Which nomogram is best for predicting non-sentinel lymph node metastasis in breast cancer patients? A meta-analysis

Strict versus Liberal Use of Sentinel Node Biopsy in Breast Cancer Surgery: Any Clinical Outcome Differences? A 20-Year Clinical Experience

Introduction

As applied to early breast cancer (BC) patients, sentinel node biopsy (SNB) has undergone major changes over the years, especially concerning the widening of indication criteria or skipping systematic axillary lymph node dissection (ALND) after a positive SN. We aimed to ascertain whether a strict versus a more liberal use of SNB resulted in different clinical outcomes in our clinical experience.

Methods

We studied consecutive BC patients undergoing SNB between January 1, 2000, and March 31, 2020. There were 1,587 patients and 1,634 SNB procedures. Cases were divided into two study groups: the "strict" SNB group (unifocal tumors up to 35 mm in which ALND was always performed for a positive SN, amounting to 1,183 SNBs), and the "liberal" SNB group (extended tumor size up to selected T3 cases, as well as multifocal or bilateral disease, and patients with previous contralateral BC, not always followed by ALND after a positive SN, amounting to 451 SNBs). Patients were closely followed up to the end of the study.

Results

Clinico-pathological variables were strikingly different between study groups, with the liberal group showing a higher risk profile. Cox regression analysis for disease recurrence did not show significant differences in axillary, lymph node, or locoregional recurrence rates or distant relapse. There were no differences in survival between groups.

Conclusion

It seems reasonable to adopt the liberal SNB approach, as the goal of surgical management in early BC patients must be attaining optimal locoregional disease control, no matter the differences in distant metastatic spread rates across different BC risk profiles.

The influence of axillary surgery and radiotherapeutic strategy on the risk of lymphedema and upper extremity dysfunction in early breast cancer patients

PURPOSE

To explore the risk factors for breast cancer-related lymphedema (BCRL) and upper extremity dysfunction (UED) in patients with early breast cancer after modern comprehensive treatment and to compare the toxicity of different treatment strategies.

METHODS

From 2017 to 2020, a total of 1369 female patients with pT1-3N0-1M0 breast cancer who underwent adjuvant radiotherapy in our centre were retrospectively reviewed. BCRL and UED were identified by the Norman and QuickDASH questionnaires. The incidence, severity and risk factors for BCRL and UED were evaluated.

RESULTS

After a median follow-up of 25 months, a total of 249 patients developed BCRL; axillary lymph node dissection (ALND), increased number of dissected nodes, right-sided and hypofractionated radiotherapy containing RNI were found to be significant risk factors (all p values < 0.05). The sentinel lymph node biopsy (SLNB)+ regional nodal irradiation (RNI) group had a significantly lower BCRL risk than the ALND + RNI group (10.8% vs. 32.5%, HR = 0.426, p = 0.020), while there was no significant difference between ALND vs. ALND + RNI or SLNB vs. SLNB + RNI. A total of 193 patients developed UED, and ALND (p = 0.02) was the only significant risk factor. The SLNB + RNI group had a significantly decreased risk of UED compared with the ALND + RNI group (7.5% vs. 23.9%, HR = 0.260, p = 0.001), and there was no significant difference between SLNB vs. SLNB + RNI or ALND vs. ALND + RNI.

CONCLUSION

Aggressive ALND remains the primary risk factor for BCRL and UED while RNI does not. Thus, replacing ALND with tailored radiotherapy would be an effective preventive strategy in early breast cancer patients.

Anatomical site and size of sentinel lymph node metastasis predicted additional axillary tumour burden and breast cancer survival

AIMS

Sentinel lymph node (SLN) biopsy is the current standard assessment for tumour burden in axillary lymph node (ALN). However, not all SLN+ patients have ALN metastasis. The prognostic implication of SLN features is not clear. We aimed to evaluate predictive factors for ALN metastasis and the clinical value of SLN features.

METHODS AND RESULTS

A total of 228 SLN+ and 228 SLN- (with matched year and grade) cases were included. Clinicopathological features in SLN, ALN and primary tumours, treatment data and survival data were analysed according to ALN status and outcome. Except for larger tumour size and the presence of LVI (both P < 0.001), no significant differences were found in SLN- and SLN+ cases. Only 31.8% of SLN+ cases with ALN dissection had ALN metastasis. The presence of macrometastases (MaM), extranodal extension (ENE), deeper level of tumour invasion in SLN and more SLN+ nodes were associated with ALN metastasis (P ≤ 0.025). Moreover, isolated tumour cells (ITC) and level of tumour invasion in SLN were independent adverse prognostic features for disease-free survival and breast cancer-specific survival, respectively. Interestingly, cases with ITC located in the subcapsular region have better survival than those in cortex (OS: χ²  = 4.046, P = 0.044).

CONCLUSIONS

Our study identified features in SLN, i.e. the level of tumour invasion at SLN and tumour size in SLN as useful predictors for both ALN metastasis and breast cancer outcome. The presence of ITC, particularly those with a deeper invasion in SLN, portended a worse prognosis. Proper attention should be taken for their management.

Predictive nomogram based on serum tumor markers and clinicopathological features for stratifying lymph node metastasis in breast cancer

BACKGROUND

This study was aimed to establish the nomogram to predict patients' axillary node status by using patients' clinicopathological and tumor characteristic factors.

METHODS

A total of 705 patients with breast cancer were enrolled in this study. All patients were randomly divided into a training group and a validation group. Univariate and multivariate ordered logistic regression were used to determine the predictive ability of each variable. A nomogram was performed based on the factors selected from logistic regression results. Receiver operating characteristic curve (ROC) analysis, calibration plots and decision curve analysis (DCA) were used to evaluate the discriminative ability and accuracy of the models.

RESULTS

Logistic regression analysis demonstrated that CEA, CA125, CA153, tumor size, vascular-invasion, calcification, and tumor grade were independent prognostic factors for positive ALNs. Integrating all the predictive factors, a nomogram was successfully developed and validated. The C-indexes of the nomogram for prediction of no ALN metastasis, positive ALN, and four and more ALN metastasis were 0.826, 0.706, and 0.855 in training group and 0.836, 0.731, and 0.897 in validation group. Furthermore, calibration plots and DCA demonstrated a satisfactory performance of our nomogram.

CONCLUSION

We successfully construct and validate the nomogram to predict patients' axillary node status by using patients' clinicopathological and tumor characteristic factors.

A New Possible Cut-Off of Cytokeratin 19 mRNA Copy Number by OSNA in the Sentinel Node of Breast Cancer Patients to Avoid Unnecessary Axillary Dissection: A 10-Year Experience in a Tertiary Breast Unit

Simple Summary

This manuscript aims to investigate the features of patients with metastatic sentinel lymph node (SLN), evaluated by OSNA, and to predict which patients have a high risk of positive ALND. The finding of the present study suggests a new cut-off of CK19 mRNA copy number in the sentinel lymph node useful to personalize surgical treatments and avoid unnecessary axillary surgical treatments.

