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Updated: Jan 13, 2026

Optimized Analysis of In Vivo and In Vitro Hepatic Steatosis
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Optimized Analysis of In Vivo and In Vitro Hepatic Steatosis

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Improving cardiovascular risk prediction in metabolic liver disease with a novel biomarker-enhanced model

Lars Hegstrom1, Yestle Kim2, Pete Vu2

  • 1Nference, Cambridge, Massachusetts, USA.

Current Medical Research and Opinion
|January 9, 2026
PubMed

Insights

A new LIVER-ASCVD+ model improves cardiovascular risk prediction in patients with Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) and Metabolic Dysfunction-Associated Steatohepatitis (MASH). This model integrates liver biomarkers, offering better accuracy than existing tools for these high-risk populations.

Area of Science:

  • Cardiology
  • Hepatology
  • Epidemiology

Background:

  • Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) and Metabolic Dysfunction-Associated Steatohepatitis (MASH) are growing global health concerns.
  • Current cardiovascular disease (CVD) risk models inadequately predict events in MASLD/MASH patients.

Purpose of the Study:

  • To develop and validate a novel regression model, LIVER-ASCVD+, for enhanced CVD risk prediction in MASLD/MASH patients.
  • To integrate traditional cardiovascular risk factors with liver biomarkers for improved accuracy.

Main Methods:

  • A retrospective cohort study of 9,185 biopsy-confirmed MASH patients.
  • Comparison of LIVER-ASCVD+ model performance against the ASCVD Risk Estimator Plus.
  • Kaplan-Meier survival analysis and propensity-matched control cohorts.

Main Results:

  • LIVER-ASCVD+ showed superior predictive accuracy for myocardial infarction/stroke (AUC: 0.68) and mortality (AUC: 0.63) versus ASCVD Risk Estimator Plus (AUCs: 0.63 and 0.54).
  • The model effectively stratified patients into distinct risk categories with significant outcome differences.
  • Kaplan-Meier analyses confirmed the model's enhanced predictive capability.

Conclusions:

  • Integrating liver biomarkers significantly improves CVD risk prediction in MASLD/MASH patients.
  • The LIVER-ASCVD+ model offers a promising tool for clinical decision-making and improving patient outcomes.
  • Further validation of the LIVER-ASCVD+ model is recommended.
Abstract

Keywords:
ASCVDMAFLDMASHNAFLDNASHmetabolic associated fatty liver diseasemetabolic dysfunction-associated steatohepatitis

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