Clinical significance of internal mammary lymph node metastasis for breast cancer: Analysis of 337 breast cancer patients

Outcomes and Trends in Axillary Management of Stage cN3b Breast Cancer Patients

BACKGROUND

There is limited data regarding sentinel lymph node biopsy (SLNB) after neoadjuvant chemotherapy (NAC) for cN3b patients, who present with both axillary and ipsilateral internal mammary node involvement. We examined trends in the use of SLNB in cN3b patients and survival by axillary procedure for those with nodal pathologic complete response (nPCR).

METHODS

Adult women with nonmetastatic cN3b invasive breast carcinoma between 2012 and 2021 were selected from the National Cancer Database. These patients were compared based on type of axillary surgery, specifically SLNB, SLNB with axillary lymph node dissection (ALND), and ALND alone. Kaplan-Meier analysis was used to compare overall survival.

RESULTS

A total of 4,236 patients were included. In 2012, 8.5% of these patients underwent SLNB alone and 18.3% underwent SLNB+ALND. In 2021, this increased to 35.1% for SLNB alone and 23.0% for SLNB with subsequent ALND (p < 0.0001). For patients who received NAC, the rate of nPCR was overall found to be 24.9%. Overall survival of patients receiving SLNB or SLNB+ALND with nPCR was not statistically significantly different from the ALND only group with nPCR (p = 0.22 and 0.57, respectively).

CONCLUSIONS

There has been increasing use of the SLNB procedure for patients with cN3b breast cancer over the past decade. In patients with nPCR, SLNB was not associated with reduced survival. For well-selected cN3b patients with an excellent clinical response to NAC, including nPCR, axillary de-escalation strategies, such as SLNB with omission of completion axillary dissection, may be considered.

Machine learning-based prediction of distant metastasis risk in invasive ductal carcinoma of the breast

More than 90% of deaths due to breast cancer (BC) are due to metastasis-related complications, with invasive ductal carcinoma (IDC) of the breast being the most common pathologic type of breast cancer and highly susceptible to metastasis to distant organs. BC patients who develop cancer metastases are more likely to have a poor prognosis and poor quality of life, so it is extremely important to recognize and diagnose whether distant metastases have occurred in IDC as early as possible. In this study, we develop a non-invasive breast cancer classification system for detecting cancer metastasis. We used Anaconda-Jupyter notebooks to develop various Python programming modules for text mining, data processing, and machine learning (ML) methods. A risk prediction model was constructed based on four algorithms: Random Forest, XGBoost, Logistic Regression, and SVM. Additionally, we developed a hybrid model based on a voting mechanism using these four algorithms as the base models. The models were compared and evaluated by the following metrics: accuracy, precision, recall, F1-score, and area under the ROC curve (AUC) values. The experimental results show that the hybrid model based on the voting mechanism exhibits the best prediction performance (accuracy: 0.867, precision: 0.929, recall: 0.805, F1-score: 0.856, AUC: 0.94). This stable risk prediction model provides a valuable reference support for doctors in assessing and diagnosing the risk of IDC hematogenous metastasis. It also improves the work efficiency of doctors and strives to provide patients with increased chances of survival.

A novel nomogram and survival analysis for different lymph node status in breast cancer based on the SEER database

INTRODUCTION

The axillary lymph node status (ALNS) and internal mammary lymph nodes (IMLN) expression associated with breast cancer are closely linked to prognosis. This study aimed to establish a nomogram to predict survival at 3, 5, and 10 years in patients with various lymph node statuses.

METHODS

We obtained data from patients with breast cancer between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER database). Chi-square analysis was performed to test for differences in the pathological characteristics of the groups, and Kaplan-Meier analysis and the log-rank test were used to plot and compare the correlation between overall survival (OS) and breast cancer specific survival (BCSS). The log-rank test was used for the univariate analysis, and statistically significant characteristics were included in the multivariate and Cox regression analyses. Finally, Independent factor identification was included in constructing the nomogram using R studio 4.2.0; area under curve (AUC) values were calculated, and receiver operating characteristic (ROC) curve, calibration, and decision curve analysis (DCA) curves were plotted for evaluation.

