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This study aimed to construct a machine learning radiomics-based model using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images to evaluate non-sentinel lymph node (NSLN) metastasis in Chinese breast cancer (BC) patients who underwent total mastectomy (TM) and had 1–2 positive sentinel lymph nodes (SLNs). In total, 494 patients were retrospectively enrolled from two hospitals, and were divided into the training (n = 286), internal validation (n = 122), and external validation (n = 86) cohorts. Features were extracted from DCE-MRI images for each patient and screened. Six ML classifies were trained and the best classifier was evaluated to calculate radiomics (Rad)-scores. A combined model was developed based on Rad-scores and clinical risk factors, then the calibration, discrimination, reclassification, and clinical usefulness were evaluated. 14 radiomics features were ultimately selected. The random forest (RF) classifier showed the best performance, with the highest average area under the curve (AUC) of 0.833 in the validation cohorts. The combined model incorporating RF-based Rad-scores, tumor size, lymphovascular invasion, and proportion of positive SLNs resulted in the best discrimination ability, with AUCs of 0.903, 0.890, and 0.836 in the training, internal validation, and external validation cohorts, respectively. Furthermore, the combined model significantly improved the classification accuracy and clinical benefit for NSLN metastasis prediction. A RF-based combined model using DCE-MRI images exhibited a promising performance for predicting NSLN metastasis in Chinese BC patients who underwent TM and had 1–2 positive SLNs, thereby aiding in individualized clinical treatment decisions. • The random forest (RF) was considered the optimal machine learning (ML) algorithm for radiomics model construction and was used to calculate the radiomics signature. • The ML radiomics-based combined model incorporating the DCE-MRI radiomics signature with clinical risk factors performed significantly better in NSLN metastasis prediction than radiomics model and clinical model. • The combined model presented as a nomogram has the potential to contribute to customizing personalized axillary surgery to avoid overtreatment for Chinese BC patients with 1-2 positive SLNs. [ABSTRACT FROM AUTHOR]

Abstract Objective For patients with 1–2 positive sentinel lymph nodes (SLN) identified by biopsy, the necessity of axillary lymph node dissection (ALND) remains a matter of debate. The primary aim of this study was to investigate the association between postoperative pathological factors and non-sentinel lymph node (NSLN) metastases in Chinese patients diagnosed with sentinel node-positive breast cancer. Methods This research involved a total of 280 individuals with SLN-positive breast cancer. The relationship between postoperative pathological variables and non-sentinel lymph node metastases was scrutinized using univariate, multivariate, and stratified analysis. Results Among the 280 patients with a complete count of SLN positives, 126 (45.0%) exhibited NSLN metastasis. Within this group, 45 cases (35.71%) had 1 SLN positive, while 81 cases (64.29%) demonstrated more than 1 SLN positive. Multivariate logistic regression analysis revealed that HER2 expression status (OR 2.25, 95% CI 1.10–4.60, P = 0.0269), LVI (OR 6.08, 95% CI 3.31–11.14, P

Objective To investigate the use of a MRI radiomics nomogram based on machine learning in predicting non-sentinel lymph node (NSLN) involvement in patients with 1-2 positive sentinel lymph nodes (SLN). Methods From January 2016 to December 2022, 408 patients with histologically confirmed breast cancer in our hospital were retrospectively analyzed. All patients had 1-2 histologically confirmed SLN metastasis. The Radcloud platform was used to extract the radiomics features inside the tumor from dynamic contrast-enhanced (DCE) MR images, and the optimal features were obtained through dimensionality reduction. Subsequently, six machine learning classifiers were developed including K-nearest neighbor, support vector machine, logistic regression, random forest (RF), linear discriminant analysis, and extreme gradient boost ( XGBoost). The best radiomics model with the highest area under the receiver operating characteristic curve (AUC) was chosen as the validation set, and the results were converted to Rad-score. The statistically significant clinicopathologic features were included in the multivariate logistic regression analysis to screen the independent risk factors of NSLN metastasis and to establish the clinical model. Furthermore, a combined model based on Rad-score and clinical risk factors was established, and a nomogram was drawn. The AUC was used to evaluate the predictive performance of the model. Results Fourteen radiomics features significantly associated with NSLN metastasis were obtained by dimensionality reduction. In the validation set, the model built based on XGBoost classifier had the lowest performance (AUC= 0.650), and the model built by RF classifier had the highest performance (AUC= 0.807). The maximum tumor diameter (odds ratio = 2. 640, P ＜ 0.001), lymphovascular invasion (odds ratio=2.970, P＜0.001), and SLN ratio (odds ratio=4.707, P＜0.001) were independent risk factors for predicting NSLN metastasis. The nomogram model combined with the RF-based Rad-scores had the best predictive performance with the AUC of 0.876 and 0.853 in the training and validation sets, respectively. The calibration curve showed good consistency with the actual results. Decision curve analysis showed that the model had high clinical application value. Conclusion Machine learning-based DCE-MRI radiomics has high application value in predicting NSLN of SLN-positive breast cancer. [ABSTRACT FROM AUTHOR]

Abstract Background The randomized trials which include ACOSOG Z0011 and IBCSG 23-01 had found that the survival rates were not different in patients with cT1/2N0 and 1–2 sentinel lymph node (SLN)-positive, macro/micrometastases who underwent breast-conserving therapy, and micrometastases who underwent total mastectomy (TM), when axillary lymph node dissection (ALND) was omitted. However, for patients with cT1/2N0 and 1–2 SLN macrometastases who underwent TM; there was still insufficient evidence from clinical studies to support whether ALND can be exempted. This study aimed to investigate the risk factors of non-sentinel lymph node (nSLN) metastasis in breast cancer patients with 1–2 SLN macrometastases undergoing TM. Methods The clinicopathological data of 1491 breast cancer patients who underwent TM and SLNB from January 2017 to February 2022 were retrospectively analyzed. Univariate and multivariate analyses were performed to analyze the risk factors for nSLN metastasis. Results A total of 273 patients with 1–2 SLN macrometastases who underwent TM were enrolled. Postoperative pathological data showed that 35.2% patients had nSLN metastasis. The results of multivariate analysis indicated that tumor size (TS) (P = 0.002; OR: 1.051; 95% CI: 1.019–1.084) and ratio of SLN macrometastases (P = 0.0001; OR: 12.597: 95% CI: 4.302–36.890) were the independent risk factors for nSLN metastasis in breast cancer patients with 1–2 SLN macrometastases that underwent TM. The ROC curve analysis suggested that when TS ≤22 mm and ratio of SLN macrometastases ≤0.33, the incidence of nSLN metastasis could be reduced to 17.1%. Conclusions The breast cancer patients with cT1/2N0 stage, undergoing TM and 1–2 SLN macrometastases, when the TS ≤22 mm and macrometastatic SLN does not exceed 1/3 of the total number of detected SLN, the incidence of nSLN metastasis is significantly reduced, but whether ALND can be exempted needs further exploration.

