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Establishment and validation of a clinical prediction model for medullary carcinoma of breast based on the Surveillance, Epidemiology, and End Results database

Published on Sep. 30, 2022Total Views: 1015 timesTotal Downloads: 516 timesDownloadMobile

Author: Rong FU 1, 2 Yan-Ru SHI 1 Yue-Xian FU 2 Jun LYU 1, 3

Affiliation: 1. School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China 2. Department of Blood Transfusion, Shaanxi Provincial Cancer Hospital, Xi’an 710061, China 3. Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China

Keywords: Medullary carcinoma of breast Nomogram Prognosis SEER

DOI: 10.12173/j.issn.1004-5511.202204049

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Objective  To establish and validate a nomogram model for predicting 5-year and 10-year survival rates of patients with medullary carcinoma of breast based on the Surveillance, Epidemiology, and End Results (SEER) database. 

Methods  The clinical data of patients diagnosed with MCB between 2000 to 2015 were collected from the SEER database, and the patients were randomized to the training set and validation set in a 7/3 ratio. Independent risk factors for the prognosis of MCB patients were determined by univariate and multivariate Cox regression analysis, and the nomogram was constructed based on the independent risk factors to predict the patients’ 5-year and 10-year survival rates. Using the index of concordance, area under the receiver operating characteristic curve (AUC), the cali-bration plots and the decision curve analysis (DCA), the prediction performance between the nomogram model and the American Joint Committee on Cancer (AJCC) staging system were compared. 

Results  A total of 2,086 MCB pa-tients were included: 1,460 in the training set and 626 in the validation set. Univariate and multivariate Cox regres-sion analysis showed that age of diagnosis, marital status, AJCC stage and surgery were risk factors associated with survival in patients with MCB, these risk factors were included in the nomogram and validated. In the training set, the nomogram showed 5-year overall survival AUC=0.698, 10- year overall survival AUC=0.707; in the validation set, the nomogram showed 5-year overall survival AUC=0.748, and 10-year overall survival AUC=0.729. The calibration plot showed that the prediction results of the nomogram model were in good agreement with the actual observations, and the clinical decision curve analysis yielded good net gains in the training and validation sets. 

Conclusion  The nomo-gram prediction model of 5-and 10-year survival of MCB patients constructed using Cox regression analysis has good predictive performance. This model not only provides a more personalized assessment of patient survival, but also serves as a reference for clinicians to choose personalized treatment plans.

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