Evidence map›Paper›PMID 35701716›Full record

ArticleHepatology international2022

A new risk stratification strategy for fatty liver disease by incorporating MAFLD and fibrosis score in a large US population.

Ya-Cong Zhang, Zhang-Yan Lyu, Bing Ma, Li-Min Li, Wei Wang, Chao Sheng, Hong-Ji Dai, Yu-Bei Huang, Fang-Fang Song, Feng-Ju Song and 1 more

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Article in Hepatology international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
  6. Article
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  8. Article
  9. Adding to the confusion in more than just the name.Clinical and molecular hepatology · 2023
    Article
  10. Article
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  12. Article
  13. MAFLD: How is it different from NAFLD?Clinical and molecular hepatology · 2023
    Review
  14. Article
  15. Review
  16. MAFLD: what 2 years of the redefinition of fatty liver disease has taught us.Therapeutic advances in endocrinology and metabolism · 2022
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Ya-Cong Zhang *Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, West Huan-Hu Rd, Ti Yuan Bei, Hexi District, Tianjin, 300060, People's Republic of China.
Zhang-Yan Lyu *Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, West Huan-Hu Rd, Ti Yuan Bei, Hexi District, Tianjin, 300060, People's Republic of China.
Bing MaDepartment of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, West Huan-Hu Rd, Ti Yuan Bei, Hexi District, Tianjin, 300060, People's Republic of China.
Li-Min LiDepartment of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, West Huan-Hu Rd, Ti Yuan Bei, Hexi District, Tianjin, 300060, People's Republic of China.
Wei WangDepartment of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, West Huan-Hu Rd, Ti Yuan Bei, Hexi District, Tianjin, 300060, People's Republic of China.
Chao ShengDepartment of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, West Huan-Hu Rd, Ti Yuan Bei, Hexi District, Tianjin, 300060, People's Republic of China.
Hong-Ji DaiDepartment of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, West Huan-Hu Rd, Ti Yuan Bei, Hexi District, Tianjin, 300060, People's Republic of China.
Yu-Bei HuangDepartment of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, West Huan-Hu Rd, Ti Yuan Bei, Hexi District, Tianjin, 300060, People's Republic of China.
Fang-Fang SongDepartment of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, West Huan-Hu Rd, Ti Yuan Bei, Hexi District, Tianjin, 300060, People's Republic of China.
Feng-Ju SongDepartment of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, West Huan-Hu Rd, Ti Yuan Bei, Hexi District, Tianjin, 300060, People's Republic of China.
Ke-Xin ChenDepartment of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, West Huan-Hu Rd, Ti Yuan Bei, Hexi District, Tianjin, 300060, People's Republic of China. chenkexin@tmu.edu.cn.ORCID http://orcid.org/0000-0003-4248-7681

Funding

Beijing-Tianjin-Hebei Basic Research Cooperation Project 20JCZXJC00090National Key R&D Program of China Grant No. 2021YFC2500400Tianjin Municipal Commission of Health and Wellness Project TJWJ2021MS008
6 · The paper itself

Abstract

backgroundMetabolic dysfunction-associated fatty liver disease (MAFLD) is a newly proposed definition of fatty liver disease (FLD) independent of excessive alcohol consumption (EAC) and hepatitis viral infection. Evidence on the mortality risk in different types of FLD [nonalcoholic FLD (NAFLD), alcoholic FLD (AFLD), and MAFLD] is sparse, hindering the identification of high-risk populations for preferential clinical surveillance.

methodsA total of 11,000 participants in the Third National Health and Nutrition Examination Survey were enrolled. Participants were categorized into three groups [FLD( - ), MAFLD( - ), and MAFLD( +)] according to FLD and MAFLD criteria, and further categorized into six groups by EAC. Multivariate Cox proportional hazard model was used to estimate the risk of all-cause, cardiovascular-related, and cancer-related mortality.

resultsDuring a median follow-up of 23.2 years, a total of 3240 deaths were identified. Compared with FLD( - )/EAC( - ) participants, MAFLD( +) individuals had higher all-cause mortality risk [hazard ratio (HR) = 1.28, 95% confidence interval (CI) = 1.18-1.39] regardless of EAC status [MAFLD( +)/NAFLD: HR = 1.22, 95%CI = 1.11-1.34; MAFLD( +)/AFLD: HR = 1.83, 95%CI = 1.46-2.28], while not for MAFLD( - ) individuals. Furthermore, diabetes-driven-MAFLD had higher mortality risk (HR = 2.00, 95%CI = 1.77-2.27) followed by metabolic dysregulation-driven-MAFLD (HR = 1.30, 95%CI = 1.06-1.60) and overweight/obesity-driven-MAFLD (HR = 1.11, 95%CI = 1.00-1.22). Additionally, MAFLD( - ) participants with elevated fibrosis score were also associated with statistically significantly higher mortality risk (HR = 3.23, 95%CI = 1.63-6.40).

conclusionsUtilizing a representative sample of the US population, we proved the validity of MAFLD subtype and fibrosis score, rather than the traditional definition (NAFLD and AFLD), in the risk stratification of FLD patients. These findings may be applied to guide the determination of surveillance options for FLD patients.

Indexed as

Fatty Liver, AlcoholicNon-alcoholic Fatty Liver DiseaseHumansLiver CirrhosisNutrition SurveysRisk AssessmentAdvanced fibrosisAlcoholic fatty liver diseaseDiabetes mellitusExcessive alcohol consumptionMetabolic dysfunction-associated fatty liver diseaseMetabolic dysregulationMortality outcomeNonalcoholic fatty liver diseaseObesityRisk stratification

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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.