A Nomogram To Predict The Overall Survival Of Breast Cancer Patients And Guide The Postoperative Adjuvant Chemotherapy In China

在中国,一种用于预测乳腺癌患者总生存期并指导术后辅助化疗的列线图

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Abstract

PURPOSE: We aim to construct a nomogram to predict breast cancer survival and guide postoperative adjuvant chemotherapy in China. PATIENTS AND METHODS: A total of 5,504 breast cancer patients from the Tianjin Breast Cancer Cases Cohort were included. Multivariable Cox regression was used to investigate the factors associated with overall survival (OS) and a nomogram was constructed based on these prognostic factors. The nomogram was internal and external validated and the performance was evaluated by area under the curve (AUC) and calibration curve. The partial score was also constructed and stratified them into low, moderate and high-risk subgroups for death according to the tripartite grouping method. Multivariate Cox regression analysis and the propensity score matching method were respectively used to test the association between adjuvant chemotherapy and OS in different risk subgroups. RESULTS: Age, diameter, histological differentiation, lymph node metastasis, estrogen, and progesterone receptor were incorporated into the nomogram and validation results showed this nomogram was well-calibrated to predict the 3-year [AUC =74.1%; 95% confidence interval (CI): 70.1-78.0%] and 5-year overall survival [AUC =72.3%; 95% CI: 69.6-75.1%]. Adjuvant chemotherapy was negatively associated with death in high risk subgroup [Hazard Ratio (HR) = 0.54; 95% CI: 0.37-0.77; P<0.001]. However, no significant association were found in groups with low (HR=1.47; 95% CI: 0.52-4.19; P=0.47) and moderate risk (HR=0.78; 95% CI: 0.42-1.48; P=0.45). The 1:1 PSM generated 822 pairs of well-matched patients and Kaplan-Meier showed the high-risk patients could benefit from chemotherapy, whereas low risk and moderate risk subjects did not appear to benefit from chemotherapy. CONCLUSION: Not all of the breast cancer patients benefit equally from chemotherapy. The nomogram could be used to evaluate the overall survival of breast cancer patients and predict the magnitude of benefit and guide adjuvant chemotherapy for breast cancer patients after surgery.

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