Non-sentinel lymph node metastasis prediction in breast cancer with metastatic sentinel lymph node: impact of molecular subtypes classification

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.

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.

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.

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.

Medico-economic impact of MSKCC non-sentinel node prediction nomogram for ER-positive HER2-negative breast cancers

Background

Avoiding axillary lymph node dissection (ALND) for invasive breast cancers with isolated tumor cells or micrometastatic sentinel node biopsy (SNB) could decrease morbidity with minimal clinical significance.

Purpose

The aim of this study is to simulate the medico-economic impact of the routine use of the MSKCC non-sentinel node (NSN) prediction nomogram for ER+ HER2- breast cancer patients.

Methods

We studied 1036 ER+ HER2- breast cancer patients with a metastatic SNB. All had a complementary ALND. For each patient, we calculated the probability of the NSN positivity using the MSKCC nomogram. After validation of this nomogram in the population, we described how the patients’ characteristics spread as the threshold value changed. Then, we performed an economic simulation study to estimate the total cost of caring for patients treated according to the MSKCC predictive nomogram results.

Results

A 0.3 threshold discriminate the type of sentinel node (SN) metastases: 98.8% of patients with pN0(i+) and 91.6% of patients with pN1(mic) had a MSKCC score under 0.3 (false negative rate = 6.4%). If we use the 0.3 threshold for economic simulation, 43% of ALND could be avoided, reducing the costs of caring by 1 051 980 EUROS among the 1036 patients.

Conclusion

We demonstrated the cost-effectiveness of using the MSKCC NSN prediction nomogram by avoiding ALND for the pN0(i+) or pN1(mic) ER+ HER2- breast cancer patients with a MSKCC score of less than or equal to 0.3.

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.

Patient-derived tumour xenografts as models for breast cancer drug development

PURPOSE OF REVIEW

Patient-derived xenografts (PDXs) are becoming increasing popular as a preclinical tool for evaluating novel therapeutic strategies in cancer. These models maintain the biological characteristics of the donor tumours and have a predictive power in the translation of cancer therapeutics into clinical settings. This review focuses on the rapidly growing body of literature on PDX models of breast cancer and their applications and challenges in cancer drug development.

RECENT FINDINGS

Several articles in the last 2 years have reported that breast cancer PDXs can reproduce the phenotype and diversity of patients' tumours. This preservation of breast cancer biology involves a number of different aspects, including gene expression patterns, mutational status, drug response and tumour architecture. These models have been shown to be a valuable tool for the identification of new treatment targets, rational drug combinations, biomarkers and mechanisms of drug resistance.

SUMMARY

The development of relevant, predictive models is key to increase the success rate for new drugs. PDX models of breast cancer hold the promise for the development of new and more efficient therapeutic strategies.

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

Purpose

This study aimed to identify the effect of breast cancer subtype on nonsentinel lymph node (NSLN) metastasis in patients with a positive sentinel lymph node (SLN).

Methods

The records of 104 early breast cancer patients with a positive SLN between April 2009 and September 2013 were retrospectively evaluated. All patients underwent axillary lymph node dissection. The effects of the tumor subtype (luminal A, luminal/HER2+, human epidermal growth factor receptor 2 [HER2] overexpression, and triple-negative) and other clinicopathological factors on NSLN metastasis were examined by univariate and multivariate statistical analyses.

Results

Fifty of 104 patients (48%) exhibited NSLN metastasis. Univariate and multivariate analyses revealed that tumor size and the ratio of positive SLNs were significant risk factors of NSLN metastasis in patients with a positive SLN. The rate of NSLN metastasis was higher in patients with luminal/HER2+ and HER2 overexpression subtypes than that in patients with other subtypes in the univariate analysis (p<0.001). In the multivariate analysis, both patients with luminal/HER2+ (p<0.006) and patients with HER2 overexpression (p<0.031) subtypes had a higher risk of NSLN metastasis than patients with the luminal A subtype.

