Evidence map›Paper›PMID 42958515›Full record

ArticleBMC gastroenterology2026

A fatty liver index-based sequential strategy for identifying hepatic steatosis in individuals with suspected steatotic liver disease.

Yan Yang, Xiongcai Feng, Hong Deng, Zhiyong Dong, Lishu Xu, Shiting Feng, Bing Liao, Congxiang Shao, Pinning Feng, Bihui Zhong and 1 more

Abstract readMulticenter Study
In one paragraph

Article in BMC gastroenterology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Yan Yang *Department of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, No. 58 Zhongshan II Road, Yuexiu District, Guangzhou, 510000, Guangdong, China.
Xiongcai Feng *Department of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, No. 58 Zhongshan II Road, Yuexiu District, Guangzhou, 510000, Guangdong, China.
Hong DengDepartment of Infectious Diseases, The Third Affiliated Hospital, Sun Yat-sen University, No.600 Tianhe Road, Tianhe District, Guangzhou, 510080, China.
Zhiyong DongDepartment of Bariatric Surgery, The First Affiliated Hospital, Jinan University, No. 613 West Huangpu Avenue, Tianhe District, Guangzhou, 510080, China.
Lishu XuDepartment of Geriatrics, Guangdong Provincial People's Hospital, No. 106 Zhongshan II Road, Yuexiu District, Guangzhou, 510000, Guangdong, China.
Shiting FengDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, No. 58 Zhongshan II Road, Yuexiu District, Guangzhou, 510000, Guangdong, China.
Bing LiaoDepartment of Pathology, The First Affiliated Hospital, Sun Yat-sen University, No. 58 Zhongshan II Road, Yuexiu District, Guangzhou, 510000, Guangdong, China.
Congxiang ShaoDepartment of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, No. 58 Zhongshan II Road, Yuexiu District, Guangzhou, 510000, Guangdong, China.
Pinning FengDepartment of Clinical Laboratory, The First Affiliated Hospital, Sun Yat-sen University, No. 58 Zhongshan II Road, Yuexiu District, Guangzhou, China. fengpn@mail.sysu.edu.cn.
Bihui ZhongDepartment of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, No. 58 Zhongshan II Road, Yuexiu District, Guangzhou, 510000, Guangdong, China. zhongbh@mail.sysu.edu.cn.
Junzhao YeDepartment of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, No. 58 Zhongshan II Road, Yuexiu District, Guangzhou, 510000, Guangdong, China. yejzh@mail2.sysu.edu.cn.

Funding

National Natural Science Foundation of China 82100648National Natural Science Foundation of China 82370587National Natural Science Foundation of China 82400663
6 · The paper itself

Abstract

objectiveFatty liver index (FLI) is widely used as a non-invasive tool for identifying hepatic steatosis but performs poorly in lean individuals and leaves a substantial proportion of individuals within an indeterminate range. This cross-sectional study evaluated whether combination strategies could improve identification of hepatic steatosis in a selected referred population with suspected steatotic liver disease (SLD).

methodsIn a derivation cohort of 1648 subjects with suspected SLD who underwent MRI-PDFF assessment between January 2015 and January 2022, we evaluated five non-invasive indices (FLI, hepatic steatosis index [HSI], liver fat score [LFS], visceral adiposity index [VAI], and triglyceride-glucose index [TyG]). Four FLI-based sequential strategies were developed and further validated in an independent biopsy-based cohort of 426 patients from five tertiary centers in South China.

resultsFLI performed best in identifying hepatic steatosis among the five non-invasive indices, with an AUROC of 0.75, but showed a high missed-identification rate exceeding 90% in individuals with BMI < 23 kg/m². In Strategy 4, the FLI-LFS sequential algorithm improved identification performance in lean individuals. In the derivation cohort, sensitivity increased from 9.4% to 78.6%, the missed-identification rate decreased from 90.6% to 21.4%, and accuracy increased from 30.0% to 73.1%. A similar improvement in missed identification was observed in the validation cohort.

conclusionsCompared with FLI alone, the sequential FLI-LFS algorithm substantially improved the identification of hepatic steatosis among lean individuals with suspected SLD. The strategy may help identify individuals who require further imaging and etiological evaluation but should not be regarded as a stand-alone tool for determining the subtype or cause of SLD.

Indexed as

Fatty LiverNon-alcoholic Fatty Liver DiseaseAdultAlgorithmsBiopsyBody Mass IndexCross-Sectional StudiesFemaleHumansIntra-Abdominal FatLiverMagnetic Resonance ImagingMaleMiddle AgedSensitivity and SpecificitySeverity of Illness IndexTriglyceridesFatty liver indexHepatic steatosisLean individualsLiver fat scoreSteatotic liver disease

Identifiers

PMID42958515
PMCPMC13718121

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.