摘要
Background On average,5-10%of patients are diagnosed with metastatic breast cancer(MBC)at the initial diagnosis.This study aimed to develop a nomogram to predict the overall survival(OS)in these patients.Methods The nomogram was based on a retrospective study of 9435 patients with de novo MBC from the Surveillance,Epidemiology,and End Results(SEER)database.The predictive accuracy and discriminative ability of the nomogram were determined using the concordance index(C-index),area under the time-dependent receiver operating characteristic curve(AUC),and calibration curve.Decision curve analysis(DCA)was employed to evaluate the benefits and advantages of our new predicting model over the 8th edition of the American Joint Committee on Cancer(AJCC)Tumor Node Metastasis(TNM)staging system.The results were validated in a retrospective study of 103 patients with de novo MBC from January 2013 to June 2022 at an institution in northwest China.Results Multivariate analysis of the primary cohort revealed that independent factors for survival were age at diagnosis,pathological type,histological grade,T stage,N stage,molecular subtype,bone metastasis,brain metastasis,liver metastasis,lung metastasis,surgery,chemotherapy,and radiotherapy.The nomogram achieved a C-index of 0.688(95%confidence interval[CI],0.682-0.694)in the training cohort and 0.875(95%CI,0.816-0.934)in the validation cohort.The AUC of the nomograms indicated good specificity and sensitivity in the training and validation cohorts,respectively.Calibration curves showed favorable consistency between the predicted and actual survival probabilities.Additionally,the DCA curve produced higher net gains than by the AJCC-TNM staging system.Finally,risk stratification can accurately identify groups of patients with de novo MBC at different risk levels.Conclusions The nomogram showed favorable predictive and discriminative abilities for OS in patients with de novo MBC.Other populations from different countries or prospective studies are needed to further validate the nomogram.
