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作者

Weizhen Zheng Pengpeng Zhou Yanbing Liu Ying Liang Yongsheng Wang

作者单位

Shandong Provincial Hospital，Jinan，China；Shandong First Medical University & Shandong Academy of Medical Sciences，Jinan，China；Shandong Cancer Hospital and Institute，Shandong First Medical University and Shandong Academy of Medical Sciences，Jinan，China；Shandong Cancer Hospital and Institute，Shandong First Medical University and Shandong Academy of Medical Sciences，Jinan，China；Shandong Cancer Hospital and Institute，Shandong First Medical University and Shandong Academy of Medical Sciences，Jinan，China；Cheeloo College of Medicine，Shandong University，Jinan，China；Shandong Cancer Hospital and Institute，Shandong First Medical University and Shandong Academy of Medical Sciences，Jinan，China

刊名

肿瘤转化研究

年份

2021

卷号

第10卷

期号

第6期

页码

2822-2830

关键词

Axillary pathologic complete response (ALND) breast cancer predictive model sentinel lymph node biopsy (SLNB)

摘要

Background For clinical lymph node positive breast cancer, the false negative rate of sentinel lymph node biopsy after neoadjuvant chemotherapy is high. Prediction of axillary response after NAC may provide a better way of patient selection. Our study was designed to evaluate factors associated with axillary pathologic complete response after NAC, and to assess the accuracy of the published Olga Kantor predictive model. Methods A total of 406 patients with cN+ breast cancer were enrolled in ...更多

Background For clinical lymph node positive breast cancer, the false negative rate of sentinel lymph node biopsy after neoadjuvant chemotherapy is high. Prediction of axillary response after NAC may provide a better way of patient selection. Our study was designed to evaluate factors associated with axillary pathologic complete response after NAC, and to assess the accuracy of the published Olga Kantor predictive model. Methods A total of 406 patients with cN+ breast cancer were enrolled in this study. All patients had received full courses of NAC before undergoing axillary lymph node dissection . Univariate analyses and multivariate analysis were performed to explore independent predictors of ypN0. Then the Olga Kantor model were validated by the data of patients enrolled. The Olga Kantor model is not ideal because the pathological breast tumor response was not available before surgery, the clinical breast tumor response was assessed in our study as a modification. The accuracy of the validation and modification of Olga Kantor model were assessed by the area under receiver operating characteristic curve . Results Age , molecular subtype , tumor grade , clinical tumor response and Ki-67 were correlated with ypN0. Age, molecular subtype and the clinical tumor response were independent predictors of ypN0 . In validation and modification model, the AUC values were 0.795 and 0.789, respectively, there were no significant differences between the two models . For model score ≤3, 4–7 and ≥8 in the modification model, the ypN0 rate were 3.9% , 22.5% and 67.7% , respectively. Conclusions The Olga Kantor predictive model had high accuracy predicting ypN0 after NAC. Our modification model achieved the same predictive efficiency but is more feasible for clinical practice. Patients with higher scores were more likely to achieve ypN0, so SLNB might be a better way than ALND. However, more patient data and multicenter cohort trials are needed to verify the study.收起

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