Development and validation of prediction models for sentinel lymph node status indicating postmastectomy radiotherapy in breast cancer: population-based study.

Abstract

Background: Postmastectomy radiotherapy (PMRT) impairs the outcome of immediate breast reconstruction in patients with breast cancer, and the sentinel lymph node (SLN) status is crucial in evaluating the need for PMRT. The aim of this study was to develop and validate models to stratify the risk of clinically significant SLN macrometastases (macro-SLNMs) before surgery.

Methods: Women diagnosed with clinically node-negative (cN0) T1-2 breast cancer were identified within the Swedish National Quality Register for Breast Cancer (2014-2017). Prediction models and corresponding nomograms based on patient and tumour characteristics accessible before surgery were developed using adaptive least absolute shrinkage and selection operator logistic regression. The prediction of at least one and more than two macro-SLNMs adheres to the current guidelines on use of PMRT and reflects the exclusion criteria in ongoing trials aiming to de-escalate locoregional radiotherapy in patients with one or two macro-SLNMs. Predictive performance was evaluated using area under the receiver operating characteristic curve (AUC) and calibration plots.

Results: Overall, 18 185 women were grouped into development (13 656) and validation (4529) cohorts. The well calibrated models predicting at least one and more than two macro-SLNMs had AUCs of 0.708 and 0.740, respectively, upon validation. By using the prediction model for at least one macro-SLNM, the risk could be updated from the pretest population prevalence of 13.2% to the post-test range of 1.6-74.6%.

Conclusion: Models based on routine patient and tumour characteristics could be used for prediction of SLN status that would indicate the need for PMRT and assist decision-making on immediate breast reconstruction for patients with cN0 breast cancer.