following a multiple logistic regression model incorporating cross-validation and assessed using receiving operating characteristic curve.

RESULTS

115 patients' data were analysed. Patients referred because of symptoms (70% vs 38%, p = 0.005), and those with ultrasound skin thickening (87% vs 59%, p = 0.055) have higher nodal burden than those referred from screening or without skin thickening. These factors were significant after multivariate analysis. The final predictive model included mode of presentation, ultrasound tumour size, cortical thickness and presence of ultrasound skin thickening. The area under curve is 0.77.

CONCLUSION

We have shown that mode of presentation and ultrasound skin thickening are independent predictors of high nodal burden at surgery. A model has been developed to predict nodal burden pre-operatively, which may lead to avoidance of axillary node clearance in patients with lower nodal burden.

ADVANCES IN KNOWLEDGE

Method of presentation and skin involvement/proximity to skin by the primary tumour are known to influence outcome and nodal involvement respectively but have not been studied with regard to nodal burden. We have shown that mode of presentation and skin thickening at ultrasound are independent predictors of high nodal burden at surgery.

Establishment and Verification of a Bagged-Trees-Based Model for Prediction of Sentinel Lymph Node Metastasis for Early Breast Cancer Patients

Purpose: Lymph node metastasis is a multifactorial event. Several scholars have developed nomograph models to predict the sentinel lymph nodes (SLN) metastasis before operation. According to the clinical and pathological characteristics of breast cancer patients, we use the new method to establish a more comprehensive model and add some new factors which have never been analyzed in the world and explored the prospect of its clinical application.

Materials and methods: The clinicopathological data of 633 patients with breast cancer who underwent SLN examination from January 2011 to December 2014 were retrospectively analyzed. Because of the imbalance in data, we used smote algorithm to oversample the data to increase the balanced amount of data. Our study for the first time included the shape of the tumor and breast gland content. The location of the tumor was analyzed by the vector combining quadrant method, at the same time we use the method of simply using quadrant or vector for comparing. We also compared the predictive ability of building models through logistic regression and Bagged-Tree algorithm. The Bagged-Tree algorithm was used to categorize samples. The SMOTE-Bagged Tree algorithm and 5-fold cross-validation was used to established the prediction model. The clinical application value of the model in early breast cancer patients was evaluated by confusion matrix and the area under receiver operating characteristic (ROC) curve (AUC).

Results: Our predictive model included 12 variables as follows: age, body mass index (BMI), quadrant, clock direction, the distance of tumor from the nipple, morphology of tumor molybdenum target, glandular content, tumor size, ER, PR, HER2, and Ki-67.Finally, our model obtained the AUC value of 0.801 and the accuracy of 70.3%.We used logistic regression to established the model, in the modeling and validation groups, the area under the curve (AUC) were 0.660 and 0.580.We used the vector combining quadrant method to analyze the original location of the tumor, which is more precise than simply using vector or quadrant (AUC 0.801 vs. 0.791 vs. 0.701, Accuracy 70.3 vs. 70.3 vs. 63.6%).

Conclusions: Our model is more reliable and stable to assist doctors predict the SLN metastasis in breast cancer patients before operation.

BI-RADS 3-5 microcalcifications: prediction of lymph node metastasis of breast cancer

Purpose

To determine whether the clinicopathological parameters and Breast Imaging Reporting and Data System (BI-RADS) 3–5 microcalcifications differed between lymph node positive (LN (+)) and lymph node negative (LN (−)) invasive ductal carcinoma (IDC).

Results

For microcalcification-associated breast cancers, seven selected features (age, tumor size, Ki-67 status, lymphovascular invasion, calcification range, calcification diameter and calcification density) were significantly associated with LN status (all P < 0.05). Multivariate logistic regression analysis found that three risk factors (age: older vs. younger OR: 0.973 P = 0.006, tumor size: larger vs. smaller OR: 1.671, P < 0.001 and calcification density: calcifications > 20/cm² vs. calcifications ≤ 20/cm² OR: 1.698, P < 0.001) were significant independent predictors. This model had an area under the receiver operating characteristic curve (AUC) of 0.701. The nodal staging (N0 and N1 χ² = 5.701, P = 0.017; N0 and N2 χ² = 6.614, P = 0.013) was significantly positively associated with calcification density. The luminal B subtype had the highest risk of LN metastasis. Multivariate analysis demonstrated that calcification > 2 cm in range (OR: 2.209) and larger tumor size (OR: 1.882) were independently predictive of LN metastasis in the luminal B subtype (AUC = 0.667).

Materials and Methods

Mammographic images of 419 female breast cancer patients were included. Associations between the risk factors and LN status were evaluated using a Chi-square test, ANOVA and binary logistic regression analysis.

Conclusions

This study found that age, tumor size and calcifications density can be conveniently used to facilitate the preoperative prediction of LN metastasis. The luminal B subtype has the highest risk of LN metastasis among the microcalcification-associated breast cancers.

