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Prognostic modeling of overall survival and analysis of K-M survival curves in patients with primary colon cancer: A SEER-based study

This study aimed to establish a validated prognostic survival column line chart by analyzing data from patients with colon cancer (CC) in the SEER database. The nomogram proposed in this study was based on the retrospective data of patients diagnosed with CC in the SEER database from 1975 to 2015. R...

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Autores principales: Li, Chongyang, Cao, Shengqin, Sun, Xuedi, Lu, Chunlei, Guo, Mingxiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256362/
https://www.ncbi.nlm.nih.gov/pubmed/37335675
http://dx.doi.org/10.1097/MD.0000000000033902
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author Li, Chongyang
Cao, Shengqin
Sun, Xuedi
Lu, Chunlei
Guo, Mingxiao
author_facet Li, Chongyang
Cao, Shengqin
Sun, Xuedi
Lu, Chunlei
Guo, Mingxiao
author_sort Li, Chongyang
collection PubMed
description This study aimed to establish a validated prognostic survival column line chart by analyzing data from patients with colon cancer (CC) in the SEER database. The nomogram proposed in this study was based on the retrospective data of patients diagnosed with CC in the SEER database from 1975 to 2015. Randomly divided into training and validation sets, the nomogram was constructed using the Cox model, and the discriminatory power of the nomogram and its predictive accuracy were determined using the consistency index and associated calibration curves. In a multifactorial analysis of the main cohort, the independent factors for survival were age, sex, race, tumor stage, and tumor grade, all of which were included in the nomogram and were prognostic factors for patients with CC (P < .05). The calibration curve of the survival probability showed good agreement between the prediction of the nomogram and the actual observation. The validation calibration curve showed good correlation and agreement between predicted and observed values. Multifactorial analysis showed that the factors affecting the prognosis of patients with CC included age, sex, race, tumor-node-metastasis stage, and tumor pathological stage. The nomogram prediction model proposed in this study has high accuracy and can provide more accurate prognostic prediction and relevant reference values for assessing the postoperative survival of CC patients and guiding clinical decision-making.
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spelling pubmed-102563622023-06-10 Prognostic modeling of overall survival and analysis of K-M survival curves in patients with primary colon cancer: A SEER-based study Li, Chongyang Cao, Shengqin Sun, Xuedi Lu, Chunlei Guo, Mingxiao Medicine (Baltimore) 4500 This study aimed to establish a validated prognostic survival column line chart by analyzing data from patients with colon cancer (CC) in the SEER database. The nomogram proposed in this study was based on the retrospective data of patients diagnosed with CC in the SEER database from 1975 to 2015. Randomly divided into training and validation sets, the nomogram was constructed using the Cox model, and the discriminatory power of the nomogram and its predictive accuracy were determined using the consistency index and associated calibration curves. In a multifactorial analysis of the main cohort, the independent factors for survival were age, sex, race, tumor stage, and tumor grade, all of which were included in the nomogram and were prognostic factors for patients with CC (P < .05). The calibration curve of the survival probability showed good agreement between the prediction of the nomogram and the actual observation. The validation calibration curve showed good correlation and agreement between predicted and observed values. Multifactorial analysis showed that the factors affecting the prognosis of patients with CC included age, sex, race, tumor-node-metastasis stage, and tumor pathological stage. The nomogram prediction model proposed in this study has high accuracy and can provide more accurate prognostic prediction and relevant reference values for assessing the postoperative survival of CC patients and guiding clinical decision-making. Lippincott Williams & Wilkins 2023-06-09 /pmc/articles/PMC10256362/ /pubmed/37335675 http://dx.doi.org/10.1097/MD.0000000000033902 Text en Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC) (https://creativecommons.org/licenses/by-nc/4.0/) , where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.
spellingShingle 4500
Li, Chongyang
Cao, Shengqin
Sun, Xuedi
Lu, Chunlei
Guo, Mingxiao
Prognostic modeling of overall survival and analysis of K-M survival curves in patients with primary colon cancer: A SEER-based study
title Prognostic modeling of overall survival and analysis of K-M survival curves in patients with primary colon cancer: A SEER-based study
title_full Prognostic modeling of overall survival and analysis of K-M survival curves in patients with primary colon cancer: A SEER-based study
title_fullStr Prognostic modeling of overall survival and analysis of K-M survival curves in patients with primary colon cancer: A SEER-based study
title_full_unstemmed Prognostic modeling of overall survival and analysis of K-M survival curves in patients with primary colon cancer: A SEER-based study
title_short Prognostic modeling of overall survival and analysis of K-M survival curves in patients with primary colon cancer: A SEER-based study
title_sort prognostic modeling of overall survival and analysis of k-m survival curves in patients with primary colon cancer: a seer-based study
topic 4500
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256362/
https://www.ncbi.nlm.nih.gov/pubmed/37335675
http://dx.doi.org/10.1097/MD.0000000000033902
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