Gail model and fifth edition of ultrasound BI-RADS help predict axillary lymph node metastasis in breast cancer-A multicenter prospective study

作者全名："Gao, Lu-Ying; Ran, Hai-Tao; Deng, You-Bin; Luo, Bao-Ming; Zhou, Ping; Chen, Wu; Zhang, Yu-Hong; Li, Jian-Chu; Wang, Hong-Yan; Jiang, Yu-Xin"

作者地址："[Gao, Lu-Ying; Li, Jian-Chu; Wang, Hong-Yan; Jiang, Yu-Xin] Chinese Acad Med Sci & Peking Union Med Coll, Peking Union Med Coll Hosp, Dept Ultrasound, State Key Lab Complex Severe & Rare Dis, Beijing, Peoples R China; [Ran, Hai-Tao] Chongqing Med Univ, Dept Ultrasound, Affiliated Hosp 2, Chongqing, Peoples R China; [Deng, You-Bin] Huazhong Univ Sci & Technol, Tongji Hosp, Dept Ultrasound, Tongji Med Coll, Wuhan, Peoples R China; [Luo, Bao-Ming] Sun Yat Sen Univ, Sun Yat Sen Mem Hosp, Dept Ultrasound, Guangzhou, Peoples R China; [Zhou, Ping] Cent South Univ, Dept Ultrasound, Xiangya Hosp 3, Changsha, Peoples R China; [Chen, Wu] Shanxi Med Univ, Dept Ultrasound, Hosp 1, Taiyuan, Peoples R China; [Zhang, Yu-Hong] Dalian Med Univ, Dept Ultrasound, Hosp 2, Dalian, Peoples R China"

通信作者："Wang, HY; Jiang, YX (通讯作者)，Chinese Acad Med Sci & Peking Union Med Coll, Peking Union Med Coll Hosp, Dept Ultrasound, 1 Shuai Fu Yuan, Beijing 100730, Peoples R China."

来源：ASIA-PACIFIC JOURNAL OF CLINICAL ONCOLOGY

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:000800861300001

JCR分区：Q4

影响因子：1.9

年份：2022

卷号：　

期号：　

开始页：　

结束页：　

文献类型：Article; Early Access

关键词：axillary lymph node metastasis; breast cancer; Breast Imaging-Reporting and Data System (BI-RADS); elastography; Gail model

摘要："Rationale and Objectives We aim to assess the performance of the Gail model and the fifth edition of ultrasound BI-RADS (Breast Imaging Reporting and Data System) in breast cancer for predicting axillary lymph node metastasis (ALNM). Materials and Methods We prospectively studied 958 female patients with breast cancer between 2018 and 2019 from 35 hospitals in China. Based on B-mode, color Doppler, and elastography, radiologists classified the degree of suspicion based on the fifth edition of BI-RADS. Individual breast cancer risk was assessed with the Gail model. The association between the US BI-RADS category and the Gail model in terms of ALNM was analyzed. Results We found that US BI-RADS category was significantly and independently associated with ALNM (P < 0.001). The sensitivity, specificity, and accuracy of BI-RADS category 5 for predicting ALNM were 63.6%, 71.6%, and 68.6%, respectively. Combining the Gail model with the BI-RADS category showed a significantly higher sensitivity than using the BI-RADS category alone (67.8% vs. 63.6%, P < 0.001). The diagnostic accuracy of the BI-RADS category combined with the Gail model was better than that of the Gail model alone (area under the curve: 0.71 vs. 0.50, P < 0.001). Conclusion Based on the conventional ultrasound and elastography, the fifth edition of ultrasound BI-RADS category could be used to predict the ALNM of breast cancer. ALNM was likely to occur in patients with BI-RADS category 5. The Gail model could improve the diagnostic sensitivity of the US BI-RADS category for predicting ALNM in breast cancer."

基金机构：National Natural Science Foundation of China [81601517]; National Natural Science Foundation of Beijing [7202156]; Foundation of ihecc [2018C0032-2]; Peking UnionMedical College Reform in Education Project [10023201900113]

基金资助正文："National Natural Science Foundation of China, Grant/Award Number: 81601517; National Natural Science Foundation of Beijing, Grant/Award Number: 7202156; Foundation of ihecc, Grant/Award Number: 2018C0032-2; Peking UnionMedical College Reform in Education Project, Grant/Award Number: 10023201900113"