Nomograms for preoperative prediction of axillary nodal status in breast cancer

Background

Axillary staging in patients with breast cancer and clinically node‐negative disease is performed by sentinel node biopsy (SLNB). The aim of this study was to integrate feasible preoperative variables into nomograms to guide clinicians in stratifying treatment options into no axillary staging for patients with non‐metastatic disease (N0), SLNB for those with one or two metastases, and axillary lymph node dissection (ALND) for patients with three or more metastases.

Methods

Patients presenting to Skåne University Hospital, Lund, with breast cancer were included in a prospectively maintained registry between January 2009 and December 2012. Those with a preoperative diagnosis of nodal metastases were excluded. Patients with data on hormone receptor status, human epidermal growth factor receptor 2 and Ki‐67 expression were included to allow grouping into surrogate molecular subtypes. Based on logistic regression analyses, nomograms summarizing the strength of the associations between the predictors and each nodal status endpoint were developed. Predictive performance was assessed using the area under the receiver operating characteristic (ROC) curve. Bootstrap resampling was performed for internal validation.

Results

Of the 692 patients eligible for analysis, 248 were diagnosed with node‐positive disease. Molecular subtype, age, mode of detection, tumour size, multifocality and vascular invasion were identified as predictors of any nodal disease. Nomograms that included these predictors demonstrated good predictive abilities, and comparable performances in the internal validation; the area under the ROC curve was 0·74 for N0versus any lymph node metastasis, 0·70 for one or two involved nodes versusN0, and 0·81 for at least three nodes versus two or fewer metastatic nodes.

Conclusion

The nomograms presented facilitate preoperative decision‐making regarding the extent of axillary surgery.

Defines need for staging?

Arm lymphoscintigraphy after axillary lymph node dissection or sentinel lymph node biopsy in breast cancer

PURPOSE

Compare the lymphatic flow in the arm after breast cancer surgery and axillary lymph node dissection (ALND) versus sentinel lymph node biopsy (SLNB) using lymphos-cintigraphy (LS).

PATIENTS AND METHODS

A cross-sectional study with 39 women >18 years who underwent surgical treatment for unilateral breast cancer and manipulation of the axillary lymph node chain through either ALND or SLNB, with subsequent comparison of the lymphatic flow of the arm by LS. The variables analyzed were the area reached by the lymphatic flow in the upper limb and the sites and number of lymph nodes identified in the ALND or SLNB groups visualized in the three phases of LS acquisition (immediate dynamic and static images, delayed scan images). For all analyses, the level of significance was set at 5%.

RESULTS

There was a significant difference between the ALND and SLNB groups, with predominant visualization of lymphatic flow and/or lymph nodes in the arm and axilla (P=0.01) and extra-axillary lymph nodes (P<0.01) in the ALND group. There was no significant difference in the total number of lymph nodes identified between the two groups. However, there was a significant difference in the distribution of lymph nodes in these groups. The cubital lymph node was more often visualized in the immediate dynamic images in the ALND group (P=0.004), while the axillary lymph nodes were more often identified in the delayed scan images of the SLNB group (P<0.01). The deltopectoral lymph node was only identified in the ALND group, but with no significant difference.

CONCLUSION

The lymphatic flow from the axilla was redirected to alternative extra-axillary routes in the ALND group.

Prediction of nonsentinel lymph node metastasis in breast cancer patients with one or two positive sentinel lymph nodes

OBJECTIVE

The aim of the present study was to investigate the association between non sentinel lymph node metastasis (NSLNM) and clinicopathological factors, particularly in the case of sentinel lymph node (SLN) metastasis in one or two, in clinically node negative patients with breast cancer.

METHODS

Between 10/2010 and 10/2014, 350 sentinel lymph node biopsy (SLNB) were performed in patients with histologically proven primary breast cancer in our clinic. The data collection includes the following characteristics: age, pathological tumor size, histological type, histological grade, lymphovascular invasion (LVI), number of positive SLN, size of the SLN metastasis (macrometastasis, micrometastasis, isolated tumor cells), multifocality (MF), extracapsuler invasion (ECI) of the SLN, the estrogen receptor (ER) status, the progesterone receptor (PR) status and the Her 2 receptor status, Ki 67 reseptor status. Data were collected retrospectively and then analyzed.

RESULTS

A successful SLN biopsy were performed in 345 (98.5%) cases. SLN metastases were detected in 110 (31.8%) cases. These patients then underwent axillary dissection; among these patients, 101 (91.8%) had only one to two positive SLNs. Of the 101 patients with positive SLN biopsies, 32 (31.6%) had metastases in the NSLNs. Univariate and multivariate analysis showed that lymphovascular invasion, extracapsular invasion (ECI), Her-2 receptor positive, and Ki-67 > 14% were related to NSLNM (p<.0.05).

CONCLUSION

The predicting factors of NSLNM were LVI, ECI, Ki-67 level, Her-2 reseptor positive and but should be further validated in our institutions, different institutions and different patient groups prospectively.