乳腺癌新辅助治疗Miller/Payne分级相关临床病理特征分析及预测模型建立

Clinicopathological characteristics related to Miller/Payne grading system of breast carcinoma after neoadjuvant therapy and establishment of novel prediction models

目的:探讨浸润性乳腺癌新辅助治疗后Miller/Payne(MP)分级相关临床病理特征,并建立MP分级预测模型。方法:收集北京大学肿瘤医院2016年9月至2019年9月1053例确诊为非特殊型浸润性乳腺癌并遵循中国临床肿瘤学会(CSCO)《乳腺癌诊疗指南》行新辅助治疗的患者临床病理资料,包括年龄、性别、组织学分级、免疫组织化学染色结果和术前淋巴结转移情况等,应用R软件进行数据统计分析,并建立MP分级预测模型。结果:1053例经新辅助治疗患者中,316例(316/1053,30%)术后评判为MP5级,737例(737/1053,70%)为非MP5级。新辅助治疗后MP5级与非MP5级相比较,在组织学分级、雌激素受体(ER)/孕激素受体(PR)表达情况、HER2检测结果、Ki-67阳性指数以及分子分型上的差异有统计学意义(P<0.05);单因素和多因素Logistic回归分析进一步显示,上述临床病理特征也是MP5级的独立影响因素;采取5重交叉验证的方法评估模型的性能,得到不同模型的灵敏度和特异度。结论:非特殊型浸润性乳腺癌新辅助治疗后,高组织学分级、ER阴性、PR阴性、HER2阳性、高Ki-67阳性指数以及分子分型与MP5级相关,且是其独立影响因素;通过比较推荐使用梯度提升树模型,可对临床诊疗提供一定帮助。

Objective To investigate the correlation between clinicopathological features and Miller/Payne(MP)grading system of breast carcinoma after neoadjuvant treatment and to establish novel prediction models.Methods A total of 1053 cases of invasive breast carcinoma NOS that undertaken neoadjuvant treatment according to Guidelines of CSCO for Breast Cancer were selected at the Key Laboratory of Carcinogenesis and Translational Research,Peking University Cancer Hospital&Institute from September 2016 to September 2019,and the clinical,pathologic data,MP grading and immunohistochemical staining were evaluated.Statistical analysis was conducted using R software.Several novel computer models on prediction of MP grading were established and validated.Results Among 1053 patients who accepted neoadjuvant treatment,316 patients(316/1053,30%)were evaluated as MP5 postoperatively,and 737 patients(737/1053,70%)did not meet MP5 level.MP5 had significant association with histological grade,ER and PR expression,HER2 status,Ki-67 index and molecular classification(P<0.05).Univariate/multivariate logistic regression analyses further showed that the above clinicopathological features were also independent influencing factors of MP5 grade;five-fold cross-validation was used to evaluate the performance of the models,and the sensitivity and specificity of different models were obtained.Conclusions MP grading of invasive breast carcinoma NOS after neoadjuvant treatment is associated with high histological grade,negative ER and PR expression,HER2 positivity,high Ki-67 index and molecular classification,which are independent influence factors.GBM model recommended through comparison can provide some help for clinical diagnosis and treatment.