Subtype is a predictive factor of nonsentinel lymph node involvement in sentinel node-positive breast cancer patients

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.

Ultrasonography and clinicopathological features of breast cancer in predicting axillary lymph node metastases

Background

Early identification of axillary lymph node metastasis (ALNM) in breast cancer (BC) is still a clinical difficulty. There is still no good method to replace sentinel lymph node biopsy (SLNB). The purpose of our study was to develop and validate a nomogram to predict the probability of ALNM preoperatively based on ultrasonography (US) and clinicopathological features of primary tumors.

Methods

From September 2019 to April 2022, the preoperative US) and clinicopathological data of 1076 T1-T2 BC patients underwent surgical treatment were collected. Patients were divided into a training set (875 patients from September 2019 to October 2021) and a validation set (201 patients from November 2021 to April 2022). Patients were divided into positive and negative axillary lymph node (ALN) group according pathology of axillary surgery. Compared the US and clinicopathological features between the two groups. The risk factors for ALNM were determined using multivariate logistic regression analysis, and a nomogram was constructed. AUC and calibration were used to assess its performance.

Results

By univariate and multivariate logistic regression analysis, age (p = 0.009), histologic grades (p = 0.000), molecular subtypes (p = 0.000), tumor location (p = 0.000), maximum diameter (p = 0.000), spiculated margin (p = 0.000) and distance from the skin (p = 0.000) were independent risk factors of ALNM. Then a nomogram was developed. The model was good discriminating with an AUC of 0.705 and 0.745 for the training and validation set, respectively. And the calibration curves demonstrated high agreement. However, in further predicting a heavy nodal disease burden (> 2 nodes), none of the variables were significant.

Conclusion

This nomogram based on the US and clinicopathological data can predict the presence of ALNM good in T1-T2 BC patients. But it cannot effectively predict a heavy nodal disease burden (> 2 nodes).

A novel nomogram for decision-making assistance on exemption of axillary lymph node dissection in T1–2 breast cancer with only one sentinel lymph node metastasis

Background

T1–2 breast cancer patients with only one sentinel lymph node (SLN) metastasis have an extremely low non-SLN (NSLN) metastatic rate and are favorable for axillary lymph node dissection (ALND) exemption. This study aimed to construct a nomogram-based preoperative prediction model of NSLN metastasis for such patients, thereby assisting in preoperatively selecting proper surgical procedures.

Methods

A total of 729 T1–2 breast cancer patients with only one SLN metastasis undergoing sentinel lymph node biopsy and ALND were retrospectively selected from Harbin Medical University Cancer Hospital between January 2013 and December 2020, followed by random assignment into training (n=467) and validation cohorts (n=262). A nomogram-based prediction model for NSLN metastasis risk was constructed by incorporating the independent predictors of NSLN metastasis identified from multivariate logistic regression analysis in the training cohort. The performance of the nomogram was evaluated by the calibration curve and the receiver operating characteristic (ROC) curve. Finally, decision curve analysis (DCA) was used to determine the clinical utility of the nomogram.

Results

Overall, 160 (21.9%) patients had NSLN metastases. Multivariate analysis in the training cohort revealed that the number of negative SLNs (OR: 0.98), location of primary tumor (OR: 2.34), tumor size (OR: 3.15), and lymph-vascular invasion (OR: 1.61) were independent predictors of NSLN metastasis. The incorporation of four independent predictors into a nomogram-based preoperative estimation of NSLN metastasis demonstrated a satisfactory discriminative capacity, with a C-index and area under the ROC curve of 0.740 and 0.689 in the training and validation cohorts, respectively. The calibration curve showed good agreement between actual and predicted NSLN metastasis risks. Finally, DCA revealed the clinical utility of the nomogram.

Conclusion

The nomogram showed a satisfactory discriminative capacity of NSLN metastasis risk in T1–2 breast cancer patients with only one SLN metastasis, and it could be used to preoperatively estimate NSLN metastasis risk, thereby facilitating in precise clinical decision-making on the selective exemption of ALND in such patients.

Relation Between Tumor Size and Lymph Node Metastasis According to Subtypes of Breast Cancer

Purpose

Tumor size and lymph node metastasis are important factors that contribute to the progression of breast cancer. We aimed to analyze the relationship between tumor size and lymph node metastasis molecular subtype and examine the effects of nodal metastasis on overall survival (OS).

