Development and validation of a prediction model for early screening of people at high risk for colorectal cancer
作者机构:Department of General SurgeryNingbo No.2 HospitalNingbo 315000Zhejiang ProvinceChina Center for Health EconomicsFaculty of Humanities and Social SciencesUniversity of NottinghamNingbo 315100Zhejiang ProvinceChina Department of Global HealthNingbo Institute of Life and Health IndustryUniversity of Chinese Academy of SciencesNingbo 315000Zhejiang ProvinceChina School of Public HealthMedical College of Soochow UniversitySuzhou 215123Jiangsu ProvinceChina
出 版 物:《World Journal of Gastroenterology》 (世界胃肠病学杂志(英文版))
年 卷 期:2024年第30卷第5期
页 面:450-461页
核心收录:
学科分类:1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
基 金:Supported by the Project of NINGBO Leading Medical Health Discipline,No.2022-B11 Ningbo Natural Science Foundation,No.202003N4206 Public Welfare Foundation of Ningbo,No.2021S108
主 题:Colorectal cancer Early screening model High-risk population Nomogram model Questionnaire survey Dietary habit Living habit
摘 要:BACKGROUND Colorectal cancer(CRC)is a serious threat *** early screening is suggested to be the most effective method to prevent and control CRC,the current situation of early screening for CRC is still not *** China,the incidence of CRC in the Yangtze River Delta region is increasing dramatically,but few studies have been ***,it is necessary to develop a simple and efficient early screening model for *** To develop and validate an early-screening nomogram model to identify individuals at high risk of *** Data of 64448 participants obtained from Ningbo Hospital,China between 2014 and 2017 were retrospectively *** cohort comprised 64448 individuals,of which,530 were excluded due to missing or incorrect *** 63918,7607(11.9%)individuals were considered to be high risk for CRC,and 56311(88.1%)were *** participants were randomly allocated to a training set(44743)or validation set(19175).The discriminatory ability,predictive accuracy,and clinical utility of the model were evaluated by constructing and analyzing receiver operating characteristic(ROC)curves and calibration curves and by decision curve ***,the model was validated internally using a bootstrap resampling *** Seven variables,including demographic,lifestyle,and family history information,were *** logistic regression analysis revealed that age[odds ratio(OR):1.03,95%confidence interval(CI):1.02-1.03,P0.001],body mass index(BMI)(OR:1.07,95%CI:1.06-1.08,P0.001),waist circumference(WC)(OR:1.03,95%CI:1.02-1.03 P0.001),lifestyle(OR:0.45,95%CI:0.42-0.48,P0.001),and family history(OR:4.28,95%CI:4.04-4.54,P0.001)were the most significant predictors of high-risk *** lifestyle was a protective factor,whereas family history was the most significant risk *** area under the curve was 0.734(95%CI:0.723-0.745)for the final validation set ROC curve and 0.735(95%CI:0.728-0.742)for the training s