Performance of a clinical and imaging-based multivariate model as decision support tool to help save unnecessary surgeries for high-risk breast lesions.

Of 699 HRL in 652 patients, 525(75%) had reference standard available, and 48/525(9.1%) showed cancer at surgical excision. Excision (84.5% vs 51.1%) and upgrade (17.6%vs1.8%) rates were higher in HR-I compared to HR-II (p < 0.01). In HR-I, small needle size < 12G vs ≥ 12G [32.1% vs 13.2%, p < 0.01] and less cores [< 6 vs ≥ 6, 28.6%vs13.7%, p = 0.01] were significantly associated with higher cancer upgrades. Our multivariate model had an AUC = 0.87, saving 28.1% of benign surgeries with 100% sensitivity, based on HRL subtype, lesion size(mm, continuous), needle size (< 12G vs ≥ 12G) and biopsy modality (US vs MRI vs stereotactic) CONCLUSION: Our multivariate model using lesion size, needle size and patient age had a high diagnostic performance in decreasing unnecessary surgeries and shows promise as a decision support tool.