A 10-miRNA risk score-based prediction model for pathological complete response to neoadjuvant chemotherapy in hormone receptor-positive breast cancer
A 10-miRNA risk score-based prediction model for pathological complete response to neoadjuvant chemotherapy in hormone receptor-positive breast cancer
复制标题
基于 10-miRNA 风险评分的激素受体阳性乳腺癌新辅助化疗病理完全缓解预测模型
DOI：
10.1007/s11427-022-2104-3
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发表时间：
2022-05-13
影响因子：
9.1
通讯作者：
Song, Erwei
中科院分区：
文献类型：
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作者：
Gong, Chang;Cheng, Ziliang;Song, Erwei
激素受体（HR）阳性乳腺癌患者通常对新辅助化疗（NAC）的病理完全缓解（pCR）相对较低。在这里，我们推导出了一个基于10-microRNA风险评分（10-miRNA RS）的模型，该模型在预测pCR方面具有更好的性能，并在755例HR阳性乳腺癌患者中验证了其与无病生存期（DFS）的关系（训练，内部和外部验证集分别为273，265和217）。该模型以列线图形式呈现，包括四个参数：我们先前研究中发现的10-miRNA RS、孕酮受体（PR）、人表皮生长因子受体2（HER 2）状态和体积转移常数（K-transs）。在训练集、内部验证集和外部验证集分别显示了基于10-miRNA RS的模型的良好校准和区分，曲线下面积（AUC）为0.865、0.811和0.804。NAC治疗后诺模图评分越高（>92.2）的患者DFS越长（危险比=0.57; 95%CI：0.39-0.83; P=0.004）。综上所述，我们的数据表明，基于10-miRNA RS的模型可以精确地识别更多能够达到NAC pCR的患者，这可能有助于临床医生制定个性化的初始治疗策略，从而使HR阳性乳腺癌患者获得更好的临床预后。
Patients with hormone receptor (HR)-positive tumors breast cancer usually experience a relatively low pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). Here, we derived a 10-microRNA risk score (10-miRNA RS)-based model with better performance in the prediction of pCR and validated its relation with the disease-free survival (DFS) in 755 HR-positive breast cancer patients (273, 265, and 217 in the training, internal, and external validation sets, respectively). This model, presented as a nomogram, included four parameters: the 10-miRNA RS found in our previous study, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) status, and volume transfer constant (K-trans). Favorable calibration and discrimination of 10-miRNA RS-based model with areas under the curve (AUC) of 0.865, 0.811, and 0.804 were shown in the training, internal, and external validation sets, respectively. Patients who have higher nomogram score (>92.2) with NAC treatment would have longer DFS (hazard ratio=0.57; 95%CI: 0.39-0.83; P=0.004). In summary, our data showed the 10-miRNA RS-based model could precisely identify more patients who can attain pCR to NAC, which may help clinicians formulate the personalized initial treatment strategy and consequently achieves better clinical prognosis for patients with HR-positive breast cancer.