Drug-induced Liver InjuryNCT05532345
Discrimination of DILI and AIH by Artificial Intelligence
An observational study of Drug-induced Liver Injury and Autoimmune Hepatitis, run by Beijing Friendship Hospital at 1 site in China.
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. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Drug-induced Liver Injury, Autoimmune Hepatitis
- How many people
- 2,583 participants
- Where
- 1 siteChina
- Study dates
- 1 Jul 2022to 31 May 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: Hospitalized patients with a definite diagnosis of DILI and AIH were recruited from all hospitals between January 2009 to December 2025. This study was approved by the Institutional Ethical Review Board (2022-P2-263-01).
Who may be able to join
- Drug-induced liver injury
- 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.
- RUCAM was between 3-5, the medical records were further reviewed by the three authors to determine the eligibility.
- Autoimmune hepatitis
- The revised International Autoimmune Hepatitis Group (IAIHG) diagnostic score≥6 points.
- Liver biopsy available, which is compatible with typical features of AIH.
- If liver biopsy was unavailable, patients who achieved biochemical resolution after sustained immunosuppressive therapy.
Who cannot join
- Drug-induced liver injury
- Hepatotropic viral infection: hepatitis A, B, C, D and E.
- Non-hepatotropic viral infection: cytomegalovirus (CMV) and Epstein-Barr virus (EBV), etc.
- Hypoxic ischemic hepatitis and congestive liver disease.
- Alcohol consumption: male >40g/d, female >20g/d, and ≥5 years.
- Biliary obstruction, primary biliary cholangitis; primary sclerosing cholangitis.
Show all 24Show fewer
- Autoimmune hepatitis.
- Parasitic infection.
- Sepsis.
- Previous liver transplantation or bone marrow transplantation.
- Pregnancy or lactation.
- Genetic and metabolic liver diseases.
- Autoimmune hepatitis
- Hepatotropic viral infection: hepatitis A, B, C, D and E.
- Non-hepatotropic viral infection: cytomegalovirus (CMV) and Epstein-Barr virus (EBV), etc.
- Hypoxic ischemic hepatitis and congestive liver disease.
- Alcohol consumption: male >40g/d, female >20g/d, and ≥5 years.
- Biliary obstruction, primary biliary cholangitis; primary sclerosing cholangitis.
- Drug-induced liver injury.
- Parasitic infection.
- Sepsis.
- Previous liver transplantation or bone marrow transplantation.
- Pregnancy or lactation.
- Genetic and metabolic liver diseases.
Trial locations and contacts
1 site in 1 country.
China1 site
Beijing Friendship Hospital, Capital Medical University
Beijing, 100050
About this study
Official title: Development and Validation of a Machine Learning Model to Differentiate Drug-induced Liver Injury and Autoimmune Hepatitis
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
Read the detailed description
Research Objectives:
- To develop a machine learning-based model from retrospective data.
- To validate the machine learning-based model from internal dataset and external datasets nationwide.
- To setup a website or application based on the above model to discriminate Drug-induced liver injury and Autoimmune hepatitis.
- Conditions
- Drug-induced Liver Injury, Autoimmune Hepatitis
- Keywords
- Artificial intelligence, Differential diagnose
- Medical subject headings
- Chemical and Drug Induced Liver Injury, Hepatitis, Autoimmune
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Development group, retrospectively collecting | The training set includes 80% of the development dataset from Beijing Friendship Hospital (Retrospectively collecting DILI 649 cases and AIH 180 cases in total) | |
| Validation group, retrospectively collecting | The internal validation group includes 20% of the development dataset from Beijing Friendship Hospital (Retrospectively collecting DILI 649 cases and AIH 180 cases in total). External validation groups include Fifth Medical Center of Chinese PLA Medical Center(Retrospectively collecting DILI 585 cases and AIH 400 cases in total), Beijing You'an Hospital (Retrospectively collecting DILI 266 cases and AIH 100 cases in total) and additional seven tertiary hospitals throughout China (Retrospectively collecting DILI 182 cases and AIH 92 cases in total, including Tianjin Second People's Hospital, Heilongjiang Provincial Hospital, Affiliated Hospital of Qingdao University, the First Affiliated Hospital of Xiamen University, Traditional Chinese Medical Hospital of Xinjiang Uygur Autonomous Region, Lanzhou University Second Hospital, Qinghai Provincial People's Hospital). | |
| Real-World validation group, prospectively and retrospectively collecting | Real-World validation data will be prospectively and retrospectively collected from Beijing Friendship Hospital (78 cases for DILI and 51 cases for AIH) |
What is being measured
The primary outcome is the main question the study is designed to answer.
