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NCT Number: NCT06888310

Optimizing Noninvasive assessMent Of DysmEtabolic Compensated Advanced Liver Disease

Non-alcoholic fatty liver disease (NAFLD) is responsible for a significant proportion of liver-related deaths and healthcare costs in the United States, accounting for approximately 36% of liver-related deaths and over one billion dollars in annual healthcare expenses. [PMID: 34863359] A recent analysis of healthcare costs in Italy showed that out of the 9,729 NAFLD/NASH patients who were hospitalized and analyzed, the vast majority (97%) did not have advanced liver disease, while 1.3% had compensated advanced liver disease (cACLD), 3.1% had decompensated cirrhosis, 0.8% had hepatocellular carcinoma, and 0.1% underwent liver transplantation.

The burden of comorbidities was high across all patient cohorts, and patients with cACLD required a greater number of inpatient services, outpatient visits, and the pharmacy fills compared to those without advanced liver disease. As disease severity increased, mean total annual costs also increased primarily due to higher inpatient services costs. In Italy, as in other EU countries, most of the healthcare costs for patients were attributed to NAFLD/NASH-related liver complications. Thus, the optimization of the non-invasive diagnosis of cACLD represents an urgent need in dysmetabolic liver disease. These advancements will play a crucial role in early detection, risk stratification, and effective management of highly prevalent liver diseases such as NAFLD/NASH and their progression.

Active, not recruiting

This study is active but is not currently recruiting participants.

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Key information

Conditions

NASH Digestive System Diseases Fatty Liver Liver Diseases NAFLD Non-alcoholic Fatty Liver Disease

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Fondazione Policlinico Universitario Agostino Gemelli IRCCS, UOC Medicina Interna e Trapianto di Fegato

Roma, 00168, Italy

About this study

The study aims to significantly enhance diagnostic innovation and contribute to the existing literature on the stratification of cACLD caused by metabolic-dysfunction liver disease, a major factor leading to cirrhosis, liver cancer, and liver transplant in individuals with non-communicable diseases. By integrating radiomics, digital pathology, non-invasive scores, and omics the results are expected to provide novel evidence for diagnostic advancements.

The incorporation of AI is anticipated to lead to more efficient diagnostic management, effectively addressing the impact of cACLD on healthcare systems. The outcomes of this research will yield a substantial database and intellectual content, both of which will be made available to the scientific community and multiple stakeholders, including patient associations, policymakers, healthcare providers, and industry players.

The primary goal is to foster innovation in diagnostics and mitigate the impact of cACLD on national health systems. By accurately predicting individuals at higher risk of liver or extra-hepatic complications, this study aims to revolutionize diagnostic methods, ultimately leading to improved patient outcomes and resource optimization in healthcare settings.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • age>=18; sex (M,F);
  • dysmetabolic liver disease according new nomenclature definition;
  • suspicion of cACLD by LSM>=10 with VCTE;
  • routine esogastroduodenoscopy report within 12 months of VCTE for identification of high-risk varices (HRV).

Exclusion criteria

  • portal vein thrombosis,
  • infiltrative liver neoplasms, and conditions are known for their potential influence on the LSM results (congestive liver disease, extrahepatic biliary obstruction, ALT > 5x upper normal limit).

Treatment and study plan

extra blood sampling

Procedure

search for biomarkers for the prevention of liver disease

Primary outcomes

  1. number of patients identified with single diagnostic method

    Time frame: 24 months

    evaluate the efficacy of risk-stratification pathways for cACLD detection and outcome prediction in adults (age>18 years) with dysmetabolic liver disease in a tertiary care setting.

Secondary outcomes

  1. number of patients identified with innovative diagnostic method omic-based

    Time frame: 24 months

    evaluate the possible integration of liquid biopsy for cACLD detection and outcome prediction

Sponsors and collaborators

Lead sponsor

Fondazione Policlinico Universitario Agostino Gemelli IRCCS

Other

Registry information

Official study title

Optimizing Noninvasive assessMent Of DysmEtabolic Compensated Advanced Liver Disease by Integration of Artificial Intelligence Model and omicS Data

Acronym: MODELS

Important dates

Study start
2024
Primary completion
2026
Study completion
2027
First posted
Mar 21, 2025
Registry last updated
Sep 2, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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