Development and validation of a prognostic model to predict the prognosis of patients with colorectal gastrointestinal stromal tumor: A large international population-based cohort study

BackgroundColorectal gastrointestinal stromal tumors (GISTs), mesenchymal malignancy, only accounts for about 6% of GISTs, but prognosis is generally poor. Given the rarity of colorectal GISTs, the prognostic values of clinicopathological features in the patients remain unclear. Nomograms can provid...

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Main Authors: Yiding Li, Yujie Zhang, Yang Fu, Wanli Yang, Xiaoqian Wang, Lili Duan, Liaoran Niu, Junfeng Chen, Wei Zhou, Jinqiang Liu, Jing Wang, Daiming Fan, Liu Hong
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-11-01
Series:Frontiers in Oncology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.1004662/full
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author Yiding Li
Yujie Zhang
Yang Fu
Wanli Yang
Xiaoqian Wang
Lili Duan
Liaoran Niu
Junfeng Chen
Wei Zhou
Jinqiang Liu
Jing Wang
Daiming Fan
Liu Hong
author_facet Yiding Li
Yujie Zhang
Yang Fu
Wanli Yang
Xiaoqian Wang
Lili Duan
Liaoran Niu
Junfeng Chen
Wei Zhou
Jinqiang Liu
Jing Wang
Daiming Fan
Liu Hong
author_sort Yiding Li
collection DOAJ
description BackgroundColorectal gastrointestinal stromal tumors (GISTs), mesenchymal malignancy, only accounts for about 6% of GISTs, but prognosis is generally poor. Given the rarity of colorectal GISTs, the prognostic values of clinicopathological features in the patients remain unclear. Nomograms can provide a visual interface to help calculate the predicted probability of a patient meeting a specific clinical endpoint and communicate it to the patient.MethodsWe included a total of 448 patients with colorectal GISTs diagnosed between 2000 and 2019 from the Surveillance, Epidemiology, and End Results (SEER) database. For nomogram construction and validation, patients in the SEER database were divided randomly into the training cohort and internal validation cohort at a ratio of 7:3, while 44 patients with colorectal GISTs from our hospital patient data set between 2010 to 2016 served as the external validation cohort. The OS curves were drawn using the Kaplan–Meier method and assessed using the log-rank test. And, Fine and Gray’s competing-risks regression models were conducted to assess CSS. We performed univariate and multivariate analyses to select prognostic factors for survival time and constructed a predictive nomogram based on the results of the multivariate analysis.ResultsThrough univariate and multivariate analyses, it is found that age, primary site, SEER stage, surgery, and tumor size constitute significant risk factors for OS, and age, primary site, histological grade, SEER stage, American Joint Committee for Cancer (AJCC) stage, surgery, and tumor size constitute risk factors for CSS. We found that the nomogram provided a good assessment of OS and CSS at 1-, 3- and 5- year in patients with colorectal GISTs. The calibration plots for the training, internal validation and external validation cohorts at 1-, 3- and 5- year OS and CSS indicated that the predicted survival rates closely correspond to the actual survival rates.ConclusionWe constructed and validated an unprecedented nomogram to predict OS and CSS in patients with colorectal GISTs. The nomogram had the potential as a clinically predictive tool for colorectal GISTs prognosis, and can be used as a potential, objective and additional tool for clinicians in predicting the prognosis of colorectal GISTs patients worldwide. Clinicians could wield the nomogram to accurately evaluate patients’ OS and CSS, identify high-risk patients, and provide a baseline to optimize treatment plans.
