Number Of Positive Sentinel Lymph Node Research Articles

Risk Factors for Non-sentinel Lymph Node Metastasis in HR+/HER2- Breast Cancer With cN0.

This study aimed to identify the risk factors associated with non-sentinel lymph node (non-SLN) metastasis in case of hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer with cN0 on preoperative exam, where the sentinel lymph node (SLN) is positive. We conducted a retrospective review of medical records from the Chonnam National University Hwasun Hospital, spanning from January 2013 to January 2020, focusing on patients with HR+, HER2- breast cancer. Specifically, we collected the clinical and pathological data for those patients who underwent axillary lymph node dissection (ALND) due to positive SLN. Among the 166 patients who underwent ALND after positive SLNs, median patient age was 52 years. Univariate analyses demonstrated a significant association between non-SLN metastasis and the number of positive SLNs (p=0.039), SLN positive ratio (p<0.001), and primary tumor size (p=0.018). Multivariate analysis revealed that an SLN ratio >0.55 (p=0.004, HR=3.007, 95% CI=1.427-6.335) was independently associated with non-SLN metastasis. However, neither the number of positive SLN nor primary tumor size showed associations with non-SLN metastases. In patients with HR+, HER2- breast cancer who are cN0, completion of ALND should be considered when the positive SLN ratio is ≥0.55. This approach aims to provide the opportunity for survival benefit through additional adjuvant therapy or to contribute to de-escalation of unnecessary surgery.

Abstract PO3-02-08: Risk factors and a new predictive nomogram for predicting the Non-sentinel Lymph Node Metastasis in 708 early-stage Breast Cancer Patients with Positive Sentinel Nodes in China

Abstract Objective: The management of positive sentinel lymph node biopsies (SLNB) in patients with early-stage breast cancer remains a matter of controversy. Some studies have shown that not all breast cancer patients with positive sentinel lymph nodes (SLNs) benefit from further axillary lymph node dissection (ALND). Our study aims to analyse the risk factors and construct a new nomogram to predict non-sentinel lymph node (NSLN) metastasis in Chinese early-stage breast cancer patients with positive sentinel lymph nodes. Methods: The clinical data of 708 patients with early-stage breast cancer who attended The Fourth Hospital of Hebei Medical University for surgical treatment from January 2016 to December 2021 was retrospectively analyzed. All of them were female breast cancer patients with positive sentinel lymph nodes and underwent ALND. The patients were divided into modeling group and validation group according to the time of treatment. The patients in the modeling group were divided into a positive NSLN group and a negative NSLN group. The characteristics: age, maximum tumor diameter, the number of positive SLNs, proportion of positive SLNs, vessel carcinoma embolus, nerve invasion, status of ER, PR, HER-2 and Ki-67 were included in the analysis. And the independent risk factors of NSLN metastasis were screened by univariate (chi-square test) and multivariate (logistic regression) analysis. A nomogram model was established according to the screened independent risk factors, and the model was externally validated by the validation group. The ROC curve was plotted to calculate the area under the curve (AUC) and evaluate the predictive power of the nomogram model. A calibration curve and decision curve analysis (DCA) were used to evaluate the performance of the model. Results: Among the 708 patients, (modeling group n=410, validation group n=298), the average age, average number of positive SLNs, and NSLN positive rate were 50.9±11.1, 1.55±0.87 and 25.71%. The univariate analysis revealed statistically significant differences in the number of positive SLNs (P&amp;lt; 0.001), the proportion of positive SLNs (P &amp;lt; 0.001), vessel carcinoma embolus (P=0.001), nerve invasion (P=0.012), and ER status (P=0.029) in the NSLN-positive group compared with the negative group. The multifactorial logistic regression analysis revealed that the number of positive SLN (P=0.002; OR: 1.700; 95% CI: 1.219-2.370), the proportion of positive SLN (P=0.048; OR: 3.214; 95% CI: 1.001-10.490), vessel carcinoma embolus (P=0.010; OR: 2.076; 95% CI: 1.194-3.612), nerve invasion (P=0.024; OR: 2.119; 95% CI: 1.221-3.678), and ER status (P=0.045; OR: 2.978; 95% CI: 1.022-8.675) were independent risk factors for NSLN positivity. Furthermore, the nomogram was built using these 5 factors and validated on 298 patients in the validation group. The AUC was 0.728 (P&amp;lt; 0.001; 95%CI: 0.673-0.784) in the modeling group and 0.810 (P&amp;lt;0.001; 95%CI: 0.735-0.886) in the validation group. The calibration curves of the modeling and validation groups were close to the ideal curve, and DCA also showed that the model could be applied in clinical practice. Conclusion: For early-stage breast cancer with positive SLNs, these factors as the positive number of SLNs &amp;gt; 2, the ratio of positive SLNs &amp;gt; 50%, vessel carcinoma embolus, nerve invasion and ER-positive could predict NSLN metastasis well. The proposed nomogram appears to accurately estimate the likelihood of positive NSLNs and may greatly help the surgeon to decide intraoperatively whether to perform further ALND and avoid non-essential ALND as well as postoperative complications. Citation Format: Zhenchuan Song, Xueyi Zhao, Liu Yang. Risk factors and a new predictive nomogram for predicting the Non-sentinel Lymph Node Metastasis in 708 early-stage Breast Cancer Patients with Positive Sentinel Nodes in China [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-02-08.