Background: The randomized trials which include ACOSOG Z0011 and IBCSG 23-01 had found that the survival rates were not different in patients with cT1/2N0 and 1–2 sentinel lymph node (SLN)-positive, macro/micrometastases who underwent breast-conserving therapy, and micrometastases who underwent total mastectomy (TM), when axillary lymph node dissection (ALND) was omitted. However, for patients with cT1/2N0 and 1–2 SLN macrometastases who underwent TM; there was still insufficient evidence from clinical studies to support whether ALND can be exempted. This study aimed to investigate the risk factors of non-sentinel lymph node (nSLN) metastasis in breast cancer patients with 1–2 SLN macrometastases undergoing TM. Methods: The clinicopathological data of 1491 breast cancer patients who underwent TM and SLNB from January 2017 to February 2022 were retrospectively analyzed. Univariate and multivariate analyses were performed to analyze the risk factors for nSLN metastasis. Results: A total of 273 patients with 1–2 SLN macrometastases who underwent TM were enrolled. Postoperative pathological data showed that 35.2% patients had nSLN metastasis. The results of multivariate analysis indicated that tumor size (TS) (P = 0.002; OR: 1.051; 95% CI: 1.019–1.084) and ratio of SLN macrometastases (P = 0.0001; OR: 12.597: 95% CI: 4.302–36.890) were the independent risk factors for nSLN metastasis in breast cancer patients with 1–2 SLN macrometastases that underwent TM. The ROC curve analysis suggested that when TS ≤22 mm and ratio of SLN macrometastases ≤0.33, the incidence of nSLN metastasis could be reduced to 17.1%. Conclusions: The breast cancer patients with cT1/2N0 stage, undergoing TM and 1–2 SLN macrometastases, when the TS ≤22 mm and macrometastatic SLN does not exceed 1/3 of the total number of detected SLN, the incidence of nSLN metastasis is significantly reduced, but whether ALND can be exempted needs further exploration. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: This study aimed to develop a model incorporating axillary tail position on mammography (AT) for the prediction of non-sentinel Lymph Node (NSLN) metastasis in patients with initial clinical node positivity (cN+).Methods and Materials: The study reviewed a total of 257 patients with cN+ breast cancer who underwent both sentinel lymph node biopsy (SLNB) and axillary lymph node dissection (ALND) following neoadjuvant chemotherapy (NAC). A logistic regression model was developed based on these factors and the results of post-NAC AT and axillary ultrasound (AUS).Results: Four clinical factors with p<0.1 in the univariate analysis, including ycT0(odds ratio [OR]: 4.84, 95% confidence interval [CI]: 2.13-11.91, p<0.001), clinical stage before NAC (OR: 2.68, 95%CI: 1.15-6.58, p=0.025), estrogen receptor (ER) expression (OR: 3.29, 95%CI: 1.39-8.39, p=0.009), and HER2 status (OR: 0.21, 95%CI: 0.08-0.50, p=0.001), were independent predictors of NSLN metastases. The clinical model based on the above four factors resulted in the area under the curve (AUC) of 0.82(95%CI: 0.76-0.88) in the training set and 0.83(95% CI: 0.74-0.92) in the validation set. The results of post-NAC AUS and AT were added to the clinical model to construct a clinical imaging model for the prediction of NSLN metastasis with AUC of 0.87(95%CI: 0.81-0.93) in the training set and 0.89(95%CI: 0.82-0.96) in the validation set.Conclusions: The study incorporated the results of post-NAC AT and AUS with other clinal factors to develop a model to predict NSLN metastasis in patients with initial cN+ before surgery. This model performed excellently, allowing physicians to select patients for whom unnecessary ALND could be avoided after NAC. [ABSTRACT FROM AUTHOR]

Background: T1-2 breast cancer patients with only one sentinel lymph node (SLN) metastasis have an extremely low non-SLN (NSLN) metastatic rate and are favorable for axillary lymph node dissection (ALND) exemption. This study aimed to construct a nomogram-based preoperative prediction model of NSLN metastasis for such patients, thereby assisting in preoperatively selecting proper surgical procedures. Methods: A total of 729 T1-2 breast cancer patients with only one SLN metastasis undergoing sentinel lymph node biopsy and ALND were retrospectively selected from Harbin Medical University Cancer Hospital between January 2013 and December 2020, followed by random assignment into training (n=467) and validation cohorts (n=262). A nomogram-based prediction model for NSLN metastasis risk was constructed by incorporating the independent predictors of NSLN metastasis identified from multivariate logistic regression analysis in the training cohort. The performance of the nomogram was evaluated by the calibration curve and the receiver operating characteristic (ROC) curve. Finally, decision curve analysis (DCA) was used to determine the clinical utility of the nomogram. Results: Overall, 160 (21.9%) patients had NSLN metastases. Multivariate analysis in the training cohort revealed that the number of negative SLNs (OR: 0.98), location of primary tumor (OR: 2.34), tumor size (OR: 3.15), and lymph-vascular invasion (OR: 1.61) were independent predictors of NSLN metastasis. The incorporation of four independent predictors into a nomogram-based preoperative estimation of NSLN metastasis demonstrated a satisfactory discriminative capacity, with a C-index and area under the ROC curve of 0.740 and 0.689 in the training and validation cohorts, respectively. The calibration curve showed good agreement between actual and predicted NSLN metastasis risks. Finally, DCA revealed the clinical utility of the nomogram. Conclusion: The nomogram showed a satisfactory discriminative capacity of NSLN metastasis risk in T1-2 breast cancer patients with only one SLN metastasis, and it could be used to preoperatively estimate NSLN metastasis risk, thereby facilitating in precise clinical decision-making on the selective exemption of ALND in such patients. [ABSTRACT FROM AUTHOR]