Methods

We retrospectively reviewed the data of 16,552 patients who underwent breast surgery in Samsung Medical Center between 2000 and 2015. Information on tumor size (largest diameter of the invasive component), number of positive lymph nodes, and molecular subtype were obtained. We constructed a linear regression model to evaluate the relationship between tumor size and lymph node metastasis. To determine the effect of nodal metastasis on OS, we performed a Cox proportional regression analysis with Np/T (number of metastatic lymph nodes [n]/tumor size [cm]).

Results

This study included 12,007 patients with a median follow-up of 62 months. The linear regression coefficients were 1.043 for luminal A, 1.024 for luminal B, 0.656 for HER2, and 0.435 for triple-negative breast cancer (TNBC) subtypes. No significant difference was observed in the coefficients between the luminal A and B subtypes (p = 0.797), while all other coefficients showed significant difference. After adjusting for other risk factors, the hazard ratio (HR) of Np/T for each subtype was significant for OS: luminal A (HR, 1.134; 95% confidence interval [CI], 1.097–1.171; p < 0.001), luminal B (HR, 1.049; 95% CI, 1.013–1.086; p = 0.007), HER2 (HR, 1.069; 95% CI, 1.014–1.126; p = 0.013), and TNBC (HR, 1.038; 95% CI, 1.01–1.067; p = 0.008).

Conclusion

The incidence of lymph node metastasis differed according to molecular subtype. Luminal types have higher incidence of nodal metastasis than HER2 and TNBC. The HR of Np/T was highest in luminal A subtypes and lowest in TNBC subtypes.

A nomogram to predict non-sentinel lymph node metastasis in patients with initial cN+ breast cancer that downstages to cN0 after neoadjuvant chemotherapy

BACKGROUND AND OBJECTIVES

This study mainly explored the factors that influence non-sentinel lymph node (NSLN) metastasis in patients with breast cancer (BC) whose axillary lymph nodal status changed from clinically node positive (cN+) to clinically node negative (cN0) after neoadjuvant chemotherapy (NAC).

METHODS

We retrospectively analyzed the clinicopathological factors affecting NSLN metastasis in a total of 179 patients with cN+ BC downstaged to cN0 (120 in the training set and 59 in the validation set) who underwent both sentinel lymph node (SLN) biopsy and axillary lymph node dissection following NAC.

RESULTS

Among 179 patients enrolled, the overall NSLN metastatic rate was 24.0% (95% confidence interval [CI]: 17.7%-30.3%). In multivariate logistic regression analysis, the number of positive SLNs achieving a pathological complete remission of the breast and clinical node staging was independent predictors of NSLN metastasis. A nomogram was established based on these factors and displayed a good discriminatory capability, with an area under the curve of 0.919 (95% CI: 0.865-0.973) for the training set and 0.900 (95% CI: 0.812-0.988) for the validation set and its clinical utility was confirmed by the decision curve analysis.

CONCLUSIONS

The nomogram established showed the ability to predict NSLN metastases in patients with initial cN+ BC that downstaged to cN0 after NAC.

Sentinel Node Biopsy in Early Breast Cancer Patients with Palpable Axillary Node

BACKGROUND

Sentinel lymph node biopsy is a reliable method for evaluation of the axillary lymph node status in early stage breast cancer patients with non-palpable lymph nodes. The present study evaluated the status of sentinel and non-sentinel lymph nodes in T1T2 patients with palpable axillary lymph nodes.

MATERIALS AND METHODS

One hundred and two women with early breast cancer were investigated in this study. Patients were selected for axillary sentinel lymph node biopsy and then surgery .Then the rates of false negative and true positive, and diagnostic accuracy of sentinel lymph nodes biopsy were evaluated. In addition, the hormone receptors status of the tumor was determined through IHC and data was analyzed in SPSS21.

