Preoperative Nomogram for Predicting Sentinel Lymph Node Metastasis Risk in Breast Cancer: A Potential Application on Omitting Sentinel Lymph Node Biopsy

Frontiers in Oncology

Lijuan Yuan¹  Yanming Dong¹  Ping Yang¹  Lin Yang¹  Shujia Peng¹  Xi’E Hu¹  Zhenyu Yang¹  Guoqiang Bao¹  Ting Wang²  Jingyi Xue³ 

[1] Department of General Surgery, The Second Affiliated Hospital of Air Force Medical University, Xi’an, China;Department of Vascular Surgery and Thyroid-Breast Surgery, The First Affiliated Hospital of Air Force Medical University, Xi’an, China;The Second Clinical Medical College, Shaanxi University of Chinese Medicine, Xianyang, China;

关键词: breast cancer;    nomogram;    SLN;    metastasis;    ultrasound;    external validation;   

DOI  :  10.3389/fonc.2021.665240

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown