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Yao, K

Mayo Clinic

Endeavor Health

Citations 2

American Society of Breast Surgeons, Society of Breast Imaging, and College of American Pathology 2026 Guidelines for the Management of Proliferative Lesions With Atypia and Lobular Carcinoma In Situ
Nakhlis, Faina, King, Tari A., Heller, Samantha L., Allison, Kimberly H., Boolbol, Susan, Pass, Helen A., Johnson, Nathalie M., Boughey, JC , Yao, K, Nakhlis, Faina , Bedrosian, Isabelle , Heller, Samantha Lynn , Allison, Kimberly H. , Boolbol, Susan K., Pass, Helen A. , Johnson, Nathalie , Yao, Katharine

JAMA Surgery | August 19, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1001/jamasurg.2026.3552 Get It

Importance Many patients are diagnosed with atypical lesions or lobular carcinoma in situ (LCIS); however, evidence- and consensus-based guidelines for the management of many of these lesions are limited. Observations The American Society of Breast Surgeons, in collaboration with the Society of Breast Imaging and College of American Pathology, assembled a steering group to create guidelines for the management of atypical lesions and LCIS, inclusive of flat epithelial atypia (FEA), atypical ductal hyperplasia (ADH), atypical lobular hyperplasia (ALH), classic LCIS (C-LCIS), and the variant LCIS forms pleomorphic LCIS (P-LCIS) and florid LCIS (F-LCIS). The natural history of ADH, ALH, and C-LCIS suggests that these lesions are associated with an elevated future breast cancer risk; therefore, patients diagnosed with these lesions should be recommended to undergo comprehensive risk assessment and counseling about breast cancer risk-reducing strategies. The magnitude of future breast cancer risk associated with P-LCIS and F-LCIS remains uncertain, yet if these lesions are determined to be hormone receptor positive, risk-reducing medications should be considered. There is no evidence that FEA is associated with an elevated future breast cancer risk. A second pathology review confirmation is recommended for ADH, should be considered for FEA, and is not necessary for ALH or LCIS. Currently available evidence supports the need to diagnostically excise most ADH, P-LCIS, and F-LCIS cases identified on core biopsy, although some ADH cases fulfilling strict criteria and multidisciplinary consensus can be observed. P-LCIS and F-LCIS require a negative margin, but ADH does not. ALH and C-LCIS can be safely observed if the core biopsy diagnosis is concordant with imaging features (ie, radiographic-pathologic concordance is established). Provided radiologic-pathologic concordance is confirmed, diagnostic excision is generally not indicated after a diagnosis of FEA alone. Conclusions and Relevance These guidelines provide evidence-informed, consensus-based recommendations for the management of atypical lesions of the breast, including ADH, ALH, FEA, C-LCIS, P-LCIS, and F-LCIS. Practicing clinicians who treat patients with atypical breast lesions or LCIS should consider integrating these guidelines into clinical management.
MRI-based Prognostic Model in Early-Stage HR+/HER2- Breast Cancer
Howard, Frederick, Stringer‐Reasor, Erica, McMahon, Jennifer, Yao, K, Zhang, Yuhan, Weitz, Michelle, Kannan, Vignesh , Cole, John, Peterson, Joseph, Cook, Daniel, Feiger, Bradley, Boughey, Judy, Goetz, Matthew, Saha, Poornima , Stringer-Reasor, Erica , Abdou, Yara George , Yao, Katharine , Cole, John, Peterson, Joseph, Goetz, Matthew

No container title available | June 28, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.21203/rs.3.rs-9772767/v1 Get It

Abstract Current genomic assays provide prognostic information and guide chemotherapy decisions in early-stage hormone receptor–positive/human epidermal growth factor receptor 2–negative (HR+/HER2−) breast cancer, but limited tissue sampling may incompletely capture tumor heterogeneity. We developed and validated an image-based artificial intelligence (AI) model integrating dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and clinicopathologic features to predict recurrence risk in early-stage HR+/HER2 − breast cancer. In this retrospective multi-institutional study, the model was trained using pre-treatment imaging and clinicopathologic data from 522 patients and independently validated in 550 additional patients treated between 2010 and 2023. By analyzing spatial tumor characteristics, the model generated individualized recurrence risk scores that outperformed clinicopathologic features alone. In the validation cohort, median age was 53 years (range, 24–90), 15.6% of patients self-identified as African American, 89.7% had clinical T1–T2 disease, and 34.4% had 1–3 positive lymph nodes. Five-year recurrence-free survival was 93.8% (95% CI, 90.0–96.2%) among patients classified as low risk compared with 82.6% (95% CI, 74.8–88.1%) among those classified as high risk, corresponding to an adjusted hazard ratio of 2.28. Prognostic performance was maintained across clinically relevant subgroups, including age and nodal status. These findings support the potential of a noninvasive image-based AI approach for real-time prognostication and treatment personalization in early-stage HR+/HER2 − breast cancer.