有丝分裂指数
细胞凋亡
增殖指数
分级(工程)
乳腺癌
肿瘤科
危险系数
增殖标记
内科学
有丝分裂
医学
生物
癌症
病理
免疫组织化学
置信区间
遗传学
生态学
作者
Asmaa Ibrahim,Michael S. Toss,N Atallah,Mansour Al Saleem,Andrew R. Green,Emad A. Rakha
出处
期刊:Histopathology
[Wiley]
日期:2023-02-13
卷期号:82 (7): 1029-1047
被引量:2
摘要
Aims Breast cancer (BC) risk stratification is critical for predicting behaviour and guiding management decision‐making. Despite the well‐established prognostic value of cellular proliferation in BC, the interplay between proliferation and apoptosis remains to be defined. In this study, we hypothesised that the combined proliferation and apoptosis indices can provide a more accurate in‐vivo growth rate measure and a precise prognostic predictor. Methods and results Apoptotic and mitotic figures were counted in whole slide images (WSI) generated from haematoxylin and eosin‐stained sections of 1545 BC cases derived from two well‐defined BC cohorts. Counts were carried out visually within defined areas. There was a significant correlation between mitosis and apoptosis scores. High apoptotic counts were associated with features of aggressive behaviour, including high grade, high pleomorphism score and hormonal receptor negativity. Although the mitotic index (MI) and apoptotic index (AI) were independent prognostic indicators, the prognostic value was synergistically higher when combined. BC patients with a high combined AI and MI had the shortest survival. Replacing the mitosis score with the mitosis–apoptosis index in the Nottingham grading system revealed that the modified grade with the new score had a higher significant association with BC‐specific survival with a higher hazard ratio. Conclusion Apoptotic figures count provides additional prognostic value in BC when combined with MI; such a combination can be implemented to assess the behaviour of BC and provides an accurate prognostic indicator. This can be considered when using artificial intelligence algorithms to assess proliferation in BC.
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