Development and Validation of a Predictive Scoring System for Colorectal Cancer Patients With Liver Metastasis: A Population-Based Study

Liver metastasis in colorectal cancer (CRC) is common and has an unfavorable prognosis. This study aimed to establish a functional nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with colorectal cancer liver metastasis (CRCLM). A total of 9,736 patients...

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Autores principales:	Yinghao Cao, Songqing Ke, Shenghe Deng, Lizhao Yan, Junnan Gu, Fuwei Mao, Yifan Xue, Changmin Zheng, Wentai Cai, Hongli Liu, Han Li, Fumei Shang, Zhuolun Sun, Ke Wu, Ning Zhao, Kailin Cai
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	colorectal cancer liver metastasis primary tumpur site nomogram overall survival cancer-specific survival Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/c6dea168e6a644f781f1d0bf12dc2983
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spelling	oai:doaj.org-article:c6dea168e6a644f781f1d0bf12dc29832021-12-01T21:51:22ZDevelopment and Validation of a Predictive Scoring System for Colorectal Cancer Patients With Liver Metastasis: A Population-Based Study2234-943X10.3389/fonc.2021.719638https://doaj.org/article/c6dea168e6a644f781f1d0bf12dc29832021-12-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fonc.2021.719638/fullhttps://doaj.org/toc/2234-943XLiver metastasis in colorectal cancer (CRC) is common and has an unfavorable prognosis. This study aimed to establish a functional nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with colorectal cancer liver metastasis (CRCLM). A total of 9,736 patients with CRCLM from 2010 to 2016 were randomly assigned to training, internal validation, and external validation cohorts. Univariate and multivariate Cox analyses were performed to identify independent clinicopathologic predictive factors, and a nomogram was constructed to predict CSS and OS. Multivariate analysis demonstrated age, tumor location, differentiation, gender, TNM stage, chemotherapy, number of sampled lymph nodes, number of positive lymph nodes, tumor size, and metastatic surgery as independent predictors for CRCLM. A nomogram incorporating the 10 predictors was constructed. The nomogram showed favorable sensitivity at predicting 1-, 3-, and 5-year OS, with area under the receiver operating characteristic curve (AUROC) values of 0.816, 0.782, and 0.787 in the training cohort; 0.827, 0.769, and 0.774 in the internal validation cohort; and 0.819, 0.745, and 0.767 in the external validation cohort, respectively. For CSS, the values were 0.825, 0.771, and 0.772 in the training cohort; 0.828, 0.753, and 0.758 in the internal validation cohort; and 0.828, 0.737, and 0.772 in the external validation cohort, respectively. Calibration curves and ROC curves revealed that using our models to predict the OS and CSS would add more benefit than other single methods. In summary, the novel nomogram based on significant clinicopathological characteristics can be conveniently used to facilitate the postoperative individualized prediction of OS and CSS in CRCLM patients.Yinghao CaoSongqing KeShenghe DengLizhao YanJunnan GuFuwei MaoYifan XueChangmin ZhengWentai CaiHongli LiuHan LiFumei ShangZhuolun SunKe WuNing ZhaoKailin CaiFrontiers Media S.A.articlecolorectal cancerliver metastasisprimary tumpur sitenomogramoverall survivalcancer-specific survivalNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENFrontiers in Oncology, Vol 11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	colorectal cancer liver metastasis primary tumpur site nomogram overall survival cancer-specific survival Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	colorectal cancer liver metastasis primary tumpur site nomogram overall survival cancer-specific survival Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Yinghao Cao Songqing Ke Shenghe Deng Lizhao Yan Junnan Gu Fuwei Mao Yifan Xue Changmin Zheng Wentai Cai Hongli Liu Han Li Fumei Shang Zhuolun Sun Ke Wu Ning Zhao Kailin Cai Development and Validation of a Predictive Scoring System for Colorectal Cancer Patients With Liver Metastasis: A Population-Based Study
description	Liver metastasis in colorectal cancer (CRC) is common and has an unfavorable prognosis. This study aimed to establish a functional nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with colorectal cancer liver metastasis (CRCLM). A total of 9,736 patients with CRCLM from 2010 to 2016 were randomly assigned to training, internal validation, and external validation cohorts. Univariate and multivariate Cox analyses were performed to identify independent clinicopathologic predictive factors, and a nomogram was constructed to predict CSS and OS. Multivariate analysis demonstrated age, tumor location, differentiation, gender, TNM stage, chemotherapy, number of sampled lymph nodes, number of positive lymph nodes, tumor size, and metastatic surgery as independent predictors for CRCLM. A nomogram incorporating the 10 predictors was constructed. The nomogram showed favorable sensitivity at predicting 1-, 3-, and 5-year OS, with area under the receiver operating characteristic curve (AUROC) values of 0.816, 0.782, and 0.787 in the training cohort; 0.827, 0.769, and 0.774 in the internal validation cohort; and 0.819, 0.745, and 0.767 in the external validation cohort, respectively. For CSS, the values were 0.825, 0.771, and 0.772 in the training cohort; 0.828, 0.753, and 0.758 in the internal validation cohort; and 0.828, 0.737, and 0.772 in the external validation cohort, respectively. Calibration curves and ROC curves revealed that using our models to predict the OS and CSS would add more benefit than other single methods. In summary, the novel nomogram based on significant clinicopathological characteristics can be conveniently used to facilitate the postoperative individualized prediction of OS and CSS in CRCLM patients.
format	article
author	Yinghao Cao Songqing Ke Shenghe Deng Lizhao Yan Junnan Gu Fuwei Mao Yifan Xue Changmin Zheng Wentai Cai Hongli Liu Han Li Fumei Shang Zhuolun Sun Ke Wu Ning Zhao Kailin Cai
author_facet	Yinghao Cao Songqing Ke Shenghe Deng Lizhao Yan Junnan Gu Fuwei Mao Yifan Xue Changmin Zheng Wentai Cai Hongli Liu Han Li Fumei Shang Zhuolun Sun Ke Wu Ning Zhao Kailin Cai
author_sort	Yinghao Cao
title	Development and Validation of a Predictive Scoring System for Colorectal Cancer Patients With Liver Metastasis: A Population-Based Study
title_short	Development and Validation of a Predictive Scoring System for Colorectal Cancer Patients With Liver Metastasis: A Population-Based Study
title_full	Development and Validation of a Predictive Scoring System for Colorectal Cancer Patients With Liver Metastasis: A Population-Based Study
title_fullStr	Development and Validation of a Predictive Scoring System for Colorectal Cancer Patients With Liver Metastasis: A Population-Based Study
title_full_unstemmed	Development and Validation of a Predictive Scoring System for Colorectal Cancer Patients With Liver Metastasis: A Population-Based Study
title_sort	development and validation of a predictive scoring system for colorectal cancer patients with liver metastasis: a population-based study
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/c6dea168e6a644f781f1d0bf12dc2983
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Development and Validation of a Predictive Scoring System for Colorectal Cancer Patients With Liver Metastasis: A Population-Based Study

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