Digital Pathology and AI for Liver Outcomes in MASLD

NCT06344364 | Completed

• 1 other identifier: PHN 1-080-23
• Study Type: observational
• Target: 1,241
• Locations: 2 countries
• Sites: 3

Brief Summary

The aim of this multi-center, retrospective epidemiologic study is to confirm the prognostic performance of the Digital Pathology (DP) FibroNest Phenotypic Fibrosis Composite Score (Ph-FCS), derived from standard digital pathology liver biopsy images, in predicting clinical hepatic decompensation events in patients with metabolic dysfunction-associated steatohepatitis (MASH).

Conditions

Metabolic Dysfunction-associated Steatotic Liver Disease

Keywords

NAFLD; MAFLD; digital pathology; artificial intelligence; fibrosis score; liver disease; hepatic decompensation

Outcome Measures

Primary Outcomes (1)

• Performance of Hepatic Decompensation Event predictive value of the FibroNest Ph-FCS

  Area under Receiver Operating Characteristic Curve (AUROC) of the FibroNest Ph-FCS, as a prognostic/diagnostic biomarker for liver related events in patients with MASH.

  Time-to-event analysis between 2 and 10 years

Secondary Outcomes (3)

• Performance of Hepatic Decompensation Event predictive value of the NASH-CRN Fibrosis Stage, a biopsy-based score for fibrosis severity

  Time-to-event analysis between 2 and 10 years

• Performance of Hepatic Decompensation Event predictive value of the FIB-4 biomarker, a non-invasive test

  Time-to-event analysis between 2 and 10 years

• Performance of Hepatic Decompensation Event predictive value of the elastography (Fibroscan) biomarker, a non-invasive test

  Time-to-event analysis between 2 and 10 years

Study Arms (2)

Non-Liver Related Event

Absence of any of the liver events described in the second group in the patient clinical follow-up.

Diagnostic Test: Digital Pathology FibroNest Phenotypic Fibrosis Composite Score (Ph-FCS)

Liver Related Event

Liver-related events include liver-related death, hepatic decompensation events (variceal hemorrhage, ascites, hepatic encephalopathy), and hepatocellular carcinoma.

Diagnostic Test: Digital Pathology FibroNest Phenotypic Fibrosis Composite Score (Ph-FCS)

Interventions

Digital Pathology FibroNest Phenotypic Fibrosis Composite Score (Ph-FCS) DIAGNOSTIC_TEST

Biomarker name: FibroNest Phenotypic Fibrosis Composite Score Acronym: FibroNest Ph-FCS Type of Biomarker: Histologic based, Digital, Quantitative Image Analysis, Imaging modality Definition: A quantitative, normalized (no unit) and continuous composite score that aggregates quantitative histological features of fibrosis severity measured by high resolution quantitative image analysis.

Liver Related Event; Non-Liver Related Event

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Adult pts ( \>=18 years old) with MASLD defined histologically with \>1 year of clinical follow up and available recording liver-related outcomes either through hospitalization ICD-10 codes or through clinical observation.

You may qualify if:

• Adult pts ( \>=18 years old) with MASLD defined histologically.
• Liver biopsy with fibrosis stains available for digitization or already digitized.
• Clinical follow-up \>1 year available recording liver-related outcomes either through hospitalization ICD-10 codes or through clinical observation

Sponsors & Collaborators

• Chinese University of Hong Kong: collaborator
• University of Seville: collaborator
• Fundacio Clinic Barcelona: collaborator
• Sorbonne University: collaborator
• PharmaNest, Inc: lead

Study Sites (3)

The Chinese University of Hong Kong

Shatin, Hong Kong

Location

Fundació de Recerca Clinic Barcelona

Barcelona, Spain

Location

University of Seville

Seville, 41004, Spain

Location

Related Publications (3)

• Kendall TJ, Jimenez-Ramos M, Turner F, Ramachandran P, Minnier J, McColgan MD, Alam M, Ellis H, Dunbar DR, Kohnen G, Konanahalli P, Oien KA, Bandiera L, Menolascina F, Juncker-Jensen A, Alexander D, Mayor C, Guha IN, Fallowfield JA. An integrated gene-to-outcome multimodal database for metabolic dysfunction-associated steatotic liver disease. Nat Med. 2023 Nov;29(11):2939-2953. doi: 10.1038/s41591-023-02602-2. Epub 2023 Oct 30.

  PMID: 37903863 BACKGROUND

• Ratziu V, Chen L, Petitjean L. et al. Novel Artificial Intelligence-Assisted Digital Pathology Quantitative Image Analysis Predicts the occurrence of Liver-related Clinical Events in the Multicentric, European, Hepatic Outcomes and Survival Fatty Liver Registry (HITSURFR) Study. Hepatology. 78(S1) S1-S2154 2084-A

  BACKGROUND

• Sanyal AJ, Van Natta ML, Clark J, Neuschwander-Tetri BA, Diehl A, Dasarathy S, Loomba R, Chalasani N, Kowdley K, Hameed B, Wilson LA, Yates KP, Belt P, Lazo M, Kleiner DE, Behling C, Tonascia J; NASH Clinical Research Network (CRN). Prospective Study of Outcomes in Adults with Nonalcoholic Fatty Liver Disease. N Engl J Med. 2021 Oct 21;385(17):1559-1569. doi: 10.1056/NEJMoa2029349.

  PMID: 34670043 RESULT

MeSH Terms

Conditions

Non-alcoholic Fatty Liver Disease; Liver Diseases

Condition Hierarchy (Ancestors)

Fatty Liver; Digestive System Diseases

Study Officials

• Vlad Ratziu, MD, PhD

  Sorbonne University

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: March 27, 2024
• First Posted: April 3, 2024
• Study Start: September 1, 2025
• Primary Completion: March 1, 2026
• Study Completion: March 15, 2026
• Last Updated: March 23, 2026

Record last verified: 2026-03

Data Sharing

• IPD Sharing: Will not share

Locations

ES (2); HK (1)