Prediction of sentinel lymph node status in patients with early breast cancer using breast imaging as an alternative to surgical staging – A systematic review and meta-analysis

Background Prediction models for sentinel lymph node status could offer an alternative to surgical axillary staging in patients with early breast cancer. Several imaging modalities have been used with various approaches to feature engineering. This systematic review and meta-analysis aimed to evaluate prediction models for sentinel lymph node (SLN) status using breast imaging in patients with early breast cancer to summarize the current evidence and to identify areas requiring additional research. Methods The systematic literature search strategy was based on the following Population, Intervention, Comparison, and Outcome (PICO): P: female patients with clinically node-negative invasive breast cancer scheduled to undergo primary surgery; I: breast imaging; C: upfront sentinel lymph node biopsy; and O: prediction model performance regarding SLN status. The search was conducted in PubMed, Embase, Web of Science, Cochrane, and the Cumulative Index to Nursing and Allied Health Literature databases were searched in March 2024. The screening of records, data collection, and bias assessments were performed independently by two reviewers. The risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool and Prediction Model Study Risk of Bias Assessment Tool. A meta-analysis using a random-effects model was performed to assess performance and heterogeneity overall and in subgroups. Results The literature search resulted in the inclusion of 32 articles in the systematic review. Assessments using QUADAS-2 revealed four studies with a high risk of bias, which were excluded from the meta-analysis. The meta-analysis revealed heterogeneity in overall performance and subgroups, except in the magnetic resonance imaging (MRI)-based studies, with a pooled area under the curve of 0.85 (95% confidence interval 0.82–0.87). Meta-regression analyses indicated that MRI, including only one imaging modality, and model calibration assessment upon validation contributed to the heterogeneity. Conclusions This systematic review and meta-analysis revealed that prediction models using breast imaging, particularly MRI, could be a noninvasive alternative to surgical axillary staging in patients with early breast cancer. The results illustrate the heterogeneity between studies and the need for additional high-quality studies. Systematic review registration PROSPERO CRD42022301852, available at https://www.crd.york.ac.uk/PROSPERO