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Development and Validation of a Nomogram for Predicting Survival in Male Patients With Breast Cancer
Male breast cancer (MBC) is rare, and most patients are diagnosed at an advanced stage. We aimed to develop a reliable nomogram to predict breast cancer-specific survival (BCSS) for MBC patients, thus helping clinical diagnosis and treatment. Based on data from the Surveillance, Epidemiology, and En...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6527749/ https://www.ncbi.nlm.nih.gov/pubmed/31139562 http://dx.doi.org/10.3389/fonc.2019.00361 |
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author | Chen, Siying Liu, Yang Yang, Jin Liu, Qingqing You, Haisheng Dong, Yalin Lyu, Jun |
author_facet | Chen, Siying Liu, Yang Yang, Jin Liu, Qingqing You, Haisheng Dong, Yalin Lyu, Jun |
author_sort | Chen, Siying |
collection | PubMed |
description | Male breast cancer (MBC) is rare, and most patients are diagnosed at an advanced stage. We aimed to develop a reliable nomogram to predict breast cancer-specific survival (BCSS) for MBC patients, thus helping clinical diagnosis and treatment. Based on data from the Surveillance, Epidemiology, and End Results (SEER) database, 2,451 patients diagnosed with MBC from 2010 to 2015 were selected for this study. They were randomly assigned to either a training cohort (n = 1715) or a validation cohort (n = 736). The Multivariate Cox proportional hazards regression analysis was used to determine the independent prognostic factors, which were then utilized to build a nomogram for predicting 3- and 5-year BCSS. The discrimination and calibration of the new model was evaluated using the Concordance index (C-index) and calibration curves, while its accuracy and benefits were assessed by comparing it to the traditional AJCC staging system using the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), and the decision curve analysis (DCA). Multivariate models revealed that age, AJCC stage, ER status, PR status, and surgery all showed a significant association with BCSS. A nomogram based on these variables was constructed to predict survival in MBC patients. Compared to the AJCC stage, the C-index (training group: 0.840 vs. 0.775, validation group: 0.818 vs. 0.768), the areas under the receiver operating characteristic curve of the training set (3-year AUC: 0.852 vs. 0.778, 5-year AUC: 0.841 vs. 0.774) and the validation set (3-year AUC: 0.778 vs. 0.752, 5-year AUC: 0.852 vs. 0.794), and the calibration plots of this model all exhibited better performance. Additionally, the NRI and IDI confirmed that the nomogram was a great prognosis tool. Finally, the 3- and 5-year DCA curves yielded larger net benefits than the traditional AJCC stage. In conclusion, we have successfully established an effective nomogram to predict BCSS in MBC patients, which can assist clinicians in determining the appropriate therapy strategies for individual male patients. |
format | Online Article Text |
id | pubmed-6527749 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-65277492019-05-28 Development and Validation of a Nomogram for Predicting Survival in Male Patients With Breast Cancer Chen, Siying Liu, Yang Yang, Jin Liu, Qingqing You, Haisheng Dong, Yalin Lyu, Jun Front Oncol Oncology Male breast cancer (MBC) is rare, and most patients are diagnosed at an advanced stage. We aimed to develop a reliable nomogram to predict breast cancer-specific survival (BCSS) for MBC patients, thus helping clinical diagnosis and treatment. Based on data from the Surveillance, Epidemiology, and End Results (SEER) database, 2,451 patients diagnosed with MBC from 2010 to 2015 were selected for this study. They were randomly assigned to either a training cohort (n = 1715) or a validation cohort (n = 736). The Multivariate Cox proportional hazards regression analysis was used to determine the independent prognostic factors, which were then utilized to build a nomogram for predicting 3- and 5-year BCSS. The discrimination and calibration of the new model was evaluated using the Concordance index (C-index) and calibration curves, while its accuracy and benefits were assessed by comparing it to the traditional AJCC staging system using the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), and the decision curve analysis (DCA). Multivariate models revealed that age, AJCC stage, ER status, PR status, and surgery all showed a significant association with BCSS. A nomogram based on these variables was constructed to predict survival in MBC patients. Compared to the AJCC stage, the C-index (training group: 0.840 vs. 0.775, validation group: 0.818 vs. 0.768), the areas under the receiver operating characteristic curve of the training set (3-year AUC: 0.852 vs. 0.778, 5-year AUC: 0.841 vs. 0.774) and the validation set (3-year AUC: 0.778 vs. 0.752, 5-year AUC: 0.852 vs. 0.794), and the calibration plots of this model all exhibited better performance. Additionally, the NRI and IDI confirmed that the nomogram was a great prognosis tool. Finally, the 3- and 5-year DCA curves yielded larger net benefits than the traditional AJCC stage. In conclusion, we have successfully established an effective nomogram to predict BCSS in MBC patients, which can assist clinicians in determining the appropriate therapy strategies for individual male patients. Frontiers Media S.A. 2019-05-14 /pmc/articles/PMC6527749/ /pubmed/31139562 http://dx.doi.org/10.3389/fonc.2019.00361 Text en Copyright © 2019 Chen, Liu, Yang, Liu, You, Dong and Lyu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Chen, Siying Liu, Yang Yang, Jin Liu, Qingqing You, Haisheng Dong, Yalin Lyu, Jun Development and Validation of a Nomogram for Predicting Survival in Male Patients With Breast Cancer |
title | Development and Validation of a Nomogram for Predicting Survival in Male Patients With Breast Cancer |
title_full | Development and Validation of a Nomogram for Predicting Survival in Male Patients With Breast Cancer |
title_fullStr | Development and Validation of a Nomogram for Predicting Survival in Male Patients With Breast Cancer |
title_full_unstemmed | Development and Validation of a Nomogram for Predicting Survival in Male Patients With Breast Cancer |
title_short | Development and Validation of a Nomogram for Predicting Survival in Male Patients With Breast Cancer |
title_sort | development and validation of a nomogram for predicting survival in male patients with breast cancer |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6527749/ https://www.ncbi.nlm.nih.gov/pubmed/31139562 http://dx.doi.org/10.3389/fonc.2019.00361 |
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