Authors
V V Kometova, L M Mikhaleva, V V Rodionov, M V Rodionova, L A Ashrafyan
Published in
Arkhiv patologii. Volume 88. Issue 3. Pages 92-97.
Abstract
Breast cancer (BC) is a complex, clinically and morphologically heterogeneous disease for which integral morphological and molecular genetic parameters are of key importance. This paper describes the evolution of semiquantitative tumor grading systems, beginning with the classical Greenough, Patey-Scarff, and Bloom-Richardson systems and ending with modern mathematical methods based on the grade of BC malignancy. Integral prognostic indices are presented in detail, including the Nottingham Prognostic Index (NPI), its modifications (NPI+, METASTASIS), the Total malignancy score (TMS), as well as new digital models and artificial intelligence algorithms predicting lymph node metastasis (LN) and response to therapy. The advantages of these indices in risk stratification and treatment selection are highlighted, as are their limitations related to tumor heterogeneity, dependence on research methods, and the need for integration with molecular genetic testing and digital technologies to further improve a personalized approach to breast cancer patient care. The following open scientific online resources were used to search for literature sources: PubMed, eLibrary, and the National Library of Medicine. Sources were selected using keywords (indicated in the appropriate field) and publication dates.
PMID:
42313850
Bibliographic data and abstract were imported from PubMed on 19 Jun 2026.
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