Abstract

(1) Background: The main discriminant in breast cancer prognosis is axillary lymph node status. In a select cohort of patients, axillary lymph node dissection (ALND) may be safely spared. This study aimed to determine a new possible cut-off of cytokeratin (CK) 19 mRNA copy number in the SLN to predict cases at high risk of positive ALND. (2) Methods: Clinical records of 1339 patients were retrospectively reviewed and were separated into two groups according to the axillary status (negative: ALNs− and positive ALNs+). Receiver operative characteristic (ROC) curves were used to identify a new optimal cut-off of CK19 mRNA copy number in SLN; (3) Results: Large tumor size and high grade were found mostly in ALNs+. Results from the ROC analyses, with an AUC of 82.1%, identified a new cut-off (9150 CK19 mRNA copies) showing 94% sensitivity, 67.3% specificity, 61.2% positive, and 95.3% negative predictive values; (4) OSNA remains the most-important intra-operative tool to identify patients who can benefit from ALND but with the traditional cut-off, many patients undergo needless ALND. The results of the present study suggest a new cut-off helpful to personalize surgical treatment and avoid unnecessary invasive procedures.

Radiotherapy of Breast Cancer—Professional Guideline 1st Central-Eastern European Professional Consensus Statement on Breast Cancer

The international radiotherapy (RT) expert panel has revised and updated the RT guidelines that were accepted in 2020 at the 4th Hungarian Breast Cancer Consensus Conference, based on new scientific evidence. Radiotherapy after breast-conserving surgery (BCS) is indicated in ductal carcinoma in situ (stage 0), as RT decreases the risk of local recurrence (LR) by 50–60%. In early stage (stage I-II) invasive breast cancer RT remains a standard treatment following BCS. However, in elderly (≥70 years) patients with stage I, hormone receptor-positive tumour, hormonal therapy without RT can be considered. Hypofractionated whole breast irradiation (WBI) and for selected cases accelerated partial breast irradiation are validated treatment alternatives to conventional WBI administered for 5 weeks. Following mastectomy, RT significantly decreases the risk of LR and improves overall survival of patients who have 1 to 3 or ≥4 positive axillary lymph nodes. In selected cases of patients with 1 to 2 positive sentinel lymph nodes axillary dissection can be substituted with axillary RT. After neoadjuvant systemic treatment (NST) followed by BCS, WBI is mandatory, while after NST followed by mastectomy, locoregional RT should be given in cases of initial stage III–IV and ypN1 axillary status.

A Nomogram Based on Molecular Biomarkers and Radiomics to Predict Lymph Node Metastasis in Breast Cancer

Background

The aim of this study was to explore the feasibility and efficacy of a non-invasive quantitative imaging evaluation model to assess the lymphatic metastasis of breast cancer based on a radiomics signature constructed using conventional T1-weighted image (T1WI) enhanced MRI and molecular biomarkers.

Methods

Patients with breast cancer diagnosed via lymph biopsies between June 2015 and June 2019 were selected for the study. All patients underwent T1WI contrast-enhancement before treatment; lymph biopsy after surgery; and simultaneous Ki-67, COX-2, PR, Her2 and proliferating cell nuclear antigen detection. All images were imported into ITK-SNAP for whole tumor delineation, and AK software was used for radiomics feature extraction. Next, the radiomics signature Rad-score was constructed after reduction of specific radiomic features. A multiple regression logistic model was built by combining the Rad-score and molecular biomarkers based on the minimum AIC.

Results

In all, 100 patients were enrolled in this study, including 45 with non-lymph node (LN) metastasis and 55 with LN metastasis. A total of 1,051 texture feature parameters were extracted, and LASSO was used to reduce the dimensionality of the radiomics features. The log(λ) was set to 0.002786, and 19 parameters were retained for the construction of the radiomics tag Rad-score. ROC was used to evaluate the diagnostic efficiency of Rad-score: the area under the ROC curve (AUC) of the Rad-score for identifying non-lymphatic and lymphatic metastases was 0.891 in the training cohort and 0.744 in the validation cohort. With the incorporation of tumor molecular markers, the AUCs of the training cohort and validation cohort of the nomogram were 0.936 and 0.793, respectively, which were notably higher than the AUCs of the clinical parameters in the training and validation cohorts (0.719 and 0.588, respectively).

Conclusion

The combined model constructed using the Rad-score and molecular biomarkers can be used as an effective non-invasive method to assess LN metastasis of breast cancer. Furthermore, it can be used to quantitatively evaluate the risk of breast cancer LN metastasis before surgery.

A Predictive Model for Nonsentinel Node Status after Sentinel Lymph Node Biopsy in Sentinel Lymph Node-Positive Chinese Women with Early Breast Cancer

BACKGROUND

Axial lymph node dissection (ALND) is needed in patients with positive sentinel lymph node (SLN). ALND is easy to cause upper limb edema. Therefore, accurate prediction of nonsentinel lymph nodes (non-SLN) which may not need ALND can avoid excessive dissection and reduce complications. We constructed a new prognostic model to predict the non-SLN metastasis of Chinese breast cancer patients.

METHODS

We enrolled 736 patients who underwent sentinel lymph node biopsy (SLNB); 228 (30.98%) were diagnosed with SLNB metastasis which was determined by intraoperative pathological detection and further accepted ALND. We constructed a prediction model by univariate analysis, multivariate analysis, "R" language, and binary logistic regression in the abovementioned 228 patients and verified this prediction model in 60 patients.

RESULTS

Based on univariate analysis using α = 0.05 as the significance level for type I error, we found that age (P=0.045), tumor size (P=0.006), multifocality (P=0.011), lymphovascular invasion (P=0.003), positive SLN number (P=0.009), and negative SLN number (P=0.034) were statistically significant. Age was excluded in multivariate analysis, and we constructed a predictive equation to assess the risk of non-SLN metastasis: Logit(P)=Ln(P/1 - P)=0.267∗a+1.443∗b+1.078∗c+0.471∗d - 0.618∗e - 2.541 (where "a" represents tumor size, "b" represents multifocality, "c" represents lymphovascular invasion, "d" represents the number of metastasis of SLN, and "e" represents the number of SLNs without metastasis). AUCs for the training group and validation group were 0.715 and 0.744, respectively. When setting the risk value below 22.3%, as per the prediction equation's low-risk interval, our model predicted that about 4% of patients could avoid ALND.

CONCLUSIONS

This study established a model which demonstrated good prognostic performance in assessing the risk of non-SLN metastasis in Chinese patients with positive SLNs.

Predictive factors of non-sentinel lymph node disease in breast cancer patients with positive sentinel lymph node

INTRODUCTION

Management of positive sentinel lymph node biopsy (SLNB) in breast cancer remains a matter of debate. Our aim was to evaluate the incidence and identify predictive factors of non-sentinel lymph node metastases.

METHODS

Retrospective review of all cN0 breast cancer patients treated between January 2013 and December 2017, with positive SLNB that were submitted to ALND.

