Development and validation of an online dynamic nomogram based on the atherogenic index of plasma to screen nonalcoholic fatty liver disease

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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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-023-01808-0.

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Most cited references 30

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Global epidemiology of nonalcoholic fatty liver disease-Meta-analytic assessment of prevalence, incidence, and outcomes.

Zobair Younossi, Aaron Koenig, Dinan Abdelatif … (2016)

Nonalcoholic fatty liver disease (NAFLD) is a major cause of liver disease worldwide. We estimated the global prevalence, incidence, progression, and outcomes of NAFLD and nonalcoholic steatohepatitis (NASH). PubMed/MEDLINE were searched from 1989 to 2015 for terms involving epidemiology and progression of NAFLD. Exclusions included selected groups (studies that exclusively enrolled morbidly obese or diabetics or pediatric) and no data on alcohol consumption or other liver diseases. Incidence of hepatocellular carcinoma (HCC), cirrhosis, overall mortality, and liver-related mortality were determined. NASH required histological diagnosis. All studies were reviewed by three independent investigators. Analysis was stratified by region, diagnostic technique, biopsy indication, and study population. We used random-effects models to provide point estimates (95% confidence interval [CI]) of prevalence, incidence, mortality and incidence rate ratios, and metaregression with subgroup analysis to account for heterogeneity. Of 729 studies, 86 were included with a sample size of 8,515,431 from 22 countries. Global prevalence of NAFLD is 25.24% (95% CI: 22.10-28.65) with highest prevalence in the Middle East and South America and lowest in Africa. Metabolic comorbidities associated with NAFLD included obesity (51.34%; 95% CI: 41.38-61.20), type 2 diabetes (22.51%; 95% CI: 17.92-27.89), hyperlipidemia (69.16%; 95% CI: 49.91-83.46%), hypertension (39.34%; 95% CI: 33.15-45.88), and metabolic syndrome (42.54%; 95% CI: 30.06-56.05). Fibrosis progression proportion, and mean annual rate of progression in NASH were 40.76% (95% CI: 34.69-47.13) and 0.09 (95% CI: 0.06-0.12). HCC incidence among NAFLD patients was 0.44 per 1,000 person-years (range, 0.29-0.66). Liver-specific mortality and overall mortality among NAFLD and NASH were 0.77 per 1,000 (range, 0.33-1.77) and 11.77 per 1,000 person-years (range, 7.10-19.53) and 15.44 per 1,000 (range, 11.72-20.34) and 25.56 per 1,000 person-years (range, 6.29-103.80). Incidence risk ratios for liver-specific and overall mortality for NAFLD were 1.94 (range, 1.28-2.92) and 1.05 (range, 0.70-1.56).

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Mechanisms of NAFLD development and therapeutic strategies

Mary Rinella, Arun Sanyal, Scott Friedman … (2018)

There has been a rise in the prevalence of nonalcoholic fatty liver disease (NAFLD), paralleling a worldwide increase in diabetes and metabolic syndrome. NAFLD, a continuum of liver abnormalities from nonalcoholic fatty liver (NAFL) to nonalcoholic steatohepatitis (NASH), has a variable course but can lead to cirrhosis and liver cancer. Here we review the pathogenic and clinical features of NAFLD, its major comorbidities, clinical progression and risk of complications and in vitro and animal models of NAFLD enabling refinement of therapeutic targets that can accelerate drug development. We also discuss evolving principles of clinical trial design to evaluate drug efficacy and the emerging targets for drug development that involve either single agents or combination therapies intended to arrest or reverse disease progression.

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The Fatty Liver Index: a simple and accurate predictor of hepatic steatosis in the general population

Giorgio Bedogni, Stefano Bellentani, Lucia Miglioli … (2006)

Background Fatty liver (FL) is the most frequent liver disease in Western countries. We used data from the Dionysos Nutrition & Liver Study to develop a simple algorithm for the prediction of FL in the general population. Methods 216 subjects with and 280 without suspected liver disease were studied. FL was diagnosed by ultrasonography and alcohol intake was assessed using a 7-day diary. Bootstrapped stepwise logistic regression was used to identify potential predictors of FL among 13 variables of interest [gender, age, ethanol intake, alanine transaminase, aspartate transaminase, gamma-glutamyl-transferase (GGT), body mass index (BMI), waist circumference, sum of 4 skinfolds, glucose, insulin, triglycerides, and cholesterol]. Potential predictors were entered into stepwise logistic regression models with the aim of obtaining the most simple and accurate algorithm for the prediction of FL. Results An algorithm based on BMI, waist circumference, triglycerides and GGT had an accuracy of 0.84 (95%CI 0.81–0.87) in detecting FL. We used this algorithm to develop the "fatty liver index" (FLI), which varies between 0 and 100. A FLI < 30 (negative likelihood ratio = 0.2) rules out and a FLI ≥ 60 (positive likelihood ratio = 4.3) rules in fatty liver. Conclusion FLI is simple to obtain and may help physicians select subjects for liver ultrasonography and intensified lifestyle counseling, and researchers to select patients for epidemiologic studies. Validation of FLI in external populations is needed before it can be employed for these purposes.

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Author and article information

Contributors

Xian-E. Peng: fmuxe@163.com

Journal

Journal ID (nlm-ta): Lipids Health Dis

Journal ID (iso-abbrev): Lipids Health Dis

Title: Lipids in Health and Disease

Publisher: BioMed Central (London )

ISSN (Electronic): 1476-511X

Publication date (Electronic): 29 March 2023

Publication date PMC-release: 29 March 2023

Publication date Collection: 2023

Volume: 22

Electronic Location Identifier: 44

Affiliations

[1 ]GRID grid.256112.3, ISNI 0000 0004 1797 9307, 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

[2 ]GRID grid.411504.5, ISNI 0000 0004 1790 1622, Grade 2022, Clinical Medicine Major, Integrated Chinese and Western medicine school, , Fujian University of Traditional Chinese Medicine, ; 350108 Fuzhou, China

[3 ]GRID grid.256112.3, ISNI 0000 0004 1797 9307, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, ; Fuzhou, 350108 China

Article

Publisher ID: 1808

DOI: 10.1186/s12944-023-01808-0

PMC ID: 10053077

PubMed ID: 36991386

SO-VID: 511fffdb-982e-42b7-822c-75667467daf0

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 30 December 2022

Date accepted : 22 March 2023

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;

Award ID: 81473047

Funded by: FundRef http://dx.doi.org/10.13039/501100003392, Natural Science Foundation of Fujian Province;

Award ID: 2019J01316

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ScienceOpen disciplines: Biochemistry

Keywords: nonalcoholic fatty liver disease,dynamic nomogram,noninvasive models

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ScienceOpen disciplines: Biochemistry

Keywords: nonalcoholic fatty liver disease, dynamic nomogram, noninvasive models

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Development and validation of an online dynamic nomogram based on the atherogenic index of plasma to screen nonalcoholic fatty liver disease

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Most cited references 30

Global epidemiology of nonalcoholic fatty liver disease-Meta-analytic assessment of prevalence, incidence, and outcomes.

Mechanisms of NAFLD development and therapeutic strategies

The Fatty Liver Index: a simple and accurate predictor of hepatic steatosis in the general population

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