Discrimination of DILI and AIH by Artificial Intelligence

Autoimmune Hepatitis Clinical Trial

Official title:

Development and Validation of a Machine Learning Model to Differentiate Drug-induced Liver Injury and Autoimmune Hepatitis

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT05532345
• Other study ID #: 2022-P2-263-01
• Status: Completed
• Start date: July 1, 2022
• Est. completion date: May 31, 2023

Study information

• Verified date: July 2023
• Source: Beijing Friendship Hospital
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

A retrospective, multi-center, non-interventional cohort study has been going to explore whether artificial intelligence can discriminate Drug-induced liver injury and Autoimmune hepatitis. A machine learning-based tool will be developed and validated to help clinicians to differentiate between Drug-induced liver injury and Autoimmune hepatitis

Description:

Research Objectives: 1. To develop a machine learning-based model from retrospective data. 2. To validate the machine learning-based model from internal dataset and external datasets nationwide. 3. To setup a website or application based on the above model to discriminate Drug-induced liver injury and Autoimmune hepatitis.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 2583
• Est. completion date: May 31, 2023
• Est. primary completion date: May 31, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: N/A and older

Eligibility

Inclusion Criteria:

• Drug-induced liver injury

1. RUCAM =6 and met one of the following biochemical conditions: a.) ALT=5 ULN, b.) or ALP =2 ULN, iii) or ALT=3 ULN and TBil=2 ULN.

2. RUCAM was between 3-5, the medical records were further reviewed by the three authors to determine the eligibility.

• Autoimmune hepatitis

1. The revised International Autoimmune Hepatitis Group (IAIHG) diagnostic score=6 points.

2. Liver biopsy available, which is compatible with typical features of AIH.

3. If liver biopsy was unavailable, patients who achieved biochemical resolution after sustained immunosuppressive therapy.

Exclusion Criteria:

• Drug-induced liver injury

1. Hepatotropic viral infection: hepatitis A, B, C, D and E.

2. Non-hepatotropic viral infection: cytomegalovirus (CMV) and Epstein-Barr virus (EBV), etc.

3. Hypoxic ischemic hepatitis and congestive liver disease.

4. Alcohol consumption: male >40g/d, female >20g/d, and =5 years.

5. Biliary obstruction, primary biliary cholangitis; primary sclerosing cholangitis.

6. Autoimmune hepatitis.

7. Parasitic infection.

8. Sepsis.

9. Previous liver transplantation or bone marrow transplantation.

10. Pregnancy or lactation.

11. Genetic and metabolic liver diseases.

• Autoimmune hepatitis

1. Hepatotropic viral infection: hepatitis A, B, C, D and E.

2. Non-hepatotropic viral infection: cytomegalovirus (CMV) and Epstein-Barr virus (EBV), etc.

3. Hypoxic ischemic hepatitis and congestive liver disease.

4. Alcohol consumption: male >40g/d, female >20g/d, and =5 years.

5. Biliary obstruction, primary biliary cholangitis; primary sclerosing cholangitis.

6. Drug-induced liver injury.

7. Parasitic infection.

8. Sepsis.

9. Previous liver transplantation or bone marrow transplantation.

10. Pregnancy or lactation.

11. Genetic and metabolic liver diseases.

Related Conditions & MeSH terms

• Autoimmune Hepatitis
• Chemical and Drug Induced Liver Injury
• Drug-induced Liver Injury
• Hepatitis
• Hepatitis, Autoimmune

Locations

Country	Name	City	State
China	Beijing Friendship Hospital, Capital Medical University	Beijing

Sponsors (1)

Lead Sponsor	Collaborator
Beijing Friendship Hospital

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Accuracy of the model in the differential diagnosis of DILI and AIH	The ratio of the correct number of forecasts to the total number of forecasts	May 31, 2023
Primary	The confidence of the model in the differential diagnosis of DILI and AIH	The confidence and 95% confidence internal of the model in determining whether each case is DILI or AIH	May 31, 2023