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Construction and validation of a prognostic model for predicting overall survival of primary adrenal malignant tumor patients: A population-based study with 1,080 patients

OBJECTIVE: Primary adrenal malignant tumor is rare. The factors affecting the prognosis remain poorly defined. This study targeted to construct and corroborate a model for predicting the overall survival of adrenal malignant tumor patients. METHODS: We investigated the SEER database for patients wit...

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Autores principales: Xie, Wenhao, Zhang, Yida, Cao, Runfu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9637840/
https://www.ncbi.nlm.nih.gov/pubmed/36353609
http://dx.doi.org/10.3389/fsurg.2022.1025213
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author Xie, Wenhao
Zhang, Yida
Cao, Runfu
author_facet Xie, Wenhao
Zhang, Yida
Cao, Runfu
author_sort Xie, Wenhao
collection PubMed
description OBJECTIVE: Primary adrenal malignant tumor is rare. The factors affecting the prognosis remain poorly defined. This study targeted to construct and corroborate a model for predicting the overall survival of adrenal malignant tumor patients. METHODS: We investigated the SEER database for patients with primary adrenal malignant tumor. 1,080 patients were divided into a construction cohort (n = 756) and a validation cohort (n = 324), randomly. The prognostic factors for overall survival were evaluated using univariate and multivariate Cox analyses. The nomogram was constructed and then validated with C-index, calibration curve, time-dependent ROC curve, and decision curve analysis in both cohorts. Then we divided the patients into 3 different risk groups according to the total points of the nomogram and analyzed their survival status by Kaplan-Meier curve with log-rank test. RESULTS: The baseline characteristics of these two cohorts were not statistically different (P > 0.05). Using univariate and multivariate Cox analyses, 5 variables, including age, tumor size, histological type, tumor stage, and surgery of primary site, were distinguished as prognostic factors (P < 0.05). Based on these variables, we constructed a nomogram to predict the 3- year, 5- year, and 10-year overall survival. The C-indexes were 0.780 (0.760–0.800) in the construction cohort and 0.780 (0.751–0.809) in the validation cohort. In both cohorts, the AUC reached a fairly high level at all time points. The internal and external calibration curves and ROC analysis showed outstanding accuracy and discrimination. The decision curves indicated excellent clinical usefulness. The best cut-off values for the total points of the nomogram were 165.4 and 243.1, and the prognosis was significantly different for the three different risk groups (P < 0.001). CONCLUSION: We successfully constructed a model to predict the overall survival of primary adrenal malignant tumor patients. This model was validated to perform brilliantly internally and externally, which can assist us in individualized clinical management.
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spelling pubmed-96378402022-11-08 Construction and validation of a prognostic model for predicting overall survival of primary adrenal malignant tumor patients: A population-based study with 1,080 patients Xie, Wenhao Zhang, Yida Cao, Runfu Front Surg Surgery OBJECTIVE: Primary adrenal malignant tumor is rare. The factors affecting the prognosis remain poorly defined. This study targeted to construct and corroborate a model for predicting the overall survival of adrenal malignant tumor patients. METHODS: We investigated the SEER database for patients with primary adrenal malignant tumor. 1,080 patients were divided into a construction cohort (n = 756) and a validation cohort (n = 324), randomly. The prognostic factors for overall survival were evaluated using univariate and multivariate Cox analyses. The nomogram was constructed and then validated with C-index, calibration curve, time-dependent ROC curve, and decision curve analysis in both cohorts. Then we divided the patients into 3 different risk groups according to the total points of the nomogram and analyzed their survival status by Kaplan-Meier curve with log-rank test. RESULTS: The baseline characteristics of these two cohorts were not statistically different (P > 0.05). Using univariate and multivariate Cox analyses, 5 variables, including age, tumor size, histological type, tumor stage, and surgery of primary site, were distinguished as prognostic factors (P < 0.05). Based on these variables, we constructed a nomogram to predict the 3- year, 5- year, and 10-year overall survival. The C-indexes were 0.780 (0.760–0.800) in the construction cohort and 0.780 (0.751–0.809) in the validation cohort. In both cohorts, the AUC reached a fairly high level at all time points. The internal and external calibration curves and ROC analysis showed outstanding accuracy and discrimination. The decision curves indicated excellent clinical usefulness. The best cut-off values for the total points of the nomogram were 165.4 and 243.1, and the prognosis was significantly different for the three different risk groups (P < 0.001). CONCLUSION: We successfully constructed a model to predict the overall survival of primary adrenal malignant tumor patients. This model was validated to perform brilliantly internally and externally, which can assist us in individualized clinical management. Frontiers Media S.A. 2022-10-24 /pmc/articles/PMC9637840/ /pubmed/36353609 http://dx.doi.org/10.3389/fsurg.2022.1025213 Text en © 2022 Xie, Zhang and Cao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . 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 Surgery
Xie, Wenhao
Zhang, Yida
Cao, Runfu
Construction and validation of a prognostic model for predicting overall survival of primary adrenal malignant tumor patients: A population-based study with 1,080 patients
title Construction and validation of a prognostic model for predicting overall survival of primary adrenal malignant tumor patients: A population-based study with 1,080 patients
title_full Construction and validation of a prognostic model for predicting overall survival of primary adrenal malignant tumor patients: A population-based study with 1,080 patients
title_fullStr Construction and validation of a prognostic model for predicting overall survival of primary adrenal malignant tumor patients: A population-based study with 1,080 patients
title_full_unstemmed Construction and validation of a prognostic model for predicting overall survival of primary adrenal malignant tumor patients: A population-based study with 1,080 patients
title_short Construction and validation of a prognostic model for predicting overall survival of primary adrenal malignant tumor patients: A population-based study with 1,080 patients
title_sort construction and validation of a prognostic model for predicting overall survival of primary adrenal malignant tumor patients: a population-based study with 1,080 patients
topic Surgery
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9637840/
https://www.ncbi.nlm.nih.gov/pubmed/36353609
http://dx.doi.org/10.3389/fsurg.2022.1025213
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