Study on metastasis patterns of male breast cancer and construction and validation of a predictive model for distant metastasis

WEI Bo; YANG Shuai; SUN Wantong; LI Guozheng; LIU Lei; YANG Lingbing; FU Zitong; PANG Tianze; ZHOU Ziyue; SUI Shiyao; XU Shouping

doi:10.3969/j.issn.1674-4136.2024.04.008

Abstract：Objective To investigate the patterns of distant metastasis in male breast cancer(MBC),analyze the risk factors for distant metastasis in MBC,and further construct and validate a predictive model for distant metastasis in MBC.Methods A retrospective analysis of clinical and pathological data of MBC patients from the Surveillance,Epidemiology,and End Results(SEER)database from 2010 to 2020 was conducted.The patients were randomly divided into a training set and a testing set in a 7∶3 ratio.Additionally,one hundred and twenty-five MBC patients treated at Cancer Hospital Affiliated to Harbin Medical University from 2010 to 2020 were selected as an external validation set.Univariate and multivariate analyses were conducted on the training set to identify independent factors influencing distant metastasis in MBC.A Logistic regression prediction model was constructed,and the model was evaluated using receiver operating characteristic curve(ROC),calibration curve,and decision curve analysis(DCA).A web-based calculator was developed to enable online use of the model.Results Among 3,592 MBC patients in the SEER database,354 patients had distant metastasis at the initial diagnosis,accounting for 9.86%of the total.Bone was the most common site of metastasis(3.81%).The results of the multivariate Logistic analysis showed that marital status,time from diagnosis to treatment,histological type,T stage,N stage,and molecular subtype were independent risk factors for distant metastasis in MBC.A Logistic regression prediction model was constructed based on these independent factors and validated:the area under the curve(AUC)was 0.838 for the training set,0.836 for the testing set,and 0.717 for the external validation set,indicating good predictive performance of the model.The calibration curve showed high consistency between the predicted and actual results of distant metastasis in MBC patients,and the DCA curve showed that the model could provide higher clinical benefits to patients.Conclusions The predictive model constructed in this study has good predictive performance for distant metastasis in MBC patients,which can help clinicians identify high-risk patients early and develop personalized treatment plans for patients.