Evidence map›Paper›PMID 39638772›Full record

ArticleDiabetes, obesity & metabolism2025

The fibrosis investigating navigator in diabetes (FIND): A tool to predict liver fibrosis risk in subjects with diabetes.

Mingkai Li, Hongsheng Yu, Sizhe Wan, Fulan Hu, Qingtian Luo, Wei Gong

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Article in Diabetes, obesity & metabolism, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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3 citing papers in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Mingkai LiDepartment of Gastroenterology, Shenzhen Hospital, Southern Medical University, Shenzhen, People's Republic of China.
Hongsheng YuDepartment of Gastroenterology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, People's Republic of China.
Sizhe WanDepartment of Gastroenterology, Shenzhen Hospital, Southern Medical University, Shenzhen, People's Republic of China.ORCID 0000-0002-8498-2288
Fulan HuDepartment of Biostatistics and Epidemiology, Public Health college, Shenzhen University Medical School, Shenzhen, People's Republic of China.ORCID 0000-0002-2386-1503
Qingtian LuoDepartment of Gastroenterology and Endoscopy Center, Shenzhen Nanshan People's Hospital, the 6th Affiliated Hospital of Shenzhen University Medical School, Shenzhen, People's Republic of China.
Wei GongDepartment of Gastroenterology, Shenzhen Hospital, Southern Medical University, Shenzhen, People's Republic of China.ORCID 0009-0008-2137-9669

Funding

Guangdong Basic and Applied Basic Research Foundation 2021A1515110799Guangdong Basic and Applied Basic Research Foundation 2023A1515010144Medicine Plus Program of Shenzhen University 2024YG014National Natural Science Foundation of China 82401448Shenzhen Nanshan District Science and Technology Plan Funding Major Program NSZD2024015Shenzhen Science and Technology Program JCYJ20220530142000001
6 · The paper itself

Abstract

backgroundType 2 diabetes increases the risk of cirrhosis and liver cancer. Noninvasive and early assessment of liver fibrosis is essential. We aimed to develop a score to aid in the initial assessment of liver fibrosis in the diabetic population.

methodsA fibrosis investigating navigator in diabetes (FIND) score was developed and validated in the NHANES dataset (2017-2020). Fibrosis was defined as a liver stiffness measurement (LSM) ≥8.0 kPa. The diagnostic accuracies of FIB-4, NFS, LiverRisk, steatosis-associated fibrosis estimator (SAFE) and metabolic dysfunction-associated fibrosis (MAF-5) were compared. FIND was also externally validated in various liver diseases via biopsy as a reference in an Asian centre between 2016 and 2020. Finally, we examined the prognostic implications of the FIND index utilizing data from the UK Biobank cohort (2006-2010).

resultsThe FIND score model yielded an AUROC of 0.781 for the prediction of an LSM ≥8 kPa in the validation set, which was consistently greater than that of other available models (all p < 0.05). In the whole NHANES dataset, the 85% sensitivity cut-off of 0.16 corresponded to a NPV of 91.9%, whereas the 85% specificity cut-off of 0.31 corresponded to a PPV of 50.6%. FIND displayed overall accuracies similar to those of the other models in staging fibrosis stages, with biopsy used as a reference. In the UK Biobank cohort, FIND >0.31 was associated with an increased risk of all-cause and liver-related mortality in the diabetic population in adjusted models (HR, 1.75; 95% CI, 1.62-1.89; HR, 23.59; 95% CI, 13.67-40.69).

conclusionsIn diabetes patients, the novel FIND score performs well in identifying subjects at risk of liver fibrosis and predicting all-cause and liver-related mortality.

Indexed as

Diabetes Mellitus, Type 2Liver CirrhosisAdultAgedElasticity Imaging TechniquesFemaleHumansLiverMaleMiddle AgedNutrition SurveysPredictive Value of TestsPrognosisRisk AssessmentRisk Factorsfatty liver diseaseliverobesity caretype 2 diabetes

Identifiers

PMID39638772
PMCPMC11802394

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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.