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
Measured: May 31, 2023
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
Measured: May 31, 2023
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted8 Sep 2022
- Study start1 Jul 2022
- Primary completion31 May 2023
- Study completion31 May 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Drug-induced Liver InjuryStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Retrospective
- Enrolment
- 2,583 participants (actual)
Sponsor and investigators
- Lead sponsor
- Beijing Friendship Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Xinyan Zhao, Dr., Study chair, Beijing Friendship HospitalYing Sun, Dr., Principal investigator, The Fifth Medical Department of the PLAJing Zhang, Dr., Principal investigator, Capital Medical University Affiliated Beijing You'an HospitalJia Li, Dr., Principal investigator, Tianjin Second People's HospitalLiang Wang, Dr., Principal investigator, Lanzhou University Affiliated Second HospitalXiaoli Hu, Dr., Principal investigator, Heilongjiang Provicial HospitalJingshou Chen, Dr., Principal investigator, The First Affiliated Hospital of Xiamen UniversityFeng Guo, Dr., Principal investigator, Xinjiang Uygur Autonomous Region Hospital of Traditional Chinese Medicine
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05532345
- Sponsor's protocol ID
- 2022-P2-263-01
- Status last verified
- Jul 2023
- First submitted
- 29 Aug 2022
- Last updated
- 6 Jul 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Wang Y, Lin X, Sun Y, Liu J, Li J, Tian Q, Guo F, Hu X, Wang L, Li P, Chen J, Wang Y, Ma Z, Jia J, Zhang J, Zou Z, Zhao X. Development and Validation of a Novel Model to Discriminate Idiosyncratic Drug-Induced Liver Injury and Autoimmune Hepatitis. Liver Int. 2025 Feb;45(2):e16239. doi: 10.1111/liv.16239.
PubMed 39817622
Study at a glance
From the registry record, last updated by the sponsor on 6 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development and Validation of a Machine Learning Model to Differentiate Drug-induced Liver Injury and Autoimmune Hepatitis
- ClinicalTrials.gov ID
- NCT05532345
- Acronym / sponsor ID
- 2022-P2-263-01
- Conditions
- Drug-induced Liver Injury, Autoimmune Hepatitis
- Keywords
- Artificial intelligence, Differential diagnose
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 2,583 participants (actual)
- Lead sponsor
- Beijing Friendship HospitalUniversity, hospital or other
- Study start
- 1 Jul 2022 (actual)
- Primary completion
- 31 May 2023 (actual)
- Study completion
- 31 May 2023 (actual)
- First posted
- 8 Sep 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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
Detailed description
Research Objectives:
- To develop a machine learning-based model from retrospective data.
- To validate the machine learning-based model from internal dataset and external datasets nationwide.
- To setup a website or application based on the above model to discriminate Drug-induced liver injury and Autoimmune hepatitis.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Development group, retrospectively collecting | – | –The training set includes 80% of the development dataset from Beijing Friendship Hospital (Retrospectively collecting DILI 649 cases and AIH 180 cases in total) |
| Validation group, retrospectively collecting | – | –The internal validation group includes 20% of the development dataset from Beijing Friendship Hospital (Retrospectively collecting DILI 649 cases and AIH 180 cases in total). External validation groups include Fifth Medical Center of Chinese PLA Medical Center(Retrospectively collecting DILI 585 cases and AIH 400 cases in total), Beijing You'an Hospital (Retrospectively collecting DILI 266 cases and AIH 100 cases in total) and additional seven tertiary hospitals throughout China (Retrospectively collecting DILI 182 cases and AIH 92 cases in total, including Tianjin Second People's Hospital, Heilongjiang Provincial Hospital, Affiliated Hospital of Qingdao University, the First Affiliated Hospital of Xiamen University, Traditional Chinese Medical Hospital of Xinjiang Uygur Autonomous Region, Lanzhou University Second Hospital, Qinghai Provincial People's Hospital). |
| Real-World validation group, prospectively and retrospectively collecting | – | –Real-World validation data will be prospectively and retrospectively collected from Beijing Friendship Hospital (78 cases for DILI and 51 cases for AIH) |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Hospitalized patients with a definite diagnosis of DILI and AIH were recruited from all hospitals between January 2009 to December 2025. This study was approved by the Institutional Ethical Review Board (2022-P2-263-01).
Key inclusion criteria (7 listed)
- Drug-induced liver injury
- Autoimmune hepatitis
Key exclusion criteria (24 listed)
- Drug-induced liver injury
- Autoimmune hepatitis
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Accuracy of the model in the differential diagnosis of DILI and AIH
Time frame: May 31, 2023
The ratio of the correct number of forecasts to the total number of forecasts
The confidence of the model in the differential diagnosis of DILI and AIH
Time frame: May 31, 2023
The confidence and 95% confidence internal of the model in determining whether each case is DILI or AIH
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Jul 2026.
- Derived from this study: PubMed 39817622Wang Y, Lin X, Sun Y, Liu J, Li J, Tian Q, Guo F, Hu X, Wang L, Li P, Chen J, Wang Y, Ma Z, Jia J, Zhang J, Zou Z, Zhao X. Development and Validation of a Novel Model to Discriminate Idiosyncratic Drug-Induced Liver Injury and Autoimmune Hepatitis. Liver Int. 2025 Feb;45(2):e16239. doi: 10.1111/liv.16239.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Xinyan Zhao, Dr. study chair
Beijing Friendship Hospital
Ying Sun, Dr. principal investigator
The Fifth Medical Department of the PLA
Jing Zhang, Dr. principal investigator
Capital Medical University Affiliated Beijing You'an Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Drug-induced Liver Injury and Autoimmune Hepatitis, run by Beijing Friendship Hospital at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 7 inclusion and 24 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 6 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy of the model in the differential diagnosis of DILI and AIH (time frame: May 31, 2023). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05532345, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Jul 2026.