RESULTS

Of the 328 patients included, the majority of tumors were cT1 or cT2, with lymphovascular invasion in 58.4% of cases. The mean isolated nodes in SLNB was 2.7, with a mean of 1.6 positive nodes, 60.7% with extracapsular extension. Regarding ALND, a mean of 13.9 nodes were isolated, with a mean of 2.1 positive nodes. There was no residual disease in the ALND in 50.9% of patients, with 18.9% having ≥4 positive nodes. In the multivariate analysis, lymphovascular invasion, extracapsular extension in SLN, largest SLN metastases size (>10 mm) and ratio of positive SNL (>50%) were independent predictors of non-sentinel lymph node metastases. These four factors were used to build a non-pondered score to predict the probability of a positive ALND after a positive SLNB. The AUC of the model was 0.69 and 81% of patients with score = 0 and 65.6% with score = 1 had no additional disease in ALND.

CONCLUSION

The absence of non-sentinel lymph node metastases in the majority of patients with 1-2 positive SLN with low risk score questions the need of ALND in this population. The identified predictive factors may help select patients in which ALND can be omitted.

Sentinel Lymph Node Positive Rate Predicts Non-Sentinel Lymph Node Metastasis in Breast Cancer

BACKGROUND

To investigate retrospectively an association between the number of metastatic sentinel lymph nodes (SLNs) per total number of SLNs per patient (i.e., the SLN positive rate, or SLN-PR) and non-SLN metastasis in breast cancer.

METHODS

A large population (n = 2250) underwent SLN dissection from January 1, 2014 to January 1, 2020; 627 (27.87%) had at least one positive SLN (SLN⁺). Among these, 283 underwent axillary lymph node (ALN) dissection, and formed the test group. Four external validation groups comprised 43 patients treated in 2019. SLN mappings were examined using methylene blue and indocyanine green. Lymph node ultrasound, SLN-PR, and pathological characteristics were compared between patients with and without non-SLN metastasis. An SLN-PR cutoff value was calculated using receiver operating characteristic (ROC) curves. Associations between clinicopathological variables and SLN-PR with non-SLN metastasis were analyzed by multivariate logistic regression model.

RESULTS

The median age was 47 years (IQR: 42-56 y). The median number of resected SLNs was 4. Patients with positive non-SLNs (126/283, 44.52%) had a median of 2 positive node. SLN-PR > 0.333 was a risk factor for non-SLN positivity (area under the ROC curve, 0.726); and carried significantly higher risk of non-SLN metastasis (P < 0.001). This was validated in the external group.

CONCLUSIONS

SLN-PR > 0.333 was associated with greater risk of non-SLN metastasis. This provides a reference to non-SLN metastasis in patients with SLN metastasis, an indication for ALN dissection and choice of adjuvant treatment.

Clinical relevance of a degree of extracapsular extension in a sentinel lymph node in breast cancer patients: a single-centre study

In some breast cancer (BC) patients, an examination of lymph nodes dissected during sentinel lymph node biopsy (SLNB) demonstrates a presence of metastatic lesions and extracapsular extension (ECE) in a SLN. This study aimed to evaluate clinical relevance of ECE in BC patients. This is a retrospective analysis of 891 patients with cancer metastases to SLN, referred to supplementary axillary lymph node dissection (ALND), hospitalized between Jan 2007 and Dec 2017. Clinical and epidemiological data was evaluated. Long-term treatment outcomes were analysed. In 433 (48.6%) patients, cancer metastases were limited to the SLN (group I), in 61 (6.8%) patients the SLN capsule was exceeded focally (≤ 1 mm—group II). In 397 (44.6%) patients, a more extensive ECE was found (> 1 mm—group III). Metastases to non-sentinel lymph nodes (nSLNs) were diagnosed in 27.0% patients from group I, 44.3% patients from group II and in 49.6% patients from group III. No statistically significant differences were observed in long-term treatment outcomes for compared groups. The presence of ECE is accompanied by a higher stage of metastatic lesions in the lymphatic system. The differences in this respect were statistically significant, when compared to the group of ECE(−) patients. ECE, regardless of its extent, did not impact the long-term treatment results. ECE remains an indication for supplementary ALND and for other equivalent cancer treatment procedures, regardless of ECE size.

Predicting Nonsentinel Lymph Node Metastasis in Breast Cancer: A Multicenter Retrospective Study

BACKGROUND

Sentinel lymph node (SLN) biopsy has been the standard modality for breast cancer patients with clinically node negative disease. In patients who undergo axillary lymph node dissection (ALND) due to SLN metastasis, the harvested nodes (non-SLNs) often contain no metastasis. Here, we evaluated the predictive factors associated with non-SLN metastasis in breast cancer patients.

MATERIALS AND METHODS

This was a retrospective study of patients with operable cT1-3, cN0 invasive breast cancer who underwent SLN biopsy followed by ALND due to SLN metastasis. The clinicopathologic factors and predictive factors of non-SLN metastasis were analyzed. The optimal cutoff for the Ki67 index and the number of positive and negative SLNs that were predictive of non-SLN metastasis were evaluated using receiver operating characteristic curves.

RESULTS

The median number of SLN and non-SLN was 3 and 11, respectively. Of the 150 patients, 52 (35.0%) had metastases in non-SLNs. The optimal cutoffs for the Ki67 index and the number of positive and negative SLNs were of 12%, 2, and 1, respectively. In the univariate analysis, the Ki67 index and the number of positive SLNs≥2 and negative SLNs≤1 were higher in the non-SLN + group than that in the non-SLN - group. The number of negative SLNs was as a predictive factor for non-SLNs metastasis in the multivariate analysis.

CONCLUSIONS

The number of negative SLNs predicts the risk of non-SLN metastasis in breast cancer. When deciding on whether to omit ALND, the number of positive and negative SLNs should be considered.

Are Breast Cancer Nomograms Still Valid to Predict the Need for Axillary Dissection?

BACKGROUND

Nomograms can help in estimating the nodal status among clinically node-negative patients. Yet their validity in external cohorts over time is unknown. If the nodal stage can be estimated preoperatively, the need for axillary dissection can be decided.

OBJECTIVES

The aim of this study was to validate three existing nomograms predicting 4 or more axillary lymph node metastases.

METHOD

The risk for ≥4 lymph node metastases was calculated for n = 529 eligible breast cancer patients using the nomograms of Chagpar et al. [Ann Surg Oncol. 2007;14:670-7], Katz et al. [J Clin Oncol. 2008;26(13):2093-8], and Meretoja et al. [Breast Cancer Res Treat. 2013;138(3):817-27]. Discrimination and calibration were calculated for each nomogram to determine their validity.

RESULTS

In this cohort, the AUC values for the Chagpar, Katz, and Meretoja models were 0.79 (95% CI 0.74-0.83), 0.87 (95% CI 0.83-0.91), and 0.82 (95% CI 0.76-0.86), respectively, showing good discrimination between patients with and without high nodal burdens.

CONCLUSION

This study presents support for the use of older breast cancer nomograms and confirms their current validity in an external population.

