A Dutch Prediction Tool to Assess the Risk of Additional Axillary Non–Sentinel 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.

Is Residual Nodal Disease at Axillary Dissection Associated with Tumor Subtype in Patients with Low Volume Sentinel Node Metastasis After Neoadjuvant Chemotherapy?

BACKGROUND

In patients with a positive sentinel lymph node (SLN) after neoadjuvant chemotherapy (NAC), the likelihood of residual nodal disease at axillary dissection (ALND) is high. Whether non-SLN metastasis frequency varies based on tumor subtype and SLN metastasis size is uncertain. We examined the association between tumor subtype and frequency of non-SLN metastases in patients with SLN micro- vs macrometastases after NAC.

METHODS

Patients with invasive breast cancer and a positive SLN biopsy after NAC between July 2008 and July 2019 were identified. Associations between tumor subtype, SLN disease volume, and frequency of non-SLN metastases were examined.

RESULTS

Among 273 patients with ≥ 1 positive SLN and a completion ALND, mean age was 51 years, 87% of tumors were ductal, 80% were clinically node-positive at presentation, and 85% were cT2-3. The frequency of non-SLN metastases was non-significantly higher in HR+/HER2- (61%) vs. HER2+ (52%) and triple negative tumors (45%) (p = 0.09). Frequency of SLN micrometastasis was 9% for triple negative tumors compared with 17% for HR+/HER2- and 34% for HER2+ tumors (p = 0.015). Size of SLN metastasis (micro- vs. macrometastases) was not associated with non-SLN metastasis frequency or number within any subtype.

CONCLUSIONS

In patients with a positive SLN after NAC, the likelihood of non-SLN metastasis at ALND was high across all tumor subtypes and did not vary significantly for SLN micro- versus macrometastases. ALND is recommended for SLN micro- and macrometastases after NAC, irrespective of tumor subtype.

Residual lymph node tumour burden following removal of a single axillary sentinel lymph with macrometastatic disease in women with screen-detected invasive breast cancer

Background

Women with screen-detected invasive breast cancer who have macrometastatic disease on axillary sentinel lymph node biopsy (SLNB) are usually offered either surgical axillary node clearance (ANC) or axillary radiotherapy. These treatments can lead to significant complications for patients. The aim of this study was to identify a group of patients who may not require completion ANC.

Methods

Data from the NHS Breast Screening Programme between 1 April 2012 and 31 March 2017 were interrogated to identify women with invasive breast carcinoma and a single sentinel lymph node (SLN) with macrometastatic disease who subsequently proceeded to completion ANC. Univariable and multivariable analyses were performed to identify patients with a single positive SLN who had no further lymph node metastasis on ANC.

Results

Of the 2401 women included in the cohort, the presence of non-sentinel node disease was significantly affected by: the number of nodes obtained at SLNB (odds ratio (OR) 0.49 for retrieval of more than 1 node), invasive size of tumour (OR 1.63 for size greater than 20 mm), surgical treatment (OR 1.34 for mastectomy), human epidermal growth factor receptor (HER) 2 status (OR 0.71 for HER2 positivity), and patient age (OR 1.10 for age less than 50 years; OR 1.46 for age greater than 70 years). Patients aged less than 70 years, with tumour size smaller than 2 cm, more than one node retrieved on SLNB, and who had breast-conserving surgery had a lower chance of positive non-sentinel nodes on completion ANC compared with other patients.

Conclusion

This study, of a purely screen-detected breast cancer cohort, identified a subset of patients who may be spared completion ANC in the event of a single axillary SLN with macrometastasis.

Omitting ALND Is Not Safe for a Cohort of Early-Stage Breast Cancer Patients with 1-2 SLNs Macro-Metastases and Breast-Conserving Therapy: A Single-Center Retrospective Study

Background:

Omitting axillary lymph node dissection (ALND) is recommended for early-stage breast cancer patients with 1–2 sentinel lymph nodes (SLNs) macro-metastases and breast-conserving therapy. However, it is not safe for part of patients, so it is significant to find risk factors and develop a predictive model of non-SLNs metastases in breast cancer patients with 1–2 SLNs macro-metastases and breast-conserving therapy.

