Preoperative predictive factors affecting sentinel lymph node positivity in breast cancer and comparison of their effectiveness with existing nomograms

Abstract

This study aimed to establish a strong regression model by revealing the preoperative predictive factors for sentinel lymph node (SLN) positivity in patients with early stage breast cancer (ESBC). In total, 445 patients who underwent SLN dissection for ESBC were included. All data that may be potential predictors of SLN positivity were retrospectively analyzed. Tumor size >2 cm, human epidermal growth factor receptor 2 (HER2) + status, lymphovascular invasion (LVI), palpable tumor, microcalcifications, multifocality or multicentricity, and axillary ultrasonographic findings were defined as independent predictors of SLN involvement. The area under the receiver operating characteristic (ROC) curve (AUC) values were 0.797, 0.808, and 0.870 for the Memorial Sloan-Kettering Cancer Center (MSKCC) nomogram, MD Anderson Cancer Center (MDACC) nomogram, and our regression model, respectively (P < .001). The recent model for predicting SLN status in ESBC was found to be stronger than existing nomograms. Parameters not included in current nomograms, such as palpable tumors, microcalcifications, and axillary ultrasonographic findings, are likely to make this model more meaningful.

Construction and validation of a nomogram prediction model for axillary lymph node metastasis of cT1 invasive breast cancer

“…Some studies have also reported that the size of a breast mass is also one of the most important factors that affect axillary lymph node metastasis (Ceylan et al, 2022), but in this study, the size of the breast tumor was not an independent factor for predicting axillary lymph node metastasis. It may be because the patients included in this study all had cT1 invasive breast cancer, the largest tumor diameter was less than or equal to 2 cm, and most of the previous studies included patients with cT2 invasive breast cancer.…”

Prediction of sentinel lymph node metastasis in breast cancer patients based on preoperative features: a deep machine learning approach

“…Viale et al, Bevilacqua et al, and Hassan et al proposed the same association between progesterone receptor status and SLN metastasis, and Ceylan et al proposed HER-2 status association with SLN metastasis. Bevilacqua et al and Hassan et al also proposed the association of estrogen receptor status 22 , 24 , 27 , 36 . All these studies used logistic regression analysis to develop their model, except Hassan et al model, which was developed using a support vector machine.…”

“…Accurate prediction of SLN involvement is essential in helping physicians make informed treatment decisions. Studies evaluated several factors and their relevance in predicting SLN involvement in breast cancer patients 22 – 27 . Despite advances observed in the literature, accurately predicting SLN involvement remains challenging due to the condition’s complexity and the lack of adequate interpretation and data analysis.…”

“…Despite advances observed in the literature, accurately predicting SLN involvement remains challenging due to the condition’s complexity and the lack of adequate interpretation and data analysis. Conventional data-driven prediction methods have been proposed in nomogram design models and based on a combination of risk factors 27 . Yet, the generalizability and reliability of these proposed methods have been questioned due to the small sample size and lack of proper validation 28 , 29 .…”

Development and validation of nomograms for predicting axillary non-SLN metastases in breast cancer patients: A retrospective analysis

“…There is a great deal of variation in its predictive value among different populations. The MSKCC nomogram has been tested in many studies; some reported that the MSKCC nomogram had an AUC ranging from 0.73 to 0.80 (16,17), but research from China reported values ranging from 0.677 to 0.688 (18)(19)(20). Likely due to the smaller validated sample size, these Chinese studies showed predictive abilities that were lower than those of the original research study.…”