Predictive factors of non-sentinel lymph node disease in breast cancer patients with positive sentinel lymph node

INTRODUCTION

Management of positive sentinel lymph node biopsy (SLNB) in breast cancer remains a matter of debate. Our aim was to evaluate the incidence and identify predictive factors of non-sentinel lymph node metastases.

METHODS

Retrospective review of all cN0 breast cancer patients treated between January 2013 and December 2017, with positive SLNB that were submitted to ALND.

RESULTS

Of the 328 patients included, the majority of tumors were cT1 or cT2, with lymphovascular invasion in 58.4% of cases. The mean isolated nodes in SLNB was 2.7, with a mean of 1.6 positive nodes, 60.7% with extracapsular extension. Regarding ALND, a mean of 13.9 nodes were isolated, with a mean of 2.1 positive nodes. There was no residual disease in the ALND in 50.9% of patients, with 18.9% having ≥ four positive nodes. In the multivariate analysis, lymphovascular invasion, extracapsular extension in SLN, largest SLN metastases size (>10 mm) and ratio of positive SNL (> 50%) were independent predictors of non-sentinel lymph node metastases. These four factors were used to build a non-pondered score to predict the probability of a positive ALND after a positive SLNB. The AUC of the model was 0.69 and 81% of patients with score = 0 and 65.6% with score = 1 had no additional disease in ALND.

CONCLUSION

The absence of non-sentinel lymph node metastases in the majority of patients with 1-2 positive SLN with low risk score questions the need of ALND in this population. The identified predictive factors may help select patients in which ALND can be omitted.

Can a machine-learning model improve the prediction of nodal stage after a positive sentinel lymph node biopsy in breast cancer?

Background: The current standard for evaluating axillary nodal burden in clinically node negative breast cancer is sentinel lymph node biopsy (SLNB). However, the accuracy of SLNB to detect nodal stage N2-3 remains debatable. Nomograms can help the decision-making process between axillary treatment options. The aim of this study was to create a new model to predict the nodal stage N2-3 after a positive SLNB using machine learning methods that are rarely seen in nomogram development.Material and methods: Primary breast cancer patients who underwent SLNB and axillary lymph node dissection (ALND) between 2012 and 2017 formed cohorts for nomogram development (training cohort, N = 460) and for nomogram validation (validation cohort, N = 70). A machine learning method known as the gradient boosted trees model (XGBoost) was used to determine the variables associated with nodal stage N2-3 and to create a predictive model. Multivariate logistic regression analysis was used for comparison.Results: The best combination of variables associated with nodal stage N2-3 in XGBoost modeling included tumor size, histological type, multifocality, lymphovascular invasion, percentage of ER positive cells, number of positive sentinel lymph nodes (SLN) and number of positive SLNs multiplied by tumor size. Indicating discrimination, AUC values for the training cohort and the validation cohort were 0.80 (95%CI 0.71-0.89) and 0.80 (95%CI 0.65-0.92) in the XGBoost model and 0.85 (95%CI 0.77-0.93) and 0.75 (95%CI 0.58-0.89) in the logistic regression model, respectively.Conclusions: This machine learning model was able to maintain its discrimination in the validation cohort better than the logistic regression model. This indicates advantages in employing modern artificial intelligence techniques into nomogram development. The nomogram could be used to help identify nodal stage N2-3 in early breast cancer and to select appropriate treatments for patients.

Predicting the risk of sarcopenia in elderly patients with patellar fracture: development and assessment of a new predictive nomogram

Purpose

To develop a risk prediction model for postoperative sarcopenia in elderly patients with patellar fractures in China.

Patients and methods

We conducted a community survey of patients aged ≥55 years who underwent surgery for patellar fractures between January 2013 and October 2018, through telephone interviews, community visits, and outpatient follow-up. We established a predictive model for assessing the risk of sarcopenia after patellar fractures. We developed the prediction model by combining multivariate logistic regression analysis with the least absolute shrinkage model and selection operator regression (lasso analysis) as well as the Support Vector Machine (SVM) algorithm. The predictive quality and clinical utility of the predictive model were determined using C-index, calibration plots, and decision curve analysis. We also conducted internal sampling methods for qualitative assessment.

Result

We recruited 137 participants (53 male; mean age, 65.7 years). Various risk factors were assessed, and low body mass index and advanced age were identified as the most important risk factor (P < 0.05). The prediction rate of the model was good (C-index: 0.88; 95% CI [0.80552–0.95448]), with a satisfactory correction effect. The C index is 0.97 in the validation queue and 0.894 in the entire cohort. Decision curve analysis suggested good clinical practicability.

Conclusion

Our prediction model shows promise as a cost-effective tool for predicting the risk of postoperative sarcopenia in elderly patients based on the following: advanced age, low body mass index, diabetes, less outdoor exercise, no postoperative rehabilitation, different surgical methods, diabetes, open fracture, and removal of internal fixation.

Nomogram-based estimate of axillary nodal involvement in ACOSOG Z0011 (Alliance): validation and association with radiation protocol variations

PURPOSE

A substantial proportion of patients enrolled on ACOSOG Z0011 received protocol-deviant radiation treatment. It is currently unknown whether these deviations involved the use of more extensive fields in patients at higher nomogram-predicted risk.

METHODS

We used the M.D. Anderson (MDA) and Memorial Sloan-Kettering (MSK) nomograms to estimate risk of additional positive axillary nodes using surgical pathology information. In the control arm, we compared axillary dissection (AD) findings to nomogram-predicted estimates for validation. We used logistic regression to evaluate whether nomogram-estimated higher risk of nodal involvement was associated with high tangent (HT) or supraclavicular (SCV) radiation fields for patients with known radiation field design.

RESULTS

552/856 (64.5%) had complete details for the MDA nomogram. Mean MDA risk estimate in both treatment arms was 23.8%. Estimated risk for patients on the AD arm with positive nodes was 25.9%. Higher risk estimate was associated with additional positive nodes in the AD arm (OR 1.04, 95% CI 1.02-1.06, p < 0.0001). We observed significant association with higher MDA nomogram-estimated risk and SCV radiation (OR 1.07, 95% CI 1.04-1.10, p < 0.0001) but not HT (OR 0.99, 95% CI 0.96-1.02, p = 0.52) The MSK nomogram had similar associations.

CONCLUSION

MDA and MSK nomogram risk estimates were associated with lymph node risk in ACOSOG Z0011. Radiation oncologists' use of differing radiation fields were associated with treating higher risk patients. ClinicalTrials.gov id: NCT00003854.

Intraoperative Prediction Of Non-Sentinel Lymph Node Metastasis Based On The Molecular Assay In Breast Cancer Patients

Purpose

The aim of the study is to construct an intraoperative nomogram for the prediction of non-sentinel lymph node (NSLN) metastasis based on the one-step nucleic acid amplification assay in breast cancer patients.

Methods

A total of 552 patients were enrolled in the training study and 1090 patients were enrolled in the validation study. The nomogram was constructed based on the molecular assay with logistic multivariate regression analysis in the training study and was validated in the validation study.

