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A nomogram for predicting breast cancer specific survival in elderly patients with breast cancer: a SEER population-based analysis

BACKGROUND: The number of elderly patients diagnosed with breast cancer is increasing worldwide. However, treatment decisions for these patients are highly variable. Although researchers have identified the effects of surgery, radiotherapy, endocrine therapy, and chemotherapy in elderly patients wit...

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Autores principales: Yang, Ruoning, Wu, Yunhao, Qi, Yana, Liu, Weijing, Huang, Ya, Zhao, Xin, Chen, Ruixian, He, Tao, Zhong, Xiaorong, Li, Qintong, Zhou, Li, Chen, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10518930/
https://www.ncbi.nlm.nih.gov/pubmed/37749538
http://dx.doi.org/10.1186/s12877-023-04280-8
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author Yang, Ruoning
Wu, Yunhao
Qi, Yana
Liu, Weijing
Huang, Ya
Zhao, Xin
Chen, Ruixian
He, Tao
Zhong, Xiaorong
Li, Qintong
Zhou, Li
Chen, Jie
author_facet Yang, Ruoning
Wu, Yunhao
Qi, Yana
Liu, Weijing
Huang, Ya
Zhao, Xin
Chen, Ruixian
He, Tao
Zhong, Xiaorong
Li, Qintong
Zhou, Li
Chen, Jie
author_sort Yang, Ruoning
collection PubMed
description BACKGROUND: The number of elderly patients diagnosed with breast cancer is increasing worldwide. However, treatment decisions for these patients are highly variable. Although researchers have identified the effects of surgery, radiotherapy, endocrine therapy, and chemotherapy in elderly patients with breast cancer, clinicians still struggle to make appropriate decisions for these patients. METHODS: We identified 75,525 female breast cancer patients aged ≥ 70 years in the Surveillance, Epidemiology, and End Results (SEER) database treated between January 1, 2010, and December 31, 2016. The patients were further divided into training and testing cohorts. The cumulative occurrence of breast cancer-specific deaths (BCSDs) and other cause-specific deaths (OCSD) was calculated using the cumulative incidence function. In the univariate analysis, risk factors were screened using the Fine-Gray model. In the multivariate analysis for competing risks, the sub-distribution hazard ratio with a 95% confidence interval for each independent predictor associated with BCSD was calculated for the construction of nomograms. Based on the above analyses, a competing risk nomogram was constructed to predict the probability of BCSD in the 1st, 3rd, and 5th years after treatment. During validation, the concordance index (C-index) was selected to quantify the predictive ability of the competing risk model. RESULTS: A total of 33,118 patients were included in this study, with 24,838 in the training group and 8,280 in the testing group. Age, race, marital status, cancer grade, tumor stage, node stage, estrogen receptor status, progesterone receptor status, human epidermal growth factor receptor--2 status, and treatment including surgery, radiation, and chemotherapy were used to establish a nomogram. The C-index of 0.852 (0.842-0.862) in the training cohort and 0.876 (0.868-0.892) in the testing cohort indicated satisfactory discriminative ability of the nomogram. Calibration plots showed favorable consistency between the nomogram predictions and actual observations in both the training and validation cohorts. CONCLUSIONS: Our study identified independent predictors of BCSD in elderly patients with breast cancer. A prognostic nomogram was developed and validated to aid clinical decision-making. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-023-04280-8.
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spelling pubmed-105189302023-09-26 A nomogram for predicting breast cancer specific survival in elderly patients with breast cancer: a SEER population-based analysis Yang, Ruoning Wu, Yunhao Qi, Yana Liu, Weijing Huang, Ya Zhao, Xin Chen, Ruixian He, Tao Zhong, Xiaorong Li, Qintong Zhou, Li Chen, Jie BMC Geriatr Research BACKGROUND: The number of elderly patients diagnosed with breast cancer is increasing worldwide. However, treatment decisions for these patients are highly variable. Although researchers have identified the effects of surgery, radiotherapy, endocrine therapy, and chemotherapy in elderly patients with breast cancer, clinicians still struggle to make appropriate decisions for these patients. METHODS: We identified 75,525 female breast cancer patients aged ≥ 70 years in the Surveillance, Epidemiology, and End Results (SEER) database treated between January 1, 2010, and December 31, 2016. The patients were further divided into training and testing cohorts. The cumulative occurrence of breast cancer-specific deaths (BCSDs) and other cause-specific deaths (OCSD) was calculated using the cumulative incidence function. In the univariate analysis, risk factors were screened using the Fine-Gray model. In the multivariate analysis for competing risks, the sub-distribution hazard ratio with a 95% confidence interval for each independent predictor associated with BCSD was calculated for the construction of nomograms. Based on the above analyses, a competing risk nomogram was constructed to predict the probability of BCSD in the 1st, 3rd, and 5th years after treatment. During validation, the concordance index (C-index) was selected to quantify the predictive ability of the competing risk model. RESULTS: A total of 33,118 patients were included in this study, with 24,838 in the training group and 8,280 in the testing group. Age, race, marital status, cancer grade, tumor stage, node stage, estrogen receptor status, progesterone receptor status, human epidermal growth factor receptor--2 status, and treatment including surgery, radiation, and chemotherapy were used to establish a nomogram. The C-index of 0.852 (0.842-0.862) in the training cohort and 0.876 (0.868-0.892) in the testing cohort indicated satisfactory discriminative ability of the nomogram. Calibration plots showed favorable consistency between the nomogram predictions and actual observations in both the training and validation cohorts. CONCLUSIONS: Our study identified independent predictors of BCSD in elderly patients with breast cancer. A prognostic nomogram was developed and validated to aid clinical decision-making. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-023-04280-8. BioMed Central 2023-09-25 /pmc/articles/PMC10518930/ /pubmed/37749538 http://dx.doi.org/10.1186/s12877-023-04280-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Yang, Ruoning
Wu, Yunhao
Qi, Yana
Liu, Weijing
Huang, Ya
Zhao, Xin
Chen, Ruixian
He, Tao
Zhong, Xiaorong
Li, Qintong
Zhou, Li
Chen, Jie
A nomogram for predicting breast cancer specific survival in elderly patients with breast cancer: a SEER population-based analysis
title A nomogram for predicting breast cancer specific survival in elderly patients with breast cancer: a SEER population-based analysis
title_full A nomogram for predicting breast cancer specific survival in elderly patients with breast cancer: a SEER population-based analysis
title_fullStr A nomogram for predicting breast cancer specific survival in elderly patients with breast cancer: a SEER population-based analysis
title_full_unstemmed A nomogram for predicting breast cancer specific survival in elderly patients with breast cancer: a SEER population-based analysis
title_short A nomogram for predicting breast cancer specific survival in elderly patients with breast cancer: a SEER population-based analysis
title_sort nomogram for predicting breast cancer specific survival in elderly patients with breast cancer: a seer population-based analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10518930/
https://www.ncbi.nlm.nih.gov/pubmed/37749538
http://dx.doi.org/10.1186/s12877-023-04280-8
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