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Regression of metabolic dysfunction-associated steatotic liver disease in older adults: Short- and long-term prediction models in the NHIS-senior and UK Biobank cohorts.

Created on 29 Sep 2026

Authors

Taeho Kwak, Eun Seok Kang, Jihun Song, Batuhan Gökbulut, Seohui Jang, Minjeong Kang, Jeongin Lee, Seokjin Kong, Yihyun Kim, Jin-Hyun Park, Sangwook Cheon, Jinhyeok Choi, Jaewon Khil, Hye Jun Kim, Bilguuntuguldur Samaindagva, Hwamin Lee, Yohwan Lim, Seogsong Jeong

Published in

Nutrition, metabolism, and cardiovascular diseases : NMCD. Pages 104816. May 29, 2026. Epub May 29, 2026.

Abstract

We developed and validated prediction models for regression of metabolic dysfunction-associated steatotic liver disease (MASLD) in older adults.
Using data from the Korean National Health Insurance Service-Senior cohort, we included older patients with MASLD, defined fatty-liver-index≥30 and at least one cardiometabolic risk factors (CMRFs) at baseline. MASLD regression was assessed at short-term (3-year) and long-term (6-year) follow-ups, defined the absence of steatotic liver disease or any CMRFs. Logistic regression (LR) and decision tree (DT) models were developed to predict MASLD regression, and their performance was evaluated using area under the receiver-operating-characteristic-curve (auROC). The developed models were externally validated in the UK-Biobank cohort. Among 168,198 older adults with MASLD, regression occurred in 38,687 (23.0%) within the short-term period and 30,204 (18.0%) in the long-term period. Internally, auROCs were 0.787/0.760 (LR/DT) for short-term prediction and 0.754/0.720 (LR/DT) for long-term prediction, respectively. Externally, auROCs for short-term predictions were 0.825/0.813 (LR/DT) and 0.784/0.752 (LR/DT) for long-term prediction in the UK-Biobank.
We developed an interpretable prediction score for short- and long-term regression of MASLD with good performance. This tool may enable personalized and proactive management by identifying individuals likely to experience regression, thereby informing targeted lifestyle or pharmacologic interventions.

PMID:
42805812
Bibliographic data and abstract were imported from PubMed on 29 Sep 2026.

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