摘要
目的探讨自动乳腺超声(ABUS)特征联合Ki-67预测三阴性乳腺癌(TNBC)新辅助化疗(NAC)后病理完全缓解(pCR)的预测价值。方法回顾性选取2019年3月-2023年12月空军军医大学西京医院收治的127例女性TNBC患者,均在接受ABUS检查后行NAC和手术治疗,根据术后病理结果分为pCR组(n=60)与病理未完全缓解(npCR)组(n=67)。比较两组NAC治疗前各项参数的差异,采用LASSO回归筛选TNBC患者NAC治疗后pCR的影响因素,采用多因素logistic回归构建预测模型。应用Bootstrap方法(1000次重抽样)对预测模型进行内部验证;采用受试者操作特征(ROC)曲线评估模型的区分度,通过De-long检验比较不同预测模型的ROC曲线下面积(AUC),采用校准曲线评估模型的准确性,决策曲线分析(DCA)评价模型的临床获益。结果两组TNBC患者NAC治疗前的年龄、Ki-67、绝经状态、肿瘤类型、后方回声、冠状面汇聚征、冠状面跳跃征、冠状面白墙征比较差异有统计学意义(P<0.05);LASSO回归分析显示,Ki-67、冠状面汇聚征、冠状面白墙征是TNBC患者NAC治疗后pCR的独立影响因素(P<0.05);基于这些因素构建的多因素logistic回归Ki-67模型的AUC为0.733(95%CI 0.646~0.819),ABUS特征模型的AUC为0.777(95%CI 0.695~0.858),ABUS特征联合Ki-67模型的AUC为0.816(95%CI 0.741~0.890)。De-long检验显示,联合模型的AUC高于ABUS特征模型和Ki-67模型,差异均有统计学意义(P<0.05);ABUS特征模型的AUC与Ki-67模型比较差异无统计学意义(P=0.40);Hosmer-Lemeshow检验显示,联合模型的拟合度良好(P=0.304)。内部验证结果显示,联合模型的一致性指数(C-index)为0.820(95%CI 0.726~0.879),表明模型稳定性良好;校准曲线显示联合模型的预测概率与实际概率具有良好的一致性,DCA曲线显示模型具有较好的临床获益。结论构建的ABUS特征联合Ki-67模型可用于预测TNBC患者NAC治疗后pCR的概率,为TNBC临床治疗方案的制定提供参考。
Objective To explore the predictive value of automated breast ultrasound(ABUS)features combined with Ki-67 in predicting pathological complete response(pCR)after neoadjuvant chemotherapy(NAC)in triple-negative breast cancer(TNBC).Methods A retrospective analysis was conducted on 127 female TNBC patients treated at Xijing Hospital,Air Force Medical University from March 2019 to December 2023.All patients underwent NAC and surgical treatment after ABUS examination.Based on postoperative pathological results,patients were divided into pCR group(n=60)and non-pathological complete response(npCR)group(n=67).Differences in various parameters before NAC were compared between the two groups.LASSO regression was used to identify independent factors influencing pCR after NAC in TNBC patients,and a predictive model was constructed using multivariate logistic regression.The prediction model was internally validated using the Bootstrap method(1000 resamples).The discriminative ability of the model was evaluated using receiver operating characteristic(ROC)curves,and the area under the curves(AUCs)of different prediction models were compared using De-long's test.The accuracy of the model was assessed using calibration curves,and the clinical benefit of the model was evaluated using clinical decision curve analysis(DCA).Results Significant differences were observed between two groups in terms of age,Ki-67,menopausal status,tumor type,posterior echo,coronal plane convergence sign,coronal plane skip sign,and coronal plane white wall sign before NAC(P<0.05).LASSO regression analysis showed that Ki-67,coronal plane convergence sign,and coronal plane white wall sign were independent influencing factors of pCR after NAC in TNBC patients(P<0.05).The AUC of the multivariate logistic regression model based on Ki-67 was 0.733(95%CI 0.646-0.819),the AUC of ABUS model was 0.777(95%CI 0.695-0.858),and the AUC of ABUS combined with Ki-67 model was 0.816(95%CI 0.741-0.890).De-long's test showed that the AUC of the combined model was higher than those of ABUS feature model and Ki-67 model,with statistically significant differences(P<0.05).There was no significant difference in the AUC between ABUS feature model and Ki-67 model(P=0.40).Hosmer-Lemeshow test indicated that the combined model had a good fit(P=0.304).Internal validation results showed that the combined model had a good stability with a consistency index(C-index)of 0.820(95%CI 0.726-0.879).The calibration curve demonstrated good consistency between the predicted and actual probabilities of the combined prediction model,and the DCA curve indicated that the model had favorable clinical benefit.Conclusion The combined ABUS feature and Ki-67 model can be used to predict the probability of pCR after NAC in TNBC patients,providing a reference for the formulation of clinical treatment plans in TNBC patients.
作者
赵阳
肖迎聪
巨艳
党晓智
薛文欣
李洋
宋宏萍
Zhao Yang;Xiao Ying-Cong;Ju Yan;Dang Xiao-Zhi;Xue Wen-Xin;Li Yang;Song Hong-Ping(Department of Ultrasound Medicine,Xijing Hospital of Air Force Medical University,Xi'an,Shaanxi 710032,China;School of Medical Technology,Shaanxi University of Traditional Chinese Medicine,Xianyang,Shaanxi 712046,China)
出处
《解放军医学杂志》
北大核心
2025年第6期695-702,共8页
Medical Journal of Chinese People's Liberation Army
基金
国家自然科学基金面上项目(82071934,82471991)
西京医院助推项目创新医学研究专项(XJZT25CX03)。
关键词
自动乳腺超声
KI-67
新辅助化疗
三阴性乳腺癌
病理完全缓解
automatic breast ultrasound
Ki-67
neoadjuvant chemotherapy
triple negative breast cancer
pathological complete response
作者简介
赵阳,硕士研究生,主要从事乳腺疾病超声诊断方面的研究;通信作者:宋宏萍,E-mail:song.hp@foxmail.com。
