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Nomogram based on intramuscular adipose tissue content for predicting the prognosis of patients with gallbladder cancer after radical resection

BACKGROUND: To investigate the predictive value of intramuscular adipose tissue content (IMAC) on the outcome of gallbladder cancer (GBC) patients after resection, by then develop and evaluate a nomogram to predict the prognosis of GBC patients. METHODS: This research incorporated 123 patients with...

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Autores principales: Zheng, Chongming, Chen, Xiaotian, Zhang, Zhewei, Li, Anlvna, Wang, Junwei, Cai, Tingting, Tang, Yanping, An, Xuewen, Lu, Fei, Chen, Gang, Xiang, Youqun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9372254/
https://www.ncbi.nlm.nih.gov/pubmed/35966285
http://dx.doi.org/10.21037/tcr-22-123
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author Zheng, Chongming
Chen, Xiaotian
Zhang, Zhewei
Li, Anlvna
Wang, Junwei
Cai, Tingting
Tang, Yanping
An, Xuewen
Lu, Fei
Chen, Gang
Xiang, Youqun
author_facet Zheng, Chongming
Chen, Xiaotian
Zhang, Zhewei
Li, Anlvna
Wang, Junwei
Cai, Tingting
Tang, Yanping
An, Xuewen
Lu, Fei
Chen, Gang
Xiang, Youqun
author_sort Zheng, Chongming
collection PubMed
description BACKGROUND: To investigate the predictive value of intramuscular adipose tissue content (IMAC) on the outcome of gallbladder cancer (GBC) patients after resection, by then develop and evaluate a nomogram to predict the prognosis of GBC patients. METHODS: This research incorporated 123 patients with a pathological diagnosis of GBC. Evaluating the prognosis by the Kaplan-Meier method. Independent predictors of overall survival (OS) were screened using multifactorial Cox regression analysis, and a nomogram was constructed from these. Consistency index and calibration curve were used to identify and calibrate the nomogram. The accuracy of the nomogram was assessed by receiver operating characteristic (ROC) curve and decision curve analysis (DCA) was used to assess the net benefit. RESULTS: Patients with high IMAC showed a worse prognosis. A nomogram was constructed to predict OS based on IMAC. The C-index for the nomogram was 0.804. The calibration curve showed well performance of the nomogram. The area under the ROC curve (AUC) for the nomogram at three and five years was 0.839 and 0.785, respectively. A high net benefit was demonstrated by DCA. CONCLUSIONS: IMAC was a valid predictor for GBC patients. A nomogram with good performance is constructed to predict the prognosis of GBC patients.
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spelling pubmed-93722542022-08-13 Nomogram based on intramuscular adipose tissue content for predicting the prognosis of patients with gallbladder cancer after radical resection Zheng, Chongming Chen, Xiaotian Zhang, Zhewei Li, Anlvna Wang, Junwei Cai, Tingting Tang, Yanping An, Xuewen Lu, Fei Chen, Gang Xiang, Youqun Transl Cancer Res Original Article BACKGROUND: To investigate the predictive value of intramuscular adipose tissue content (IMAC) on the outcome of gallbladder cancer (GBC) patients after resection, by then develop and evaluate a nomogram to predict the prognosis of GBC patients. METHODS: This research incorporated 123 patients with a pathological diagnosis of GBC. Evaluating the prognosis by the Kaplan-Meier method. Independent predictors of overall survival (OS) were screened using multifactorial Cox regression analysis, and a nomogram was constructed from these. Consistency index and calibration curve were used to identify and calibrate the nomogram. The accuracy of the nomogram was assessed by receiver operating characteristic (ROC) curve and decision curve analysis (DCA) was used to assess the net benefit. RESULTS: Patients with high IMAC showed a worse prognosis. A nomogram was constructed to predict OS based on IMAC. The C-index for the nomogram was 0.804. The calibration curve showed well performance of the nomogram. The area under the ROC curve (AUC) for the nomogram at three and five years was 0.839 and 0.785, respectively. A high net benefit was demonstrated by DCA. CONCLUSIONS: IMAC was a valid predictor for GBC patients. A nomogram with good performance is constructed to predict the prognosis of GBC patients. AME Publishing Company 2022-07 /pmc/articles/PMC9372254/ /pubmed/35966285 http://dx.doi.org/10.21037/tcr-22-123 Text en 2022 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Zheng, Chongming
Chen, Xiaotian
Zhang, Zhewei
Li, Anlvna
Wang, Junwei
Cai, Tingting
Tang, Yanping
An, Xuewen
Lu, Fei
Chen, Gang
Xiang, Youqun
Nomogram based on intramuscular adipose tissue content for predicting the prognosis of patients with gallbladder cancer after radical resection
title Nomogram based on intramuscular adipose tissue content for predicting the prognosis of patients with gallbladder cancer after radical resection
title_full Nomogram based on intramuscular adipose tissue content for predicting the prognosis of patients with gallbladder cancer after radical resection
title_fullStr Nomogram based on intramuscular adipose tissue content for predicting the prognosis of patients with gallbladder cancer after radical resection
title_full_unstemmed Nomogram based on intramuscular adipose tissue content for predicting the prognosis of patients with gallbladder cancer after radical resection
title_short Nomogram based on intramuscular adipose tissue content for predicting the prognosis of patients with gallbladder cancer after radical resection
title_sort nomogram based on intramuscular adipose tissue content for predicting the prognosis of patients with gallbladder cancer after radical resection
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9372254/
https://www.ncbi.nlm.nih.gov/pubmed/35966285
http://dx.doi.org/10.21037/tcr-22-123
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