Evidence mapPaperPMID 40533869Full record

ArticleDiabetology & metabolic syndrome2025

Decoding survival in MASLD: the dominant role of metabolic factors.

Zhiqiang Jin, Cheng Zeng, Yang Yang, Shan Zhong, Zhi Zhou

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Article in Diabetology & metabolic syndrome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers 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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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Zhiqiang Jin *Department of Infectious Diseases, Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, The Second Affiliated Hospital, Chongqing Medical University, No 288, Tianwen Avenue, Chayuan, Nan'an District, Chongqing, 401336, China.
Cheng Zeng *Department of Infectious Diseases, Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, The Second Affiliated Hospital, Chongqing Medical University, No 288, Tianwen Avenue, Chayuan, Nan'an District, Chongqing, 401336, China.
Yang YangDepartment of Infectious Diseases, Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, The Second Affiliated Hospital, Chongqing Medical University, No 288, Tianwen Avenue, Chayuan, Nan'an District, Chongqing, 401336, China.
Shan ZhongDepartment of Infectious Diseases, Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, The Second Affiliated Hospital, Chongqing Medical University, No 288, Tianwen Avenue, Chayuan, Nan'an District, Chongqing, 401336, China.
Zhi ZhouDepartment of Infectious Diseases, Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, The Second Affiliated Hospital, Chongqing Medical University, No 288, Tianwen Avenue, Chayuan, Nan'an District, Chongqing, 401336, China. zhouzhi2300@hospital.cqmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetabolic factors are considered to influence disease progression in patients with Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD), but the impact of individual metabolic factors on the survival rate of patients with MASLD is still unclear.

aimsThis article aims to reveal how metabolic components affect the survival of patients with this disease.

methodsA total of 3,086 participants with MASLD based on the diagnostic criteria established at the Delphi conference from NHANES III were included in this analysis. COX regression model (C-index = 0.64) was used to analyze the all-cause and attributable mortality of different number of metabolic factors. Elastic Network Regression model (C-index = 0.69), Accelerated Failure Time model and Randomized Survival Forest model (C-index = 0.63) based on machine learning were used to analyze the weight of each metabolic factor, and a Metabolism-related survival risk score formula was established and verified.

resultsThis study found that not only the number of metabolic factors had different effects on all-cause survival in MASLD patients, but also the degree of impact of different metabolic factors on survival was quite different, among which poor glycemic control was the most important influencing factor.

conclusionThis study highlights the clinical value of relevant metabolic factors in predicting survival in the MASLD patient population. Related metabolic factors can be used as surrogate biomarkers for the follow-up of MASLD patients.

Indexed as

Machine learning algorithmsMASLDMetabolic factorsPrognosis

Identifiers

PMID40533869
PMCPMC12175318

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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 Socratic graph.