RESULTS

In this study, the mean age of the patients was 49 years, 85% had invasive ductal carcinoma  in their pathology reports, 77% were ER/PR positive, 30% HER2 positive and 9.8% triple negative and 69% had KI67<14%. In frozen pathology, 15.7 and 84.3% were sentinel positive and negative, respectively, and in the final pathology, 41 and 58.8% were sentinel positive and negative, respectively. This difference arises from the false negative rate of the frozen pathology, which was about 31.3%. The sensitivity, specificity, and diagnostic accuracy of the frozen section were 24, 90 and 43%, respectively. Lymphovascular invasion is an important effective factor in the involvement of sentinel and non-sentinel lymph nodes. Statistical analysis showed that the probability of sentinel and non-sentinel lymph nodes involvement was higher in receptor positive patients and those with KI67>14% (p<0.002) whereas the rate of involvement was lower in triple negative patients.

CONCLUSION

Sentinel node biopsy can be used in a significant percentage of breast cancer patients with palpable and reactive axillary lymph nodes.

Imaging Predictors for Nonsentinel Lymph Node Metastases in Breast Cancer Patients

Background

The relationship between imaging features and nonsentinel lymph node (NSLN) metastasis is not clear.

Objectives

To determine whether imaging features could predict NSLN metastasis in sentinel lymph node (SLN)-positive breast cancer patients and to provide new clues for avoiding unnecessary axillary lymph node dissection.

Method

171 patients with clinically negative axillary lymph nodes and a pathologically positive SLN were recruited between January 2007 and January 2014. According to the Breast Imaging Reporting and Data System (BI-RADS), the effects of clinicopathological factors, especially imaging features, on NSLN metastases were assessed by univariate and multivariate statistical analyses.

Results

The average number of dissected SLNs was 2.11 (range, 1-6); 56 of the 171 (32.75%) patients exhibited NSLN metastases. In univariate analysis, tumor size, number of positive SLNs, ratio of positive SLNs, mammographic mass margins, ultrasonographic mass margins, and ultrasonographic vascularity were significantly correlated with NSLN involvement. Furthermore, through multivariate analysis, tumor size, number of positive SLNs, mammographic mass margins, and ultrasonographic vascularity were still independent predictors of NSLN involvement. Additionally, in SLN-positive patients, number of positive SLNs and ultrasonographic vascularity could also predict the tumor burden in NSLN.

Conclusions

In addition to tumor size and the number of positive SLNs, mammographic mass margins and ultrasonographic vascularity were also independent predictors of NSLN metastases in SLN-positive patients of breast cancer. The number of positive SLNs and ultrasonographic vascularity could also predict the tumor burden in NSLN.

Predictors of non-sentinel lymph node metastasis in clinical early stage (cT1-2N0) breast cancer patients with 1-2 metastatic sentinel lymph nodes

OBJECTIVE

The purpose of this study was to determine the risk factors that caused non-sentinel lymph nodes (nonSLNs) metastasis by considering the clinicopathological characteristics of patients who have 1-2 sentinel lymph node (SLN) metastasis in the clinical early stage (T1-2, N0) breast cancer.

METHODS

The demographic and clinicopathological characteristics of the patients were recorded retrospectively. Among these, age, size of the primary breast tumor, tumor localization and multifocality/multicentricity status, preoperative serum Neutrophil/Lymphocyte rate (NLR), c-erbB2/HER2-neu status, Estrogen Receptor (ER) and Progesterone Receptor (PR) status, primary tumor proliferation index (Ki-67), histopathological grade, molecular subtypes, histopathological subtypes, nipple/areola infiltration, Lymphatic Invasion (LI), Vascular Invasion (VI), Perineural Invasion (PNI), number of metastatic SLN m(SLN), mSLN diameter, SLN Extranodal Extension (ENE) status, and number of metastatic nonSLNs were recorded.

RESULTS

According to the univariate analysis, the HER2 positivity, Ki-67≥%20, mSLN diameter, LI, VI, PNI, ENE and molecular subtypes were found to be significant. However, the age, tumor localization, multifocality/multicentricity, T stage, ER and PR status, tumor size, histopathological grade and subtypes, nipple/areola infiltration and NLR were not found to be significant. In the multivariate analysis, significant independent predictors in nonSLN metastasis development were found to be HER2 positivity, PNI, mSLN diameter ≥10,5 mm and ENE.