Results

A novel nomogram model was constructed with the total tumor load, the clinical primary tumor size, the number of positive and negative sentinel lymph nodes. The area under the receiver operating characteristic curve (AUC) of the model was 0.842. The AUC of the model which was sensitive to discern the patients with the stage of pN1 and ≥pN2 was 0.861.

Conclusion

The nomogram model will help to guide the axillary management intraoperatively and precisely confirm the target region of radiotherapy postoperatively.

Predicting non-sentinel lymph node metastasis in Australian breast cancer patients: are the nomograms still useful in the post-Z0011 era?

BACKGROUND

Axillary lymph node dissection (ALND) can be avoided in breast cancer patients with low-volume disease in the sentinel lymph nodes (SLNs) according to Z0011 trial. We believe that nomograms developed for predicting non-sentinel lymph node (NSLN) metastases can guide the axillary treatment in patients who do not fully match the criteria of Z0011 study. We identified risk factors and evaluated the performance of three nomograms to predict NSLN status in patients with positive SLNs.

METHODS

Data from 526 breast cancer patients with positive SLNs who underwent ALND at two Australian hospitals from 2002 to 2015 were studied. Univariate and multivariate associations for NSLN metastasis were analysed. Predictive models evaluated were MD Anderson Cancer Centre (MDA), Helsinki University Hospital and Memorial Sloan Kettering Cancer Centre.

RESULTS

Thirty-nine per cent of patients demonstrated NSLN metastasis. The multivariate analysis identified extranodal extension (OR 3.2, 95% CI 2.07-4.80), tumour size >2 cm (OR 2.5, 95% CI 1.66-3.89), macrometastasis (OR 1.9, 95% CI 1.09-3.47), positive SLN ratio >0.5 (OR 1.7, 95% CI 1.16-2.60) and lymphovascular invasion (OR 1.6, 95% CI 1.09-2.44) as independent predictors for NSLN metastasis. MDA nomogram showed the best discrimination (area under the curve of 0.74) and a 9% false negative rate for predicted probability of NSLN metastasis ≤10%.

CONCLUSION

Our results suggest that presence of extranodal extension and tumour size >2 cm may influence the need of further axillary treatment. Conversely, ALND can be safety spared in low risk patients identified by MDA nomogram.

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.

Predictors of nonsentinel lymph node metastasis in patients with breast cancer with metastasis in the sentinel node

To predict the factors related to axillary nonsentinel lymph node (NSLN) metastasis in patients with positive sentinel lymph node (SLN) of early breast cancer.The retrospective data are collected from the patients with positive SLN who received further completion axillary lymph node dissection (cALND) in Peking Union Medical Hospital between March 2016 and December 2017. Univariate analysis was conducted on data with various clinicopathologic factors at first. Those factors with statistic significance (P < .05) in univariate analysis were then used to implement multivariate analysis and logistic regression.There were total of 734 patients who received SLN biopsy , among whom 153 cases were included in our study. About 39.22% (60/153) of 153 paitents with positive SLN had no NSLN metastasisted to SLN. Univariate analysis showed that 3 variables were significantly correlated with NSLN involvement: tumor size (X = 10.384, P = .001), SLN metastasis ratio (number of positive SLNs/number of SLNs removed × 100%) (X = 10.365, P = .001) and the number of negative sentinel nodes (X = 10.384, P = .006). In multivariate analysis and logistic regression, tumor size (odds ratio [OR] = 3.392, 95% confidence interval [CI]: 1.409-8.166, P = .006) and SLN metastasis ratio (OR = 3.514, 95% CI: 1.416-8.72, P = .007) were the independent risk factors. While the number of negative sentinel nodes (OR = 0.211, 95% CI: 0.063-0.709, P = .014) was the independent protective factor. The calculated risk resulted in an area under the curve of 0.746 (95% CI: 0.644-0.848), suggesting stable discriminative capability in Chinese population.For those patients with positive SLN, larger tumor burden and SLN metastasis ratio are independent risk factors for NSLN metastasis. However, the more of the detected negative SLN, the less possibility with NSLN involvement.

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.

Preoperative prediction of sentinel lymph node metastasis in breast cancer based on radiomics of T2-weighted fat-suppression and diffusion-weighted MRI

OBJECTIVES

To predict sentinel lymph node (SLN) metastasis in breast cancer patients using radiomics based on T₂-weighted fat suppression (T₂-FS) and diffusion-weighted MRI (DWI).

METHODS

We enrolled 146 patients with histologically proven breast cancer. All underwent pretreatment T₂-FS and DWI MRI scan. In all, 10,962 texture and four non-texture features were extracted for each patient. The 0.623 + bootstrap method and the area under the curve (AUC) were used to select the features. We constructed ten logistic regression models (orders of 1-10) based on different combination of image features using stepwise forward method.

RESULTS

For T₂-FS, model 10 with ten features yielded the highest AUC of 0.847 in the training set and 0.770 in the validation set. For DWI, model 8 with eight features reached the highest AUC of 0.847 in the training set and 0.787 in the validation set. For joint T₂-FS and DWI, model 10 with ten features yielded an AUC of 0.863 in the training set and 0.805 in the validation set.

CONCLUSIONS

Full utilisation of breast cancer-specific textural features extracted from anatomical and functional MRI images improves the performance of radiomics in predicting SLN metastasis, providing a non-invasive approach in clinical practice.

KEY POINTS

• SLN biopsy to access breast cancer metastasis has multiple complications. • Radiomics uses features extracted from medical images to characterise intratumour heterogeneity. • We combined T ₂ -FS and DWI textural features to predict SLN metastasis non-invasively.

Is extracapsular nodal extension in sentinel nodes a predictor for nonsentinel metastasis and is there an impact on survival parameters?-A retrospective single center cohort study with 324 patients

The Z0011 trial has fundamentally changed axillary management in breast cancer patients. However, some important questions remain, like the role of extracapsular nodal extension (ENE) in positive sentinel nodes and the need for further axillary treatment. In this retrospective cohort study, we reviewed and analyzed data from 342 clinically node negative (cN0) breast cancer patients with a positive sentinel node and subsequent axillary lymph node dissection (ALND) from the BRENDA data base. The 104 (30.4%) ENE positive patients had a significantly higher proportion of ≥3 positive axillary lymph nodes (65.0%) compared to ENE negative patients with a positive sentinel node (21.4%). Likewise, ENE positive patients had significantly more often lymph node metastasis size >2 mm (96.2%) than ENE negative patients (72.7%). T1 status was observed significantly more often in ENE negative patients (53.2%) than in ENE positive patients (24.0%). While ENE was linked to worse overall survival in univariate analysis, this effect disappeared when adjusting for nodal status, age, and comorbidities in multivariate analysis. ENE of the sentinel node is an important predictor for nonsentinel lymph node involvement. We suggest that ENE influences survival only via a higher number of positive nodes - one of the most predictive parameters for survival outcome in breast cancer.

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.

Nomograms for preoperative prediction of axillary nodal status in breast cancer

Background

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

Methods

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

Results

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

Conclusion

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

Defines need for staging?

