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评估Ki-67在乳腺癌患者对新辅助化疗反应中的预测作用。

Assessment of the Predictive Role of Ki-67 in Breast Cancer Patients' Responses to Neoadjuvant Chemotherapy.

作者信息

Rais Ghizlane, Mokfi Rania, Boutaggount Farah, Maskrout Meryem, Bennour Soundouss, Senoussi Chaymae, Rais Fadoua

机构信息

Department of Medical Oncology CHU Souss Massa, Biomed Laboratory, University Ibn Zohr Agadir Faculty of Medicine and Pharmacy of Agadir, Morocco.

Department of Medical Oncology CHU Souss Massa, University Ibn Zohr Agadir Faculty of Medicine and Pharmacy of Agadir, Agadir, Morocco.

出版信息

Eur J Breast Health. 2024 Jul 1;20(3):199-206. doi: 10.4274/ejbh.galenos.2024.2024-3-8.

DOI:10.4274/ejbh.galenos.2024.2024-3-8
PMID:39257012
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11589294/
Abstract

OBJECTIVE

Neoadjuvant chemotherapy (NAC) in breast cancer (BC) is being considered for a broader range of cases, including locally advanced tumors and situations where downstaging could reduce extensive surgery. Several trials have explored predictive markers of pathological complete response (pCR). The role of Ki-67 as a predictor of pCR has been demonstrated in studies. However, the cut-off remains vague, given the lack of standardization of measurement methods. The aim of our study was to evaluate the predictive value of Ki-67 in response to NAC and to identify the cut-off values that exhibit the strongest correlation with best response.

MATERIALS AND METHODS

This retrospective study included 187 patients who had undergone surgery following NAC for BC at the CHU Souss Massa of Agadir between January 2020 and January 2023. Logistic regression was used to assess the correlation between Ki-67 and patients' characteristics. Optimal Ki-67 cutoff was identified by receiver operating characteristic curve. Kaplan-Meier curves were used to assess disease-free survival (DFS), and survival comparisons were assessed with the log-rank test.

RESULTS

The median age was 51.8±10.7 years and 51.4% of tumors were smaller than 5 cm. Node invasion was found in 55.4%. Luminal B subtype was found in 49.7%, followed by human epidermal growth factor receptor-2 (HER-2)-positive in 27.4%, triple-negative in 14.3% and Luminal A in 8.6%. pCR occurred in 40% of patients overall. Subgroup analysis revealed a significant association between pCR and tumor size (<0.001), lymph node involvement (<0.001), grade 2 (<0.001), vascular invasion (<0.001), and positive HER-2 status ( = 0.022). In statistical analysis, pathological responses were improved in patients with Ki-67 >35% (<0.001). DFS was 98.8% at 12 months. No statistical difference was found in DFS according to Ki-67 values and pCR status.

CONCLUSION

Our results indicate that Ki-67 is a predictive marker for response in the neoadjuvant setting in BC patients. Our study showed that a Ki-67 cut-off >35% predicts a better pCR rate in response to NAC. However, this cutoff value remains controversial due to the absence of a standard method of measurement, with inter- and intra-observer variability. It would be necessary to validate this cutoff in other studies.

摘要

目的

乳腺癌(BC)的新辅助化疗(NAC)正被应用于更广泛的病例,包括局部晚期肿瘤以及降期可减少广泛手术的情况。多项试验探索了病理完全缓解(pCR)的预测标志物。Ki-67作为pCR预测指标的作用已在研究中得到证实。然而,由于测量方法缺乏标准化,其临界值仍不明确。我们研究的目的是评估Ki-67对NAC反应的预测价值,并确定与最佳反应相关性最强的临界值。

材料与方法

这项回顾性研究纳入了2020年1月至2023年1月期间在阿加迪尔苏斯马萨大学医院接受BC-NAC术后手术的187例患者。采用逻辑回归评估Ki-67与患者特征之间的相关性。通过受试者工作特征曲线确定最佳Ki-67临界值。采用Kaplan-Meier曲线评估无病生存期(DFS),并使用对数秩检验进行生存比较。

结果

中位年龄为51.8±10.7岁,51.4%的肿瘤小于5cm。55.4%发现有淋巴结侵犯。49.7%为Luminal B亚型,其次是27.4%的人表皮生长因子受体2(HER-2)阳性、14.3%的三阴性和8.6%的Luminal A亚型。总体40%的患者出现pCR。亚组分析显示pCR与肿瘤大小(<0.001)、淋巴结受累(<0.001)、2级(<0.001)、血管侵犯(<0.001)和HER-2阳性状态(=0.022)之间存在显著关联。在统计分析中,Ki-67>35%的患者病理反应有所改善(<0.001)。12个月时DFS为98.8%。根据Ki-67值和pCR状态,DFS未发现统计学差异。

结论

我们的结果表明,Ki-67是BC患者新辅助治疗反应的预测标志物。我们的研究表明,Ki-67临界值>35%预测NAC反应时pCR率更高。然而,由于缺乏标准测量方法,存在观察者间和观察者内变异性,该临界值仍存在争议。有必要在其他研究中验证该临界值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ba6/11589294/2eb51dba09b6/EurJBreastHealth-20-199-figure-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ba6/11589294/65de5ded6088/EurJBreastHealth-20-199-figure-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ba6/11589294/084bfb28bcdf/EurJBreastHealth-20-199-figure-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ba6/11589294/e8d60584dd01/EurJBreastHealth-20-199-figure-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ba6/11589294/2eb51dba09b6/EurJBreastHealth-20-199-figure-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ba6/11589294/65de5ded6088/EurJBreastHealth-20-199-figure-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ba6/11589294/084bfb28bcdf/EurJBreastHealth-20-199-figure-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ba6/11589294/e8d60584dd01/EurJBreastHealth-20-199-figure-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ba6/11589294/2eb51dba09b6/EurJBreastHealth-20-199-figure-4.jpg

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