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A novel nutrition-related nomogram for the survival prediction of colorectal cancer-results from a multicenter study
BACKGROUND: Precisely predicting the short- and long-term survival of patients with cancer is important. The tumor-node-metastasis (TNM) stage can accurately predict the long-term, but not short-term, survival of cancer. Nutritional status can affect the individual status and short-term outcomes of...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814216/ https://www.ncbi.nlm.nih.gov/pubmed/36600242 http://dx.doi.org/10.1186/s12986-022-00719-8 |
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author | Ruan, Guo-Tian Song, Meng-Meng Zhang, Kang-Ping Xie, Hai-Lun Zhang, Qi Zhang, Xi Tang, Meng Zhang, Xiao-Wei Ge, Yi-Zhong Yang, Ming Zhu, Li-Chen Shi, Han-Ping |
author_facet | Ruan, Guo-Tian Song, Meng-Meng Zhang, Kang-Ping Xie, Hai-Lun Zhang, Qi Zhang, Xi Tang, Meng Zhang, Xiao-Wei Ge, Yi-Zhong Yang, Ming Zhu, Li-Chen Shi, Han-Ping |
author_sort | Ruan, Guo-Tian |
collection | PubMed |
description | BACKGROUND: Precisely predicting the short- and long-term survival of patients with cancer is important. The tumor-node-metastasis (TNM) stage can accurately predict the long-term, but not short-term, survival of cancer. Nutritional status can affect the individual status and short-term outcomes of patients with cancer. Our hypothesis was that incorporating TNM stage and nutrition-related factors into one nomogram improves the survival prediction for patients with colorectal cancer (CRC). METHOD: This multicenter prospective primary cohort included 1373 patients with CRC, and the internal validation cohort enrolled 409 patients with CRC. Least absolute shrinkage and selection operator regression analyses were used to select prognostic indicators and develop a nomogram. The concordance (C)-index, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to assess the prognostic discriminative ability of the nomogram, TNM stage, Patient-Generated Subjective Global Assessment (PGSGA), and TNM stage + PGSGA models. The overall survival (OS) curve of risk group stratification was calculated based on the nomogram risk score. RESULTS: TNM stage, radical resection, reduced food intake, activities and function declined, and albumin were selected to develop the nomogram. The C-index and calibration plots of the nomogram showed good discrimination and consistency for CRC. Additionally, the ROC curves and DCA of the nomogram showed better survival prediction abilities in CRC than the other models. The stratification curves of the different risk groups of the different TNM categories were significantly different. CONCLUSION: The novel nomogram showed good short- and long-term outcomes of OS in patients with CRC. This model provides a personalized and convenient prognostic prediction tool for clinical applications. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12986-022-00719-8. |
format | Online Article Text |
id | pubmed-9814216 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-98142162023-01-06 A novel nutrition-related nomogram for the survival prediction of colorectal cancer-results from a multicenter study Ruan, Guo-Tian Song, Meng-Meng Zhang, Kang-Ping Xie, Hai-Lun Zhang, Qi Zhang, Xi Tang, Meng Zhang, Xiao-Wei Ge, Yi-Zhong Yang, Ming Zhu, Li-Chen Shi, Han-Ping Nutr Metab (Lond) Research BACKGROUND: Precisely predicting the short- and long-term survival of patients with cancer is important. The tumor-node-metastasis (TNM) stage can accurately predict the long-term, but not short-term, survival of cancer. Nutritional status can affect the individual status and short-term outcomes of patients with cancer. Our hypothesis was that incorporating TNM stage and nutrition-related factors into one nomogram improves the survival prediction for patients with colorectal cancer (CRC). METHOD: This multicenter prospective primary cohort included 1373 patients with CRC, and the internal validation cohort enrolled 409 patients with CRC. Least absolute shrinkage and selection operator regression analyses were used to select prognostic indicators and develop a nomogram. The concordance (C)-index, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to assess the prognostic discriminative ability of the nomogram, TNM stage, Patient-Generated Subjective Global Assessment (PGSGA), and TNM stage + PGSGA models. The overall survival (OS) curve of risk group stratification was calculated based on the nomogram risk score. RESULTS: TNM stage, radical resection, reduced food intake, activities and function declined, and albumin were selected to develop the nomogram. The C-index and calibration plots of the nomogram showed good discrimination and consistency for CRC. Additionally, the ROC curves and DCA of the nomogram showed better survival prediction abilities in CRC than the other models. The stratification curves of the different risk groups of the different TNM categories were significantly different. CONCLUSION: The novel nomogram showed good short- and long-term outcomes of OS in patients with CRC. This model provides a personalized and convenient prognostic prediction tool for clinical applications. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12986-022-00719-8. BioMed Central 2023-01-04 /pmc/articles/PMC9814216/ /pubmed/36600242 http://dx.doi.org/10.1186/s12986-022-00719-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Ruan, Guo-Tian Song, Meng-Meng Zhang, Kang-Ping Xie, Hai-Lun Zhang, Qi Zhang, Xi Tang, Meng Zhang, Xiao-Wei Ge, Yi-Zhong Yang, Ming Zhu, Li-Chen Shi, Han-Ping A novel nutrition-related nomogram for the survival prediction of colorectal cancer-results from a multicenter study |
title | A novel nutrition-related nomogram for the survival prediction of colorectal cancer-results from a multicenter study |
title_full | A novel nutrition-related nomogram for the survival prediction of colorectal cancer-results from a multicenter study |
title_fullStr | A novel nutrition-related nomogram for the survival prediction of colorectal cancer-results from a multicenter study |
title_full_unstemmed | A novel nutrition-related nomogram for the survival prediction of colorectal cancer-results from a multicenter study |
title_short | A novel nutrition-related nomogram for the survival prediction of colorectal cancer-results from a multicenter study |
title_sort | novel nutrition-related nomogram for the survival prediction of colorectal cancer-results from a multicenter study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814216/ https://www.ncbi.nlm.nih.gov/pubmed/36600242 http://dx.doi.org/10.1186/s12986-022-00719-8 |
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