Abstract Background Since the introduction of sentinel node biopsy (SLNB) in unifocal vulvar cancer (diameter of

Abstract Background Whether non‐sentinel lymph node (SLN)‐positive melanoma patients can benefit from completion lymph node dissection (CLND) is still unclear. The current study was performed to identify the prognostic role of non‐SLN status in SLN‐positive melanoma and to investigate the predictive factors of non‐SLN metastasis in acral and cutaneous melanoma patients. Methods The records of 328 SLN‐positive melanoma patients who underwent radical surgery at four cancer centers from September 2009 to August 2017 were reviewed. Clinicopathological data including age, gender, Clark level, Breslow index, ulceration, the number of positive SLNs, non‐SLN status, and adjuvant therapy were included for survival analyses. Patients were followed up until death or June 30, 2019. Multivariable logistic regression modeling was performed to identify factors associated with non‐SLN positivity. Log‐rank analysis and Cox regression analysis were used to identify the prognostic factors for disease‐free survival (DFS) and overall survival (OS). Results Among all enrolled patients, 220 (67.1%) had acral melanoma and 108 (32.9%) had cutaneous melanoma. The 5‐year DFS and OS rate of the entire cohort was 31.5% and 54.1%, respectively. More than 1 positive SLNs were found in 123 (37.5%) patients. Positive non‐SLNs were found in 99 (30.2%) patients. Patients with positive non‐SLNs had significantly worse DFS and OS (log‐rank P

Objective To investigate the metastasis of non-sentinel lymph node (NSLN) in breast cancer patients with 1~2 positive axillary sentinel lymph nodes (SLN) and the related risk factors. Methods Clinicopathologic parameters of 383 breast cancer patients with 1~2 positive SLNs admitted in our hospital from 2016 to 2018 were collected and retrospectively studied. Univariate and multivariate analysis were used to explore the related predictors of NSLN metastasis. Results In the enrolled 383 patients, only 149 (38.9%) were observed with NSLN metastasis. Univariate analysis showed ultrasound axillary lymph node (ALN) status (P < 0.001), number of positive SLN (P=0.007), number of negative SLN (P < 0.001), number of SLN dissected (P < 0.001), metastatic rate of SLN (P < 0.001) and lymph-vascular invasion (LVI, P=0.003) were related with NSLN metastasis. Multivariate logistic regressive analysis indicated that ultrasound ALN status (P=0.001), number of negative SLN (P=0.019), metastatic rate of SLN (P=0.037), LVI (P=0.039) and HER2 over-expression (P=0.026) were the independent predictive factors of NSLN metastasis. Conclusion Ultrasound ALN status, number of negative SLN, metastatic rate of SLN, LVI and HER2 over-expression can be used as the independent predictive factors of NSLN metastasis. Attention should be paid to the clinicopathological characteristics when decision of avoiding axillary lymph node dissection in breast cancer patients with 1~2 positive SLNs.

Background/aim: 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., Patients and Methods: 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., Results: 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., Conclusion: 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., (Copyright © 2024 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Axillary strategy decisions have become more complex and controversial in considering minimally traumatic therapy instead of sentinel lymph node biopsy, axillary lymph node dissection or regional nodal irradiation for people with breast cancer. The purpose of this study was to noninvasively predict sentinel lymph node (SLN) and non-sentinel lymph node (NSLN) status based on pre-operative sonographic and clinicopathologic features to determine optimal decisions regarding axillary therapy. In total, 701 patients with breast cancer from two independent centers were retrospectively analyzed. The SLN model (SLNM) for predicting SLN status and the NSLN model (NSLNM) for predicting NSLN status were trained based on a training set using the random-forest algorithm, and their performance was validated using an independent external test set. A receiver operating characteristic curve was drawn to obtain the area under the curve, which was used to assess performance. The area under the curve for the SLNM in the training and test, respectively, was 94.2% and 83.0%, and for the NSLNM, 99.5% and 92.7%. The SLNM and NSLNM accurately predicted that 61.46% (319/519) and 17.53% (91/519), respectively, of our participants were non-metastatic. The overall benefit of the three models was 78.99% in our participants. The two models for predicting SLN and NSLN status showed excellent application potential in optimizing axillary strategies. [ABSTRACT FROM AUTHOR]

AIM: Our aim was to evaluate the efficacies of different nomogram approaches, including the Memorial Sloan Kettering Cancer Centre (MSKCC), Stanford University, Tenon Hospital, Cambridge University and TR methods, in patients operated for breast cancer. MATERIAL AND METHOD: The study included 60 breast cancer patients who were operated on for breast cancer at Ankara Numune Training and Research Hospital, A2 General Surgery Clinic, between 2007 and 2012. All patients were sentinel lymph node (SLN)-positive and had undergone axillary lymph node dissection (ALND). Five different scoring systems were applied retrospectively to these 60 patients. Receiver operating characteristics (ROC) curves were created for the nomograms and the area under the curve (AUC) sensitivity and specificity results were calculated. RESULTS: Twenty-two patients (37%) had axillary non-SLN metastases. AUC values of MSKCC, Stanford, Cambridge, Tenon and TR nomogram were calculated as 0.646, 0.644, 0.62, 0.595, and 0.66, respectively. A significant difference was found between the groups with and without non-SLN metastasis in terms of SLN metastasis size (p = 0.013). CONCLUSION: The MSKCC, Stanford, Cambridge, Tenon, and TR nomogram models were found to have insufficient power to discriminate between patients with and without non-SLN metastases in patients with SLN-positive breast cancer (AUC values <0.70). [ABSTRACT FROM AUTHOR]

Background: Since the introduction of sentinel node biopsy (SLNB) in unifocal vulvar cancer (diameter of < 4 cm) and unsuspicious groin lymph nodes, the morbidity rate of patients has significantly decreased globally. In contrast to SLNB, bilateral inguinofemoral lymphadenectomy (IFL) has been associated with increased risk of common morbidities. Current guidelines (NCCN, ESGO, RCOG, and German) recommend that in cases of unilaterally positive sentinel lymph node (SLN), bilateral IFL should be performed. However, two recent publications by Woelber et al. and Nica et al. contradict the current guideline, since a significant rate of positive non sentinel lymph nodes in IFL contralaterally was not observed [Woelber et al. 0% (p = 0/28) and Nica et al. 5.3% (p = 1/19)].Methods: A retrospective single-center analysis conducted in the University Hospital of Dusseldorf, evaluating vulvar cancer patients treated with SLNB from 2002 to 2018.Results: 22.2% of women (n = 4/18) were found to have contralateral IFL groin metastasis after an initial diagnosis of unilateral SLN metastasis. The depth of tumor infiltrating cells correlated significantly and positively with the rate of incidence of groin metastasis (p = 0.0038).Conclusion: Current guideline for bilateral IFL should remain as the standard management. Therefore, this depth may be taken into account as an indication for bilateral IFL. The management of VC and SLNB should be performed in a high volume center with an experienced team in marking SLN and performing the adequate surgical procedure. Well conducted counseling of the patients outlining advantages but also potential oncological risks of this technique especially concerning rate of groin recurrence is critical. [ABSTRACT FROM AUTHOR]

