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Ki-67 指数、孕激素受体表达、组织学分级和肿瘤大小在预测乳腺癌复发风险中的作用:一项连续队列研究。

Ki-67 index, progesterone receptor expression, histologic grade and tumor size in predicting breast cancer recurrence risk: A consecutive cohort study.

机构信息

Department of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, 100730, P. R. China.

出版信息

Cancer Commun (Lond). 2020 Apr;40(4):181-193. doi: 10.1002/cac2.12024. Epub 2020 Apr 14.

Abstract

BACKGROUND

The 21-gene recurrence score (RS) assay has been recommended by major guidelines for treatment decision in hormone receptor (HR)-positive early breast cancer (EBC). However, the genomic assay is not accessible and affordable worldwide. Alternatively, an increasing number of studies have shown that traditional immunohistochemistry (IHC) can partially or even completely replace the role of the 21-gene genomic assay. Here, we developed and validated a predictive model (IHC3 model) combining the Ki-67 index, progesterone receptor (PR) expression, histologic grade, and tumor size to predict the recurrence risk of HR-positive EBC.

METHODS

The data from 389 patients (development set) with HR-positive, human epidermal growth factor receptor 2-negative, lymph node non-metastasized invasive breast cancer were used to construct the IHC3 model based on the Surexam 21-gene RS and the TAILORx clinical trial criteria. An additional 146 patients with the same characteristics constituted the validation set. The predictive accuracy of the IHC3 model was compared with that of Orucevic et al.'s nomogram. Invasive disease-free survival (IDFS) was analyzed in the IHC3 predictive low-recurrence risk (pLR) group and the predictive high-recurrence risk (pHR) group. The Pearson chi-square test, Fisher exact test, and log-rank test were used for analysis.

RESULTS

The pLR and pHR group could be easily stratified using the decision tree model without network dependence. The accuracies of the IHC3 model were 86.1% in the development set and 87.7% in the validation set. The predictive accuracy of the IHC3 model and Orucevic et al.'s nomogram for the whole cohort was 86.5% and 86.9%, respectively. After a 52-month of median follow-up, a significant difference was found in IDFS between of the IHC3 pLR and the pHR groups (P = 0.001) but not in the IDFS between the low- and high-recurrence risk groups according to the Surexam® 21-gene RS and the TAILORx clinical trial criteria (P = 0.556) or 21-gene binary RS group (P = 0.511).

CONCLUSIONS

The proposed IHC3 model could reliably predict low and high recurrence risks in most HR-positive EBC patients. This easy-to-use predictive model may be a reliable replacement for the 21-gene genomic assay in patients with EBC who have no access to or cannot afford the 21-gene genomic assay.

摘要

背景

21 基因复发评分(RS)检测已被主要指南推荐用于激素受体(HR)阳性早期乳腺癌(EBC)的治疗决策。然而,该基因检测在全球范围内无法获得且费用高昂。此外,越来越多的研究表明,传统的免疫组化(IHC)可以部分甚至完全替代 21 基因基因检测。在这里,我们开发并验证了一个预测模型(IHC3 模型),该模型结合了 Ki-67 指数、孕激素受体(PR)表达、组织学分级和肿瘤大小,用于预测 HR 阳性 EBC 的复发风险。

方法

我们使用来自 389 例 HR 阳性、人表皮生长因子受体 2 阴性、淋巴结未转移的浸润性乳腺癌患者(开发集)的数据,基于 Surexam 21 基因 RS 和 TAILORx 临床试验标准构建 IHC3 模型。另外 146 例具有相同特征的患者构成验证集。比较了 IHC3 模型的预测准确性与 Orucevic 等人的列线图。在 IHC3 预测低复发风险(pLR)组和预测高复发风险(pHR)组中分析了无浸润性疾病生存(IDFS)。采用 Pearson χ²检验、Fisher 确切检验和对数秩检验进行分析。

结果

决策树模型无需网络依赖即可轻松分层 pLR 和 pHR 组。IHC3 模型在开发集和验证集中的准确率分别为 86.1%和 87.7%。IHC3 模型和 Orucevic 等人的列线图对整个队列的预测准确性分别为 86.5%和 86.9%。中位随访 52 个月后,IHC3 pLR 组和 pHR 组之间的 IDFS 差异有统计学意义(P=0.001),但根据 Surexam®21 基因 RS 和 TAILORx 临床试验标准或 21 基因二进制 RS 组(P=0.556),低复发风险和高复发风险组之间的 IDFS 差异无统计学意义(P=0.511)。

结论

所提出的 IHC3 模型可可靠地预测大多数 HR 阳性 EBC 患者的低复发风险和高复发风险。该易于使用的预测模型可能是 EBC 患者 21 基因基因检测的可靠替代品,这些患者无法获得或无法承担 21 基因基因检测的费用。

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