Association between postoperative pathological results and non-sentinel nodal metastasis in breast cancer patients with sentinel lymph node-positive breast cancer

ObjectiveFor 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.MethodsThis 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.ResultsAmong 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.ConclusionIn 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.

Prognostic value of the number of biopsied sentinel lymph nodes for Chinese patients with melanoma: A single-center retrospective study.

Sentinel lymph node biopsy (SLNB) helps to determine accurate pathological stages and facilitates strategies for regional disease control in melanoma. However, whether the number of biopsied sentinel lymph nodes (SLNs) influences the patients' survival is rarely investigated. Acral or cutaneous melanoma patients with no history of nodal disease who received SLNB in Fudan University Shanghai Cancer Center (FUSCC) from January 1, 2017, to December 31, 2021 were retrospectively enrolled. Clinicopathological variables including Breslow index, ulceration, number of positive SLNs, SLN/non-SLN status were analyzed. The pathologic nodal (pN) stage and pathological stage were defined. A total of 381 eligible patients were enrolled in this study, of whom 132 (34.7%) patients were diagnosed with SLN-positive. The median number of biopsied SLNs was 2 (range: 1 to 20). Different numbers of biopsied SLNs did not influence the release-free survival (RFS) of the general patients. However, patients with >2 SLNs had a longer RFS than those with 1-2 SLNs in T4, N1a group and those who rejected complete lymph node dissection (CLND). In patients with T4 melanomas, N1a melanomas and those that did not undergo a CLND, the prognosis of those with three or more SLNs retrieved seemed to be improved.

A Nomogram for Identifying HR+/Her2- Breast Cancer Patients with Positive Sentinel Lymph Nodes and Omitted Axillary Lymph Node Dissection Who Need Abemaciclib Therapy.

BACKGROUND The efficacy of abemaciclib in high-risk patients with early-stage HR+/Her2- breast cancer has been verified by MonarchE. However, accurately determining the number of axillary lymph node (ALN) metastases remains challenging. The Z0011 trial changed the axillary management strategy, eliminating the need for axillary lymph node dissection (ALND) in patients with 1-2 sentinel lymph node (SLN) metastases. Therefore, further exploration is needed to identify patients who could benefit from abemaciclib therapy. MATERIAL AND METHODS This retrospective study included cT1-2N0M0 HR+/Her2- patients with 1-2 positive SLNs who underwent ALND. Clinicopathological data were collected, and logistic regression analyses identified independent predictors for ≥4 positive ALNs. A predictive nomogram was developed, and discrimination and calibration were evaluated using the C-index and calibration curve. Clinical efficacy was assessed using decision curve analysis (DCA). RESULTS We enrolled 444 patients, with 77 (17.3%) having ≥4 positive ALNs. Independent predictors for ≥4 positive ALNs included abnormal ALN on ultrasound, mammographic calcifications, T stage, and the number of positive SLNs. The nomogram demonstrated an AUC of 0.777 (95% CI: 0.735-0.815, P<0.001), and internal validation showed good calibration and discrimination (C-index, 0.802; 95% CI: 0.779-0.824). DCA revealed a positive net benefit for risk levels ranging from 5% to 54%. CONCLUSIONS This nomogram is a convenient and reliable tool to predict the risk of ≥4 positive ALNs in HR+/Her2- patients. It aids in protocol selection by identifying SLN-positive patients who may benefit from abemaciclib therapy without ALND.

