Validation of a data-driven clustering model for MASLD: Evidence from three large-scale Asian cohorts

This study provides scientific justification for applying a validated clustering model to metabolic dysfunction-associated steatotic liver disease (MASLD), demonstrating that patient subgroups identified by data-driven methods carry distinct risks for cardiovascular and liver-related outcomes. These findings are important for clinicians, researchers, and policymakers as they highlight that MASLD is not a uniform disease but rather comprises heterogeneous subgroups with differing prognoses. In practice, this work supports subgroup-based strategies to personalize treatment, improve risk stratification, and optimize the allocation of healthcare resources. The results also offer a foundation for future research into targeted therapeutic interventions while acknowledging the need for further validation in diverse populations.

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Publication Details

Journal
JHEP Reports
Published
2025-10-18
DOI
https://doi.org/10.1016/j.jhepr.2025.101645
Citations
2
Primary Topic
Liver Disease Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
2.71
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article

Validation of a data-driven clustering model for MASLD: Evidence from three large-scale Asian cohorts

Wen‐Yue Liu, Sherlot Juan Song, George Boon‐Bee Goh, François Pattou et al.
2 citations
JHEP Reports
Liver Disease Diagnosis and Treatment
2.71
article

Validation of a data-driven clustering model for MASLD: Evidence from three large-scale Asian cohorts

Wen‐Yue Liu, Sherlot Juan Song, George Boon‐Bee Goh, François Pattou, Siyi Lei, Terry Cheuk‐Fung Yip, Ming‐Hua Zheng, Violeta Raverdy, Rui Fan, Guillemette Marot, Xiaodong Zhou, Daniel Yan Zheng Lim, Jimmy Che‐To Lai, Yong Mong Bee, Qin‐Fen Chen, Giovanni Targher, Liyou Lian, Grace Lai–Hung Wong, Christopher D. Byrne, Tong Ye, Vincent Wai‐Sun Wong, C. Y. Hong, Chloe Yitian Guo
article en
2 citations

Abstract

This study provides scientific justification for applying a validated clustering model to metabolic dysfunction-associated steatotic liver disease (MASLD), demonstrating that patient subgroups identified by data-driven methods carry distinct risks for cardiovascular and liver-related outcomes. These findings are important for clinicians, researchers, and policymakers as they highlight that MASLD is not a uniform disease but rather comprises heterogeneous subgroups with differing prognoses. In practice, this work supports subgroup-based strategies to personalize treatment, improve risk stratification, and optimize the allocation of healthcare resources. The results also offer a foundation for future research into targeted therapeutic interventions while acknowledging the need for further validation in diverse populations.

JHEP ReportsVol. 8(1)
University of Verona (IT), Inserm (FR), National University of Singapore (SG), Chinese University of Hong Kong (HK), Singapore General Hospital (SG), Université de Lille (FR), Wenzhou Medical University (CN), Institut Pasteur de Lille (FR), Southampton General Hospital (GB), First Affiliated Hospital of Wenzhou Medical University (CN), University Hospital Southampton NHS Foundation Trust (GB), Centre Hospitalier Universitaire de Lille (FR), Ospedale Sacro Cuore Don Calabria (IT), Duke-NUS Medical School (SG), University of Southampton (GB)
Openalex Percentile: Top 8%
Liver Disease Diagnosis and Treatment
2.71
DOIOpen Access PDFOpenAlex
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