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A Novel Prognostic Model and Practical Nomogram for Predicting the Outcomes of Colorectal Cancer: Based on Tumor Biomarkers and Log Odds of Positive Lymph Node Scheme

BACKGROUND: Emerging evidence shows that serum tumor biomarkers (TBs) and log odds of positive lymph node scheme (LODDS) are closely associated with the prognosis of colorectal cancer (CRC) patients. The aim of our study is to validate the predictive value of TBs and LODDS clinically and to develop...

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Autores principales: Zhu, Jun, Hao, Jun, Ma, Qian, Shi, Tingyu, Wang, Shuai, Yan, Jingchuan, Chen, Rujie, Xu, Dong, Jiang, Yu, Zhang, Jian, Li, Jipeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8085421/
https://www.ncbi.nlm.nih.gov/pubmed/33937076
http://dx.doi.org/10.3389/fonc.2021.661040
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author Zhu, Jun
Hao, Jun
Ma, Qian
Shi, Tingyu
Wang, Shuai
Yan, Jingchuan
Chen, Rujie
Xu, Dong
Jiang, Yu
Zhang, Jian
Li, Jipeng
author_facet Zhu, Jun
Hao, Jun
Ma, Qian
Shi, Tingyu
Wang, Shuai
Yan, Jingchuan
Chen, Rujie
Xu, Dong
Jiang, Yu
Zhang, Jian
Li, Jipeng
author_sort Zhu, Jun
collection PubMed
description BACKGROUND: Emerging evidence shows that serum tumor biomarkers (TBs) and log odds of positive lymph node scheme (LODDS) are closely associated with the prognosis of colorectal cancer (CRC) patients. The aim of our study is to validate the predictive value of TBs and LODDS clinically and to develop a robust prognostic model to predict the overall survival (OS) of patients with CRC. METHODS: CRC patients who underwent radical resection and with no preoperative chemotherapy were enrolled in the study. The eligible population were randomized into training (70%) and test (30%) cohorts for the comprehensive evaluation of the prognostic model. Clinical implications of serum biomarkers and LODDS were identified by univariate and multivariate Cox proportion regression analysis. The predictive ability and discriminative performance were evaluated by Kaplan–Meier (K–M) curves and receiver operating characteristic (ROC) curves. Clinical applicability of the prognostic model was assessed by decision curve analysis (DCA), and the corresponding nomogram was constructed based on the above factors. RESULTS: A total of 1,202 eligible CRC patients were incorporated into our study. Multivariable COX analysis demonstrated that CA199 (HR = 1.304), CA125 (HR = 1.429), CEA (HR = 1.307), and LODDS (HR = 1.488) were independent risk factors for OS (all P < 0.0001). K–M curves showed that the high-risk group possessed a shorter OS than the low-risk counterparts. The area under curves (AUCs) of the model for 1-, 3- and 5-year OS were 86.04, 78.70, and 76.66% respectively for the train cohort (80.35, 77.59, and 74.26% for test cohort). Logistic DCA and survival DCA confirmed that the prognostic model displayed more clinical benefits than the conventional AJCC 8(th) TNM stage and CEA model. The nomograms were built accordingly, and the calibration plot for the probability of survival at 3- or 5-years after surgery showed an optimal agreement between prediction and actual observation. CONCLUSIONS: Preoperative serum TBs and LODDS have significant clinical implications for CRC patients. A novel prognostic model incorporating common TBs (CA199, CA125, and CEA) and LODDS displayed better predictive performance than both single factor and the TNM classification. A novel nomogram incorporating TBs and LODDS could individually predict OS in patients with CRC.
