Interobserver consistency and diagnostic challenges in HER2-ultralow breast cancer: a multicenter study.

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Tác giả: C Cai, J He, Z Li, B Liu, H Liu, X Liu, Y Liu, J Miao, W Pang, Y Sang, J Shang, Q Shao, P Wang, X Wang, Y Wang, S Wu, X Xu, J Yan, M Yue, Y Zhang, Z Zhang, M Zhao

Ngôn ngữ: eng

Ký hiệu phân loại: 133.594 Types or schools of astrology originating in or associated with a

Thông tin xuất bản: England : ESMO open , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 581756

 BACKGROUND: Recent advancements in novel antibody-drug conjugates (ADCs) have demonstrated efficacy in patients with human epidermal growth factor receptor 2 (HER2)-ultralow breast cancer (BC), expanding the eligibility for anti-HER2 targeted therapy to include some patients previously categorized as HER2 immunohistochemistry (IHC) 0. This expansion underscores the need for pathologists to accurately differentiate HER2-null and HER2-ultralow. MATERIALS AND METHODS: Thirty-six pathologists from four centers nationwide conducted microscopic visual assessments on HER2 IHC slides from 50 consecutive BC surgical specimens, all previously diagnosed as HER2 IHC 0. RESULTS: The interobserver consistency in differentiating HER2-null from HER2-ultralow, measured by Fleiss κ, was only 0.230-lower than the consistency for combined HER2 IHC 0 cases (Fleiss κ = 0.344) and binary classification (HER2-null versus HER2-non-null
  Fleiss κ = 0.292). High agreement for HER2-null versus HER2-ultralow differentiation was achieved in only 4% of cases, while combining them into HER2 IHC 0 raised high agreement cases to 32%, higher than the 18% seen in the binary classification. Consensus among the 36 pathologists aligned with historical scores in 72% of cases
  however, when subdividing HER2 IHC 0 into HER2-null and HER2-ultralow, the consistency dropped to 54%. CONCLUSIONS: The low consistency among pathologists in distinguishing HER2-null, -ultralow, and 1+ cases may impact patient eligibility for new ADC therapies. To address this challenge, there is a need for improved detection methods, artificial intelligence-assisted quantitative assessments, and larger clinical datasets to refine the definition of HER2-ultralow.
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