Yi Sun1,2, Yuqiang Li3, Jiannan Wu1,2, Huan Tian1,2, Huanhuan Liu1,2, Yingqing Fang1,2, Yudong Li1,2, Fengyan Yu4,5. 1. Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China. 2. Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107 Yanjiang West Road, Guangzhou, 510120, China. 3. Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, 410013, China. 4. Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China. yufengy@mail.sysu.edu.cn. 5. Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107 Yanjiang West Road, Guangzhou, 510120, China. yufengy@mail.sysu.edu.cn.
Abstract
PURPOSE: To assess the prognostic risk factors and establish prognostic nomograms based on lymph node ratio (LNR) to predict the survival of young patients with breast cancer (BC). METHODS: Patients aged < 40 years and diagnosed with BC between 2010 and 2016 from the Surveillance, Epidemiology and End Results database were assessed. Nomograms incorporating LNR were constructed to predict overall survival (OS) and breast cancer-specific survival (BCSS) based on Cox proportional hazards model. The performance of the nomograms was assessed by C-index, calibration curves, receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and risk group stratification and compared with the TNM staging system. RESULTS: Based on the univariate and multivariate Cox regression analysis, significant prognostic factors were identified and integrated to create the nomograms for OS and BCSS. The calibration curves indicated optimal agreement between model predictions and actual observations. The nomograms showed favorable sensitivity with a C-index of 0.8351 (95% CI 0.8234-0.8469) for OS and 0.8474 (95% CI 0.8355-0.8594) for BCSS. The ROC curves of the nomograms showed better predictive ability than those of the TNM staging system for OS (AUC: 0.8503 vs. 0.7819) and BSCC (AUC: 0.8607 vs. 0.8081). Significant differences in Kaplan-Meier curves were observed in patients stratified into different risk groups (p < 0.001). CONCLUSIONS: These nomograms provided more accurate individualized risk prediction of OS and BCSS and may assist clinicians in making decisions for young patients with BC.
PURPOSE: To assess the prognostic risk factors and establish prognostic nomograms based on lymph node ratio (LNR) to predict the survival of young patients with breast cancer (BC). METHODS:Patients aged < 40 years and diagnosed with BC between 2010 and 2016 from the Surveillance, Epidemiology and End Results database were assessed. Nomograms incorporating LNR were constructed to predict overall survival (OS) and breast cancer-specific survival (BCSS) based on Cox proportional hazards model. The performance of the nomograms was assessed by C-index, calibration curves, receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and risk group stratification and compared with the TNM staging system. RESULTS: Based on the univariate and multivariate Cox regression analysis, significant prognostic factors were identified and integrated to create the nomograms for OS and BCSS. The calibration curves indicated optimal agreement between model predictions and actual observations. The nomograms showed favorable sensitivity with a C-index of 0.8351 (95% CI 0.8234-0.8469) for OS and 0.8474 (95% CI 0.8355-0.8594) for BCSS. The ROC curves of the nomograms showed better predictive ability than those of the TNM staging system for OS (AUC: 0.8503 vs. 0.7819) and BSCC (AUC: 0.8607 vs. 0.8081). Significant differences in Kaplan-Meier curves were observed in patients stratified into different risk groups (p < 0.001). CONCLUSIONS: These nomograms provided more accurate individualized risk prediction of OS and BCSS and may assist clinicians in making decisions for young patients with BC.
Entities:
Keywords:
Breast cancer; Cancer-specific survival; Nomograms; Overall survival; Young patients