Multicenter prospective evaluation of the reliability of the combined use of two models to predict non-sentinel lymph node status in breast cancer patients with metastatic sentinel lymph nodes: the MSKCC nomogram and the Tenon score. Results of the NOTEGS study

Background:

The purpose of this study was to prospectively evaluate the combined use of The Memorial Sloan Kettering Cancer Center nomogram and Tenon score to select, in patients with metastatic sentinel lymph node (SN), those at low risk of metastatic non-SN for whom additional axillary lymph node dissection (ALND) could be avoided.

Methods:

From January 2011 to July 2012, a prospective non-interventional nationwide study was conducted (NCT01509963). We sought to identify the false reassurance rate (FRR, a negative test result is false) in patients with both a ⩽10% probability of metastatic non-SN with the MSKCC nomogram and a Tenon score ⩽3.5 (low risk): the proportion of patients with metastatic non-SN at additional ALND. Our hypothesis was that these patients would have a FRR⩽5%.

Results:

Data on 2822 patients with breast cancer from 53 institutions were prospectively recorded. At least one SN was metastatic (isolated tumour cells, micro- or macrometastases) in 696 patients (24.7%). Among patients with ALND and complete data to calculate combined risk (n=504), 67 and 437 patients had low and high combined risk, respectively. Patients at low risk had less ALND (47%) compared to patients at high risk (P<0.001). This study did not meet its primary objective because the FRR in patients with low risk was 16.4% (11 out of 67) (95% confidence interval (CI): 9.7–23.1%). In the high-risk group, 33.9% (148 out of 437) (95% CI: 29.6–38.4%) had non-SN metastases (P=0.004).

Conclusions:

In this controlled prospective study, metastatic SN patients with both a ⩽10% probability of metastatic non-SN with the MSKCC nomogram and a Tenon score ⩽3.5 failed to identify patients at low risk of metastatic non-SN when completion ALND was not systematic.

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.

A cut-off of 2150 cytokeratin 19 mRNA copy number in sentinel lymph node may be a powerful predictor of non-sentinel lymph node status in breast cancer patients

Since 2007, one-step nucleic acid amplification (OSNA) has been used as a diagnostic system for sentinel lymph node (SLN) examination in patients with breast cancer. This study aimed to define a new clinical cut-off of CK19 mRNA copy number based on the calculation of the risk that an axillary lymph node dissection (ALND) will be positive. We analyzed 1529 SLNs from 1140 patients with the OSNA assay and 318 patients with positive SLNs for micrometastasis (250 copies) and macrometastasis (5000 copies) underwent ALND. Axillary non–SLNs were routinely examined. ROC curves and Youden’s index were performed in order to identify a new cut-off value. Logistic regression models were performed in order to compare OSNA categorical variables created on the basis of our and traditional cut-off to better identify patients who really need an axillary dissection. 69% and 31% of OSNA positive patients had a negative and positive ALND, respectively. ROC analysis identified a cut-off of 2150 CK19 mRNA copies with 95% sensitivity and 51% specificity. Positive and negative predictive values of this new cut-off were 47% and 96%, respectively. Logistic regression models indicated that the cut-off of 2150 copies better discriminates patients with node negative or positive in comparison with the conventional OSNA cut-off (p<0.0001). This cut-off identifies false positive and false negative cases and true-positive and true negative cases very efficiently, and therefore better identifies which patients really need an ALND and which patients can avoid one. This is why we suggest that the negative cut-off should be raised from 250 to 2150. Furthermore, we propose that for patients with a copy number that ranges between 2150 and 5000, there should be a multidisciplinary discussion concerning the clinical and bio-morphological features of primary breast cancer before any decision is taken on whether to perform an ALND or not.

The appropriate axillary procedure after a positive sentinel node in breast cancer patients: the "Hôpital Tenon" score revisited. A two-institution study

INTRODUCTION

Until recently, completion ALND has been considered the standard of care after a positive SN in breast cancer patients. However, most patients will not display further axillary involvement. The Tenon score is a simple nomogram that can be used intraoperatively to avoid completion ALND in low-risk patients. We aimed at validating the Tenon score on a SN-positive patient sample that had been preoperatively selected using axillary US examination.

PATIENTS AND METHOD

We used a retrospective analysis of our bicentric database that included 246 breast cancer patients with a positive SN. We calculated sensitivity, specificity, as well as positive and negative predictive values for each cut-off point. ROCs were constructed and corresponding AUC values were calculated as a measure of discriminative capacity.

RESULTS

At least one non-SN was positive in 52 patients (21.1 %). 118 patients (48 %) had a score up to 5. Among them, three had at least one positive non-SN. NPV was 97.5 %. Using that threshold, the ROCs analysis showed an AUC of 0.822 (95 % CI 0.764-0.880).

CONCLUSION

Use of preoperative axillary US examination led to a modification of the proposed Tenon cut-off value from 3.5 to 5 to attain good predictive power for non-SN status. Straightforward intraoperative use of the Tenon score may be considered an advantage over other available nomograms.

Validation of Six Nomograms for Predicting Non-sentinel Lymph Node Metastases in a Dutch Breast Cancer Population

Background

The usefulness of axillary lymph node dissection (ALND) in patients with positive sentinel nodes (SN) is still an ongoing debate. Several nomograms have been developed for predicting non-sentinel lymph node metastases (NSLNM). We validated six nomograms using data from 10 years of breast cancer surgery in our hospital.

Methods

We retrospectively analyzed all patients with a proven breast malignancy and a SN procedure between 2001 and 2011 in our hospital.

Results

Data from 1084 patients were reviewed; 260 (24 %) had a positive SN. No patients with isolated tumor cells, 6 patients (8 %) with micrometastases, and 65 patients (41 %) with macrometastases had additional axillary NSLNM. In 2 patients (3 %) with micrometastases, the ALND influenced postoperative treatment. In the group of patients with macrometastases tumor size >2 cm, extranodal growth and having no negative SNs were predictors of NSLNM. The revised MD Anderson Cancer Center and Helsinki nomograms performed the best, with an area under the curve value of 0.78.

Conclusions

ALND could probably be safely omitted in most patients with micrometastases but is still indicated in patients with macrometastases, especially in patients with tumor size >2 cm, extranodal growth, and no negative SNs. The revised MD Anderson Cancer Center and Helsinki nomograms were the most predictive in our patient group.

A head to head comparison of nine tools predicting non-sentinel lymph node status in sentinel node positive breast cancer women

BACKGROUND AND OBJECTIVES

This study was conducted to evaluate the performance of available tools predicting non-sentinel lymph node (non-SLN) status in women with SLN positive breast cancer and to see if they can be safely used in everyday clinical practice.

METHODS

Data of 220 women with breast cancer who underwent a SLN biopsy at the Máxima Medical Centre between 2000-2008 were analysed. Tools evaluated were: the models from Memorial Sloan Kettering Cancer Centre, Stanford, Mayo, Cambridge, Gur, and MOU, and the scores from Saidi, Tenon, and MDA. Model performance was assessed using calibration, discrimination and Nagelkerke's explained variation.

