乳腺癌风险分层对预测恶性程度和指导治疗决策非常关键。尽管细胞增殖在乳腺癌中具有很好的预后价值，但细胞增殖和细胞凋亡之间的相互作用还未明确。本研究假设联合评估细胞增殖指数和细胞凋亡指数可提供更准确的体内生长速率度量和精确的预后预测。 通过计数经过苏木精-伊红染色的1545例乳腺癌病例的全幅图像中的凋亡和有丝分裂细胞，观察它们在特定区域内的分布并进行统计。在有丝分裂和凋亡评分之间存在显著的相关性。高的凋亡细胞计数与恶性的行为特征相关，包括高级别、高多样性分数和激素受体阴性。虽然有丝分裂指数（MI）和凋亡指数（AI）是独立的预后指标，但是当它们结合时，预后价值协同作用更大。具有高联合AI和MI的乳腺癌患者生存时间最短。在诺丁汉分级系统中，用有丝分裂-凋亡指数替代有丝分裂分数，新分数的修改等级具有更高的BC特异性生存显著相关性和更高的危害比值。 因此，当结合MI时，凋亡细胞计数为BC提供了额外的预后价值，这种联合评估可用于评估乳腺癌的恶性程度，提供准确的预后指标。在使用人工智能算法评估乳腺癌增殖时，可以考虑使用此方法。本文受版权保护，版权所有。

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.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.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.This article is protected by copyright. All rights reserved.