Objective To identify the risk factors of non-sentinel lymph node ( nSLN) metastasis in breast cancer patients with I ~ 2 positive axillary sentinel lymph node ( SLN) and construct an accurate prediction model. Methods Retrospective chart review Was performed in 917 breast cancer patients who underwent surgery treatment between 2002 and 2017 and pathologically confirmed 1-2 positive SLNs. According to the date of surgery, patients were divided into training group ( 497 cases) and validation group ( 420 cases) . A nomogram was lmilt to predict nSLN metastasis and the accuracy of the model was validated. Results Among the 917 patients, 251 (27.4%·) had nSLN metastasis. Univariate analysis showed tumor grade, lymphovasculm· invasion ( LVI) ., extra-capsular extension ( ECE), the number of positive and negative SLN and macro-metastatis of SLN were associated with nSLN metastasis ( all P<0.05). Multivariate Logistic regression analysis showed the numbers of positive SLN, negative SLN mHl micro-metastasis of SLN were independent predictors of nSLN metashatis ( all P < 0.05 ) . A nomogram was constructed based on the 6 factors. The area under the receiver operating characteristic curve was 0. 718 for the training group and 0.742 for the validation group. Conclusion We have developed a nomogram that uses 6 risk factors commonly available to accurately estimate the likelihood of nSLN metastasis for individual patient, which might he helpful for radiation oncologists to make a decision on regional nodal irradiation. [ABSTRACT FROM AUTHOR]

Background: Sentinel lymph node biopsy (SLNB) has replaced axillary lymph node dissection (ALND) in early breast cancer patients as the first line surgical approach to axillary nodes. Further dissection is performed only when SLN is involved by tumor cells. However, in a significant proportion of patients, non-sentinel nodes are still not involved and axillary dissection has no additional therapeutic benefits. Selective axillary clearance has been considered to prevent unnecessary dissection. The purpose of this study was to define predictors of non-sentinel lymph node involvement in patients with positive SLNB. Methods: Patients with early stage breast cancer and positive SLNB who underwent ALNDin a referral hospital in Tehran, Iran between2010 and 2012 were recruited into the study. Relations between different clinico-pathological characteristics and involvement of non-sentinel nodes were investigated. Results: From 139 patients who had positive SLNB and underwent ALND, only in 71 cases (51%) positive non-sentinel lymph nodes (NSLNs) were detected. In univariate analysis, there was no association between tumor size, lymphovascular invasion, ER, PR and HER-2 expression and NSLN metastasis. In contrast, presence of more than one SLN (P = 0.016) and a sentinel node ratio (SNR) more than 0.5 showed a significant association (P< 0.001). Only the latter remained as the significant predictor of NSLN involvement in mutltivariate analysis (P < 0.001, OR = 3.706). Conclusions: Based on our results, patients with a SNR more than 0.5 were more commonly diagnosed with NSLN metastasis. Thus, it is recommended that surgeons think twice before skipping ALND in this subgroup of patients.

Background: With the development of precise treatment for breast cancer, the current trend of clinical treatment aims to limit axillary surgery as much as possible. At present, there is an unmet need to predict the probability of patients with a low risk of non-sentinel lymph node (SLN) metastasis and determine whether the omission of axillary lymph node dissection (ALND) is appropriate., Methods: We retrospectively analyzed the data of patients with breast cancer who underwent sentinel lymph node biopsy (SLNB) and ALND. The patients were randomly assigned to training and validation sets. The associations between non-SLN metastasis (NSLNM) and ultrasonography and clinicopathological characteristics were assessed by multivariate logistic regression. Then, a nomogram model was constructed and validated using the calibration curve and the receiver operating characteristic curve., Results: Vascular infiltration, positive SLN number, negative SLN number, human epidermal growth factor receptor 2 (HER2) status, and lymph node shape were identified as independent predictive factors for positive NSLNM. The areas under the curve of the nomogram model to predict NSLNM were 0.793 and 0.780 in the training and validation sets, respectively, and P=0.161 and P=0.768 in the Hosmer-Lemeshow goodness of fit test, respectively., Conclusions: A nomogram model based on ultrasonography and clinicopathological features predicting NSLNM was established in our study, which is helpful for accurately assessing the risk of NSLNM in invasive breast cancer and providing evidence for individual surgical procedures involving axillary lymph nodes., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://gs.amegroups.com/article/view/10.21037/gs-23-58/coif). The authors have no conflicts of interest to declare., (2023 Gland Surgery. All rights reserved.)

Background: The sentinel lymph node biopsy (SLN) is a basic staging method in all primary cutaneous melanomas ≥pT1b. The standard technique is a triple technique consisting of preoperative lymphoscintigraphy, intraoperative blue-dye lymphography, and gamma-probe assessment. We performed the analysis of long-term results in a very large one-institution series of cutaneous melanoma patients. Methods: We have analyzed treatment results of a group of 1764 consecutive patients with cutaneous melanoma, who underwent SLN biopsy between 1997 and 2008 in one tertiary center. Additionally, we have analyzed the outcomes of a group of 473 patients with positive SLN biopsy undergoing completion lymph node dissection (CLND). Median follow-up time was 5.3 years. Results: Metastases to SLN (SLN+) were found in 19.9 %. Eight-year overall survival (OS) rate in the entire group was 73.5 %, 80 % without SLN metastases (SLN-) and 50 % in group with SLN+ (p < 0.001). Independent prognostic factors for OS were as follows: presence of metastases to SLN, primary tumor ulceration, and higher mitotic index (>5/mm2) of primary tumor. The nodal recurrences in the biopsied lymphatic basin were 5.4 %. The metastases to non-sentinel lymph nodes (NSLN found in 27 % of patients with SLN+) correlated (on multivariable logistic regression analysis) with primary tumor thickness >4 mm, SLN metastatic deposit size >1 mm, and extracapsular involvement of SLN. In an additionally analyzed SLN+ group, the NSLN involvement was related to poorer prognosis (8-year OS rate NSLN- vs NSLN+: 59.6 vs. 34.7 %, respectively). The independent prognostic factors for OS in the SLN+ group were a higher Breslow thickness and ulceration of primary tumor, metastases to more than 1 lymph nodes. Conclusions: The long-term results confirm crucial prognostic significance of SLN biopsy in cutaneous melanoma. We identified factors related to NSLN involvement, which in the future may limit indications for CLND. [ABSTRACT FROM AUTHOR]