RESULTS

The MSKCC nomogram showed best overall performance with best discrimination (AUC 0.69), second best calibration, and highest explained variation (31%). The 10% low risk threshold led to defining only 22% (38/176) of the women as being low risk while in fact 66% (116/176) were non-SLN negative. The false negative rate was 13% (5/38).

CONCLUSIONS

Current models for predicting non-SLN metastases in SLN positive breast cancer are not yet ready for implementation in general practice. Further research efforts should improve model performance in selecting patients or perhaps find a role in support in the paradigm shift to a "treat none unless" approach.

Axillary nodal metastases in Italian early breast cancer patients with positive sentinel lymph node: can axillary node dissection be avoided by using predictive nomograms?

AIMS AND BACKGROUND

Clinical guidelines recommend axillary lymph node dissection (ALND) in cases of metastatic sentinel lymph node (SNL) in patients with clinically node-negative early breast cancer. However, a relevant number of ALND could be avoided in a subset of patients in whom the risk of non-SNL metastases is low. In order to define this population, several authors have proposed mathematical models, which have been validated in many studies. These studies reached different conclusions regarding which model demonstrated the best statistical discrimination power, mainly due to differences in clinical and pathologic variables used, and particularly differences in the number of dissected SLNs.

METHODS

We retrospectively reviewed clinically node-negative patients who underwent ALND in our surgical ward after the diagnosis of breast cancer metastases on SLN biopsy from January 2000 to December 2012. The predictive accuracy of the widely used nomograms to predict the risk of additional nodal disease in our patients with SLN breast cancer metastases was measured by receiver operating characteristic curve. We then attempted to develop a new nomogram by analyzing the dataset.

RESULTS

A total of 105 patients were included in this study, with ratio of metastatic lymph node/removed lymph node of about 0.89; we found axillary nodal metastases on ALND in only 31 patients (29.5%). Applied to our dataset, Mayo nomogram showed the best area under the receiving operator characteristic curve (0.74) followed by our model (0.71). Instead, the Memorial Sloan-Kettering model showed poor discrimination, as did Tenon (0.56).

CONCLUSIONS

Based on our data, we cannot recommend the clinical use of validated predictive nomograms in order to avoid ALND. We suggest setting up a multicenter Italian study to build a model specific to our setting and based on larger series.

Predictive Factors for Non-Sentinel Lymph Node Metastasis in Patients With Clinically Node-Negative Ipsilateral Multiple Breast Cancer Treated With Total Mastectomy

BACKGROUND

Recent clinical trials have shown that axillary lymph node dissection can be omitted even with positive sentinel nodes (SN) unless the patient undergoes total mastectomy without irradiation. The aim of our study was to identify predictive factors for non-SN metastasis among patients with solitary or multiple breast cancer treated with total mastectomy.

PATIENTS AND METHODS

Clinically node-negative breast cancer patients with pathologically node-positive disease treated with total mastectomy and axillary dissection after SN biopsy were retrospectively analyzed. Significant pathologic predictive factors for positive non-SN metastasis were also examined.

RESULTS

There were 47 multiple and 143 solitary breast cancer patients. Pathologic diagnosis demonstrated that smaller invasion size but larger tumor size, including adjacent noninvasive cancer, was observed in multiple breast cancer. The number of involved SNs and the rate of non-SN metastasis were similar between the multiple and solitary groups. Regarding predictive factors for non-SN metastasis, lymphatic invasion and SN macrometastasis were significant factors in the solitary group, and pathologic invasion size > 2 cm was the only significant factor in the multiple group.

CONCLUSION

Larger pathologic invasion size was important for predicting non-SN metastasis in multiple breast cancer.

Prediction of macrometastasis in axillary lymph nodes of patients with invasive breast cancer and the utility of the SUV lymph node/tumor ratio using FDG-PET/CT

Background

Axillary lymph node dissection (ALND) is important for improving the prognosis of patients with node-positive breast cancer. However, ALND can be avoided in select micrometastatic cases, preventing complications such as lymphedema or paresthesia of the upper limb. To appropriately omit ALND from treatment, evaluation of the axillary tumor burden is critical. The present study evaluated a method for preoperative quantification of axillary lymph node metastasis using positron emission tomography/computed tomography (PET/CT).

Methods

The records of breast cancer patients who received radical surgery at the Gifu University Hospital (Gifu, Japan) between 2009 and 2014 were reviewed. The axillary lymph nodes were preoperatively evaluated by PET/CT. Lymph nodes were dissected by sentinel lymph node biopsy (SLNB) or ALND and were histologically diagnosed by experienced pathologists. The maximum standardized uptake value (SUVmax) was measured in both the axillary lymph node (SUV-LN) and primary tumor (SUV-T). The SUV-LN/T ratio (NT ratio) was calculated by dividing the SUV-LN by the SUV-T, and the efficacies of the NT ratio and SUV-LN were compared using receiver operating characteristic (ROC) curve analysis. The diagnostic performance was also compared between the techniques with the McNemar test.

Results

A total of 171 operable invasive breast cancer patients were enrolled, comprising 69 node-positive patients (macrometastasis (Mac): n = 55; micrometastasis (Mic): n = 14) and 102 node-negative patients (Neg). The NT ratio for node-positive patients was significantly higher than in node-negative patients (0.5 vs. 0.316, respectively, P = 0.041). The NT ratio for Mac patients (0.571) was significantly higher than in Mic (0.227) and Neg (0.316) patients (P <0.01 and P = 0.021, respectively). The areas under the curves (AUCs) by ROC analysis for the NT ratio and SUV-LN were 0.647 and 0.811, respectively (P <0.01). In patients with an SUV-T ≥2.5, the modified AUCs for the NT ratio and SUV-LV were 0.757 and 0.797 (not significant).

Conclusion

The NT ratio and SUV-LN are significantly higher in patients with axillary macrometastasis than in those with micrometastasis or no metastasis. The NT ratio and SUV-LN can help quantify axillary lymph node metastasis and may assist in macrometastasis identification, particularly in patients with an SUV-T ≥2.5.

Electronic supplementary material

The online version of this article (doi:10.1186/s12957-014-0424-2) contains supplementary material, which is available to authorized users.

p53 expression in breast cancer predicts tumors with low probability of non-sentinel nodes infiltration

AIM

Several predictive tools of non-sentinel lymph nodes neoplastic involvement when a positive sentinel lymph node is found have been described. However, molecular factors have been rarely evaluated to build these tools. The aim of this study was to establish which factors predicted non-sentinel lymph nodes infiltration in our setting, including some molecular factors.

MATERIAL AND METHODS

We carried out a retrospective review of 161 patients with breast cancer and a positive sentinel lymph node who had undergone axillary lymph node dissection, none of whom had received neoadjuvant treatment. Features evaluated as predictive factors for non-sentinel node positivity were: menopausal status, tumor size, histological subtype, histological grade, lymphovascular invasion, extracapsular invasion, Ki67 index, hormonal receptors, CerbB2 and p53 expression, size of sentinel lymph node metastases and number of sentinel lymph nodes affected.