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spelling pubmed-80854212021-05-01 A Novel Prognostic Model and Practical Nomogram for Predicting the Outcomes of Colorectal Cancer: Based on Tumor Biomarkers and Log Odds of Positive Lymph Node Scheme Zhu, Jun Hao, Jun Ma, Qian Shi, Tingyu Wang, Shuai Yan, Jingchuan Chen, Rujie Xu, Dong Jiang, Yu Zhang, Jian Li, Jipeng Front Oncol Oncology BACKGROUND: Emerging evidence shows that serum tumor biomarkers (TBs) and log odds of positive lymph node scheme (LODDS) are closely associated with the prognosis of colorectal cancer (CRC) patients. The aim of our study is to validate the predictive value of TBs and LODDS clinically and to develop a robust prognostic model to predict the overall survival (OS) of patients with CRC. METHODS: CRC patients who underwent radical resection and with no preoperative chemotherapy were enrolled in the study. The eligible population were randomized into training (70%) and test (30%) cohorts for the comprehensive evaluation of the prognostic model. Clinical implications of serum biomarkers and LODDS were identified by univariate and multivariate Cox proportion regression analysis. The predictive ability and discriminative performance were evaluated by Kaplan–Meier (K–M) curves and receiver operating characteristic (ROC) curves. Clinical applicability of the prognostic model was assessed by decision curve analysis (DCA), and the corresponding nomogram was constructed based on the above factors. RESULTS: A total of 1,202 eligible CRC patients were incorporated into our study. Multivariable COX analysis demonstrated that CA199 (HR = 1.304), CA125 (HR = 1.429), CEA (HR = 1.307), and LODDS (HR = 1.488) were independent risk factors for OS (all P < 0.0001). K–M curves showed that the high-risk group possessed a shorter OS than the low-risk counterparts. The area under curves (AUCs) of the model for 1-, 3- and 5-year OS were 86.04, 78.70, and 76.66% respectively for the train cohort (80.35, 77.59, and 74.26% for test cohort). Logistic DCA and survival DCA confirmed that the prognostic model displayed more clinical benefits than the conventional AJCC 8(th) TNM stage and CEA model. The nomograms were built accordingly, and the calibration plot for the probability of survival at 3- or 5-years after surgery showed an optimal agreement between prediction and actual observation. CONCLUSIONS: Preoperative serum TBs and LODDS have significant clinical implications for CRC patients. A novel prognostic model incorporating common TBs (CA199, CA125, and CEA) and LODDS displayed better predictive performance than both single factor and the TNM classification. A novel nomogram incorporating TBs and LODDS could individually predict OS in patients with CRC. Frontiers Media S.A. 2021-04-16 /pmc/articles/PMC8085421/ /pubmed/33937076 http://dx.doi.org/10.3389/fonc.2021.661040 Text en Copyright © 2021 Zhu, Hao, Ma, Shi, Wang, Yan, Chen, Xu, Jiang, Zhang and Li 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). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the ]copyright owner(s) are credited and that he 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 Oncology
Zhu, Jun
Hao, Jun
Ma, Qian
Shi, Tingyu
Wang, Shuai
Yan, Jingchuan
Chen, Rujie
Xu, Dong
Jiang, Yu
Zhang, Jian
Li, Jipeng
A Novel Prognostic Model and Practical Nomogram for Predicting the Outcomes of Colorectal Cancer: Based on Tumor Biomarkers and Log Odds of Positive Lymph Node Scheme
title A Novel Prognostic Model and Practical Nomogram for Predicting the Outcomes of Colorectal Cancer: Based on Tumor Biomarkers and Log Odds of Positive Lymph Node Scheme
title_full A Novel Prognostic Model and Practical Nomogram for Predicting the Outcomes of Colorectal Cancer: Based on Tumor Biomarkers and Log Odds of Positive Lymph Node Scheme
title_fullStr A Novel Prognostic Model and Practical Nomogram for Predicting the Outcomes of Colorectal Cancer: Based on Tumor Biomarkers and Log Odds of Positive Lymph Node Scheme
title_full_unstemmed A Novel Prognostic Model and Practical Nomogram for Predicting the Outcomes of Colorectal Cancer: Based on Tumor Biomarkers and Log Odds of Positive Lymph Node Scheme
title_short A Novel Prognostic Model and Practical Nomogram for Predicting the Outcomes of Colorectal Cancer: Based on Tumor Biomarkers and Log Odds of Positive Lymph Node Scheme
title_sort novel prognostic model and practical nomogram for predicting the outcomes of colorectal cancer: based on tumor biomarkers and log odds of positive lymph node scheme
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8085421/
https://www.ncbi.nlm.nih.gov/pubmed/33937076
http://dx.doi.org/10.3389/fonc.2021.661040
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