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spelling doaj.art-8e1caac6603b4a9faed3054ea5f54da42022-12-22T04:33:56ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-11-011210.3389/fonc.2022.10046621004662Development and validation of a prognostic model to predict the prognosis of patients with colorectal gastrointestinal stromal tumor: A large international population-based cohort studyYiding Li0Yujie Zhang1Yang Fu2Wanli Yang3Xiaoqian Wang4Lili Duan5Liaoran Niu6Junfeng Chen7Wei Zhou8Jinqiang Liu9Jing Wang10Daiming Fan11Liu Hong12State key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi’an, ChinaDepartment of Histology and Embryology, School of Basic Medicine, Xi’an Medical University, Xi’an, ChinaSchool of Basic Medical Sciences, Fourth Military Medical University, Xi’an, ChinaState key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi’an, ChinaState key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi’an, ChinaState key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi’an, ChinaState key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi’an, ChinaState key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi’an, ChinaState key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi’an, ChinaState key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi’an, ChinaDepartment of Immunology, Fourth Military Medical University, Xi’an, ChinaState key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi’an, ChinaState key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi’an, ChinaBackgroundColorectal gastrointestinal stromal tumors (GISTs), mesenchymal malignancy, only accounts for about 6% of GISTs, but prognosis is generally poor. Given the rarity of colorectal GISTs, the prognostic values of clinicopathological features in the patients remain unclear. Nomograms can provide a visual interface to help calculate the predicted probability of a patient meeting a specific clinical endpoint and communicate it to the patient.MethodsWe included a total of 448 patients with colorectal GISTs diagnosed between 2000 and 2019 from the Surveillance, Epidemiology, and End Results (SEER) database. For nomogram construction and validation, patients in the SEER database were divided randomly into the training cohort and internal validation cohort at a ratio of 7:3, while 44 patients with colorectal GISTs from our hospital patient data set between 2010 to 2016 served as the external validation cohort. The OS curves were drawn using the Kaplan–Meier method and assessed using the log-rank test. And, Fine and Gray’s competing-risks regression models were conducted to assess CSS. We performed univariate and multivariate analyses to select prognostic factors for survival time and constructed a predictive nomogram based on the results of the multivariate analysis.ResultsThrough univariate and multivariate analyses, it is found that age, primary site, SEER stage, surgery, and tumor size constitute significant risk factors for OS, and age, primary site, histological grade, SEER stage, American Joint Committee for Cancer (AJCC) stage, surgery, and tumor size constitute risk factors for CSS. We found that the nomogram provided a good assessment of OS and CSS at 1-, 3- and 5- year in patients with colorectal GISTs. The calibration plots for the training, internal validation and external validation cohorts at 1-, 3- and 5- year OS and CSS indicated that the predicted survival rates closely correspond to the actual survival rates.ConclusionWe constructed and validated an unprecedented nomogram to predict OS and CSS in patients with colorectal GISTs. The nomogram had the potential as a clinically predictive tool for colorectal GISTs prognosis, and can be used as a potential, objective and additional tool for clinicians in predicting the prognosis of colorectal GISTs patients worldwide. Clinicians could wield the nomogram to accurately evaluate patients’ OS and CSS, identify high-risk patients, and provide a baseline to optimize treatment plans.https://www.frontiersin.org/articles/10.3389/fonc.2022.1004662/fullcolorectal gastrointestinal stromal tumorsnomogramprognostic factorssurvival rateSEER database
spellingShingle Yiding Li
Yujie Zhang
Yang Fu
Wanli Yang
Xiaoqian Wang
Lili Duan
Liaoran Niu
Junfeng Chen
Wei Zhou
Jinqiang Liu
Jing Wang
Daiming Fan
Liu Hong
Development and validation of a prognostic model to predict the prognosis of patients with colorectal gastrointestinal stromal tumor: A large international population-based cohort study
Frontiers in Oncology
colorectal gastrointestinal stromal tumors
nomogram
prognostic factors
survival rate
SEER database
title Development and validation of a prognostic model to predict the prognosis of patients with colorectal gastrointestinal stromal tumor: A large international population-based cohort study
title_full Development and validation of a prognostic model to predict the prognosis of patients with colorectal gastrointestinal stromal tumor: A large international population-based cohort study
title_fullStr Development and validation of a prognostic model to predict the prognosis of patients with colorectal gastrointestinal stromal tumor: A large international population-based cohort study
title_full_unstemmed Development and validation of a prognostic model to predict the prognosis of patients with colorectal gastrointestinal stromal tumor: A large international population-based cohort study
title_short Development and validation of a prognostic model to predict the prognosis of patients with colorectal gastrointestinal stromal tumor: A large international population-based cohort study
title_sort development and validation of a prognostic model to predict the prognosis of patients with colorectal gastrointestinal stromal tumor a large international population based cohort study
topic colorectal gastrointestinal stromal tumors
nomogram
prognostic factors
survival rate
SEER database
url https://www.frontiersin.org/articles/10.3389/fonc.2022.1004662/full
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