Background One-step nucleic acid amplification (OSNA) examines lymph node metastasis in a semiquantitative manner with molecular biology techniques. In this study, we conducted a whole-node analysis of non-sentinel lymph nodes (SLNs) using the OSNA method in SLN metastasis-positive breast cancer patients. Methods With the OSNA method, we compared the rates of positivity of non-SLN metastasis in cases with both SLN micro- and macrometastases. Results The rates of non-SLN metastasis positivity in those with SLN micrometastasis and macrometastasis were 44% and 48%, respectively, and this difference was not significant. When the study of non-SLN metastasis positivity was focused only on macrometastases, the rates of non-SLN metastasis positivity in patients with SLN micrometastasis and macrometastasis were 19% and 22%, respectively, and there was no significant difference. Conclusion Regardless of the copy number of SLN metastases, non-SLN metastases were found in approximately half of the cases. [ABSTRACT FROM AUTHOR]

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, Cerb B2 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. [ABSTRACT FROM AUTHOR]

Background: The necessity of complete axillary lymph node dissection (CALND) after sentinel lymph node biopsy (SLNB) for women with sentinel lymph node metastases is a matter of debate because non-sentinel lymph nodes after CALND contain no further metastases in about 50 % of cases. Our study aims to determine the applicability in our setting of two different validated nomograms to predict axillary lymph node status after SLNB. Methods: We collected data about all women who underwent SLNB in our Department of Surgery from 2007 to 2010, focusing on tumor, patient, and breast characteristics. Data was analyzed by R (version 2.15.2); p < 0.05 was considered significant. Results: Among 511 women who underwent SLNB, 126 received CALND due to sentinel lymph node metastasis, and 73.0 % of these had no further metastatic non-sentinel lymph node. The area under the receiver operating characteristic (ROC) curves for the Memorial Sloan-Kettering Cancer Center (MSKCC) nomogram and the Tenon score were 78.5 % (95 % CI 70.1-86.8 %) and 77.0 % (95 % CI 67.9-86.0 %) ( p = 0.678), respectively. Conclusions: Both the MSKCC nomogram and the Tenon score were predictive for the axillary non-sentinel lymph node status by SLNB. The MSKCC nomogram was the more accurate of the two and the Tenon score was the easier one to apply. [ABSTRACT FROM AUTHOR]

Aim To evaluate whether axillary ultrasound in combination with a biopsy ( AUS +/− Bx) can predict the involvement of the non-sentinel lymph nodes ( NSLN). Methods A review of all operable breast cancer patients who underwent AUS +/− Bx at our tertiary care center from January 2010 to April 2011 was performed. All patients underwent AUS as part of their pre-operative evaluation. If the AUS was suspicious, a fine-needle aspiration or core-needle biopsy was performed. Results Of 88 patients included in our final analysis, 20 (23%) had positive AUS + Bx and underwent axillary lymph node dissection ( ALND) at time of definitive surgery. In all, 68 of the 88 patients (77.3%) had negative AUS +/− Bx and underwent sentinel lymph node ( SLN) Bx at the time of definitive surgery. If the SLN Bx was negative, no further axillary surgery was performed and the NSLN were assumed to be negative. If the SLN Bx was positive, ALND was performed. Of the 68 patients, 62 (91%) had a negative NSLN. Patients with positive AUS + Bx carry a relative risk of 2.02 ( P < 0.00002) of having positive NSLN. Conclusion In operable breast cancer patients, a negative AUS+/− Bx may be a predictor of non-involvement of the NSLN. [ABSTRACT FROM AUTHOR]

Abstract: Background: The complex lymphatic drainage in the head and neck makes sentinel lymph node biopsy (SLNB) for melanomas in this region challenging. This study describes the incidence, and location of additional positive nonsentinel lymph nodes (NSLN) in patients with cutaneous head and neck melanoma following a positive SLNB. Methods: A retrospective review was performed using a single institution prospective database. Patients with a primary melanoma in the head or neck with a positive cervical SLNB were identified. The lymphadenectomy specimen was divided intraoperatively into lymph node levels I–V, and NSLN status determined for each level. Results: Of 387 patients with melanoma of the head and neck who underwent cervical SLNB, 54 had a positive SLN identified (14%). Thirty six patients (67%) underwent immediate completion lymph node dissection (CLND) of whom eight patients (22%) had a positive NSLN. The remaining 18 patients (33%) did not undergo CLND and were observed. Half of positive NSLNs (50%) were in the same lymph node level as the SLN and 33% were in an immediately adjacent level; only two patients were found to have NSLNs in non-adjacent levels. The only factor predictive of NSLN involvement was the size of the tumor deposit in the SLN>0.2 mm (p = 0.05). Superficial parotidectomy at CLND revealed metastatic melanoma only in patients with a positive parotid SLN. Conclusions: A positive NLSN was identified in 22% of patients undergoing CLND after a positive SLNB. The majority of positive NSLNs are found within or immediately adjacent to the nodal level containing the SLN. [Copyright &y& Elsevier]

