Development of a Fatty Liver Index Based on Real‐World Data

ABSTRACT Background The aim of this study was to develop and validate a fatty liver index based on laboratory data (FLI‐L) and a fatty liver index based on both physical examination and laboratory data (FLI‐PL) in the hope of providing a more convenient, accurate, and quantitative method for the diagnosis of fatty liver disease. Methods The study included data for 12,391 patients obtained from the Third Medical Center of Chinese PLA General Hospital. FLI‐L and FLI‐PL were developed using binary logistic regression analysis. The diagnostic performance of the FLI‐L and FLI‐PL was evaluated using the area under the receiver‐operating characteristic curve (AUC‐ROC) with sensitivity, specificity, and positive and negative likelihood ratios. FLI‐L and FLI‐PL were subsequently validated in 3170 patients from the same hospital. Results The AUC‐ROC for FLI‐L was 0.876 with a cut‐off value of 55.03. Sensitivity was 81.35 and specificity was 78.28, with an accuracy of 79.99% for discriminating between patients with and without fatty liver disease. The AUC‐ROC for FLI‐PL was 0.902 with a cut‐off value of 20.51. Sensitivity was 85.10 and specificity was 79.64. FLI‐PL classified 91.65% of patients correctly. Conclusion FLI‐L and FLI‐PL is used for simple and accurate quantitative diagnosis of fatty liver disease. This study provides evidence to support the use of this index in clinical management.

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Publication Details

Journal
iLABMED
Published
2025-03-01
DOI
https://doi.org/10.1002/ila2.75
Primary Topic
Liver Disease Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

Development of a Fatty Liver Index Based on Real‐World Data

Wenzhen Ding, Jing Zhang, Yufei Wang, Cui Zhang et al.
iLABMED
Liver Disease Diagnosis and Treatment
article

Development of a Fatty Liver Index Based on Real‐World Data

Wenzhen Ding, Jing Zhang, Yufei Wang, Cui Zhang, Xueping Ma, Xiaoli Yang, Wenjing Lu, Yingli Li, Lanlan Liu
article en

Abstract

ABSTRACT Background The aim of this study was to develop and validate a fatty liver index based on laboratory data (FLI‐L) and a fatty liver index based on both physical examination and laboratory data (FLI‐PL) in the hope of providing a more convenient, accurate, and quantitative method for the diagnosis of fatty liver disease. Methods The study included data for 12,391 patients obtained from the Third Medical Center of Chinese PLA General Hospital. FLI‐L and FLI‐PL were developed using binary logistic regression analysis. The diagnostic performance of the FLI‐L and FLI‐PL was evaluated using the area under the receiver‐operating characteristic curve (AUC‐ROC) with sensitivity, specificity, and positive and negative likelihood ratios. FLI‐L and FLI‐PL were subsequently validated in 3170 patients from the same hospital. Results The AUC‐ROC for FLI‐L was 0.876 with a cut‐off value of 55.03. Sensitivity was 81.35 and specificity was 78.28, with an accuracy of 79.99% for discriminating between patients with and without fatty liver disease. The AUC‐ROC for FLI‐PL was 0.902 with a cut‐off value of 20.51. Sensitivity was 85.10 and specificity was 79.64. FLI‐PL classified 91.65% of patients correctly. Conclusion FLI‐L and FLI‐PL is used for simple and accurate quantitative diagnosis of fatty liver disease. This study provides evidence to support the use of this index in clinical management.

iLABMEDVol. 3(1)
Chinese PLA General Hospital (CN), Jinzhou Medical University (CN)
National Natural Science Foundation of China
Reduced inequalities
Openalex Percentile: Top 93%
Liver Disease Diagnosis and Treatment
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