A nomogram based on genotypic and clinicopathologic factors to predict the non-sentinel lymph node metastasis in Chinese women breast cancer patients.

Sentinel lymph node biopsy (SLNB) is the standard treatment for breast cancer patients with clinically negative axilla. However, axillary lymph node dissection (ALND) is still the standard care for sentinel lymph node (SLN) positive patients. Clinical data reveals about 40-75% of patients without non-sentinel lymph node (NSLN) metastasis after ALND. Unnecessary ALND increases the risk of complications and detracts from quality of life. In this study, we expect to develop a nomogram based on genotypic and clinicopathologic factors to predict the risk of NSLN metastasis in SLN-positive Chinese women breast cancer patients. This retrospective study collected data from 1,879 women breast cancer patients enrolled from multiple centers. Genotypic features contain 96 single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility, therapy and prognosis. SNP genotyping was identified by the quantitative PCR detection platform. The genetic features were divided into two clusters by the mutational stability. The normalized polygenic risk score (PRS) was used to evaluate the combined effect of each SNP cluster. Recursive feature elimination (RFE) based on linear discriminant analysis (LDA) was adopted to select the most useful predictive features, and RFE based on support vector machine (SVM) was used to reduce the number of SNPs. Multivariable logistic regression models (i.e., nomogram) were built for predicting NSLN metastasis. The predictive abilities of three types of model (based on only clinicopathologic information, the integrated clinicopathologic and all SNPs information, and integrated clinicopathologic and significant SNPs information) were compared. Internal and external validations were performed and the area under ROC curves (AUCs) as well as a series of evaluation indicators were assessed. 229 patients underwent SLNB followed by ALND and without any neo-adjuvant therapy, 79 among them (34%) had a positive axillary NSLN metastasis. The LDA-RFE identified the characteristics including lymphovascular invasion, number of positive SLNs, number of negative SLNs and two SNP clusters as significant predictors of NSLN metastasis. Furthermore, the SVM-RFE selected 29 significant SNPs in the prediction of NSLN metastasis. In internal validation, the median AUCs of the clinical and all SNPs combining model, the clinical and 29 significant SNPs combining model, and the clinical model were 0.837, 0.795 and 0.708 respectively. Meanwhile, in external validation, the AUCs of the three models were 0.817, 0.815 and 0.745 respectively. We present a new nomogram by combining genotypic and clinicopathologic factors to achieve higher sensitivity and specificity comparing with traditional clinicopathologic factors to predict NSLN metastasis in Chinese women breast cancer. It is recommended that more validations are required in prospective studies among different patient populations.

Development and validation of a pre- and intra-operative scoring system that distinguishes between non-advanced and advanced axillary lymph node metastasis in breast cancer with positive sentinel lymph nodes: a retrospective study

BackgroundThere are currently no scoring-type predictive models using only easily available pre- and intraoperative data developed for assessment of the risk of advanced axillary lymph node metastasis (ALNM) in patients with breast cancer with metastatic sentinel lymph nodes (SLNs). We aimed to develop and validate a scoring system using only pre- and intraoperative data to distinguish between non-advanced (≤ 3 lymph nodes) and advanced (> 3 lymph nodes) ALNM in patients with breast cancer with metastatic SLNs.MethodsWe retrospectively identified 804 patients with breast cancer (cT1-3cN0) who had metastatic SLNs and had undergone axillary lymph node dissection (ALND). We evaluated the risk factors for advanced ALNM using logistic regression analysis and developed and validated a scoring system for the prediction of ALNM using training (n = 501) and validation (n = 303) cohorts, respectively. The predictive performance was assessed using the receiver operating characteristic (ROC) curve, area under the curve (AUC), and calibration plots.ResultsUltrasound findings of multiple suspicious lymph nodes, SLN macrometastasis, the ratio of metastatic SLNs to the total number of SLNs removed, and the number of metastatic SLNs were significant risk factors for advanced ALNM. Clinical tumor size and invasive lobular carcinoma were of borderline significance. The scoring system based on these six variables yielded high AUCs (0.90 [training] and 0.89 [validation]). The calibration plots of frequency compared to the predicted probability showed slopes of 1.00 (training) and 0.85 (validation), with goodness-of-fit for the model. When the cutoff score was set at 4, the negative predictive values (NPVs) of excluding patients with advanced ALNM were 96.8% (training) and 96.9% (validation). The AUC for predicting advanced ALNM using our scoring system was significantly higher than that predicted by a single independent predictor, such as the number of positive SLNs or the proportion of positive SLNs. Similarly, our scoring system also showed good discrimination and calibration ability when the analysis was restricted to patients with one or two SLN metastases.ConclusionOur easy-to-use scoring system can exclude advanced ALNM with high NPVs. It may contribute to reducing the risk of undertreatment with adjuvant therapies in patients with metastatic SLNs, even if ALND is omitted.