Introduction: The one-step nucleic acid amplification (OSNA) is a molecular procedure that yields a semiquantitative result for detection of nodal metastasis. Size of metastasis in the sentinel lymph node (SLN) by conventional histology has been described as a predictive factor for additional axillary metastasis. The objective of this study is to quantify intraoperatively the total tumoral load (TTL) in the positive SLNs assessed by OSNA and to determine whether this TTL predicts non-SLN metastasis in patients with clinically node negative early stage breast cancer. Methods: 306 patients with cT1-3N0 invasive breast cancer who had undergone intraoperative SLN evaluation by OSNA were included. TTL was defined as the addition of CK19 mRNA copies of each positive SLN (copies/μL). Results: TTL was a predictive factor of additional non-SLN metastasis in the complete axillary lymph node dissection (cALND) (OR, 1.67; 95% CI, 1.18–2.35). In the multivariate analysis, the TTL was a predictor of non-SLN metastasis in HR positive patients (OR, 1.69; 95% CI, 1.19–2.41). In our cohort of patients, with a TTL ≤1.2 × 105 copies/μL, there was a specificity of 85.3% and negative predictive value (NPV) of 80%. If we consider only the HR positive patients, with a TTL ≤5 × 105 copies/μL there was a specificity of 86.7% and NPV of 83.7%. Conclusions: TTL assessed by OSNA assay predicts for additional non-SLN metastasis and this intraoperative tool can help guiding decisions on performing a cALND in breast cancer patients. [ABSTRACT FROM AUTHOR]

To reduce the morbidity of complementary axillary lymph node dissection and the reoperation rate after sentinel lymph node (SN) biopsy, the use of predictive models of metastatic non-SN in case of positive SN can be useful. Before being used in routine, these models have to be validated in independent populations based on discrimination and calibration. However, the main issue is their clinical utility based not only on the low false negative rate but also on its potential to discriminate patients with a low risk of non-SN involvement. This article is intended to recall the different types of predictive models used, their definition and to present and compare different published models to estimate the risk of invasion of non-SN in case of positive SN. [ABSTRACT FROM AUTHOR]

To present a systemic review and meta-analysis to evaluate the nomograms developed to predict non-sentinel lymph node (NSLN) metastasis in breast cancer patients. We focused on the six nomograms (Cambridge, MSKCC, Mayo, MDA, Tenon, and Stanford) that are the most widely validated. The AUCs were converted to odds ratios for the meta-analysis. In total, the Cambridge, Mayo, MDA, MSKCC, Stanford, and Tenon models were validated in 2,156, 2,431, 843, 8,143, 3,700, and 3,648 patients, respectively. The pooled AUCs for the Cambridge, MDA, MSKCC, Mayo, Tenon, and Stanford models were 0.721, 0.706, 0.715, 0.728, 0.720, and 0.688, respectively. Subgroup analysis revealed that in populations with a higher micrometastasis rate in the SLNs, the Tenon and Stanford models had a significantly higher predictive accuracy. A meta-regression analysis revealed that the SLN micrometastasis rate, but not the NSLN-positivity rate, was associated with improved predictive accuracy in the Tenon and Stanford models. The performance of the MSKCC and Cambridge models was not influenced by these two factors. All of these prediction models perform better than random chance. The Stanford model seems to be relatively inferior to the other models. The accuracy of the Tenon and Stanford models is influenced by the tumor burden in the SLNs. [ABSTRACT FROM AUTHOR]

Background: T1-2 breast cancer patients with only one sentinel lymph node (SLN) metastasis have an extremely low non-SLN (NSLN) metastatic rate and are favorable for axillary lymph node dissection (ALND) exemption. This study aimed to construct a nomogram-based preoperative prediction model of NSLN metastasis for such patients, thereby assisting in preoperatively selecting proper surgical procedures., Methods: A total of 729 T1-2 breast cancer patients with only one SLN metastasis undergoing sentinel lymph node biopsy and ALND were retrospectively selected from Harbin Medical University Cancer Hospital between January 2013 and December 2020, followed by random assignment into training (n=467) and validation cohorts (n=262). A nomogram-based prediction model for NSLN metastasis risk was constructed by incorporating the independent predictors of NSLN metastasis identified from multivariate logistic regression analysis in the training cohort. The performance of the nomogram was evaluated by the calibration curve and the receiver operating characteristic (ROC) curve. Finally, decision curve analysis (DCA) was used to determine the clinical utility of the nomogram., Results: Overall, 160 (21.9%) patients had NSLN metastases. Multivariate analysis in the training cohort revealed that the number of negative SLNs (OR: 0.98), location of primary tumor (OR: 2.34), tumor size (OR: 3.15), and lymph-vascular invasion (OR: 1.61) were independent predictors of NSLN metastasis. The incorporation of four independent predictors into a nomogram-based preoperative estimation of NSLN metastasis demonstrated a satisfactory discriminative capacity, with a C-index and area under the ROC curve of 0.740 and 0.689 in the training and validation cohorts, respectively. The calibration curve showed good agreement between actual and predicted NSLN metastasis risks. Finally, DCA revealed the clinical utility of the nomogram., Conclusion: The nomogram showed a satisfactory discriminative capacity of NSLN metastasis risk in T1-2 breast cancer patients with only one SLN metastasis, and it could be used to preoperatively estimate NSLN metastasis risk, thereby facilitating in precise clinical decision-making on the selective exemption of ALND in such patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Liu, Lin, Li, Zhang, Zhang, Wu, Wang, Yang and Xu.)

Abstract: Objective: In the study, our aim was to evaluate the predictability of four different nomograms on non-sentinel lymph node metastases (NSLNM) in breast cancer (BC) patients with positive sentinel lymph node (SLN) biopsy in a multi-center study. Methods: We identified 607 patients who had a positive SLN biopsy and completion axillary lymph node dissection (CALND) at seven different BC treatment centers in Turkey. The BC nomograms developed by the Memorial Sloan Kettering Cancer Center (MSKCC), Tenon Hospital, Cambridge University, and Stanford University were used to calculate the probability of NSLNM. Area under (AUC) Receiver Operating Characteristics Curve (ROC) was calculated for each nomogram and values greater than 0.70 were accepted as demonstrating good discrimination. Results: Two hundred and eighty-seven patients (287) of 607 patients (47.2%) had a positive axillary NSLNM. The AUC values were 0.705, 0.711, 0.730, and 0.582 for the MSKCC, Cambridge, Stanford, and Tenon models, respectively. On the multivariate analysis; overall metastasis size (OMS), lymphovascular invasion (LVI), and proportion of positive SLN to total SLN were found statistically significant. We created a formula to predict the NSLNM in our patient population and the AUC value of this formula was 0.8023. Conclusions: The MSKCC, Cambridge, and Stanford nomograms were good discriminators of NSLNM in SLN positive BC patients in this study. A newly created formula in this study needs to be validated in prospective studies in different patient populations. A nomogram to predict NSLNM in patients with positive SLN biopsy developed at one institution should be used with caution. [Copyright &y& Elsevier]

