瘦型代谢功能障碍相关脂肪性肝病风险预测模型的构建与验证  

Construction and validation of a risk prediction model for lean metabolic dysfunction-associated steatotic liver disease

作　　者：秦嘉怡 周学谦 孟祥勇 陈文生 QIN Jiayi;ZHOU Xueqian;MENG Xiangyong;CHEN Wensheng(Department of Gastroenterology,First Affiliated Hospital,Army Medical University(Third Military Medical University),Chongqing,China)

机构地区：[1]陆军军医大学(第三军医大学)第一附属医院消化内科,重庆

出　　处：《陆军军医大学学报》2025年第9期969-979,共11页Journal of Army Medical University

基　　金：国家自然科学基金面上项目(82070599)。

摘　　要：目的探讨瘦型人群发生代谢功能障碍相关脂肪性肝病(metabolic dysfunction-associated steatotic liver disease,MASLD)的危险因素,并构建风险预测模型。方法本研究基于美国国家健康和营养检查调查数据库(2017年1月至2020年3月),纳入1123名成年个体。通过简单随机抽样将其分为训练集(n=561)和验证集(n=562),并收集有关人口统计学、人体测量学、生活方式、基础疾病和实验室检查结果的数据。在训练集中运用LASSO回归筛选潜在变量,再通过多因素Logistic回归确定瘦型MASLD的独立危险因素。基于这些危险因素,构建瘦型MASLD预测模型(prediction model for lean metabolic dysfunction-associated steatotic liver disease,LMPM)。为评估LMPM的临床价值,将其与脂肪肝指数(fatty liver index,FLI)和肝脂肪变性指数(hepatic steatosis index,HSI)这两种常用的非酒精性脂肪性肝病预测模型进行比较。通过受试者工作特征曲线下面积(area under the receiver operating characteristiccurve,AUC)、净重新分类指数(netreclassificationindex,NRI)、综合判别改善指数(integrated discrimination improvement,IDI)、校准曲线、决策曲线和临床影响曲线对模型的性能进行评价和内部验证。结果本研究确定年龄、腰围和甘油三酯为瘦型人群发生MASLD的独立危险因素。基于上诉指标建立的LMPM在训练集和验证集中表现出良好的区分能力,AUC值分别为0.86(95%CI:0.82~0.89)和0.81(95%CI:0.77~0.85),明显优于FLI[训练集AUC=0.83(95%CI:0.79~0.87);验证集AUC=0.74(95%CI:0.70~0.79)]和HSI[训练集AUC=0.71(95%CI:0.66~0.76);验证集AUC=0.71(95%CI:0.65~0.76)]。相较于FLI和HSI,LMPM在训练集和验证集中NRI和IDI均得到改善。校准曲线显示出LMPM的高准确性,决策曲线和临床影响曲线均表明LMPM提供了更大的临床益处。结论年龄、腰围和甘油三酯是瘦型MASLD的独立危险因素,据此构建的用于评估瘦型人群发生MASLD风险的预测模型LMPM�Objective To investigate the risk factors for the occurrence of metabolic dysfunctionassociated steatotic liver disease(MASLD) in lean individuals and construct a risk prediction model.Methods Based on the National Health and Nutrition Examination Survey(NHANES) database in the United States(from January 2017 to March 2020), 1 123 adult individuals were included in this study. Then the participants were randomly divided into a training set(n=561) and a validation set(n=562) through simple random sampling. Data on their demographics, anthropometrics, lifestyle, underlying diseases, and laboratory test results were collected. LASSO regression analysis was used to screen potential variables in the training set,and multivariate logistic regression was employed to identify independent risk factors for lean MASLD. Based on these risk factors, a prediction model for lean MASLD was constructed(LMPM). To evaluate the clinical value of the LMPM, it was compared with two commonly used prediction models for non-alcoholic fatty liver disease, the fatty liver index(FLI) and the hepatic steatosis index(HSI). The performance of the model was evaluated and internally validated using the area under the receiver operating characteristic curve(AUC), net reclassification index(NRI), integrated discrimination improvement(IDI), calibration curve, decision curve, and clinical impact curve. Results Age, waist circumference, and triglycerides(TG) were identified as independent risk factors for the development of MASLD in lean individuals. The LMPM, constructed based on these indicators, demonstrated good discriminative ability in both the training and validation sets, with AUC values of 0. 86(95%CI: 0. 82~0. 89) and 0. 81(95%CI: 0. 77~0. 85), respectively, which were significantly better than those of FLI [training set: AUC=0. 83(95%CI: 0. 79~0. 87);validation set: AUC=0. 74(95%CI: 0. 70~0. 79)]and HSI [training set: AUC=0. 71(95%CI: 0. 66~0. 76);validation set: AUC=0. 71(95%CI: 0. 65~0. 76)].Compared with FLI and HSI, the LMPM showed imp

关 键 词：瘦型代谢功能障碍相关脂肪性肝病 危险因素 预测模型 

分 类 号：R181.23[医药卫生—流行病学] R575.5[医药卫生—公共卫生与预防医学] R589.2