A New Model for Predicting Nonsentinel Lymph Node Metastasis in Early-Stage Breast Cancer Using MMP15.

Background In early-stage breast cancer (BC) patients, 40–70% of lymph node metastases are limited to the sentinel lymph nodes (SLNs). Patients at low risk for nonsentinel lymph node (NSLN) metastasis should be exempt from axillary lymph node dissection (ALND) or regional lymph node radiotherapy (RNI). Methods The present study included 237 female early-stage BC patients with positive SLNs who received ALND. Based on the clinicopathological factors of the 158 patients in the training cohort, multivariate analysis was used to determine the independent risk factors for NSLN metastasis, which were used to establish the NSLN metastasis prediction model. The calibration and discrimination of this model were tested with the training and validation cohorts and compared to the Memorial Sloan Kettering Cancer Center (MSKCC) model. Results Tumor size, neural invasion, lymphovascular invasion, expression of matrix metalloproteinase 15 (MMP15) in the cytoplasm, and the number of positive SLNs were statistically significant by multivariate analysis (P < 0.05), which were used to establish the new model. The MSKCC model was verified by the training cohort, and the area under the receiver-operating characteristic (ROC) curve was 0.733 (95% CI: 0.650–0.816), which was less than that of the new model (0.824; 95% CI: 0.760–0.889). The area under the ROC curve in the validation cohort for the new model was 0.773 (95% CI: 0.669–0.877), and the calibration performed well. The false-negative rates were 3.2%, 6.5%, and 14.5% for the predicted probability cut-offs of 50%, 60%, and 70%, respectively. Conclusions The new model included five variables: tumor size, neural invasion, lymphovascular invasion, cytoplasmic MMP15 expression, and the number of positive SLNs. The model with a cut-off of 60% could accurately identify low-risk patients with NSLN metastasis.

Risk factors of non-sentinel lymph node metastasis in 443 breast cancer patients with sentinel lymph node-positive.

Axillary lymph node dissection is the standard surgical procedure for breast cancer patients with sentinel lymph node (SLN) positive. In clinical practice, axillary lymph node dissection may be an unnecessary treatment for some breast cancer patients with non-sentinel lymph node (NSLN) negative. The aim of this study was to analyze the risk factors of NSLN metastasis in breast cancer patients with SLN positive. Four hundred fifty-six clinical early stage breast cancer patients with SLN positive were collected and analyzed in the oncological surgery department of Fujian Provincial Hospital during 2013 to 2018. All these patients underwent surgical treatment. The average age and tumor size of 443 patients with SLN positive breast cancer were (49.8 ± 10.8) years and (2.42 ± 0.94) cm. Univariate analysis showed that the size of primary tumor, the number of positive SLN, the number of negative SLN, the ratio of positive SLNs, and the type of metastases in SLN were the influencing factors of NSLN metastasis. Multivariate regression analysis showed that primary tumor size T > 2 cm (P < .001, OR = 2.609), the positive number of SLNs ≥3 (P = .002, OR = 5.435), the ratio of positive SLNs ≥ 50% (P = .017, OR = 1.770), and SLN macrometastases (P < 0.001, OR = 16.099) were independent risk factors for NSLN metastasis. Combined with the 4 independent risk factors, the area under the curve to predict NSLN metastasis was 0.747 > 0.7. For clinical early breast cancer with positive SLN, primary tumor size T > 2 cm,the positive number of SLNs ≥ 3, the ratio of positive SLNs ≥ 50%, and SLN macrometastases could predict NSLN metastasis well, and guide surgery to avoid overtreatment.

