Observational Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Sep 28, 2022; 28(36): 5364-5379
Published online Sep 28, 2022. doi: 10.3748/wjg.v28.i36.5364
Atherogenic index of plasma combined with waist circumference and body mass index to predict metabolic-associated fatty liver disease
Shao-Jie Duan, Zhi-Ying Ren, Tao Zheng, Hong-Ye Peng, Zuo-Hu Niu, Hui Xia, Jia-Liang Chen, Yuan-Chen Zhou, Rong-Rui Wang, Shu-Kun Yao
Shao-Jie Duan, Zhi-Ying Ren, Tao Zheng, Hong-Ye Peng, Zuo-Hu Niu, Hui Xia, Rong-Rui Wang, Graduate School, Beijing University of Chinese Medicine, Beijing 100029, China
Jia-Liang Chen, Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
Yuan-Chen Zhou, Graduate school, Peking University China-Japan Friendship School of Clinical Medicine, Beijing 100029, China
Shu-Kun Yao, Department of Gastroenterology, China-Japan Friendship Hospital, Beijing 100029, China
Author contributions: Duan SJ designed and performed the study, analyzed the data, and drafted the manuscript; Ren ZY, Zheng T, Peng HY, Niu ZH, and Wang RR collected the samples and clinical data of the patients; Xia H, Chen JL, and Zhou YC took part in designing the study and analyzing the data; Yao SK designed the study, supervised the study performance, and revised the manuscript.
Institutional review board statement: This study was approved by the Clinical Research Ethics Committee of China-Japan Friendship Hospital (2018-110-K79-1).
Informed consent statement: All study participants provided informed written consent prior to study enrollment.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: No additional data are available.
STROBE statement: The authors have read the STROBE Statement checklist of items, and the manuscript was prepared and revised according to the STROBE Statement checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Shu-Kun Yao, MD, Professor, Department of Gastroenterology, China-Japan Friendship Hospital, No. 2 Yinghua East Street, Chaoyang District, Beijing 100029, China. shukunyao@126.com
Received: June 26, 2022
Peer-review started: June 26, 2022
First decision: August 1, 2022
Revised: August 9, 2022
Accepted: September 8, 2022
Article in press: September 8, 2022
Published online: September 28, 2022
Abstract
BACKGROUND

Early identification of metabolic-associated fatty liver disease (MAFLD) is urgent. Atherogenic index of plasma (AIP) is a reference predictor of obesity-related diseases, but its predictive value for MAFLD remains unclear. No studies have reported whether its combination with waist circumference (WC) and body mass index (BMI) can improve the predictive performance for MAFLD.

AIM

To systematically explore the relationship between AIP and MAFLD and evaluate its predictive value for MAFLD and to pioneer a novel noninvasive predictive model combining AIP, WC, and BMI while validating its predictive performance for MAFLD.

METHODS

This cross-sectional study consecutively enrolled 864 participants. Multivariate logistic regression analysis and receiver operating characteristic curve were used to evaluate the relationship between AIP and MAFLD and its predictive power for MAFLD. The novel prediction model A-W-B combining AIP, WC, and BMI to predict MAFLD was established, and internal verification was completed by magnetic resonance imaging diagnosis.

RESULTS

Subjects with higher AIP exhibited a significantly increased risk of MAFLD, with an odds ratio of 12.420 (6.008-25.675) for AIP after adjusting for various confounding factors. The area under receiver operating characteristic curve of the A-W-B model was 0.833 (0.807-0.858), which was significantly higher than that of AIP, WC, and BMI (all P < 0.05). Subgroup analysis illustrated that the A-W-B model had significantly higher area under receiver operating characteristic curves in female, young and nonobese subgroups (all P < 0.05). The best cutoff values for the A-W-B model to predict MAFLD in males and females were 0.5932 and 0.4105, respectively. Additionally, in the validation set, the area under receiver operating characteristic curve of the A-W-B model to predict MAFLD was 0.862 (0.791-0.916). The A-W-B level was strongly and positively associated with the liver proton density fat fraction (r = 0.630, P < 0.001) and significantly increased with the severity of MAFLD (P < 0.05).

CONCLUSION

AIP was strongly and positively associated with the risk of MAFLD and can be a reference predictor for MAFLD. The novel prediction model A-W-B combining AIP, WC, and BMI can significantly improve the predictive ability of MAFLD and provide better services for clinical prediction and screening of MAFLD.

Keywords: Atherogenic index of plasma, Metabolic-associated fatty liver disease, Receiver operating characteristic curve, Predictor

Core Tip: Metabolic-associated fatty liver disease (MAFLD) is the most common chronic liver disease, and early identification of MAFLD is urgent. This study demonstrated that the atherogenic index of plasma was strongly and positively associated with the risk of MAFLD, and it can be a reference predictor for MAFLD. Then, we pioneered a novel noninvasive prediction model, A-W-B, combining atherogenic index of plasma, waist circumference, and body mass index and validated its excellent predictive performance for MAFLD. Furthermore, we also pointed out the optimal cutoff values of the A-W-B model to predict MAFLD in males and females, which will facilitate early clinical identification of MAFLD in different sex populations. This study is highly innovative, and the noninvasive prediction model, A-W-B, is convenient, affordable, and easy to obtain, which can provide better services for clinical prediction and screening of MAFLD and metabolic-related diseases.