RESULTS

A total of 279,078 patients were enrolled and analysed, demonstrating that the isolated tumour cells (ITC) group had clinicopathological characteristics similar to those of micrometastases (Mic). Multivariate analysis was performed to identify each subgroup's independent risk factors and construct a nomogram. The AUC values were 74.7 (95% CI 73.6-75.8), 72.8 (95% CI 71.9-73.8), and 71.2 (95% CI 70.2-72.2) for 3-, 5-, and 10-year OS, respectively, and 82.2 (95% CI 80.9-83.6), 80.1 (95% CI 79.0-81.2), and 75.5 (95% CI 74.3-76.8) for BCSS in overall breast cancer cases, respectively. AUC values for 3-, 5-, and 10-year OS in the ITC group were 64.8 (95% CI 56.5-73.2), 67.7 (95% CI 62.0-73.4), and 65.4 (95% CI 60.0-70.7), respectively. For those in the Mic group, AUC values for 3-, 5-, and 10-year OS were 72.9 (95% CI 70.7-75.1), 72.4 (95% CI 70.6-74.1), and 71.3 (95% CI 69.6-73.1), respectively, and AUC values for BCSS were 77.8 (95% CI 74.9-80.7), 75.7 (95% CI 73.5-77.9), and 70.3 (95% CI 68.0-72.6), respectively. In the IMLN group, AUC values for 3-, 5-, and 10-year OS were 75.2 (95% CI 71.7-78.7), 73.4 (95% CI 70.0-76.8), and 74.0 (95% CI 69.6-78.5), respectively, and AUC values for BCSS were 76.6 (95% CI 73.0-80.3), 74.1 (95% CI 70.5-77.7), and 74.7 (95% CI 69.8-79.5), respectively. The ROC, calibration, and DCA curves verified that the nomogram had better predictability and benefits.

CONCLUSION

This study is the first to investigate the predictive value of different axillary lymph node statuses and internal mammary lymph node metastases in breast cancer, providing clinicians with additional aid in treatment decisions.

Internal mammary lymph node metastasis in breast cancer patients based on anatomical imaging and functional imaging

Internal mammary lymph node (IMLN) metastasis forms part of the clinical node classification for primary breast cancer, which influences the treatment strategy. However, because of the IMLNs' complicated anatomical structures and relationships with adjacent structures, IMLN biopsy or resection is associated with a limited improvement in prognosis and a high complication rate. The positivity rate also varies broadly according to imaging modality, and there is a low rate of agreement between the imaging and pathological diagnoses, which creates imprecision in the preoperative staging. The IMLN positivity rate also varies remarkably, and there are no clear, accurate, and non-invasive modalities for diagnosing the pre-mastectomy IMLN status. Nevertheless, medical imaging modalities continue to evolve, with functional imaging and image-guided thoracoscopic biopsy of sentinel IMLNs being well established. Thus, personalized decision-making and treatment selection should be based on the modality-specific differences in the diagnosis of IMLN metastasis/recurrence and the patient's specific risk factors.

Artificial Intelligence Algorithm-Based Ultrasound Image Segmentation Technology in the Diagnosis of Breast Cancer Axillary Lymph Node Metastasis

This paper aimed to investigate the application of ultrasound image segmentation technology based on the back propagation neural network (BPNN) artificial intelligence algorithm in the diagnosis of breast cancer axillary lymph node metastasis, thereby providing a theoretical basis for clinical diagnosis. In this study, 90 breast cancer patients with axillary lymph node metastasis were selected as the research objects and rolled randomly into an experimental group and a control group. Besides, all of them were examined by ultrasound. The BPNN algorithm for the ultrasound image segmentation diagnosis method was applied to the patiens from the experimental group, while the control group was given routine ultrasound diagnosis. Thus, the value of this algorithm in ultrasonic diagnosis was compared and explored. The results showed that when the number of hidden layer nodes based on the BPNN artificial intelligence algorithm was 2, 3, 4, 5, 6, 7, and 8, the corresponding segmentation accuracy was 97.3%, 96.5%, 94.8%, 94.8%, and 94.1% in turn. Among them, the segmentation accuracy was the highest when the number of hidden layer nodes was 2. The correlation of independent variable bubble plot analysis showed that the presence or absence of capsules, the presence of crab feet or burrs in breast cancer lesions was critical influencing factors for the occurrence of axillary lymph node metastasis, and the standardized importance was 99.7% and 70.8%, respectively. Besides, the area under the two-dimensional receiver operating characteristic (ROC) curve of the BPNN artificial intelligence algorithm model classification was always greater than the area under the curve of manual segmentation, and the segmentation accuracy was 90.31%, 94.88%, 95.48%, 95.44%, and 97.65% in sequence. In addition, the segmentation specificity of different running times was higher than that of manual segmentation. In conclusion, the BPNN artificial intelligence algorithm had high accuracy, sensitivity, and specificity for ultrasound image segmentation, with a better segmentation effect. Therefore, it had a better diagnostic effect for breast cancer axillary lymph node metastasis.