Conclusion

Subtype classification should be considered as an independent factor when evaluating the risk of NSLN metastasis in patients with a positive SLN. This result supports the development of new nomograms including breast cancer subtype to increase predictive accuracy.

Is the differentiation into molecular subtypes of breast cancer important for staging, local and systemic therapy, and follow up?

Breast cancer complexity has long been known and investigated. After a first classification of the disease based on histology features, starting from the 1980s breast cancers have been distinguished on the basis of oestrogen receptor expression and later according to HER2. By 2000 the "microarray revolution" had shown that the phenotypic differences between breast cancers were a reflection of their mRNA expression profiles, while the more recent "genomic revolution" is revealing the genomic bases of breast cancer heterogeneity. However, how this huge amount of data and knowledge translate into clinically relevant practice is currently not clear. In the present review we discuss how the different breast cancer classification methods might translate into improved clinical guidelines with regard to staging, therapy, and follow up of patients with breast cancer.

[Sentinel node invasion: is it necessary to perform axillary lymph node dissection? Randomized trial SERC]

Contribution of axillary lymph node dissection (ALND) is questioned for positive sentinel node (SN), micro-metastasis and isolated tumor cells but also for macro-metastasis. The aim of this work is to precise why a prospective randomized trial is necessary and the design of this trial. Why? For positive SN, the scientific level evidence appears insufficient for validation of ALND omission as a new standard. Rational is presented with non-sentinel node involved rate and number of NSL involved at complementary ALND, axillary recurrence rate, disease free survival rate and adjuvant treatment decision impact. How? The proposed Sentinelle Envahi et Randomisation du Curage (SERC) trial will randomly assign to observation only or complementary ALND with positive SN. The aim is to demonstrate the non-inferiority of ALND omission versus ALND.

Cross-validation of three predictive tools for non-sentinel node metastases in breast cancer patients with micrometastases or isolated tumor cells in the sentinel node

BACKGROUND

We cross-validated three existing models for the prediction of non-sentinel node metastases in patients with micrometastases or isolated tumor cells (ITC) in the sentinel node, developed in Danish and Finnish cohorts of breast cancer patients, to find the best model to identify patients who might benefit from further axillary treatment.

MATERIAL AND METHOD

Based on 484 Finnish breast cancer patients with micrometastases or ITC in sentinel node a model has been developed for the prediction of non-sentinel node metastases. Likewise, two separate models have been developed in 1577 Danish patients with micrometastases and 304 Danish patients with ITC, respectively. The models were cross-validated in the opposite cohort.

RESULTS

The Danish model for micrometatases was accurate when tested in the Finnish cohort, with a slight change in AUC from 0.64 to 0.63. The AUC of the Finnish model decreased from 0.68 to 0.58 when tested in the Danish cohort, and the AUC of the Danish model for ITC decreased from 0.73 to 0.52, when tested in the Finnish cohort. The Danish micrometastatic model identified 14-22% of the patients as high-risk patients with over 30% risk of non-sentinel node metastases while less than 1% was identified by the Finish model. In contrast, the Finish model predicted a much larger proportion of patients being in the low-risk group with less than 10% risk of non-sentinel node metastases.

CONCLUSION

The Danish model for micrometastases worked well in predicting high risk of non-sentinel node metastases and was accurate under external validation.

[Breast cancer and axillary area: state of the art and perspectives]

A therapeutic surgical de-escalation has been observed since many years with an actual prolongation for axillary lymph node area treatment. Axillary lymph node dissection (ALND) omission has been studied before and after validation of sentinel node (SN) biopsy procedure. A non-inferiority of ALND omission has been reported in case of non-involved SN. ALND omission has been studied in case of SN involvement without consensus in relation with scientific level of proof and with selective indications. The purpose of this work is to make a synthesis of the experiences on this subject then to envisage the current and future perspectives.