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Nomograms to predict overall survival and cancer-specific survival in patients with adrenocortical carcinoma
PURPOSE: To develop nomogram models to predict individualized estimates of overall survival (OS) and cancer-specific survival (CSS) in patients with adrenocortical carcinoma (ACC). PATIENTS AND METHODS: A total of 751 patients with ACC were identified within the Surveillance Epidemiology, and End Re...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6300377/ https://www.ncbi.nlm.nih.gov/pubmed/30588100 http://dx.doi.org/10.2147/CMAR.S187169 |
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author | Li, Yan Bian, Xiaohui Ouyang, Junyu Wei, Shuyi He, Meizhi Luo, Zelong |
author_facet | Li, Yan Bian, Xiaohui Ouyang, Junyu Wei, Shuyi He, Meizhi Luo, Zelong |
author_sort | Li, Yan |
collection | PubMed |
description | PURPOSE: To develop nomogram models to predict individualized estimates of overall survival (OS) and cancer-specific survival (CSS) in patients with adrenocortical carcinoma (ACC). PATIENTS AND METHODS: A total of 751 patients with ACC were identified within the Surveillance Epidemiology, and End Results (SEER) database between 1973 and 2015. The predictors comprised marital status, sex, age at diagnosis, year of diagnosis, laterality, histologic grade, ethnicity, historic stage, radiation therapy, chemotherapy, and surgery of primary site. Based on the results of the multivariate logistic regression analyses, the nomogram models were used for predicting OS and CSS in patients with ACC. The nomograms were tested using concordance index (C-index) and calibration curves. RESULTS: In univariate and multivariate analyses of OS, OS was significantly associated with age at diagnosis, year of diagnosis, histologic grade, historic stage, and chemotherapy. In univariate and multivariate analyses of CSS, age at diagnosis, year of diagnosis, historic stage, and chemotherapy were the independent risk factors with CSS. These characteristics were included in the nomograms predicting OS and CSS. The nomograms demonstrated good accuracy in predicting OS and CSS, with the C-index of 0.677 and 0.672. CONCLUSION: These clinically useful tools predicted OS and CSS in patients with ACC using readily available clinicopathologic factors and could aid individualized clinical decision making. |
format | Online Article Text |
id | pubmed-6300377 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-63003772018-12-26 Nomograms to predict overall survival and cancer-specific survival in patients with adrenocortical carcinoma Li, Yan Bian, Xiaohui Ouyang, Junyu Wei, Shuyi He, Meizhi Luo, Zelong Cancer Manag Res Original Research PURPOSE: To develop nomogram models to predict individualized estimates of overall survival (OS) and cancer-specific survival (CSS) in patients with adrenocortical carcinoma (ACC). PATIENTS AND METHODS: A total of 751 patients with ACC were identified within the Surveillance Epidemiology, and End Results (SEER) database between 1973 and 2015. The predictors comprised marital status, sex, age at diagnosis, year of diagnosis, laterality, histologic grade, ethnicity, historic stage, radiation therapy, chemotherapy, and surgery of primary site. Based on the results of the multivariate logistic regression analyses, the nomogram models were used for predicting OS and CSS in patients with ACC. The nomograms were tested using concordance index (C-index) and calibration curves. RESULTS: In univariate and multivariate analyses of OS, OS was significantly associated with age at diagnosis, year of diagnosis, histologic grade, historic stage, and chemotherapy. In univariate and multivariate analyses of CSS, age at diagnosis, year of diagnosis, historic stage, and chemotherapy were the independent risk factors with CSS. These characteristics were included in the nomograms predicting OS and CSS. The nomograms demonstrated good accuracy in predicting OS and CSS, with the C-index of 0.677 and 0.672. CONCLUSION: These clinically useful tools predicted OS and CSS in patients with ACC using readily available clinicopathologic factors and could aid individualized clinical decision making. Dove Medical Press 2018-12-13 /pmc/articles/PMC6300377/ /pubmed/30588100 http://dx.doi.org/10.2147/CMAR.S187169 Text en © 2018 Li et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. |
spellingShingle | Original Research Li, Yan Bian, Xiaohui Ouyang, Junyu Wei, Shuyi He, Meizhi Luo, Zelong Nomograms to predict overall survival and cancer-specific survival in patients with adrenocortical carcinoma |
title | Nomograms to predict overall survival and cancer-specific survival in patients with adrenocortical carcinoma |
title_full | Nomograms to predict overall survival and cancer-specific survival in patients with adrenocortical carcinoma |
title_fullStr | Nomograms to predict overall survival and cancer-specific survival in patients with adrenocortical carcinoma |
title_full_unstemmed | Nomograms to predict overall survival and cancer-specific survival in patients with adrenocortical carcinoma |
title_short | Nomograms to predict overall survival and cancer-specific survival in patients with adrenocortical carcinoma |
title_sort | nomograms to predict overall survival and cancer-specific survival in patients with adrenocortical carcinoma |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6300377/ https://www.ncbi.nlm.nih.gov/pubmed/30588100 http://dx.doi.org/10.2147/CMAR.S187169 |
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