CONCLUSION

The HER2 positivity, ENE, PNI and mSLN diameter ≥10,5 mm were found to be very strong predictors in nonSLN metastasis development. The findings of this study have the potential to be a guideline for surgeons and oncologists when determining their patients' treatment plan. These components are candidates for inclusion among the clinicopathological factors that may be used in the new nomograms due to their higher sensitivity and specificity.

A mathematical prediction model incorporating molecular subtype for risk of non-sentinel lymph node metastasis in sentinel lymph node-positive breast cancer patients: a retrospective analysis and nomogram development

BACKGROUND

Molecular subtype of breast cancer is associated with sentinel lymph node status. We sought to establish a mathematical prediction model that included breast cancer molecular subtype for risk of positive non-sentinel lymph nodes in breast cancer patients with sentinel lymph node metastasis and further validate the model in a separate validation cohort.

METHODS

We reviewed the clinicopathologic data of breast cancer patients with sentinel lymph node metastasis who underwent axillary lymph node dissection between June 16, 2014 and November 16, 2017 at our hospital. Sentinel lymph node biopsy was performed and patients with pathologically proven sentinel lymph node metastasis underwent axillary lymph node dissection. Independent risks for non-sentinel lymph node metastasis were assessed in a training cohort by multivariate analysis and incorporated into a mathematical prediction model. The model was further validated in a separate validation cohort, and a nomogram was developed and evaluated for diagnostic performance in predicting the risk of non-sentinel lymph node metastasis. Moreover, we assessed the performance of five different models in predicting non-sentinel lymph node metastasis in training cohort.

RESULTS

Totally, 495 cases were eligible for the study, including 291 patients in the training cohort and 204 in the validation cohort. Non-sentinel lymph node metastasis was observed in 33.3% (97/291) patients in the training cohort. The AUC of MSKCC, Tenon, MDA, Ljubljana, and Louisville models in training cohort were 0.7613, 0.7142, 0.7076, 0.7483, and 0.671, respectively. Multivariate regression analysis indicated that tumor size (OR = 1.439; 95% CI 1.025-2.021; P = 0.036), sentinel lymph node macro-metastasis versus micro-metastasis (OR = 5.063; 95% CI 1.111-23.074; P = 0.036), the number of positive sentinel lymph nodes (OR = 2.583, 95% CI 1.714-3.892; P < 0.001), and the number of negative sentinel lymph nodes (OR = 0.686, 95% CI 0.575-0.817; P < 0.001) were independent statistically significant predictors of non-sentinel lymph node metastasis. Furthermore, luminal B (OR = 3.311, 95% CI 1.593-6.884; P = 0.001) and HER2 overexpression (OR = 4.308, 95% CI 1.097-16.912; P = 0.036) were independent and statistically significant predictor of non-sentinel lymph node metastasis versus luminal A. A regression model based on the results of multivariate analysis was established to predict the risk of non-sentinel lymph node metastasis, which had an AUC of 0.8188. The model was validated in the validation cohort and showed excellent diagnostic performance.

CONCLUSIONS

The mathematical prediction model that incorporates five variables including breast cancer molecular subtype demonstrates excellent diagnostic performance in assessing the risk of non-sentinel lymph node metastasis in sentinel lymph node-positive patients. The prediction model could be of help surgeons in evaluating the risk of non-sentinel lymph node involvement for breast cancer patients; however, the model requires further validation in prospective studies.

Analysis of factors related to non-sentinel lymph node metastasis in 296 sentinel lymph node-positive Chinese breast cancer patients

Objective:

Axillary lymph node dissection (ALND) may be unnecessary in 20%–60% of breast cancer patients with sentinel lymph node (NSLN) metastasis. The aim of the present study was to review the medical records of Chinese patients with early-stage breast cancer and positive NSLN metastasis to identify clinicopathological characteristics as risk factors for non-NSLN metastasis.

Methods:

The medical records of 2008 early-stage breast cancer patients who received intraoperative sentinel lymph node biopsy (SLNB) between 2006 and 2016 were retrospectively reviewed. These patients were clinically and radiologically lymph node-negative and had no prior history of receiving neoadjuvant chemotherapy or endocrinotherapy. The clinicopathological characteristics of patients with positive NSLN metastasis who underwent ALND were investigated.