RESULTS

Tumor size (P = 0.001), size of sentinel lymph node metastases (P = 0.001), lobular invasive carcinoma (P = 0.05) and lymphovascular invasion (P = 0.006) were significantly associated with non-sentinel lymph node positivity. Tumor p53 positive expression was strongly associated with non-sentinel lymph node negativity (P = 0.000). In multivariate analysis, all these factors but tumor size maintained their significance. The discrimination power of the model calculated by the area under the receiver-operator curve was 0.811 (95% confidence interval, 0.741-0.880).

CONCLUSION

p53 expression in breast cancer was highly predictive of non-sentinel lymph node negativity in our study. New studies should evaluate if it would be useful to add p53 expression to other existing predictive tools.

T-stage and positive sentinel nodes ratio are the useful factors to predict non-sentinel node metastasis in breast cancer patients with macro-metastasis in the sentinel node

INTRODUCTION

Current guidelines recommend completion axillary lymph node dissection (cALND) in case of a sentinel lymph node (SN) metastasis larger than 2 mm (macrometastasis). However in many patients of those, the non-sentinel lymph nodes (NSN) contain no further metastasis, indicating that axillary lymph node dissection provides no benefit. To identify cases who could have undergone omission of the ALND with confidence, we have retrospectively evaluated the predictive factors of NSN metastasis with positive macrometastasis in the SN.

METHODS

This study was based on a retrospective database of 420 patients who underwent sentinel lymph node biopsy (SNB) for breast cancer, of whom 61 patients had SN macrometastasis intra- and postoperatively. We examined predictive factors of NSN involvement in 51 cases of these 61 patients who underwent cALND. All clinical and histological variables were analyzed according to NSN status, by using Mann-Whitney U test, univariate and multivariate logistic regression model.

RESULTS

T stage and the proportion of involved SNs among all identified SNs (SN ratio) were correlated with NSN metastasis. Univariate and multivariate analysis showed that T stage and SN ratio were the independent predictive factor of NSN metastasis. The area under ROC curve for SN ratio was 0.71. The best cut off value of SN ratio was 0.667. Negative predictive value to NSN metastasis in cases with both T2 and more than 0.667 of SN ratio was 85.7%.

CONCLUSION

In patients with invasive breast cancer and macrometastasis of SN, T stage and SN ratio were useful for prediction of NSN metastasis.

Clinical usefulness of one-step nucleic acid amplification assay in the new era of sentinel lymph node biopsy for breast cancer

SUMMARY 

According to the results of the ACOSOG Z0011 trial and IBCSG trial 23-01, rapid intraoperative examinations of the sentinel lymph nodes (SLN) are needed in only a limited number of breast cancer patients, including those with more than three sentinel nodes or who undergo mastectomy. In this new era of SLN biopsies, one-step nucleic acid amplification assay is a promising method for accurately assessing metastasis in the whole SLN, and which help to accurately select patients requiring axillary dissection and reliably evaluate the risk of recurrence. One-step nucleic acid amplification assay may therefore be an alternative to conventional pathology in detecting metastasis in the SLNs, when used for both intraoperative and postoperative examinations.

Radiation dose to the nodal regions during prone versus supine breast irradiation

Background

Prone positioning for breast radiotherapy is preferable when the aim is a reduction of the dose to the ipsilateral lung or the heart in certain left-sided cases.

Materials and methods

In 100 breast cancer cases awaiting postoperative whole-breast radiotherapy, conformal radiotherapy plans were prospectively generated in both prone and supine positions. The axillary nodal region (levels I–III) and internal mammary (IM) lymph-node region in the upper three intercostal spaces were retrospectively contoured. The mean doses to the nodal regions and the volume receiving 25 Gy (V_25Gy), V_45Gy, and V_47.5Gy were compared between the two treatment positions.

Results

In most cases, the doses to axillary levels I–III and the IM lymph nodes were inadequate, regardless of the treatment position. The nodal doses were significantly lower in the prone than in the supine position. The radiation doses to levels II–III and IM nodes were especially low. The V_45Gy and V_47.5Gy of the level I axillary lymph nodes were 54.6% and 40.2%, respectively, in the supine, and 3.0% and 1.7%, respectively, in the prone position. In the supine position, only 17 patients (17%) received a mean dose of 45 Gy to the axillary level I nodes.

Conclusion

The radiation dose to the axillary and IM lymph nodes during breast radiotherapy is therapeutically insufficient in most cases, and is significantly lower in the prone position than in the supine position.

Detailed evaluation of one step nucleic acid (OSNA) molecular assay for intra-operative diagnosis of sentinel lymph node metastasis and prediction of non-sentinel nodal involvement: experience from a London teaching hospital

One step nucleic acid (OSNA) is a molecular diagnostic assay for intra-operative detection of sentinel node metastases. This study compared OSNA with standard histopathology in 283 nodes from 170 patients to evaluate sensitivity, specificity and concordance of the two methods. Additional analysis was done to investigate how cytokeratin 19 mRNA copy number affects prediction of non-sentinel node positivity. OSNA sensitivity was 93.2% and specificity 95.8%. Concordance between OSNA and histology was 95.6%. In the patients who had axillary clearance, the OSNA mRNA copy number on the sentinel node had 100% negative predictive value for histologically proven metastasis. mRNA copy numbers <1400 were not associated with histologically proven metastasis in subsequent nodes at axillary clearance. OSNA is a reliable method for the intra-operative evaluation of axillary lymph node metastasis even when half of the lymph node is used. Identification of mRNA copy number threshold predicting the positivity of non-sentinel axillary nodes seems to be feasible and would be clinically important.

Sentinel lymph node biopsy in breast cancer: predictors of axillary and non-sentinel lymph node involvement

BACKGROUND

Sentinel lymph node biopsy is a standard method for the evaluation of axillary status in patients with T1-2N0M0 breast cancers.

AIMS

To determine the prognostic significance of primary tumour-related clinico-histopathological factors on axillary and non-sentinel lymph node involvement of patients who underwent sentinel lymph node biopsy.

STUDY DESIGN

Retrospective clinical study.

METHODS

In the present study, 157 sentinel lymph node biopsies were performed in 151 consecutive patients with early stage breast cancer between June 2008 and December 2011.

RESULTS

Successful lymphatic mapping was obtained in 157 of 158 procedures (99.4%). The incidence of larger tumour size (2.543±1.21 vs. 1.974±1.04), lymphatic vessel invasion (70.6% vs. 29.4%), blood vessel invasion (84.2% vs. 15.8%), and invasive lobular carcinoma subtype (72.7% vs. 27.3%) were statistically significantly higher in patients with positive SLNs. Logistic stepwise regression analysis disclosed tumour size (odds ratio: 1.51, p=0.0021) and lymphatic vessel invasion (odds ratio: 4.68, p=0.001) as significant primary tumour-related prognostic determinants of SLN metastasis.

CONCLUSION

A close relationship was identified between tumour size and lymphatic vessel invasion of the primary tumour and axillary lymph node involvement. However, the positive predictive value of these two independent variables is low and there is no compelling evidence to recommend their use in routine clinical practice.