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. 2024 Mar 15;24(1):109.
doi: 10.1186/s12876-024-03190-2.

Using new indices to predict metabolism dysfunction-associated fatty liver disease (MAFLD): analysis of the national health and nutrition examination survey database

Xu Ming Li #  1 , Song Lian Liu #  2 , Ya Jun He  1 , Jian Chang Shu  3
Affiliations

Using new indices to predict metabolism dysfunction-associated fatty liver disease (MAFLD): analysis of the national health and nutrition examination survey database

Xu Ming Li et al. BMC Gastroenterol. .

Abstract

Background: Metabolism dysfunction-associated fatty liver disease (MAFLD), is the most common chronic liver disease. Few MAFLD predictions are simple and accurate. We examined the predictive performance of the albumin-to-glutamyl transpeptidase ratio (AGTR), plasma atherogenicity index (AIP), and serum uric acid to high-density lipoprotein cholesterol ratio (UHR) for MAFLD to design practical, inexpensive, and reliable models.

Methods: The National Health and Nutrition Examination Survey (NHANES) 2007-2016 cycle dataset, which contained 12,654 participants, was filtered and randomly separated into internal validation and training sets. This study examined the relationships of the AGTR and AIP with MAFLD using binary multifactor logistic regression. We then created a MAFLD predictive model using the training dataset and validated the predictive model performance with the 2017-2018 NHANES and internal datasets.

Results: In the total population, the predictive ability (AUC) of the AIP, AGTR, UHR, and the combination of all three for MAFLD showed in the following order: 0.749, 0.773, 0.728 and 0.824. Further subgroup analysis showed that the AGTR (AUC1 = 0.796; AUC2 = 0.690) and the combination of the three measures (AUC1 = 0.863; AUC2 = 0.766) better predicted MAFLD in nondiabetic patients. Joint prediction outperformed the individual measures in predicting MAFLD in the subgroups. Additionally, the model better predicted female MAFLD. Adding waist circumference and or BMI to this model improves predictive performance.

Conclusion: Our study showed that the AGTR, AIP, and UHR had strong MAFLD predictive value, and their combination can increase MAFLD predictive performance. They also performed better in females.

Keywords: AIP; ALB/GGT; Metabolic dysfunction-associated fatty liver; NHANES; Predictive models; UHR.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Flow chart
Fig. 2
Fig. 2
A: The roc curve for internal validation; B: The roc curve for the second validation
Fig. 3
Fig. 3
The internal validation roc curve of the subgroup
Fig. 4
Fig. 4
The internal validation roc curve of the subgroup
Fig. 5
Fig. 5
The internal validation roc curve of the subgroup
Fig. 6
Fig. 6
The second validation's roc curve for the subgroup
Fig. 7
Fig. 7
The second validation's roc curve for the subgroup
Fig. 8
Fig. 8
The second validation's roc curve for the subgroup
See this image and copyright information in PMC

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