Abstract: Aims: Sentinel lymph node (SLN) -positive melanoma patients are usually recommended completion lymph node dissection (CLND) with the aim to provide regional disease control and improve survival. Nevertheless, only 20% these patients have additional metastases in non-sentinel lymph nodes (NSLN), indicating that CLND may be unnecessary in the majority of patients. In this retrospective study, we (i) sought to identify clinico-pathological features predicting NSLN status, as well as disease-free (DFS) and -specific (DSS) survival and (ii) evaluated the applicability of previously published algorithms, which were able to define a group of patients at zero-risk for NSLN-metastasis. Methods: This analysis included 504 consecutive melanoma patients stage I and II who underwent successful SLN-biopsy (SLNB) at our institute between 1998 and 2005. Metastatic SLN were re-evaluated for tumor burden and categorized according to two different micro-anatomic classifications and the S/U-score (Size of the sentinel node metastasis >2mm/Ulceration of the primary melanoma) was assessed. DFS and DSS were calculated for all analyses. Results: Out of 504 melanoma patients stage I or II, 85 (17%) were SLN-positive and 18 of 85 (21%) were found with positive NSLN in the CLND specimen. Median follow-up was 31months. Neither primary tumor characteristics (age, gender, Clark level, Breslow thickness, ulceration of the primary melanoma, site and histological subtype of the primary melanoma), nor features of the sentinel node tumor (number and site of draining lymph node basins, number of positive sentinel nodes and size of sentinel node tumor (<2mm vs. ≥2mm) were able to predict additional positive lymph nodes in the CLND specimen. Likewise the implementation of published algorithms was not able to identify patients at negligible risk for harboring NSLN metastases. Upon univariate analysis, disease-free survival in SLN-positive patients was correlated with Breslow thickness, sentinel node tumor size >2mm and S/U score. In respect to disease-specific survival the significant prognostic parameters were Breslow thickness, ulceration, sentinel node tumor size >2mm and the S/U score. After a median follow-up of 31months recurrence rates (37% vs. 78%, p =0.02) and death from disease (24% vs. 50%, p <0.01) were significantly different in patients with SLN-metastasis only as compared to patients with NSLN-metastasis. Conclusion: NSLN status cannot be predicted in this data analysis by using clinico-pathological characteristics. Therefore, CLND is recommended for all patients after positive SLNB pending the results of the second Multicenter Selective Lymphadenectomy Trial. [Copyright &y& Elsevier]

Abstract: This study aimed at identifying factors related to sentinel lymph node (SLN) involvement in patients with tubular, cribriform, mucinous or papillary breast carcinoma and those related to non-SLN metastases if an SLN was positive. Multivariate analyses involved logistic and stepwise regressions. The SLNs harboured metastases in 85 of 572 cases, 78 of whom underwent axillary dissection; 19 presented non-SLN positive disease. Lack of lymphovascular invasion, a tumour size ⩽10mm and a single SLN removed were the factors predicting an SLN metastasis rate <10%, and patients with these features could be candidates for no surgical axillary staging. A positive SLN proportion of ⩽50% and no lymphovascular invasion were associated with a <10% rate of non-SLN invasion; patients with a positive SLN and these features could be candidates for the omission of completion axillary dissection. The opposite presentation of these factors would mandate SLN biopsy and axillary dissection, respectively. [Copyright &y& Elsevier]

Sentinel lymph node biopsy has been demonstrated to be an effective staging procedure since its introduction in 1992. The new American Joint Committee on Cancer (AJCC) classification did not consider the lack of information that would result from the less usage of the complete lymph node dissection as for a diagnostic purpose. Thus, this makes it difficult the correct staging and would leave about 20% of the further positive non-sentinel lymph nodes in the lymph node basin. In this paper, we aim to describe a new surgical technique that, combined with single-photon emission computed tomography-computed tomography (SPECT-CT), allows for better staging of melanoma patients. This is a prospective study that includes 104 patients with cutaneous melanoma. Sentinel lymph node biopsy was offered according to the AJCC guideline. Planar lymphoscintigraphy was performed in association with SPECT-CT, identifying and removing all non-biologically "excluded" lymph nodes, guiding the surgeon's hand in detection and removal of lymph nodes. Even if identification and removal of non-sentinel lymph nodes is unable to increase overall survival, it definitely gives better disease control in the basin. With a "classic" setting, the risk of leaving further lymph nodes out of the sentinel lymph node procedure is around 20%, thus, basically, the surgical sentinel lymph node of first and second lymph nodes would have therapeutic value and complete lymph node dissection classically performed. [ABSTRACT FROM AUTHOR]

Background and Objectives: Of clinically node-negative (cN0) cutaneous melanoma patients with sentinel lymph node (SLN) metastasis, between 10% and 30% harbor additional metastases in non-sentinel lymph nodes (NSLNs). Approximately 80% of SLN-positive patients have a single positive SLN., Methods: To assess whether state-of-the-art clinicopathologic models predicting NSLN metastasis had adequate performance, we studied a single-institution cohort of 143 patients with cN0 SLN-positive primary melanoma who underwent subsequent completion lymph node dissection. We used sensitivity (SE) and positive predictive value (PPV) to characterize the ability of the models to identify patients at high risk for NSLN disease., Results: Across Stage III patients, all clinicopathologic models tested had comparable performances. The best performing model identified 52% of NSLN-positive patients (SE = 52%, PPV = 37%). However, for the single SLN-positive subgroup (78% of cohort), none of the models identified high-risk patients (SE > 20%, PPV > 20%) irrespective of the chosen probability threshold used to define the binary risk labels. Thus, we designed a new model to identify high-risk patients with a single positive SLN, which achieved a sensitivity of 49% (PPV = 26%)., Conclusion: For the largest SLN-positive subgroup, those with a single positive SLN, current model performance is inadequate. New approaches are needed to better estimate nodal disease burden of these patients., (© 2021 The Authors. Journal of Surgical Oncology published by Wiley Periodicals LLC.)

