The NILS study protocol - a retrospective validation study of a preoperative decision-making tool for non-invasive lymph node staging in women with primary breast cancer [ISRCTN14341750]

Abstract

Background Routine preoperative axillary ultrasonography has proven insufficient for detecting low-burden nodal metastatic deposits. For the majority of newly diagnosed breast cancer patients presenting with clinical T1-T2 N0 disease, the standard axillary staging by sentinel lymph node biopsy is not therapeutic. The pilot non-invasive lymph node staging (NILS) artificial neural network (ANN) model to predict nodal status was published in 2019. The aim of the current study is to assess the performance measures of the model for the prediction of healthy lymph nodes in clinically N0 breast cancer patients at two breast cancer centers in Sweden. Methods This bicenter, observational, retrospective study has been designed to validate the NILS prediction model for nodal status using preoperatively collected clinicopathological and radiological data. A web-based implementation of the nodal status classifier has been developed and will be used in this study, resulting in an estimated probability of healthy lymph nodes for each study participant. Our primary endpoint is to report on the performance of the NILS prediction model to distinguish between healthy and metastatic lymph nodes (discrimination, N0 vs. N+) and compare the observed and predicted event rates of benign axillary nodal status (calibration). Discussion Internationally, there are numerous artificial intelligence projects involving non-invasive identification of N0 breast cancer. Here, we present a robust validation study based on external cohorts of our ANN model. Although validation is necessary to show generalizability, it is often overlooked. If the accuracy and discrimination reach a satisfactory level, our prediction tool can be implemented to assist medical professionals and breast cancer patients in shared decision-making on omitting sentinel node biopsy in patients predicted to be node-negative. In future, this may potentially save healthcare resources and reduce costs and adverse side effects. In addition, our study might prompt future studies of nodal metastases of malignancies in other organs, and thus might have implications beyond breast cancer. Trial registration This study has been prospectively registered in the ISRCTN registry, identification number: 14341750