Dermoscopic Features as Predictors of BRAF Mutational Status and Sentinel Lymph Node Positivity in Primary Cutaneous Melanoma

Dermoscopy is a diagnostic tool widely used in clinical practice for the detection of skin tumors, especially early stages of melanoma. Recent studies have shown that different dermoscopic features are associated with important prognostic parameters of melanoma, such as BRAF mutational status and sentinel lymph node status. More than half of all melanomas harbor a mutation in the BRAF oncogene. The current management of advanced-stage melanomas is greatly determined by the presence or absence of a mutation in this gene, as targeted therapy with BRAF kinase inhibitors is one of the first therapeutic choices for these patients. Sentinel lymph node status is one of the most significant predictors of a melanoma patient’s survival. Recent studies have shown that different dermoscopic patterns are also associated with sentinel lymph node status. This short article reviews studies that investigated correlations between dermoscopic features, BRAF mutation status and sentinel lymph node status.

Regional Lymph Node Metastases in Cutaneous Melanoma: A Single-Center Analysis from Southeast Europe

Objective: Sentinel lymph node biopsy is the standard of care for nodal staging in clinically node-negative melanoma patients. Our goal was to present 10-year results of sentinel lymph node biopsy at our institution and to evaluate the clinicopathologic factors as potential predictors of sentinel lymph node and non-sentinel lymph node metastatic involvement in patients with cutaneous melanoma. Methods: We have analyzed clinicopathologic and lymphoscintigraphic characteristics in 420 patients with cutaneous melanoma who underwent sentinel lymph node biopsy between 2010 and 2019. In addition, we have examined the results of group of patients with positive sentinel lymph node biopsy undergoing complete lymph node dissection. Results: The overall detection rate of sentinel lymph node biopsies was 97.1%, of which 18.8% was metastatic. Drainage to one regional basin was seen in 345 patients (83.1%) and to multiple drainage regions in 71 patients (17%). In-transit lymph nodes were detected in 20 patients. On univariate logistic regression analysis, male gender, primary tumor thickness with nodular histology, acral location, presence of ulceration, and the number of nodes harvested were significantly associated with sentinel lymph node biopsy status ( p < 0.05). On multivariate analysis, the Breslow thickness was the only independent predictor of sentinel lymph node biopsy status. The metastases in non-sentinel lymph node found in 26 patients with positive sentinel lymph node (35.6%) correlated on univariate, as well as on multivariate logistic regression, with tumor subtype and number of sentinel lymph node harvested. Conclusion: In addition to the well-established primary tumor thickness as a predictor of sentinel lymph node biopsy positivity, we observed acral location and nodular melanoma subtype to significantly enhance the risk of metastases in sentinel lymph node(s). Primary tumor histology and number of nodes harvested were the only statistically significant variables predicting the non-sentinel lymph node status on multivariate analysis. Lymphoscintigraphy imaging characteristics were not significantly associated with sentinel lymph node status.

Predicting of Sentinel Lymph Node Status in Breast Cancer Patients with Clinically Negative Nodes: A Validation Study

In the absence of lymph node abnormalities detectable on clinical examination or imaging, the guidelines provide for the dissection of the first axillary draining lymph nodes during surgery. It is not always possible to arrive at surgery without diagnostic doubts, and machine learning algorithms can support clinical decisions. The web calculator CancerMath (CM) allows you to estimate the probability of having positive lymph nodes valued on the basis of tumor size, age, histologic type, grading, expression of estrogen receptor, and progesterone receptor. We collected 993 patients referred to our institute with clinically negative results characterized by sentinel lymph node status, prognostic factors defined by CM, and also human epidermal growth factor receptor 2 (HER2) and Ki-67. Area Under the Curve (AUC) values obtained by the online CM application were comparable with those obtained after training its algorithm on our database. Nevertheless, by training the CM model on our dataset and using the same feature, we reached a sensitivity median value of 72%, whereas the online one was equal to 46%, despite a specificity reduction. We found that the addition of the prognostic factors Her2 and Ki67 could help improve performances on the classification of particular types of patients with the aim of reducing as much as possible the false positives that lead to axillary dissection. As showed by our experimental results, it is not particularly suitable for use as a support instrument for the prediction of metastatic lymph nodes on clinically negative patients.