Methods:

This retrospective study enrolled 228 breast cancer patients with 1–2 SLNs macro-metastases who underwent ALND and breast-conserving surgery between Jan 2012 and Dec 2017 at Cancer Hospital Chinese Academy of Medical Sciences. Chi-square test and backward stepwise binary logistic regression were used to find factors that influenced non-SLN metastases, then a predictive model was formulated and obtained its area under the curve.

Results:

Tumor pathologic invasion size, number of positive SLNs and ALN status on imaging was associated with non-SLNs metastases. The predictive model was also formulated based on these three factors to assess and the area under the curve of model was 0.708.

Conclusion:

We developed a predictive model to assess the high-risk cohort of patients of non-SLNs metastases which can be an auxiliary tool for doctors.

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.

Determinants for non-sentinel node metastases in primary invasive breast cancer: a population-based cohort study of 602 consecutive patients with sentinel node metastases

Background

Sentinel node biopsy (SNB) is the standard procedure for axillary staging in patients with clinically lymph node negative invasive breast cancer. Completion axillary lymph node dissection (c-ALND) may not be necessary for all patients as a significant number of patients have no further metastases in non-sentinel nodes (non-SN) and c-ALND may not improve survival. The first aim of our study is to identify clinicopathological determinants associated with non-SN metastases. The second aim is to determine the impact of the number of sentinel node (SN) with macro-metastases and the type of SN metastases on metastatic involvement in non-SN.

Methods

This is a retrospective study of 602 patients with primary invasive breast cancer operated on with SNB and c-ALND in Lund and Malmö during 2008–2013. All these patients had micro- and/or macro-metastases in SNs. Information was retrieved from the national Information Network for Cancer Care (INCA). The risk of metastases to non-SNs were analyzed in relation to clinicopathological determinants such as age, screening mammography, tumour size, tumour type, histological grade, estrogen status, progesterone status, HER2 status, multifocality and lymphovascular invasion. Additionally, we compared the association between the number of the SN and the type of metastases in SN with the risk of metastases to non-SNs. Binary logistic regression was used, yielding odds ratios (OR) with 95% confidence intervals (CI).

Results

We found that 211 patients (35%) had metastases in non-SNs and 391 patients (65%) had no metastases in non-SNs. Lobular type (18%) of breast cancer (1.73; 1.0 1-2.97) and multifocal (31.3%) tumours (2.20; 1.41–3.44) had a high risk of non-SNs metastases. As compared to only micro-metastases, the presence of macro-metastases in SNs was associated with a high risk of metastases to non-SNs (4.91; 3.01–8.05). The number of SN with macro-metastases, regardless of the number of SNs removed by surgery, increases the risk of finding non-SNs with metastases. The total number of SN removed by surgery had no impact on diagnosis of metastases in non-SNs. No statistically significant associations were observed regarding other studied determinants.

Conclusion

We conclude in the present study that lobular cancer and multifocal tumours were associated with a high risk of non-SN involvement. The presence of the macro-metastases in SNs and the number of SN with macro-metastases has a positive association with presence of metastases in non-SNs. The total number of SNs removed by surgery had no impact on finding metastases in non-SNs. These factors may be valuable considering whether or not to omit c-ALND.

Facilitating validation of prediction models: a comparison of manual and semi-automated validation using registry-based data of breast cancer patients in the Netherlands

Background

Clinical prediction models are not routinely validated. To facilitate validation procedures, the online Evidencio platform (https://www.evidencio.com) has developed a tool partly automating this process. This study aims to determine whether semi-automated validation can reliably substitute manual validation.

Methods

Four different models used in breast cancer care were selected: CancerMath, INFLUENCE, Predicted Probability of Axillary Metastasis, and PREDICT v.2.0. Data were obtained from the Netherlands Cancer Registry according to the inclusion criteria of the original development population. Calibration (intercepts and slopes) and discrimination (area under the curve (AUC)) were compared between semi-automated and manual validation.

Results

Differences between intercepts and slopes of all models using semi-automated validation ranged from 0 to 0.03 from manual validation, which was not clinically relevant. AUCs were identical for both validation methods.