Results:

In the present study, 296 patients with positive NSLN metastases underwent ALND. Positive non-NSLN metastases were confirmed in 95 patients (32.1%). On univariate analysis, ≥ 3 positive NSLN metastases (P <0.01), NSLN macrometastases ( P = 0.023), and lymphovascular invasion (P = 0.04) were associated with non-NSLN metastasis (P <0.05). In multivariate analysis, the number of positive SLNs was the most significant predictor of non-SLN metastasis. For patients with 0, 1, 2, or 3 associated risk factors, the non-SLN metastatic rates were 11.5%, 22.5%, 35.2%, and 73.1%, respectively.

Conclusions:

The number of positive NSLNs, NSLN macrometastases, and lymphovascular invasion were correlated with non-SLN metastasis. The number of positive SLNs was an independent predictor for non-NSLN metastasis. When 2 or 3 risk factors were present in one patient, the probability of non-NSLN was higher than that in the American College of Surgeons Oncology Group Z0011 trial (27.3%); thus, avoiding ALND should be considered carefully.

The prognostic value of regulatory T cells infiltration in HER2-enriched breast cancer microenvironment

Breast cancer represents a complex and heterogeneous disease that comprises distinct disease conditions, histological features, and clinical outcome. Since many years, it has been demonstrated as an association between HER2 amplification and poor prognosis, because its overexpression is associated with an aggressive phenotype of breast tumor cells. A significant proportion of cases have developed resistance to the current therapies available. Consequently, new prognostic markers are urgently needed to identify patients who are at the highest risk for developing metastases. During the past decade, new insights provided valuable knowledge regarding mechanisms underlying the dynamic interplayed between immune cells and tumor progression. It has been shown that the presence of a lymphocytic infiltrate, particularly of regulatory T cells, in cancer tissue, is associated with clinical outcome promoting rather than inhibiting cancer development and progression. It has been also verified that the clinical value of lymphocytic infiltration in breast cancers could be subtype-dependent, including the HER2-enriched subtype. In this context, this work summarizes proposed to discuss the prognostic value of regulatory T cell infiltration in microenvironment of HER2-enriched breast cancer.

Impact of Size of the Tumour, Persistence of Estrogen Receptors, Progesterone Receptors, HER2Neu Receptors and Ki67 Values on Positivity of Axillary Lymph Nodes in Patients with Early Breast Cancer with Clinically Negative Axillary Examination

AIM:

The study aimed to identify factors that influence the positivity of axillary lymph nodes in patients with early breast cancer and clinically negative axillary lymph nodes, who were subjected for modified radical mastectomy and axillary lymphadenectomy.

MATERIAL AND METHODS:

This study included 81 surgically treated, early breast cancer patients during the period from 08-2015 to 05-2017. All the cases have been analysed by standard histological analysis including macroscopic and microscopic examination by routine H&E staining. For determination of molecular receptors, immunostaining by PT LINK immunoperoxidase has been done for HER2neu, ER, PR, p53 and Ki67.

RESULTS:

Patients age ranged between 31-73 years, an average of 56.86 years. The mean size of a primary tumour in the surgically treated patient was 20.33 ± 6.0 mm. Axillary dissection revealed from 5 to 32 lymph nodes, with an average of 14. Metastases have been found in 1 to 7 lymph nodes, with an average 0.7. Only 26 (32.1%) of the patients showed metastases in the axillary lymph nodes. The univariant regression analysis showed that the size of a tumour and presence of HER2neu receptors on cancer cells influence the positivity of the axillary lymph nodes. The presence of the estrogen receptors, progesterone receptors have no influence on the positivity for metastatic deposits of lymph nodes. Multivariant model and logistic regression analysis as significant independent factors or predictors of positivity of the axillary lymph nodes are influenced by the tumour size only.

CONCLUSION:

Our study showed that the metastatic involvement of the axillary lymph nodes is mainly influenced by the size of a tumour and presence of HER2neu receptors in the univariant analysis. This point to the important influence of positivity of the axillary lymph nodes but, in multi-variant regressive analysis the lymph node status correlates with the tumour size only.

