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Peng H, Zhang J, Huang X, Xu M, Huang J, Wu Y, Peng XE. Development and validation of an online dynamic nomogram based on the atherogenic index of plasma to screen nonalcoholic fatty liver disease. Lipids Health Dis 2023; 22:44. [PMID: 36991386 DOI: 10.1186/s12944-023-01808-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 03/22/2023] [Indexed: 03/31/2023] Open
Abstract
BACKGROUND Nonalcoholic fatty liver disease (NAFLD), a common liver disease worldwide, can be reversed early in life with lifestyle and medical interventions. This study aimed to develop a noninvasive tool to screen NAFLD accurately. METHODS Risk factors for NAFLD were identified using multivariate logistic regression analysis, and an online NAFLD screening nomogram was developed. The nomogram was compared with reported models (fatty liver index (FLI), atherogenic index of plasma (AIP), and hepatic steatosis index (HSI)). Nomogram performance was evaluated through internal and external validation (National Health and Nutrition Examination Survey (NHANES) database). RESULTS The nomogram was developed based on six variables. The diagnostic performance of the present nomogram for NAFLD (area under the receiver operator characteristic curve (AUROC): 0.863, 0.864, and 0.833, respectively) was superior to that of the HSI (AUROC: 0.835, 0.833, and 0.810, respectively) and AIP (AUROC: 0.782, 0.773, and 0.728, respectively) in the training, validation, and NHANES sets. Decision curve analysis and clinical impact curve analysis presented good clinical utility. CONCLUSION This study establishes a new online dynamic nomogram with excellent diagnostic and clinical performance. It has the potential to be a noninvasive and convenient method for screening individuals at high risk for NAFLD.
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Affiliation(s)
- Hewei Peng
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Xuefu North Road 1St, Shangjie Town, Minhou Country, Fuzhou, 350108, Fujian, China
| | - Junchao Zhang
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Xuefu North Road 1St, Shangjie Town, Minhou Country, Fuzhou, 350108, Fujian, China
| | - Xianhua Huang
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Xuefu North Road 1St, Shangjie Town, Minhou Country, Fuzhou, 350108, Fujian, China
| | - Miao Xu
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Xuefu North Road 1St, Shangjie Town, Minhou Country, Fuzhou, 350108, Fujian, China
| | - Jingru Huang
- Grade 2022, Clinical Medicine Major, Integrated Chinese and Western medicine school, Fujian University of Traditional Chinese Medicine, 350108, Fuzhou, China
| | - Yunli Wu
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, 350108, China
| | - Xian-E Peng
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Xuefu North Road 1St, Shangjie Town, Minhou Country, Fuzhou, 350108, Fujian, China.
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, 350108, China.
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