Clinical Classification of MAFLD Based Liver Biopsy

NCT06795646 | Not Yet Recruiting DMC

• 1 other identifier: 2023ZD0508702
• Study Type: observational
• Target: 2,000
• Locations: 1 country
• Sites: 6

Brief Summary

Metabolic dysfunction-associated Fatty Liver Disease (MAFLD), also known as Non-Alcoholic Fatty Liver Disease (NAFLD), is the most common chronic progressive liver disease in China. It is closely related to the high incidence of cardiovascular-renal-metabolic syndrome and both liver and non-liver malignancies, posing a serious threat to public health. However, the diagnostic criteria for MAFLD are not unified globally, and the classification and staging still rely on liver biopsy for pathological assessment. The characteristics, mechanisms, and predictive indicators of liver and extrahepatic disease outcomes in MAFLD patients are not yet clear. The severe form of MAFLD, metabolic dysfunction-associated steatohepatitis (MASH), has been a hot and challenging area of research for non-invasive tests (NITs). However, serum markers, imaging examinations, and novel markers under development cannot replace liver biopsy for the diagnosis of MASH. Clinically, the disease outcomes of MAFLD mainly depend on metabolic cardiovascular risk factors and fibrosis staging. Both liver biopsy and NIT-diagnosed advanced fibrosis and cirrhosis can predict liver-related events and all-cause mortality risks in MAFLD patients. Artificial intelligence and machine learning methods can improve the consistency of pathologists in diagnosing MASH and fibrosis. The Agile score, which combines gender, T2DM status, AST/ALT ratio, platelet count, and liver stiffness measurement (LSM), can improve the diagnostic efficacy of advanced fibrosis and cirrhosis in MAFLD patients and the efficiency of predicting liver-related events. However, the predictive effect of fibrosis staging and its changes on liver cancer needs to be improved. There is a lack of high-quality research on early warning indicators for the incidence of CVD, chronic kidney disease, and non-liver malignancies in MAFLD patients. It is necessary to explore the role of conventional indicators such as low-density lipoprotein cholesterol, lipoprotein(a), uric acid, and high-sensitivity C-reactive protein, as well as multi-omics parameters, in the classification, staging, and risk prediction of MAFLD. MAFLD is an increasingly serious public health issue associated with a higher risk of liver-related events, cardiovascular-renal-metabolic syndrome, and malignancies. The prevalence of MAFLD in China is high, but the rate of standardized management is low. Even patients with the same classification and staging often have different clinical characteristics and outcomes. There is currently a lack of a clinical classification and early warning system for MAFLD that combines metabolic cardiovascular risk factors and NITs for different outcome risks.

Conditions

Metabolic Dysfunction Associated Steatotic Liver Disease; Metabolic Dysfunction-associated Steatohepatitis (MASH)

Keywords

MAFLD; MASLD; liver-biopsy; classification; prediction model

Outcome Measures

Primary Outcomes (1)

• composite endpoint

  Number of participants with the composite endpoint, including A. Liver-Related Events: Cirrhosis Liver decompensation Hepatocellular carcinoma Liver transplantation B. Metabolic Diseases: Type 2 Diabetes Mellitus (T2DM) Hypertension Dyslipidemia Gout C. Cardiovascular Diseases (CVD): Coronary heart disease Stroke Heart failure Atrial fibrillation D. Non-Liver Malignancies: Colorectal adenoma/adenocarcinoma Gastric cancer Esophageal cancer Pancreatic cancer Gallbladder cancer Lung cancer Prostate cancer Hematological malignancies E. Chronic Kidney Disease F. Mortality: Liver disease-related deaths Cardiovascular disease-related deaths Other causes of death

  1-20 years

Secondary Outcomes (6)

• Liver-Related Events

  1-20 years

• Metabolic Diseases

  1-20 years

• Cardiovascular Diseases (CVD)

