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Completed
NCT06344364
Digital Pathology and AI for Liver Outcomes in MASLD
Conditions: Metabolic Dysfunction-associated Steatotic Liver Disease
Sex: All
Ages: 18 Years – N/A
Healthy volunteers: No
Enrollment: 1241
Sponsor: PharmaNest, Inc
Location: The Chinese University of Hong Kong Shatin
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).
Eligibility Criteria
Inclusion Criteria:
* 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
Exclusion Criteria:
* Liver diseases other than MASLD Note: no exclusion based on bariatric surgery, significant weight loss or enrollment in NASH clinical studies, but data is collected for data analysis / competing effects (see data analysis plan)
Source: ClinicalTrials.gov (NCT06344364). StuddyBuddy aggregates publicly available trial information.