Factors Influencing Non-sentinel Node Metastasis in Patients with Macrometastatic Sentinel Lymph Node Involvement and Validation of Three Commonly Used Nomograms

OBJECTIVE

Omitting axillary lymph node dissection (ALND) in a subgroup of patients with sentinel lymph node (SLN) metastasis is becoming a widely accepted practice. Avoiding the well-known complications of ALND is the sole aim without compromising the curative intention of surgery.

MATERIALS AND METHODS

The data were probed for breast cancer patients that were operated on between February 2014 and June 2016. SLN biopsies were performed in 507 patients and out of 157 patients who underwent ALND for a metastatic SLN, 151 were found eligible for the analyses as having macrometastatic (>2mm) SLN. MD Anderson, Memorial Sloan Kettering Cancer Center and Helsinki nomograms were also tested in our patient population.

RESULTS

Pathologic tumor size greater than 2 cm, the ratio of metastatic SLN to dissected SLN, metastatic tumor greater than 1 cm and tumors that extended outside the SLN's capsule were found to be associated with non-sentinel node metastasis in both univariate and multivariate tests. MD Anderson nomogram performed well with an area under the curve (AUC) value of 0.72.

CONCLUSION

Our results suggest that ALND should be considered in patients with macrometastatic SLN greater than 10 mm in size, have extracapsular extension, have metastatic SLNs at a rate of more than 50% and whose primary tumor is greater than 2 cm.

Prognostic Factors on the Positivity for Metastases of the Axillary Lymph Nodes from Primary Breast Cancer

AIM

The aim of the study was to identify the impact of T stage, the presence of estrogen, progesterone, HER2neu receptors and the values of the Ki67 on the positivity for metastases of the axillary lymph nodes, from primary breast cancer.

MATERIAL AND METHODS

290 surgically treated patients for breast cancer were included in the study. All cases have been analyzed by standard histological analysis including microscopic analysis on standard H&E staining. For determining the molecular receptors - HER2neu, ER, PR, p53 and Ki67, immunostaining by PT LINK immunoperoxidase has been done.

RESULTS

Patients age was ranged between 18-90 years, average of 57.6+11.9. The mean size of the primary tumor in the surgically treated patient was 30.27 + 18.3 mm. On dissection from the axillary pits 8 to 39 lymph nodes were taken out, an average of 13.81+5.56. Metastases have been found in 1 to 23 lymph nodes, an average 3.14+4.71. In 59% of the patients there have been found metastases in the axillary lymph nodes. The univariate regression analysis showed that the location, size of tumor, differentiation of the tumor, stage, the value of the Ki67 and presence of lymphovascular invasion influence on the positivity of the axillary lymph nodes. The presence of the estrogen receptors, progesterone receptors and HER2neu receptors showed that they do not have influence on the positivity for metastatic deposits in axillary lymph nodes. The multivariate model and the logistic regression analysis as independent significant factors or predictors of positivity of the axillary lymph nodes are influenced by the tumor size and the positive lymphovascular invasion.

CONCLUSION

Our study showed that the involving of the axillary lymph nodes is mainly influenced by the size of the tumor and the presence of lymphovascular invasion in the tumor. Ki67 determined proliferative index in the univariate analysis points the important influence of positivity in the axillary lymph nodes, but not in the multivariate regressive analysis.

Survival impact and predictive factors of axillary recurrence after sentinel biopsy

BACKGROUND

The rate of axillary recurrence (AR) after sentinel lymph node biopsy is usually low but few studies investigated its impact on survival. Our aim was to determine the rate and predictive factors of AR in a large cohort of breast cancer patients and its impact on survival.

PATIENTS AND METHODS

From 1999 to 2013, 14,095 patients who underwent surgery for clinically N0 previously untreated breast cancer and had sentinel lymph node biopsy were analysed. A simplified score predictive of AR was established.

RESULTS

Median follow-up was 55.2 months. AR was observed in 0.51% of cases, with a median time to onset of 43.4 months. In multivariate analysis, the occurrence of AR was significantly correlated with grade 2 or 3 disease, absence of radiotherapy and tumour subtype (hormonal receptor [HR]- / human estrogen receptor [HER]+). AR rates were 1% for triple-negative tumours, 2.8% for HER2-positive tumours, 0.4% for luminal A tumours, 0.9% for HER2-negative luminal B tumours, and 0.5% for HER2-positive luminal B tumours. A simplified score predictive of the occurrence of AR was established. Patients could be divided into three different score groups (p < 0.0001). In multivariate analysis, overall survival was significantly lower in cases of AR (p < 0.0001), age >50, lymphovascular invasion, grade 3 disease, sentinel node (SN) macrometastases, tumour size >20 mm, absence of chemotherapy and triple-negative phenotype. Survival in patients with AR was significantly lower in case of early-onset (2 years) AR (p = 0.017).