Factors Influencing Non-sentinel Lymph Node Involvement in Patients with Positive Sentinel Lymph Node(s) After Neoadjuvant Chemotherapy for Breast Cancer.

When a positive sentinel lymph node (SLN) is identified after neoadjuvant chemotherapy (NAC), completion axillary lymph node dissection (cALND) is generally recommended. We sought to evaluate the rate of non-SLN positivity and factors influencing this in patients with a positive SLN following NAC. We identified all patients at our hospital between 2006 and 2021 with a positive SLN (> 0.2mm) following NAC who underwent cALND. Rates of positive non-SLN (NSLN) on cALND were compared by nodal status. Chi-square tests and multivariable logistic regression were used to assess factors predictive of positive NSLN and overall nodal burden. Overall, 229 cases (177 cN+, 52 cN0 prior to NAC) with positive SLN(s) after NAC underwent cALND. Additional NSLN involvement was found in 129/229 (56.3%) patients, including 24/52 (46.2%) cN0 and 105/177 (59.3%) cN+ patients (p = 0.09). There was a trend for patients with SLN micrometastases to be less likely to have positive NSLN(s) than those with SLN macrometastases (38.5% vs. 58.6%; p = 0.05). Subgroup analyses showed no clinicopathologic factors significantly associated with additional axillary involvement for initially cN0 patients. Factors found to significantly influence NSLN positivity in the initially cN+ subgroup were HER2 status, multicentricity/multifocality, number of positive SLNs, and size of SLN metastasis. SLN metastasis size > 5mm and three or more positive SLNs exerted the greatest influence on NSLN positivity. Rates of nodal positivity on cALND in the setting of positive SLN after NAC are high, supporting the current standard of routine cALND. In cN+ disease, NSLN positivity varies by tumor biology, multicentricity/multifocality, number of positive SLNs, and SLN metastasis size.

Development of a prediction model based on LASSO regression to evaluate the risk of non-sentinel lymph node metastasis in Chinese breast cancer patients with 1\u20132 positive sentinel lymph nodes

This study aimed to develop an intraoperative prediction model to evaluate the risk of non-sentinel lymph node (NSLN) metastasis in Chinese breast cancer patients with 1–2 positive sentinel lymph nodes (SLNs). The clinicopathologic data of 714 patients with 1–2 positive SLNs were investigated. Univariate and multivariate analyses were performed to identify the risk factors of NSLN metastasis. A new mathematical prediction model was developed based on LASSO and validated in an independent cohort of 131 patients. The area under the receiver operating characteristic curve (AUC) was used to quantify performance of the model. Patients with NSLN metastasis accounted for 37.3% (266/714) and 34.3% (45/131) of the training and validation cohorts, respectively. A LASSO regression-based prediction model was developed and included the 13 most powerful factors (age group, clinical tumour stage, histologic type, number of positive SLNs, number of negative SLNs, number of SLNs dissected, SLN metastasis ratio, ER status, PR status, HER2 status, Ki67 staining percentage, molecular subtype and P53 status). The AUCs of training and validation cohorts were 0.764 (95% CI 0.729–0.798) and 0.777 (95% CI 0.692–0.862), respectively. We presented a new prediction model with excellent clinical applicability and diagnostic performance for use by clinicians as an intraoperative clinical tool to predict risk of NSLN metastasis in Chinese breast cancer patients with 1–2 positive SLNs and make the final decisions regarding axillary lymph node dissection.

Candidates of Genomic Tests in HR+/HER2- Breast Cancer Patients With 1-2 Positive Sentinel Lymph Node Without Axillary Lymph Node Dissection: Analysis From Multicentric Cohorts.

