Predictive value of automatic breast ultrasound features combined with Ki-67 for pathological complete response after neoadjuvant chemotherapy in triple negative breast cancer
10.11855/j.issn.0577-7402.0856.2025.0325
- VernacularTitle:自动乳腺超声特征联合Ki-67对三阴性乳腺癌新辅助化疗后病理完全缓解的预测价值
- Author:
Yang ZHAO
1
;
Ying-Cong XIAO
;
Yan JU
;
Xiao-Zhi DANG
;
Wen-Xin XUE
;
Yang LI
;
Hong-Ping SONG
Author Information
1. 空军军医大学西京医院超声医学科,陕西 西安 710032;陕西中医药大学医学技术学院,陕西 咸阳 712046
- Keywords:
automatic breast ultrasound;
Ki-67;
neoadjuvant chemotherapy;
triple negative breast cancer;
pathological complete response
- From:
Medical Journal of Chinese People's Liberation Army
2025;50(6):695-702
- CountryChina
- Language:Chinese
-
Abstract:
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.
