胆结石患病风险预测模型的构建和多中心验证研究  

Establishment and Validation of a Predictive Model for Gallstone Disease in the General Population:A Multicenter Study

作　　者：于文倩 夏静 陈芳圆 焦鹏[3] 崔平 张弛 王宇[6] 单雪峰[6] 王新 YU Wenqian;XIA Jing;CHEN Fangyuan;JIAO Peng;CUI Ping;ZHANG Chi;WANG Yu;SHAN Xuefeng;WANG Xin(West China School of Public Health and West China Fourth Hospital,Sichuan University,Chengdu 610041,China;General Hospital of Western Theater Command of PLA,Chengdu 610504,China;The First People’s Hospital of Jining,Jining 272002,China;Jining Medical University,Jining 272067,China;Tianjin Medical University Cancer Institute and Hospital,Tianjin 300060,China;Bishan Hospital of Chongqing Medical University,Chongqing 402760,China)

机构地区：[1]四川大学华西公共卫生学院/四川大学华西第四医院,成都610041 [2]中国人民解放军西部战区总医院,成都610504 [3]济宁市第一人民医院,济宁272002 [4]济宁医学院,济宁272067 [5]天津医科大学肿瘤医院,天津300060 [6]重庆医科大学附属璧山医院,重庆402760

出　　处：《四川大学学报（医学版）》2024年第3期641-652,共12页Journal of Sichuan University(Medical Sciences)

基　　金：国家自然科学基金(No.81903398);中央高校基本科研基金(No.YJ2021112);四川省医学会医学科研青年创新课题(No.Q21016);四川天府峨眉计划青年人才项目(No.川峨眉第1841号);四川省科学技术厅杰出青年科学基金(No.2023NSFSC1927);四川省科技厅2023年中央引导地方项目(No.2023ZYD0097);四川大学“从0到1”创新项目(No.2023SCUH0026)资助。

摘　　要：目的 基于我国的多中心体检人群数据构建和验证胆结石患病风险预测模型,以期能及早识别胆结石高风险患者,增强人们对该疾病的预防与控制意识。方法 最终纳入96 426名研究对象,其中来自重庆医科大学附属第一医院的35 976名研究对象被划分为训练集(80%, n=28 781)和内部验证集(20%, n=7 195)。来自济宁市第一人民医院、天津医科大学肿瘤医院和重庆市开州人民医院的研究对象将作为外部验证集对模型进行验证。采用logistic回归分析探究与胆结石病(gallstone disease, GSD)相关的风险因素,并利用列线图分别构建完整和简化的风险预测模型。校准曲线、受试者特征曲线下面积(AUC)和决策曲线分析用于验证这些模型的准确性和临床效用。此外,本研究基于研究结果建立了一个在线网站便于预测模型的使用(完全模型:https://wenqianyu.shinyapps.io/Completemodel/,简化模型:https://wenqianyu.shinyapps.io/Simplified/)。结果 女性、高龄、较高的体质量指数、空腹血糖、尿酸、总胆红素、γ-谷氨酰转肽酶和脂肪肝与GSD患病风险呈正相关。胆囊息肉、总胆固醇、高密度脂蛋白胆固醇、低密度脂蛋白胆固醇和天冬氨酸转氨酶与GSD患病风险呈负相关。完全模型内部验证AUC为74.1%(95%置信区间:72.9%~75.3%)和简化模型内部验证AUC为73.7%(95%置信区间:72.5%~75.0%),两种模型的决策曲线分析和校准曲线结果显示,GSD的完全和简化风险预测模型表现出优异的预测性能。此外,完全模型与简化模型的预测性能差异无统计学意义(P>0.05)。结论 本研究所建立的胆结石患病风险预测模型,以及在线GSD患病风险评估工具可以帮助患者和临床医生进行胆结石患病风险的预测。我们推荐在实践中使用简化模型以提高筛查高风险人群的效率。使用简化模型有助于增强普通人群的自我防控意识和GSD的早期干预。Objective Gallstone disease(GSD)is one of the common digestive tract diseases with a high worldwide prevalence.The effects of GSD on patients include but are not limited to the symptoms of nausea,vomiting,and biliary colic directly caused by GSD.In addition,there is mounting evidence from cohort studies connecting GSD to other conditions,such as cardiovascular diseases,biliary tract cancer,and colorectal cancer.Early identification of patients at a high risk of GSD may help improve the prevention and control of the disease.A series of studies have attempted to establish prediction models for GSD,but these models could not be fully applied in the general population due to incomplete prediction factors,small sample sizes,and limitations in external validation.It is crucial to design a universally applicable GSD risk prediction model for the general population and to take individualized intervention measures to prevent the occurrence of GSD.This study aims to conduct a multicenter investigation involving more than 90000 people to construct and validate a complete and simplified GSD risk prediction model.Methods A total of 123634 participants were included in the study between January 2015 and December 2020,of whom 43929 were from the First Affiliated Hospital of Chongqing Medical University(Chongqing,China),11907 were from the First People’s Hospital of Jining City(Shandong,China),1538 were from the Tianjin Medical University Cancer Institute and Hospital(Tianjin,China),and 66260 were from the People’s Hospital of Kaizhou District(Chongqing,China).After excluding patients with incomplete clinical medical data,35976 patients from the First Affiliated Hospital of Chongqing Medical University were divided into a training data set(n=28781,80%)and a validation data set(n=7195,20%).Logistic regression analyses were performed to investigate the relevant risk factors of GSD,and a complete risk prediction model was constructed.Factors with high scores,mainly according to the nomograms of the complete model,were retained

关 键 词：胆结石 预测模型 列线图 回顾性研究 

分 类 号：R575.62[医药卫生—消化系统]