  1-20 years

• Non-Liver Tumors

  1-20 years

• Chronic Kidney Disease

  1-20 years

Other Outcomes (4)

• biomarker by proteomics

  baseline

• biomarker by metabolomics

  baseline

• biomarker by Immunomics

  baseline

Study Arms (1)

MAFLD diagnosed by liver-biopsy

retrospective and prospective cohort about MAFLD diagnosed by liver-biopsy

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

MAFLD patients diagnosis by liver biopsy

You may qualify if:

• Ultrasound confirmation of fatty liver and the presence of at least one of the following metabolic cardiovascular risk factors:
• BMI ≥ 24 kg/m² or waist circumference ≥ 90 cm (men) and 85 cm (women) or excessive body fat content and body fat percentage.
• Fasting blood glucose ≥ 6.1 mmol/L or 2-hour post-load blood glucose ≥ 7.8 mmol/L or HbA1c ≥ 5.7% or history of Type 2 Diabetes Mellitus (T2DM) or Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) ≥ 2.5.
• Fasting serum triglycerides ≥ 1.70 mmol/L or currently receiving lipid-lowering drug therapy.
• Serum high-density lipoprotein cholesterol (HDL-C) ≤ 1.0 mmol/L (men) and 1.3 mmol/L (women) or currently receiving lipid-lowering drug therapy.
• Blood pressure ≥ 130/85 mmHg or currently receiving antihypertensive drug therapy.
• histology of liver-biopsy

You may not qualify if:

• Excessive Alcohol Consumption: Individuals who consume alcohol equivalent to ≥30 grams of ethanol per day for males, or ≥20 grams of ethanol per day for females, or those with missing alcohol consumption information.
• Viral Hepatitis Markers: Individuals who are positive for hepatitis B surface antigen (HBsAg), positive for hepatitis C virus (HCV) antibodies, or have missing information regarding these markers.
• History of Serious Medical Conditions: Individuals with a history of malignant tumors, cardiovascular diseases, chronic kidney disease, decompensated liver cirrhosis (manifested by ascites, gastrointestinal bleeding, hepatic encephalopathy, hepatorenal syndrome, etc.), or those who have undergone liver transplantation.

Sponsors & Collaborators

• Beijing Friendship Hospital: lead
• Fudan University: collaborator
• Tianjin Second People's Hospital: collaborator
• Xinhua Hospital, Shanghai Jiao Tong University School of Medicine: collaborator
• The Affiliated Hospital of Hangzhou Normal University: collaborator
• Ruijin Hospital: collaborator

Study Sites (6)

Beijing Friendship Hospital, Capital Medical University

Beijing, Xicheng, 100050, China

Location

Hangzhou Normal University Affiliated Hospital

Hangzhou, Xicheng, 100050, China

Location

Zhongshan Hospital, Fudan University

Shanghai, Xicheng, 100050, China

Location

Shanghai Ruijin Hospital, Shanghai Jiaotong University School of Medicine

Shanghai, China

Location

Xinhua Hospital, Shanghai Jiaotong University School of Medicine

Shanghai, China

Location

Tianjin Second People's Hospital

Tianjin, China

Location

Biospecimen

Retention: SAMPLES WITH DNA

serum, PBMC, plasma, urine, feces, liver-biopsy tissues

Study Officials

• Hong You, PhD. / M.D.

  Beijing Friendship Hospital

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Jingjie Zhao, M.D.

CONTACT

01063138328; zhaojj@ccmu.edu.cn

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: OTHER
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Vice-President

Study Record Dates

• First Submitted: January 20, 2025
• First Posted: January 28, 2025
• Study Start: February 8, 2025
• Primary Completion (Estimated): December 31, 2028
• Study Completion (Estimated): December 31, 2038
• Last Updated: February 12, 2025

Record last verified: 2025-01

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, CSR, ANALYTIC CODE
• Time Frame: After the project finished
• Access Criteria: ask the principle investigator

Locations

CN (6)