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Development and validation of prognostic nomograms for early-onset colon cancer in different tumor locations: a population-based study

OBJECTIVE: The prevalence of early-onset colon cancer (EOCC) among individuals below the age of 50 has shown a marked upward trend in recent years. The embryology, clinical symptoms, incidence, molecular pathways, and oncologic outcomes differ between right-sided and left-sided colon cancers. Howeve...

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Autores principales: Zhu, Sirui, Tu, Jiawei, Pei, Wei, Zheng, Zhaoxu, Bi, Jianjun, Feng, Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10590526/
https://www.ncbi.nlm.nih.gov/pubmed/37865754
http://dx.doi.org/10.1186/s12876-023-02991-1
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author Zhu, Sirui
Tu, Jiawei
Pei, Wei
Zheng, Zhaoxu
Bi, Jianjun
Feng, Qiang
author_facet Zhu, Sirui
Tu, Jiawei
Pei, Wei
Zheng, Zhaoxu
Bi, Jianjun
Feng, Qiang
author_sort Zhu, Sirui
collection PubMed
description OBJECTIVE: The prevalence of early-onset colon cancer (EOCC) among individuals below the age of 50 has shown a marked upward trend in recent years. The embryology, clinical symptoms, incidence, molecular pathways, and oncologic outcomes differ between right-sided and left-sided colon cancers. However, the differences have not been fully researched in EOCC. Our study aims to develop and validate prognostic nomograms predicting overall survival (OS) and cancer-specific survival (CSS) for EOCC in different tumor locations based on the Surveillance, Epidemiology, and End Results (SEER) database. METHODS: Using the SEER database, a total of 5,588 patients with EOCC were extracted and divided into development and validation cohorts in a random allocation ratio of 7:3 across three groups. Univariate and multivariate Cox regression analyses were performed to identify independent prognostic factors influencing OS and CSS outcomes. These factors were then utilized to construct nomogram models. The prognostic capabilities of the three models were assessed through various evaluation metrics, including the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and validation cohorts respectively. Additionally, survival curves of the low- and high-risk groups were calculated using the Kaplan–Meier method together with the log-rank test. RESULTS: Significant differences in clinical features were observed between right-sided and left-sided EOCCs, particularly in terms of OS (52 months vs 54 months) as demonstrated by Kaplan–Meier curves. Transverse-sided EOCCs exhibited clinical characteristics similar to right-sided EOCCs, suggesting a potential shared tumor microenvironment and therapeutic considerations. Advanced stage, liver metastasis, poor grade, elevated pretreatment carcinoembryonic antigen (CEA) level, chemotherapy, and perineural invasion were identified as independent prognostic factors across all three tumor locations and were incorporated into the nomogram model. Nomograms were constructed to predict the probability of 3- and 5-year OS and CSS. The C-index and calibration plots showed that the established nomograms had good consistency between actual clinical observations and predicted outcomes. ROC curves with calculated area under the curve (AUC) values exceeded 0.8 for all three groups in both the development and validation cohorts, indicating robust predictive performance for OS and CSS. Furthermore, decision curve analysis (DCA) plots revealed a threshold probability range of 0.1 to 0.9, within which the nomogram model exhibited maximum benefit. Kaplan–Meier curves exhibited significant differences between the low- and high-risk groups in EOCC for all three tumor locations in OS and CSS, further validating the prognostic value of the nomogram models. CONCLUSIONS: We successfully developed three precise nomogram models for EOCCs in different tumor locations, providing valuable support for clinicians in guiding clinical treatments and facilitating further prospective follow-up studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12876-023-02991-1.
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spelling pubmed-105905262023-10-23 Development and validation of prognostic nomograms for early-onset colon cancer in different tumor locations: a population-based study Zhu, Sirui Tu, Jiawei Pei, Wei Zheng, Zhaoxu Bi, Jianjun Feng, Qiang BMC Gastroenterol Research OBJECTIVE: The prevalence of early-onset colon cancer (EOCC) among individuals below the age of 50 has shown a marked upward trend in recent years. The embryology, clinical symptoms, incidence, molecular pathways, and oncologic outcomes differ between right-sided and left-sided colon cancers. However, the differences have not been fully researched in EOCC. Our study aims to develop and validate prognostic nomograms predicting overall survival (OS) and cancer-specific survival (CSS) for EOCC in different tumor locations based on the Surveillance, Epidemiology, and End Results (SEER) database. METHODS: Using the SEER database, a total of 5,588 patients with EOCC were extracted and divided into development and validation cohorts in a random allocation ratio of 7:3 across three groups. Univariate and multivariate Cox regression analyses were performed to identify independent prognostic factors influencing OS and CSS outcomes. These factors were then utilized to construct nomogram models. The prognostic capabilities of the three models were assessed through various evaluation metrics, including the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and validation cohorts respectively. Additionally, survival curves of the low- and high-risk groups were calculated using the Kaplan–Meier method together with the log-rank test. RESULTS: Significant differences in clinical features were observed between right-sided and left-sided EOCCs, particularly in terms of OS (52 months vs 54 months) as demonstrated by Kaplan–Meier curves. Transverse-sided EOCCs exhibited clinical characteristics similar to right-sided EOCCs, suggesting a potential shared tumor microenvironment and therapeutic considerations. Advanced stage, liver metastasis, poor grade, elevated pretreatment carcinoembryonic antigen (CEA) level, chemotherapy, and perineural invasion were identified as independent prognostic factors across all three tumor locations and were incorporated into the nomogram model. Nomograms were constructed to predict the probability of 3- and 5-year OS and CSS. The C-index and calibration plots showed that the established nomograms had good consistency between actual clinical observations and predicted outcomes. ROC curves with calculated area under the curve (AUC) values exceeded 0.8 for all three groups in both the development and validation cohorts, indicating robust predictive performance for OS and CSS. Furthermore, decision curve analysis (DCA) plots revealed a threshold probability range of 0.1 to 0.9, within which the nomogram model exhibited maximum benefit. Kaplan–Meier curves exhibited significant differences between the low- and high-risk groups in EOCC for all three tumor locations in OS and CSS, further validating the prognostic value of the nomogram models. CONCLUSIONS: We successfully developed three precise nomogram models for EOCCs in different tumor locations, providing valuable support for clinicians in guiding clinical treatments and facilitating further prospective follow-up studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12876-023-02991-1. BioMed Central 2023-10-21 /pmc/articles/PMC10590526/ /pubmed/37865754 http://dx.doi.org/10.1186/s12876-023-02991-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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
Zhu, Sirui
Tu, Jiawei
Pei, Wei
Zheng, Zhaoxu
Bi, Jianjun
Feng, Qiang
Development and validation of prognostic nomograms for early-onset colon cancer in different tumor locations: a population-based study
title Development and validation of prognostic nomograms for early-onset colon cancer in different tumor locations: a population-based study
title_full Development and validation of prognostic nomograms for early-onset colon cancer in different tumor locations: a population-based study
title_fullStr Development and validation of prognostic nomograms for early-onset colon cancer in different tumor locations: a population-based study
title_full_unstemmed Development and validation of prognostic nomograms for early-onset colon cancer in different tumor locations: a population-based study
title_short Development and validation of prognostic nomograms for early-onset colon cancer in different tumor locations: a population-based study
title_sort development and validation of prognostic nomograms for early-onset colon cancer in different tumor locations: a population-based study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10590526/
https://www.ncbi.nlm.nih.gov/pubmed/37865754
http://dx.doi.org/10.1186/s12876-023-02991-1
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