BackgroundThe genomic tests such as the MammaPrint and Oncotype DX test are being gradually applied for hormone receptor positive/HER-2 negative (HR+/HER2-) breast cancer patients with up to three positive axillary lymph nodes (ALNs). The first results from RxPONDER trial suggested that Oncotype DX could be applied to patients with 1-2 positive sentinel lymph nodes (SLNs) without axillary lymph node dissection (ALND), which constituted 37.4% of the intent-to-treat population. However, there was no distinctive research on how to apply genomic tests precisely to HR+/HER2- patients with 1-2 positive SLNs without ALND. The purpose was to construct a nomogram using the multi-center retrospective data to predict precisely which HR+/HER2- candidates with 1-2 positive SLNs could be subjected to genomic tests (≤ 3 positive lymph nodes).MethodsWe conducted a retrospective analysis of 18,600 patients with stage I-III breast cancer patients treated with sentinel lymph node biopsy (SLNB) in Shandong Cancer Hospital, Fudan University Shanghai Cancer Center, and West China Hospital. The univariate and multivariate logistic regression analysis was conducted to identify the independent predictive factors of having ≤ 3 positive nodes among patients with 1-2 positive SLNs. A nomogram was developed based on variables in the final model with p<0.05. Calibration of the nomogram was carried out by internal validation using the bootstrap resampling approach and was displayed using a calibration curve. The discrimination of the model was evaluated using the ROC curve.ResultsBased on the database of the three institutions, a total of 18,600 breast cancer patients were identified undergoing SLNB between May 2010 and 2020. Among the 1817 HR+/HER2- patients with 1-2 positive SLNs undergoing ALND, 84.2% harbored ≤ 3 totals metastatic ALNs. The multivariate logistic regression analysis identified imaging abnormal nodes (OR=0.197, 95%CI: 0.082-0.472), the number of positive SLNs (OR=0.351, 95%CI: 0.266-0.464), the number of negative SLNs (OR=1.639, 95%CI: 1.465-1.833), pathological tumor stage (OR=0.730, 95%CI: 0.552-0.964), and lympho-vascular invasion (OR=0.287, 95%CI: 0.222-0.398) as independent predictors for the proportion of patients with ≤ 3 total metastatic ALNs (all p<0.05). These five predictors were used to create a predictive nomogram. The AUC value was 0.804 (95%CI: 0.681-0.812, p<0.001). The calibration curve showed a satisfactory fit between the predictive and actual observation based on internal validation with a bootstrap resampling frequency of 1000.ConclusionThe nomogram based on the multi-centric database showed a good accuracy and could assist the oncologist in determining precisely which HR+/HER2- candidates with 1-2 positive SLNs without ALND could perform genomic tests. In the era of SLNB and precision medicine, the combined application of genomic tests and SLNB could provide patients with a better strategy of dual de-escalation management, including the de-escalation of both surgery and systemic treatment.

Methylene Blue as Inexpensive and Reliable Sole Sentinel Lymph Node Mapping Agent for Patients with Invasive Ductal Carcinoma.

Background:Invasive ductal cancer (IDC) represents about 75% of all breast malignancies. There are many breast cancer prognostic factors, but the ones that have the most impact on the survival rates in advanced breast cancer are tumor size and regional lymph node involvement. Axillary lymph node dissection (ALND) has particularly important and undoubtful role in current surgical options for breast cancer treatment. With the introduction of sentinel lymph node biopsy (SLNB) for breast cancer patients it was possible to identify those to whom regional spread of the disease did not occur at the time of surgery, and thus spare them an unnecessary ALND procedure.Objective:To determine the rate of sentinel lymph node (SLN) detection using only methylene blue dye as a mapping agent, as well as to correlate the number of positive SLNs with the number of positive non-sentinel lymph nodes (non-SLNs).Methods:The study represents a prospective study that included 50 female patients with histologically confirmed invasive ductal carcinoma (IDC) who underwent SLNB using only methylene blue dye as the mapping agent, while the detection and harvest of SNL was done by visual control only. All patients also underwent an obligatory complete ALND, which was as that time the institutional oncological protocol for surgical treatment of histologically confirmed IDC. The final data such as tumor size, SLN and non-SLN status were obtained by further analysis of pathohistological reports from tumor biopsy and other surgical specimens.Results:The accuracy rate of SLN detection was 98%. The number of detected SLN was in the range of 1 to 6, with an average of 2 for each patient. The number of positive SLN was in significant correlation with the number of tumor-affected non-SNL (p<0,001). Further analysis showed that for each increase in the number of positive SLN by 1, the risk of positive non-SLN increased 6-fold, OR=6,22 (p<0,001).Conclusion:Use of methylene blue dye as a sole mapping agent when performing SLNB in patients with IDC is a reliable and effective method that can be safely implemented in medical institutions that lack availability of nuclear medicine services or significant monetary funds.

