Construction and validation of a risk prediction model for lean metabolic dysfunction-associated steatotic liver disease
Objective To investigate the risk factors for the occurrence of metabolic dysfunction-associated 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(f...
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Editorial Office of Journal of Army Medical University
2025-05-01
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| Series: | 陆军军医大学学报 |
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| Online Access: | https://aammt.tmmu.edu.cn/html/202412024.html |
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| author | QIN Jiayi ZHOU Xueqian MENG Xiangyong |
| author_facet | QIN Jiayi ZHOU Xueqian MENG Xiangyong |
| author_sort | QIN Jiayi |
| collection | DOAJ |
| description | Objective To investigate the risk factors for the occurrence of metabolic dysfunction-associated 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 improvements in NRI and IDI in both the training and validation sets. The calibration curve demonstrated its high accuracy, and both the decision curve analysis and the clinical impact curve analysis indicated that the LMPM provided greater clinical benefits. Conclusion Age, waist circumference, and TG are independent risk factors for lean MASLD. Based on these factors, a prediction model, named LMPM, is developed to assess the risk of MASLD in lean individuals, which exhibits good predictive performance and has certain guiding significance for the timely identification of high-risk populations.
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| format | Article |
| id | doaj-art-c88c2a4305b04df8a17eb901fda2427b |
| institution | OA Journals |
| issn | 2097-0927 |
| language | zho |
| publishDate | 2025-05-01 |
| publisher | Editorial Office of Journal of Army Medical University |
| record_format | Article |
| series | 陆军军医大学学报 |
| spelling | doaj-art-c88c2a4305b04df8a17eb901fda2427b2025-08-20T02:15:28ZzhoEditorial Office of Journal of Army Medical University陆军军医大学学报2097-09272025-05-0147996997910.16016/j.2097-0927.202412024Construction and validation of a risk prediction model for lean metabolic dysfunction-associated steatotic liver diseaseQIN Jiayi0ZHOU Xueqian1MENG Xiangyong2Department of Gastroenterology， First Affiliated Hospital， Army Medical University（Third Military Medical University）， Chongqing， ChinaDepartment of Gastroenterology， First Affiliated Hospital， Army Medical University（Third Military Medical University）， Chongqing， ChinaDepartment of Gastroenterology， First Affiliated Hospital， Army Medical University（Third Military Medical University）， Chongqing， ChinaObjective To investigate the risk factors for the occurrence of metabolic dysfunction-associated 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 improvements in NRI and IDI in both the training and validation sets. The calibration curve demonstrated its high accuracy, and both the decision curve analysis and the clinical impact curve analysis indicated that the LMPM provided greater clinical benefits. Conclusion Age, waist circumference, and TG are independent risk factors for lean MASLD. Based on these factors, a prediction model, named LMPM, is developed to assess the risk of MASLD in lean individuals, which exhibits good predictive performance and has certain guiding significance for the timely identification of high-risk populations. https://aammt.tmmu.edu.cn/html/202412024.htmllean metabolic dysfunction-associated steatotic liver diseaserisk factorsprediction model |
| spellingShingle | QIN Jiayi ZHOU Xueqian MENG Xiangyong Construction and validation of a risk prediction model for lean metabolic dysfunction-associated steatotic liver disease 陆军军医大学学报 lean metabolic dysfunction-associated steatotic liver disease risk factors prediction model |
| title | Construction and validation of a risk prediction model for lean metabolic dysfunction-associated steatotic liver disease |
| title_full | Construction and validation of a risk prediction model for lean metabolic dysfunction-associated steatotic liver disease |
| title_fullStr | Construction and validation of a risk prediction model for lean metabolic dysfunction-associated steatotic liver disease |
| title_full_unstemmed | Construction and validation of a risk prediction model for lean metabolic dysfunction-associated steatotic liver disease |
| title_short | Construction and validation of a risk prediction model for lean metabolic dysfunction-associated steatotic liver disease |
| title_sort | construction and validation of a risk prediction model for lean metabolic dysfunction associated steatotic liver disease |
| topic | lean metabolic dysfunction-associated steatotic liver disease risk factors prediction model |
| url | https://aammt.tmmu.edu.cn/html/202412024.html |
| work_keys_str_mv | AT qinjiayi constructionandvalidationofariskpredictionmodelforleanmetabolicdysfunctionassociatedsteatoticliverdisease AT zhouxueqian constructionandvalidationofariskpredictionmodelforleanmetabolicdysfunctionassociatedsteatoticliverdisease AT mengxiangyong constructionandvalidationofariskpredictionmodelforleanmetabolicdysfunctionassociatedsteatoticliverdisease |