Conclusions

This easy to use semi-automated validation option is a good substitute for manual validation and might increase the number of validations of prediction models used in clinical practice. In addition, the validation tool was considered to be user-friendly and to save a lot of time compared to manual validation. Semi-automated validation will contribute to more accurate outcome predictions and treatment recommendations in the target population.

Electronic supplementary material

The online version of this article (10.1186/s12874-019-0761-5) contains supplementary material, which is available to authorized users.

Risk factors and a predictive nomogram for non-sentinel lymph node metastases in Chinese breast cancer patients with one or two sentinel lymph node macrometastases and mastectomy

Background

Two ongoing prospective randomized trials are evaluating whether omitting axillary lymph node dissection (alnd) in patients with breast cancer (bca) and sentinel lymph node (sln) macrometastases undergoing mastectomy is safe. Determining predictive risk factors for non-sln metastases and developing a model to predict the probability of those patients having non-sln metastases is also important.

Methods

This retrospective study enrolled 396 patients with bca and 1-2 slns with macrometastases who underwent alnd and mastectomy between January 2012 and December 2016. Factors influencing the non-sln metastases were determined, and a predictive nomogram was formulated. Performance of the nomogram was evaluated by its area under the curve (auc).

Results

We developed a predictive nomogram with an auc of 0.81 (cross-validation 95% confidence interval: 0.75 to 0.86) that included 4 factors (tumour size, histologic grade, and number of negative slns and axillary lymph nodes on imaging).

Conclusions

Our predictive nomogram assesses the risk of non-sln metastases in patients with bca and 1-2 sln macrometastases undergoing mastectomy.

A new model to predict risk of nonsentinel lymph node status in Chinese sentinel lymph node-positive patients after neoadjuvant chemotherapy

There is no previous predictive model to assess risk of nonsentinel lymph node metastases (NSLN) in sentinel lymph node (SLN)-positive breast cancer patients after neoadjuvant chemotherapy (NAT). Our goal was to develop a new predictive model for SLN-positive patients after NAT, and validate this new model. A series of 513 patients with metastases in SLN who received NAT were used to evaluate factors affecting NSLN status. Logistic regression analysis was performed to develop a predictive model, which was validated by a subsequent prospective 138 patients. There were 115 (22.4%) patients with metastases in NSLN followed by axillary lymph node dissection (ALND). Multivariate analysis indicated that tumor (T) stage, number of positive SLN,micrometastases, extracapsular extension (ECE), and clinical response of primary tumor after NAT were significant independent predictors for the NSLN metastases. Area under the curve (AUC) of the model was 0.795 (95% CI, 0.734-0.861). When applied to the prospective series, the model accurately predicted the risk of NSLN disease, AUC was 0.772 (95% CI, 0.653-0.845). We present a new predictive model to assess the risk of NSLN status in Chinese SLN-positive breast cancer patients after NAT. The predictive model performed well in prospective validation but needs to be further studied in external center patients before application to clinical use.

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.

Secondary node analysis as an indicator for axillary lymphadenectomy in breast cancer patients

INTRODUCTION

Currently, there is no agreement regarding if it would be necessary to perform an axillary lymph node dissection (ALND) in patients who have macrometastases in the sentinel lymph node (SLN). We studied the utility of the secondary node analysis (SN), defined as the following node after the SLN in an anatomical and lymphatic pathway, as a sign of malignant axillary involvement.

METHODS

An observational, retrospective and multicentre study was designed to assess the utility of the SN as a sign of axillary involvement. Among 2273 patients with breast cancer, a valid sample of 283 was obtained representing those who had the SN studied. Main endpoints of our study were: the SLN, the SN and the ALND histological pattern. Sensitivity, specificity and precision of the test were also calculated.

RESULTS

SN test, in cases with positive SLN, has a sensitivity of 61.1%, a specificity of 78.7%, a positive predictive value of 45.8% and a negative predictive value of 87.3% with a precision of 74.7%.

CONCLUSION

The study of the SN together with the technique of the SLN allows a more precise staging of the axillary involvement, in patients with breast cancer, than just the SLN technique.

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.

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.