Performance of four published risk models to predict sentinel lymph-node involvement in Australian women with early breast cancer

Background: Sentinel lymph-node biopsy has reduced the need for extensive axillary surgery for staging. It still exposes women to associated morbidity. Risk models that use clinical and pathology information of the primary tumour to predict sentinel lymph-node metastasis may allow further improvements in care. This study assessed the performance of four published risk models for predicting sentinel lymph-node metastasis in Australian women with early breast cancer; including one model developed in an Australian population. Methods: The Sentinel Node Biopsy Versus Axillary Clearance (SNAC) trial dataset was used to assess model discrimination by calculating the area under the receiver-operating-characteristic curve (AUC) and the false-negative rate for sentinel lymph-node metastasis using model-predicted risk cut-points of 10%, 20%, 30%, and calibration using Hosmer-Lemeshow tests and calibration plots. Results: The sentinel node was positive in 248 of 982 (25.2%) women (158 macrometastasis, 90 micrometastasis). The AUCs of risk models ranged from 0.70 to 0.74 for prediction of any sentinel-node metastasis; 0.72 to 0.75 for macrometastasis. Calibration was poor for the three models developed outside of Australia (lack-of-fit statistics, P < 0.001). For women with a model-predicted risk of sentinel lymph-node metastasis <= 10%, observed risk was 0-13% (three models <10%), false-negative rate 0-9%; 1 -17% of women were classified in this range. Conclusion: All four models showed good discrimination for predicting sentinel lymph-node metastasis, in particular for macrometastasis. With further development such risk models could have a role in the provision of reassurance to low risk women with normal nodes sonographicaally for whom no axillary surgery is contemplated. (C) 2018 Published by Elsevier Ltd.