Abstract
BackgroundSentinel lymph node (SLN) biopsy is feasible for breast cancer (BC) patients with clinically negative axillary lymph nodes; however, complications develop in some patients after surgery, although SLN metastasis is rarely found. Previous predictive models contained parameters that relied on postoperative data, thus limiting their application in the preoperative setting. Therefore, it is necessary to find a new model for preoperative risk prediction for SLN metastasis to help clinicians facilitate individualized clinical decisions.Materials and MethodsBC patients who underwent SLN biopsy in two different institutions were included in the training and validation cohorts. Demographic characteristics, preoperative tumor pathological features, and ultrasound findings were evaluated. Multivariate logistic regression was used to develop the nomogram. The discrimination, accuracy, and clinical usefulness of the nomogram were assessed using Harrell’s C-statistic and ROC analysis, the calibration curve, and the decision curve analysis, respectively.ResultsA total of 624 patients who met the inclusion criteria were enrolled, including 444 in the training cohort and 180 in the validation cohort. Young age, high BMI, high Ki67, large tumor size, indistinct tumor margins, calcifications, and an aspect ratio ≥1 were independent predictive factors for SLN metastasis of BC. Incorporating these parameters, the nomogram achieved a robust predictive performance with a C-index and accuracy of 0.92 and 0.85, and 0.82 and 0.80 in the training and validation cohorts, respectively. The calibration curves also fit well, and the decision curve analysis revealed that the nomogram was clinically useful.ConclusionsWe established a nomogram to preoperatively predict the risk of SLN metastasis in BC patients, providing a non-invasive approach in clinical practice and serving as a potential tool to identify BC patients who may omit unnecessary SLN biopsy.
Highlights
Breast cancer (BC) is the most frequently diagnosed malignant tumor among women worldwide
1205 consecutive patients diagnosed with BC based on preoperative pathology underwent Sentinel lymph node (SLN) biopsy (SLNB)
There were no significant differences in age, BMI, menstrual status, lesion position, lymph node (LN) stage, histological type, estrogen receptor (ER) status, progesterone receptor (PR) status, Ki67, Breast Imaging Reporting and Data System (BI-RADS), tumor shape, and color Doppler flow between the training and validation cohorts; differences in some clinicopathologic characteristics were observed in patients of these two cohorts owing to the spatial span of the different institutions, according to our study
Summary
Breast cancer (BC) is the most frequently diagnosed malignant tumor among women worldwide. Identified as the first station of LN metastasis in BC, sentinel lymph nodes (SLNs) play a significant role in breast tumor invasion [3]. SLN biopsy (SLNB) is a standard method for determining the metastatic status of ALN and assists clinicians in developing individualized treatment regimens. An appropriate predictive nomogram is required to distinguish BC patients with a lower risk of SLN metastases from those at higher risk preoperatively to help doctors determine whether their patients could avoid SLNB. Sentinel lymph node (SLN) biopsy is feasible for breast cancer (BC) patients with clinically negative axillary lymph nodes; complications develop in some patients after surgery, SLN metastasis is rarely found. It is necessary to find a new model for preoperative risk prediction for SLN metastasis to help clinicians facilitate individualized clinical decisions
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