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Personalizing prognostic prediction in early-onset Colorectal Cancer

Accurately estimating prognosis based on clinicopathologic variables could improve risk stratification for patients with early-onset colorectal cancer (EOCRC). Our primary goal was to create and validate a survival nomogram with adequate performance for predicting overall survival (OS) in patients w...

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Autores principales: Liu, Jian, Liu, Zhengru, Li, Jiao, Tian, Shan, Dong, Weiguo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7545680/
https://www.ncbi.nlm.nih.gov/pubmed/33046995
http://dx.doi.org/10.7150/jca.46871
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author Liu, Jian
Liu, Zhengru
Li, Jiao
Tian, Shan
Dong, Weiguo
author_facet Liu, Jian
Liu, Zhengru
Li, Jiao
Tian, Shan
Dong, Weiguo
author_sort Liu, Jian
collection PubMed
description Accurately estimating prognosis based on clinicopathologic variables could improve risk stratification for patients with early-onset colorectal cancer (EOCRC). Our primary goal was to create and validate a survival nomogram with adequate performance for predicting overall survival (OS) in patients with EOCRC. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to identify clinical features statistically related to OS. Then we established and internally validated a survival nomogram based on surveillance, epidemiology and end results (SEER) database (N=23813). A cohort of 77 patients with EOCRC from Renmin Hospital of Wuhan University (RHWU) was employed to detect the external validity of the survival nomogram. Moreover, we compared the predictive accuracy of survival nomogram with TNM stage, and also compared the OS between endoscopy and surgery groups before and after propensity score matching (PSM) among EOCRC patients with early stage (Tis-T1N0M0). We selected seven informative indexes (N stage, M stage, perineural invasion, chemotherapy, surgery primary site, summary stage and tumor grade) for the construction of the survival nomogram. Then the survival nomogram exhibited good discrimination with C-index of 0.829, 0.841 and 0.796 in the SEER training, SEER validation and RHWU validation sets, respectively. Calibration curves showed good concordance between the survival nomogram predictions and actual outcomes for 1-year, 3-year and 5-year OS. Furthermore, the survival nomogram was superior to risk stratification by TNM stage in predicting OS among patients with EOCRC. Early-stage patients treated with endoscopy showed similar survival to those with surgery before and after PSM. We proposed a survival nomogram based on the extensively used parameters to precisely predict OS in EOCRC patients. This survival nomogram will contribute to aid oncologists better risk stratification and prognostication for patients with EOCRC.
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spelling pubmed-75456802020-10-11 Personalizing prognostic prediction in early-onset Colorectal Cancer Liu, Jian Liu, Zhengru Li, Jiao Tian, Shan Dong, Weiguo J Cancer Research Paper Accurately estimating prognosis based on clinicopathologic variables could improve risk stratification for patients with early-onset colorectal cancer (EOCRC). Our primary goal was to create and validate a survival nomogram with adequate performance for predicting overall survival (OS) in patients with EOCRC. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to identify clinical features statistically related to OS. Then we established and internally validated a survival nomogram based on surveillance, epidemiology and end results (SEER) database (N=23813). A cohort of 77 patients with EOCRC from Renmin Hospital of Wuhan University (RHWU) was employed to detect the external validity of the survival nomogram. Moreover, we compared the predictive accuracy of survival nomogram with TNM stage, and also compared the OS between endoscopy and surgery groups before and after propensity score matching (PSM) among EOCRC patients with early stage (Tis-T1N0M0). We selected seven informative indexes (N stage, M stage, perineural invasion, chemotherapy, surgery primary site, summary stage and tumor grade) for the construction of the survival nomogram. Then the survival nomogram exhibited good discrimination with C-index of 0.829, 0.841 and 0.796 in the SEER training, SEER validation and RHWU validation sets, respectively. Calibration curves showed good concordance between the survival nomogram predictions and actual outcomes for 1-year, 3-year and 5-year OS. Furthermore, the survival nomogram was superior to risk stratification by TNM stage in predicting OS among patients with EOCRC. Early-stage patients treated with endoscopy showed similar survival to those with surgery before and after PSM. We proposed a survival nomogram based on the extensively used parameters to precisely predict OS in EOCRC patients. This survival nomogram will contribute to aid oncologists better risk stratification and prognostication for patients with EOCRC. Ivyspring International Publisher 2020-09-25 /pmc/articles/PMC7545680/ /pubmed/33046995 http://dx.doi.org/10.7150/jca.46871 Text en © The author(s) This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
spellingShingle Research Paper
Liu, Jian
Liu, Zhengru
Li, Jiao
Tian, Shan
Dong, Weiguo
Personalizing prognostic prediction in early-onset Colorectal Cancer
title Personalizing prognostic prediction in early-onset Colorectal Cancer
title_full Personalizing prognostic prediction in early-onset Colorectal Cancer
title_fullStr Personalizing prognostic prediction in early-onset Colorectal Cancer
title_full_unstemmed Personalizing prognostic prediction in early-onset Colorectal Cancer
title_short Personalizing prognostic prediction in early-onset Colorectal Cancer
title_sort personalizing prognostic prediction in early-onset colorectal cancer
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7545680/
https://www.ncbi.nlm.nih.gov/pubmed/33046995
http://dx.doi.org/10.7150/jca.46871
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