Postgraduate training base Alliance of Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, China.
Department of Diagnostic Ultrasound Imaging & Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, China.
Breast Cancer Res Treat. 2023 Nov;202(1):45-55. doi: 10.1007/s10549-023-07057-0. Epub 2023 Aug 28.
The objective of this study was to develop a model combining ultrasound (US) and clinicopathological characteristics to predict the pathologic response to neoadjuvant chemotherapy (NACT) in human epidermal growth factor receptor 2 (HER2)-positive breast cancer.
This is a retrospective study that included 248 patients with HER2-positive breast cancer who underwent NACT from March 2018 to March 2022. US and clinicopathological characteristics were collected from all patients in this study, and characteristics obtained using univariate analysis at p < 0.1 were subjected to multivariate analysis and then the conventional US and clinicopathological characteristics independently associated with pathologic complete response (pCR) from the analysis were used to develop US models, clinicopathological models, and their combined models by the area under the receiver operating characteristic (ROC) curve (AUC), accuracy, sensitivity, and specificity to assess their predictive efficacy.
The combined model had an AUC of 0.808, a sensitivity of 88.72%, a specificity of 60.87%, and an accuracy of 75.81% in predicting pCR of HER2-positive breast cancer after NACT, which was significantly better than the clinicopathological model (AUC = 0.656) and the US model (AUC = 0.769). In addition, six characteristics were screened as independent predictors, namely the Clinical T stage, Clinical N stage, PR status, posterior acoustic, margin, and calcification.
The conventional US combined with clinicopathological characteristics to construct a combined model has a good diagnostic effect in predicting pCR in HER2-positive breast cancer and is expected to be a useful tool to assist clinicians in effectively determining the efficacy of NACT in HER2-positive breast cancer patients.
本研究旨在建立一种结合超声(US)和临床病理特征的模型,以预测人表皮生长因子受体 2(HER2)阳性乳腺癌新辅助化疗(NACT)的病理反应。
这是一项回顾性研究,纳入了 2018 年 3 月至 2022 年 3 月期间接受 NACT 的 248 例 HER2 阳性乳腺癌患者。本研究收集了所有患者的 US 和临床病理特征,对 p<0.1 的单变量分析特征进行多变量分析,然后利用分析中与病理完全缓解(pCR)独立相关的常规 US 和临床病理特征,建立 US 模型、临床病理模型及其联合模型,通过接受者操作特征(ROC)曲线下面积(AUC)、准确性、敏感度和特异度评估其预测效能。
联合模型预测 HER2 阳性乳腺癌 NACT 后 pCR 的 AUC 为 0.808,敏感度为 88.72%,特异度为 60.87%,准确率为 75.81%,显著优于临床病理模型(AUC=0.656)和 US 模型(AUC=0.769)。此外,筛选出 6 个特征作为独立预测因子,分别为临床 T 分期、临床 N 分期、PR 状态、后方回声、边界和钙化。
常规 US 结合临床病理特征构建的联合模型对预测 HER2 阳性乳腺癌 pCR 具有良好的诊断效果,有望成为辅助临床医生有效判断 HER2 阳性乳腺癌患者 NACT 疗效的有用工具。