CONCLUSIONS

Isolated AR is more common in Her2-positive/HR-negative triple-negative tumours with a more severe prognosis in triple-negative and Her2-positive/HR-negative tumours, and represents an independent adverse factor justifying an indication for systemic treatment for AR treatment. However, the benefit of any systemic treatment remains to be proven.

Expression of SIRT1 and apoptosis-related proteins is predictive for lymph node metastasis and disease-free survival in luminal A breast cancer

Luminal A breast cancer can present with early, unexpected lymph node metastasis, and sentinel lymph node biopsy has been reported false negative in some cases. We aimed to construct a biomarker-based model that predicts lymph node metastasis in luminal A breast cancer, using expression of silent mating type information regulation 2 homolog 1 (SIRT1) and apoptosis-related factors, which are known to be closely related. We selected tissue samples of 278 cases of luminal A invasive ductal carcinoma, constructed tissue microarrays, and performed immunohistochemical staining for SIRT1 and four apoptosis-related proteins. In constructing the best predictive model for lymph node metastasis, six clinicopathological parameters and five molecular markers were considered. Independent factors predictive of lymph node metastasis were pT stage (OR 1.829, p = 0.027), lymphovascular invasion (OR 4.128, p < 0.001), and decreased expression of caspase-3 (OR 0.535, p = 0.034) and of SIRT1 (OR 0.526, p = 0.053). A combination nuclear grade, lymphovascular invasion, increased B-cell lymphoma 2 (Bcl-2) expression, and reduced expression of caspase-3 and of SIRT1 yielded the strongest predictive performance for lymph node metastasis with an area under the curve (AUC) of 0.696. This combination was also predictive of shortened disease-free survival (73.1 vs. 67.7 months, p = 0.003). Our data support a role of SIRT1 protein as tumor suppressor in luminal A breast cancer, in association with apoptosis-related proteins. Our model based upon a combination of these biomarkers is expected to increase accuracy of prediction of lymph node metastasis in luminal A breast cancer. This might serve as a valuable tool in determining the optimal surgical strategy in breast cancer patients.

Breast Cancer Patients Undergoing Sentinel Node Biopsy: Additional Axillary Tumor Burden as a Function of the Total Number of Excised Sentinel Nodes-A Multicenter Study

BACKGROUND

Recent studies have challenged the long-standing assumption that breast cancer prognosis is determined by lymph node regional status. We assessed locoregional relapse, distant metastases, and mortality alongside additional axillary disease in breast cancer patients undergoing sentinel node (SN) biopsy.

PATIENTS AND METHODS

This prospective study assessed 1070 women with clinical T1-T2 invasive breast cancer with negative clinical/ultrasound axillae.

RESULTS

A total of 25.1% of patients had positive SN biopsy findings, of whom 69.2% had only 1 involved SN. The rate of axillary recurrence was 0.7%, with no significant differences found between patients with positive or negative SN (0.6% vs. 1.1%). There were also no significant differences in the rate of distant metastases or breast cancer-specific mortality. If we had applied the Z0011 trial suggestions, residual axillary disease would have reached 16.2%: 13.5% in patients over 50% and 21.3% in patients under 50. The rate of residual axillary disease would have been 25.2% in patients with only 1 SN (20.2% in patients over 50% and 38.2% in patients under 50). In patients with 2 SN, residual disease would have ranged from 12.0% in patients over 50% to 19.0% in patients under 50. From 3 SN on, residual disease seems negligible.

CONCLUSION

There were no significant differences in locoregional relapse, distant metastases, or mortality between patients with negative and positive SN. Patients with 3 or more SN have no additional axillary disease. In patients younger 50, one must be extremely cautious if the Z0011 suggestions are to be applied, especially if there is only 1 SN.