Development and Validation of Prediction Models for Sentinel Lymph Node Status Indicating Postmastectomy Radiotherapy in Breast Cancer: a Population-Based Study of 18 185 Women

BackgroundPostmastectomy radiotherapy (PMRT) impairs the outcome of immediate breast reconstruction (IBR) in patients with breast cancer, and the sentinel lymph node (SLN) status is crucial in evaluating the need for PMRT. This study aimed to develop models to preoperatively predict the risk for SLN metastasis indicating the need for PMRT. MethodsWomen diagnosed with clinically node-negative (cN0) T1-T2 breast cancer from January 2014 to December 2017 were identified within the Swedish National Quality Register for Breast Cancer. Nomograms for nodal prediction based on preoperatively accessible patient and tumor characteristics were developed using adaptive LASSO logistic regression. The prediction of [≥]1 and >2 SLN macrometastases (macro-SLNMs) adheres to the current guidelines on use of PMRT and reflects the exclusion criteria in ongoing clinical trials aiming to de-escalate locoregional radiotherapy in patients with 1-2 macro-SLNMs, respectively. Predictive performance was evaluated using area under the receiver operating characteristic curve (AUC) and calibration plots. ResultsOverall, 18 185 women were grouped into training (n =13 656) and validation (n = 4529) cohorts. The well-calibrated nomograms predicting [≥]1 and >2 macro-SLNMs displayed AUCs of 0.708 and 0.740, respectively, upon validation. By using the nomogram for [≥]1 macro-SLNMs, the risk could be updated from the pre-test population prevalence 13% to the post-test range 2%-75%. ConclusionNomograms based on routine patient and tumor characteristics could be used for prediction of SLN status that would indicate PMRT need and assist the decision-making on IBR for patients with cN0 breast cancer.