Identification of Risk Factors Associated with Axillary Lymph Node Metastasis for Sentinel Lymph Node-Positive Breast Cancer Patients

Objective This study aimed to identify clinicopathological factors related to the extent of axillary lymph node (ALN) involvement in early-stage BC patients with positive sentinel lymph nodes (SLNs). Methods This was a retrospective analysis of 566 patients in cT1-2N0M0 with 1-2 positive SLNs that underwent axillary lymph node dissection (ALND) at Sun Yat-Sen Memorial Hospital. The clinical and pathologic data from these patients were analyzed. Results Of these 566 patients, 235 (41.5%) exhibited NSLN metastases. Multivariate analysis revealed that the number of positive SLNs (odds ratio (OR) = 1.511; P=0.038), the ratio of metastatic/dissected SLNs (SLN metastasis rate) (OR = 2.124; P < 0.001), and lymphovascular invasion (LVI) (OR = 1.503; P=0.022) were all independent predictors of NSLN metastasis. Patients with 0, 1, 2, or 3 of these risk factors exhibited NSLN metastases in 29.3%, 35.7%, 50.8%, and 68.3% of cases, respectively. We additionally found that the number of positive SLNs (OR = 3.582; P < 0.001), SLN metastasis rate (OR = 2.505; P=0.001), LVI (OR = 2.010; P=0.004), and HER2 overexpression (OR = 1.774; P=0.034) were all independent predictors of N2 disease. When individuals had 0, 1, 2, 3, or 4 of these risk factors, they had four or more involved ALNs in 5.2%, 10.8%, 21.1%, 37.5%, and 70.6% of cases, respectively. Conclusion These results suggest that the number of positive SLNs, the SLN metastasis rate, and LVI are all significant predictors of ALN status in BC patients that have 1-2 positive SLNs and that have undergone ALND. In addition, HER2 overexpression was a significant predictor of N2 disease.

Surgeon decision-making for management of positive sentinel lymph nodes in the post-Multicenter Selective Lymphadenectomy Trial II era: A survey study.

Completion lymph node dissection (CLND) did not improve melanoma-specific survival for patients with sentinel lymph node (SLN)-positive melanoma in the second Multicenter Selective Lymphadenectomy Trial (MSLT-II). We assessed surgeons' awareness of MSLT-II and its impact on CLND recommendations. An anonymous online cross-sectional survey of the Society of Surgical Oncology membership evaluated surgeon thresholds in offering CLND using patient scenarios and clinicopathologic characteristics ranking. Of the 2881 e-mails delivered, 146 surgeons (5.1%) completed all seven scenarios. Most (129 of 131, 98%) were aware of MSLT-II and 125 (95%) found it practice-changing. Specifically, 52% (65 of 125) always, 40% usually, 6% rarely, and 3% never offered CLND before MSLT-II. Meanwhile, 4% always, 9% usually, 78% rarely, and 8% never offer CLND now, after MSLT-II (p < .0001). The most important clinicopathologic factors in determining CLND recommendations were extracapsular extension, number of positive SLN, and SLN tumor deposit size, while primary tumor mitotic index and nodal basin location were the least important. Surgical oncology fellowship training, melanoma patient volume, and academic center practice also influenced CLND recommendations. Most surgeon respondents are aware of MSLT-II, but its application in practice varies according to several clinicopathologic and surgeon factors.

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.

A nomogram based on genetic and clinicopathologic features to predict the nonsentinel lymph node metastases in Chinese women breast cancer patients.

