用于评估新辅助治疗后淋巴结阳性乳腺癌腋窝状态的风险分层系统的开发与验证：一项多中心、前瞻性、观察性研究

The development and validation of a risk stratification system for assessing axillary status after neoadjuvant therapy in node-positive breast cancer: a multicenter, prospective, observational study.

作者信息

Huang Jia-Xin, Mei Jing-Si, Chen Fei, Huang Jia-Hui, Tan Yu-Ting, Wu Yi-Wen, Liu Feng-Tao, Qiu Shao-Dong, Shi Cai-Gou, Lu Yao, Wang Xue-Yan, Huang Gui-Ling, Zhang Yu-Ting, Chen Min-Shan, Pei Xiao-Qinsg

机构信息

Department of Liver Surgery, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.

Department of Medical Ultrasound, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.

出版信息

Int J Surg. 2025 Jun 1;111(6):3731-3741. doi: 10.1097/JS9.0000000000002391. Epub 2025 May 12.

DOI:10.1097/JS9.0000000000002391

PMID:40358626

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12165591/

Abstract

OBJECTIVE

It is not clear which procedure is most optimal for axilla after neoadjuvant therapy (NAT) in node-positive breast cancer patients. Accurately identifying patients with axillary pathologic complete response (pCR) is crucial to minimize the overtreatment of axilla. This study was designed to develop a risk stratification model for axillary pCR.

METHODS

In this multicenter, prospective, observational study, node-positive breast cancer patients who received NAT followed by axillary lymph node dissection (ALND) were enrolled between June 2021 and April 2024. We assessed the performance of breast shear wave elastography (SWE) utilizing virtual touch imaging quantification in determining axillary status across ultrasound (US) nodal stages following NAT. A predictive model incorporating axilla US nodal stage and breast SWE was developed using multivariate logistic regression analysis. Last, a simplified risk score was developed based on the calculated prediction probability from this model and validated in the external test cohort.

RESULTS

The axillary pCR rates were 52.53% in the training cohort ( n = 257) and 51.79% in the external test cohorts ( n = 195). Approximately 21.67% of US N0 cases were false negatives; 42.35% of US N1 cases were false positives. With SWE, the false negative rate was 11.53% in US N0 patients and false positive rate was 22.22% in US N1 patients. The model based on dual-modality US demonstrated strong discriminatory ability (AUC, 0.93), precise calibration (slope of calibration curve, 0.99), and practical clinical utility (probability threshold, 4.5-94.5%); the percentages of accuracy, sensitivity, and specificity were 87.94%, 88.52%, and 87.41%, respectively. Patients scoring 1 demonstrated a low axillary non-pCR rate (5.21%-6.97%), potentially reducing unnecessary ALND rate (17.12%-24.10%).

CONCLUSIONS

The risk stratification model integrating axilla US and breast SWE demonstrated good performance for assessing axillary status after NAT in node-positive breast cancer and might provide guidance for less aggressive management for specific individuals.

摘要

目的

目前尚不清楚哪种手术方式对于接受新辅助治疗（NAT）的淋巴结阳性乳腺癌患者的腋窝治疗最为理想。准确识别腋窝病理完全缓解（pCR）的患者对于尽量减少腋窝的过度治疗至关重要。本研究旨在建立一种腋窝pCR的风险分层模型。

方法

在这项多中心、前瞻性、观察性研究中，纳入了2021年6月至2024年4月期间接受NAT后行腋窝淋巴结清扫术（ALND）的淋巴结阳性乳腺癌患者。我们利用虚拟触诊成像定量评估乳腺剪切波弹性成像（SWE）在确定NAT后超声（US）各淋巴结分期的腋窝状态方面的性能。使用多变量逻辑回归分析建立了一个包含腋窝US淋巴结分期和乳腺SWE的预测模型。最后，基于该模型计算出的预测概率制定了一个简化风险评分，并在外部验证队列中进行了验证。

结果

训练队列（n = 257）的腋窝pCR率为52.53%，外部验证队列（n = 195）的腋窝pCR率为51.79%。约21.67%的US N0病例为假阴性；42.35%的US N1病例为假阳性。使用SWE时，US N0患者的假阴性率为11.53%，US N1患者的假阳性率为22.22%。基于双模态US的模型显示出很强的鉴别能力（AUC，0.93）、精确的校准（校准曲线斜率，0.99）和实际临床效用（概率阈值，4.5 - 94.5%）；准确性、敏感性和特异性的百分比分别为87.94%、88.52%和87.41%。评分为1的患者腋窝非pCR率较低（5.21% - 6.97%），可能降低不必要的ALND率（17.12% - 24.10%）。