Staging for Breast Cancer With Internal Mammary Lymph Nodes Metastasis: Utility of Incorporating Biologic Factors

Purpose

To validate the 8th edition of the American Joint Committee on Cancer (AJCC) pathological prognostic staging system for breast cancer patients with internal mammary lymph nodes (IMN) metastasis (N3b disease, stage IIIC in 7th AJCC anatomical staging).

Methods

Breast cancer patients with IMN metastasis diagnosed between 2010 and 2014 were retrieved from the Surveillance, Epidemiology, and End Results program. Chi-squared test, Log-rank test, Kaplan-Meier method, and Cox proportional hazard analysis were applied to statistical analysis.

Results

We included 678 patients with N3b disease in this study. Overall, 68.4% of patients were downstaged to IIIA and IIIB diseases from the 7th anatomical staging to 8th pathological prognostic staging. The new pathological prognostic staging system had better discriminatory value on prognosis prediction among IMN-metastasized breast cancer patients, with a 5-year breast cancer-specific survival (BCSS) of 92.7, 77.4, and 66.0% in stage IIIA, IIIB, and IIIC diseases, respectively (P<0.0001), and the 5-year overall survival (OS) rates was 85.9, 72.1, and 58.7%, respectively (P<0.0001). The results of the multivariate prognostic analysis showed that the new pathological prognostic staging was the independent prognosis related to BCSS and OS, the 8th AJCC pathological prognostic stages showed worse BCSS and OS with gradually increased hazard ratios.

Conclusion

The 8th AJCC pathological prognostic staging system offers more refined prognostic stratification to IMN-metastasized breast cancer patients and endorses its use in routine clinical practice for this specific subgroup of breast cancer.

Case report: recurrent metastatic breast cancer in internal mammary dissection bed discovered at the time of coronary bypass

Introduction

Many patients who undergo coronary artery bypass surgery have a prior history of cancer and potentially chest radiation which is a known risk factor for coronary atherosclerosis. Prior radiation increases fibrosis and can make the dissection of the left internal mammary artery (LIMA) more challenging.

Case report

A 72-year-old woman with a history of stage IIA pT2N0M0 left breast intraductal carcinoma treated with lumpectomy, adjuvant chemotherapy and radiation therapy 11 years prior presented to the emergency room with a non-ST elevation myocardial infarction and was taken for cardiac catheterization followed by three-vessel coronary artery bypass grafting. The LIMA was found to be encased in scar tissue and was deemed unsuitable as a conduit, and a saphenous vein graft was bypassed to the left anterior descending artery in its place. Pathologic review of the LIMA showed nests of tumor cells infiltrating within dense fibrous tissue with areas of necrosis and calcifications consistent with recurrent breast cancer. Interestingly the patients original breast cancer was positive for estrogen receptors (ER) and progesterone receptors (PR) ER and PR and negative for HER2 and she had therefore been treated with 5 years of hormonal therapy. The recurrent cancer found in the LIMA dissection bed at the time of bypass surgery was ER, PR, and HER2 negative, suggesting hormonal therapy driven clonal selection of these metastatic tumor cells.

Discussion and conclusions

Scarring in the LIMA dissection bed in patients with a history of cancer and prior chest radiation should be carefully evaluated for the possibility of recurrent cancer. The gross appearance of tissue can be misleading and sending a biopsy for a formal frozen section histologic evaluation should be considered if there is any question of recurrent malignancy.

Should internal mammary lymph node sentinel biopsy be performed in breast cancer: a systematic review and meta-analysis

Purpose

Results from studies of internal mammary lymph node sentinel biopsy are inconsistent.