e12577 Background: Sentinel lymph node biopsy (SLNB) is the standard treatment for breast cancer patients with clinically negative axilla. However, axillary lymph node dissection (ALND) is still the standard care for sentinel lymph node (SLN) positive patients. Clinical data reveals 20–60 % of patients without non-sentinel lymph node metastasis (NSLNM) after ALND. Unnecessary ALND increases the risk of lymphedema and detracts from quality of life. In this study, we expect to develop a nomogram based on genetic and clinicopathologic features to predict the risk of NSLN metastasis in SLN-positive Chinese women breast cancer patients. Methods: This retrospective study collected data from 310 women breast cancer patients who underwent SLNB followed by ALND and without any neo-adjuvant therapy in Chinese PLA General Hospital, China, between 2016 and 2017. Genetic features contain 96 single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility and prognosis based on the GWAS studies and clinical information. SNP genotyping was identified by the quantitative PCR detection platform. The genetic features were divided into two clusters by the gene functions and signaling pathways. The polygenic risk score (PRS) was used to evaluate the combined effect of each SNP cluster. Least absolute shrinkage and selection operator (LASSO) regression model was adopted for feature selection and nomogram construction. Internal validation was performed and the area under ROC curve (AUC) was assessed. Results: 81 patients of 310 patients (26%) had a positive axillary NSLNM. The LASSO regression analysis identified the clinicopathologic characteristics including molecular subtype, cN-stage, number of positive SLNs and number of negative SLNs as significant predictors of NSLNM. Furthermore, two SNP clusters were also showed statistically significant in the prediction of NSLNM. In internal validation, the average AUC of the nomogram was 0.795 and the model was well calibrated. Conclusions: We present a new nomogram by combining genetic and clinicopathologic factors to achieve higher sensitivity and specificity comparing with traditional clinicopathologic factors to predict NSLNM in Chinese women breast cancer. It is recommended that more validations are required in prospective studies among different patient populations.

Analysis of factors related to N2- or N3-stage breast cancer associated with 1-2 positive sentinel lymph nodes in Chinese patients.

BackgroundThis study aims to determine the incidence of N2- or N3-stage disease in a cohort of patients with T1–T2 invasive breast cancer and one or two positive sentinel lymph nodes (SLNs), and identify the risk factors for N2/3 disease in this cohort.MethodsThe present study involved 298 patients with T1–T2 tumors who underwent SLN biopsy and were found to have one or two metastatic SLNs. The proportion of patients with N2/3 disease was calculated in the whole cohort, and in the T1 and T2 subgroups. Furthermore, univariate and multivariate analyses were used to identify the risk factors for N2/3 disease in the cohort.ResultsThe final N stage, as determined by the postoperative pathological examination, was N1 for 250 (83.9%) patients, and N2 or N3 for 48 (16.1%) patients (11.41% had clinical N2 disease, while 4.70% had clinical N3 disease). Among the 156 patients with T1 tumors, 17 (10.9%) patients had N2/3 disease, while for the 142 patients with T2 tumors, 31 (21.8%) patients had N2/3 disease. T2 stage, lymphovascular invasion, and the number of positive SLNs were independent predictors of N2/3 disease in the cohort (P<0.05).ConclusionsN2/3 lymph node metastasis occurs in patients with T1–T2 breast cancer, and one or two positive SLNs, particularly in patients with T2 tumors. The rate of N2/3 disease is not negligible. T2 stage, lymphovascular invasion, and the number of positive SLNs were independent predictors of N2/3 disease in the present patient population.

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.

Imaging Predictors for Nonsentinel Lymph Node Metastases in Breast Cancer Patients

Background: The relationship between imaging features and nonsentinel lymph node (NSLN) metastasis is not clear. Objectives: To determine whether imaging features could predict NSLN metastasis in sentinel lymph node (SLN)-positive breast cancer patients and to provide new clues for avoiding unnecessary axillary lymph node dissection. Method: 171 patients with clinically negative axillary lymph nodes and a pathologically positive SLN were recruited between January 2007 and January 2014. According to the Breast Imaging Reporting and Data System (BI-RADS), the effects of clinicopathological factors, especially imaging features, on NSLN metastases were assessed by univariate and multivariate statistical analyses. Results: The average number of dissected SLNs was 2.11 (range, 1–6); 56 of the 171 (32.75%) patients exhibited NSLN metastases. In univariate analysis, tumor size, number of positive SLNs, ratio of positive SLNs, mammographic mass margins, ultrasonographic mass margins, and ultrasonographic vascularity were significantly correlated with NSLN involvement. Furthermore, through multivariate analysis, tumor size, number of positive SLNs, mammographic mass margins, and ultrasonographic vascularity were still independent predictors of NSLN involvement. Additionally, in SLN-positive patients, number of positive SLNs and ultrasonographic vascularity could also predict the tumor burden in NSLN. Conclusions: In addition to tumor size and the number of positive SLNs, mammographic mass margins and ultrasonographic vascularity were also independent predictors of NSLN metastases in SLN-positive patients of breast cancer. The number of positive SLNs and ultrasonographic vascularity could also predict the tumor burden in NSLN.