Objective: To investigate the relationship between platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR) and axillary lymph node metastasis in cT1N0 breast cancer patients., Methods: The clinicopathological data of 154 patients with cT1N0 breast cancer from January 2015 to June 2020 were retrospectively analyzed. All patients underwent sentinel lymph node (SLN) biopsy. The differences of PLR and NLR levels among groups with different clinicopathological factors (age, tumor size, ER, PR, HER-2, Ki67, p53 expression levels, vascular tumor thrombus and SLN metastasis) were compared. The relationship between clinicopathological factors and metastasis of SLN and non-SLN was analyzed., Results: There were 32 patients with SLN metastasis. The cut-off values of PLR and NLR for the whole group were 142.91 and 2.84. The PLR level was higher in patients with vascular tumor thrombus and SLN metastasis (P<0.05), and the NLR level was higher in patients with P53 negative and SLN metastasis groups (P<0.05). According to univariate analysis, there were significant differences in SLN metastasis among different tumor sizes, vascular tumor thrombus states, PLR and NLR levels (P<0.05), but there was no significant difference in SLN metastasis among patients with different ages, ER, PR, HER-2, Ki67, p53 expression groups (P>0.05). According to multivariate analysis, the risk of SLN metastasis in patients with vascular tumor thrombus was higher than that in patients without vascular tumor thrombus (P<0.05). The risk of SLN metastasis in patients with high level of PLR was higher than that in patients with low level of PLR (P<0.05). The difference was not significant in SLN metastasis status among patients with different ages and ER, PR, HER-2, Ki67, p53 expression and NLR level (P>0.05)., Conclusion: High level of PLR and vascular tumor thrombus are the risk factors for SLN metastasis., Competing Interests: None., (AJTR Copyright © 2021.)

Objective: To analyze the predictive factors for non-sentinel lymph node (non-SLN) metastasis in early-stage cervical cancer., Methods: We analyzed a series of 113 patients who underwent sentinel lymph node (SLN) mapping for cervical cancer. The SLNs were examined by immunohistochemistry (IHC) when the hematoxylin-eosin stain was negative., Results: The overall bilateral detection rate was 81.5%, with a median of two SLNs resected. The study ultimately included 92 patients with SLNs that were mapped who had also undergone systematic pelvic lymph node dissection. Thirteen (14.1%) patients had positive SLNs, with a median of one positive SLN. Regarding the size of SLN metastasis, one (1.1%) had isolated tumor cells (ITC), seven (7.6%) had micrometastases, and five (5.4%) had macrometastases. Notably, 46.1% (6/13) had lymph node metastases detected only after IHC. Five (38.5%) cases had positive non-SLNs, with a median count of one positive lymph node. Parametrial invasion was the only risk factor for positive non-SLN (p = .045). Regarding the size of SLN metastasis, non-SLN involvement was present in the only case with ITC (1/1), 42.9% (3/7) of cases with micrometastases, and in 20% (1/5) with macrometastases., Conclusions: Our data suggest that parametrial invasion correlates with the risk of non-SLN metastasis in cervical cancer., (© 2021 Wiley Periodicals LLC.)

Background: Whether non-sentinel lymph node (SLN)-positive melanoma patients can benefit from completion lymph node dissection (CLND) is still unclear. The current study was performed to identify the prognostic role of non-SLN status in SLN-positive melanoma and to investigate the predictive factors of non-SLN metastasis in acral and cutaneous melanoma patients., Methods: The records of 328 SLN-positive melanoma patients who underwent radical surgery at four cancer centers from September 2009 to August 2017 were reviewed. Clinicopathological data including age, gender, Clark level, Breslow index, ulceration, the number of positive SLNs, non-SLN status, and adjuvant therapy were included for survival analyses. Patients were followed up until death or June 30, 2019. Multivariable logistic regression modeling was performed to identify factors associated with non-SLN positivity. Log-rank analysis and Cox regression analysis were used to identify the prognostic factors for disease-free survival (DFS) and overall survival (OS)., Results: Among all enrolled patients, 220 (67.1%) had acral melanoma and 108 (32.9%) had cutaneous melanoma. The 5-year DFS and OS rate of the entire cohort was 31.5% and 54.1%, respectively. More than 1 positive SLNs were found in 123 (37.5%) patients. Positive non-SLNs were found in 99 (30.2%) patients. Patients with positive non-SLNs had significantly worse DFS and OS (log-rank P < 0.001). Non-SLN status (P = 0.003), number of positive SLNs (P = 0.016), and adjuvant therapy (P = 0.025) were independent prognostic factors for DFS, while non-SLN status (P = 0.002), the Breslow index (P = 0.027), Clark level (P = 0.006), ulceration (P = 0.004), number of positive SLNs (P = 0.001), and adjuvant therapy (P = 0.007) were independent prognostic factors for OS. The Breslow index (P = 0.020), Clark level (P = 0.012), and number of positive SLNs (P = 0.031) were independently related to positive non-SLNs and could be used to develop more personalized surgical strategy., Conclusions: Non-SLN-positive melanoma patients had worse DFS and OS even after immediate CLND than those with non-SLN-negative melanoma. The Breslow index, Clark level, and number of positive SLNs were independent predictive factors for non-SLN status., (© 2020 The Authors. Cancer Communications published by John Wiley & Sons Australia, Ltd. on behalf of Sun Yat-sen University Cancer Center.)

Objective: To identify the risk factors of non-sentinel lymph node (nSLN) metastasis in breast cancer patients with 1~2 positive axillary sentinel lymph node (SLN) and construct an accurate prediction model. Methods: Retrospective chart review was performed in 917 breast cancer patients who underwent surgery treatment between 2002 and 2017 and pathologically confirmed 1-2 positive SLNs. According to the date of surgery, patients were divided into training group (497 cases) and validation group (420 cases). A nomogram was built to predict nSLN metastasis and the accuracy of the model was validated. Results: Among the 917 patients, 251 (27.4%) had nSLN metastasis. Univariate analysis showed tumor grade, lymphovascular invasion (LVI), extra-capsular extension (ECE), the number of positive and negative SLN and macro-metastasis of SLN were associated with nSLN metastasis (all P <0.05). Multivariate Logistic regression analysis showed the numbers of positive SLN, negative SLN and macro-metastasis of SLN were independent predictors of nSLN metastasis (all P <0.05). A nomogram was constructed based on the 6 factors. The area under the receiver operating characteristic curve was 0.718 for the training group and 0.742 for the validation group. Conclusion: We have developed a nomogram that uses 6 risk factors commonly available to accurately estimate the likelihood of nSLN metastasis for individual patient, which might be helpful for radiation oncologists to make a decision on regional nodal irradiation.