Methods

A comprehensive literature search was conducted in MEDLINE, EMBASE, Scopus, Cochrane database, and Clinical Trials. Studies reporting the rate of internal mammary lymph node sentinel biopsy (IMN-SLNB) positivity were identified. We performed pooled proportion meta-analysis using random-effects meta-analyses. The correlation of IMN and axillary lymph node (AXN) metastasis was also investigated.

Results

After application of inclusion and exclusion criteria, a total of 18 articles (total number of patients = 2427) were included. The pooled estimate for IMN-SLNB positivity rate was 15% (95% confidence interval (CI) 12–17%). Significant between-study heterogeneity was observed. Our results indicate that axillary lymph node metastasis is a strong predictor of IMN involvement (OR 6.01, 95% CI, 3.49, 10.34).

Conclusion

Internal mammary lymph nodes metastasis might be underestimated. Patients with positive axillary lymph nodes have a higher risk of internal lymph nodes metastasis. As a result, IMN-SLNB might be considered in these patients. Future work needs to be done to assess whether pathological confirmed IMN metastasis can affect patients’ survival.

Radiotherapy for initial clinically positive internal mammary nodes in breast cancer

Purpose

Internal mammary lymph node (IMN) involvement is associated with poor prognosis in breast cancer. This study investigated the treatment outcomes of initial clinically IMN-positive breast cancer patients who received adjuvant radiotherapy (RT), including IMN irradiation, following primary breast surgery.

Materials and Methods

We retrospectively reviewed data of 95 breast cancer patients with clinically detected IMNs at diagnosis treated with surgery and RT between June 2009 and December 2015. Patients received adjuvant RT to the whole breast/chest wall and regional lymph node (axillary, internal mammary, and supraclavicular) areas. Twelve patients received an additional boost to the IMN area.

Results

The median follow-up was 43.2 months (range, 4.5 to 100.5 months). Among 77 patients who received neoadjuvant chemotherapy, 52 (67.5%) showed IMN normalization and 19 (24.6%) showed a partial response to IMN. There were 3 and 24 cases of IMN failure and any recurrence, respectively. The 5-year IMN failure-free survival, disease-free survival (DFS), and overall survival (OS) were 96%, 70%, and 84%, respectively. IMN failure-free survival was significantly affected by resection margin status (97.7% if negative, 87.5% for close or positive margins; p = 0.009). All three patients with IMN failure had initial IMN size ≥1 cm and did not receive IMN boost irradiation. The median age of the three patients was 31 years, and all had hormone receptor-negative tumors.

Conclusion

RT provides excellent IMN control without the support of IMN surgery. Intensity-modulated radiotherapy, including IMN boost for breast cancer patients, is a safe and effective technique for regional lymph node irradiation.

Risk factors for distant metastasis of patients with primary triple-negative breast cancer

Objective: Triple-negative breast cancer (TNBC) involves higher rates of recurrence and distant metastasis. The present study sought to characterize the risk factors for distant metastasis of TNBC.

Methods: The Surveillance, Epidemiology, and End Results (SEER) database was exploited to enroll patients diagnosed with TNBC from 2010 to 2015. The eligible patients were dichotomized into locoregional and distant metastasis at the time of diagnosis. Patients’ demographics and tumor features, and treatment were evaluated to identify the risk factors for distant metastasis of primary TNBC. The categorical variables were examined by chi-square tests. Univariate and multivariate logistic regression analyses were used to determine the risk factors for distant metastasis. Breast cancer-specific survival (BCSS) and overall survival (OS) were estimated by Kaplan–Meier plots with log-rank tests.

Results: We collected 26863 patients with primary TNBC, 1330 (5.0%) of them presented with distant metastasis. In the univariate analysis, all the variables indicated statistical significance. The significant variables were subsequently enlisted into the multivariate logistic regression analysis. Age > 50, higher clinical stage T and N, and tumor size > 5 cm were independent risk factors for distant metastasis of primary TNBC. Moreover, higher clinical stage T and stage N were independent risk factors for bone metastasis of the patients. TNBC patients with either bone or visceral metastasis have poor survival, with brain metastasis worst of all, though the OS difference was not statistically significant.

Conclusions: TNBC patients with larger age, higher clinical stage, larger tumor size were more predisposed to have distant metastasis. Great attention should be paid to the prognosis of these patients with distant metastasis.