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目的：建立一个数学模型，对不完全腋窝淋巴结清扫的患者应用Ⅰ级淋巴结的信息预测Ⅱ、Ⅲ级淋巴结的状态，以指导术后辅助治疗。方法：连续收集９０例女性乳腺癌初治患者行全腋窝淋巴结清扫术的资料，全组共被切出１７９３枚淋巴结，平均每例１９．９２枚；第Ⅰ、Ⅱ和Ⅲ级分别为８５６（４７．７４％），６２０（３４．５８％），３１７（１７．６８％）枚；Ⅰ级淋巴结平均每例为９．５１枚。采用ＳＰＳＳ软件行Ｌｏｇｉｓｔｉｃ多元回归判别分析，建立数学模型。结果：该模型计算的理论值与实际资料进行比较，总符合率Ｐ２、Ｐ３分别是８５．５６％、９２．２２％。结论：建立该数学模型通过一级淋巴结的信息可预测Ⅱ、Ⅲ级淋巴结的状态，有较高符合率，对指导乳腺癌术后辅助治疗将有重要意义。
OBJECTIVE: To establish a mathematical model to predict the status of grade II and III lymph nodes using information on grade I lymph nodes in patients with incomplete axillary lymph node dissection to guide postoperative adjuvant therapy. METHODS: Continuous axillary lymph node dissection was performed in 90 women with primary breast cancer. The total number of lymph node dissections was 1,793 in the entire group, with an average of 19.92 cases in each group. Grades I, II, and III were 856 ( 47.74%), 620 (34.58%), 317 (17.68%) pieces; the average of grade I lymph nodes was 9.51 pieces. SPSS software was used for Logistic multiple regression analysis to establish a mathematical model. Results: The theoretical values calculated by this model are compared with actual data. The total coincidence rates P2 and P3 are 85.56% and 92.22%, respectively. Conclusion: The establishment of this mathematical model can predict the status of grade II and grade III lymph nodes through information of first-grade lymph nodes, and has a high coincidence rate, which will be of great significance in guiding the postoperative adjuvant treatment of breast cancer.