Non-Alcoholic Fatty Liver DiseaseNCT05560997
Metabolic Subtypes of Non-Alcoholic Fatty Liver Disease
An observational study of Non-Alcoholic Fatty Liver Disease and Machine Learning, run by Yan Bi at 1 site in China.
Trial summary
The purpose of this study was to use machine learning to explore a more precise classification of NAFLD subgroups towards informing individualized therapy. Read more about this study
- Who is it for?
- Ages 18 to 75 yearsHealthy volunteers can take part
- Conditions the study is for
- Non-Alcoholic Fatty Liver Disease, Machine Learning
- What is being tested?
- 10-year ASCVD risk estimation
- How many people
- 1,000 participants
- Where
- 1 siteChina
- Study dates
- 5 Jan 2016to 1 Jun 2025
- 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 18 to 75 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: The study enrolled subjects who underwent liver biopsy or physical examination in Drum Tower Hospital affiliated to Nanjing University Medical School.
Who may be able to join
- biopsy-proved NALD cohort:
- age 18 to 75 years
- receiving liver biopsy at the time of metabolic surgery
- relatively complete clinical information, including physical examination, biochemical and haematological assessments
- longitudinal cohort
- age 18 to 75 years
- receiving abdominal imaging examinations,
- relatively complete clinical information, including physical examination, biochemical and haematological assessments (4）follow-up time at least more than 12 months
Who cannot join
- (1)consumed excessive alcohol (≥140 g/week for males or ≥ 70 g/week for females) •
- (2) with history of other liver diseases including chronic hepatitis, biliary obstructive diseases or autoimmune hepatitis
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Division of Endocrinology, the Affiliated Drum Tower Hospital of Nanjing University
Nanjing, Jiangsu, 210008
Dalong Zhu, MD,PhD, 86-25-83-105302, zhudldr@gmail.com
Yan Bi, MD,PhD, 86-25-83-105302, biyan@nju.edu.cn
About this study
Official title: Machine Learning to Identify Metabolic Subtypes of Non-Alcoholic Fatty Liver Disease
The purpose of this study was to use machine learning to explore a more precise classification of NAFLD subgroups towards informing individualized therapy.
Read the detailed description
Clinical characteristics of NAFLD are heterogenous, but current classification for diagnosis is simply based on pathological examination. The conventional pathological classification is insufficient to reflect the complexity and heterogeneity of NAFLD and can not predict the prognosis. Towards precision treatment, a more refined metabolic classification of NAFLD phenotypes is highly demanded for a personalized diagnosis, aiming to identify patients at elevated risk of cardiovascular disease or cirrhosis. This kind of refined classification can provide a more precise diagnosis and enable more individualized preventive interventions and early treatments. In a cross-sectional cohort, unsupervised machine learning was used to cluster patients with biopsy-proved NAFLD from Drum Tower Hospital Affiliated to Nanjing University Medical School based on clinical variables. Verification of the clustering was performed in a longitudinal cohort.
- Being tested
- 10-year ASCVD risk estimation
- Medical subject headings
- Non-alcoholic Fatty Liver Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
10-year ASCVD risk estimationDiagnostic test
High CVD risk was defined as a history of CVD or a 10-year ASCVD risk ≥10%. The 10-year ASCVD risk estimation was carried out according to 2016 Chinese guidelines for the management of dyslipidemia in adults.
| Study group | Role | What they receive |
|---|---|---|
| biopsy-proved NAFLD cohort | NAFLD is defined as the presence of at least 5% steatosis based on histological examination. Receives: Diagnostic Test: 10-year ASCVD risk estimation | |
| longitudinal physical examination cohort | The diagnosis of NAFLD was based on imaging evaluation. Receives: Diagnostic Test: 10-year ASCVD risk estimation |
What is being measured
The primary outcome is the main question the study is designed to answer.
Ischemic heart disease
Objective Findings of Coronary Stenosis (≥ 50%) in at least 2 coronary artery territories (ie, left anterior descending, ramus intermedius, left circumflex, right coronary artery) involving the vain vessel, a major branch, or a bypass graft
Measured: up to 5 years
Documented heart disease checklist
Documented Myocardial Infarction or Percutaneous Coronary Intervention or Coronary Artery Bypass Grafting
Measured: up to 5 years
histological cirrhosis checklist
cirrhosis was defined as widespread disruption of normal liver structure by the formation of pseudolobules or Scheuer stage 4 fibrosis in pathological findings.
Measured: up to 5 years
hepatocellular carcinoma
the diagnosis of hepatocellular carcinoma was based on well-established diagnostic imaging criteria and/or histology.
Measured: up to 5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted30 Sep 2022
- Study start5 Jan 2016
- Primary completion30 Oct 2024 (estimated)
- Study completion1 Jun 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Non-Alcoholic Fatty Liver DiseaseStudies 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
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 1,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Yan Bi
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Yan Bi, The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05560997
- Sponsor's protocol ID
- NAFLDcluster
- Status last verified
- Sep 2023
- First submitted
- 26 Sep 2022
- Last updated
- 21 Jun 2024
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 21 Jun 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Machine Learning to Identify Metabolic Subtypes of Non-Alcoholic Fatty Liver Disease
- ClinicalTrials.gov ID
- NCT05560997
- Acronym / sponsor ID
- NAFLDcluster
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 1,000 participants (estimated)
- Lead sponsor
- Yan BiUniversity, hospital or other
- Study start
- 5 Jan 2016 (actual)
- Primary completion
- 30 Oct 2024 (estimated)
- Study completion
- 1 Jun 2025 (estimated)
- First posted
- 30 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.
The purpose of this study was to use machine learning to explore a more precise classification of NAFLD subgroups towards informing individualized therapy.
Detailed description
Clinical characteristics of NAFLD are heterogenous, but current classification for diagnosis is simply based on pathological examination. The conventional pathological classification is insufficient to reflect the complexity and heterogeneity of NAFLD and can not predict the prognosis. Towards precision treatment, a more refined metabolic classification of NAFLD phenotypes is highly demanded for a personalized diagnosis, aiming to identify patients at elevated risk of cardiovascular disease or cirrhosis. This kind of refined classification can provide a more precise diagnosis and enable more individualized preventive interventions and early treatments. In a cross-sectional cohort, unsupervised machine learning was used to cluster patients with biopsy-proved NAFLD from Drum Tower Hospital Affiliated to Nanjing University Medical School based on clinical variables. Verification of the clustering was performed in a longitudinal cohort.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| biopsy-proved NAFLD cohort | – | Diagnostic Test: 10-year ASCVD risk estimationNAFLD is defined as the presence of at least 5% steatosis based on histological examination. |
| longitudinal physical examination cohort | – | Diagnostic Test: 10-year ASCVD risk estimationThe diagnosis of NAFLD was based on imaging evaluation. |
Who may qualify
- Ages
- 18 to 75 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- The study enrolled subjects who underwent liver biopsy or physical examination in Drum Tower Hospital affiliated to Nanjing University Medical School.
Key inclusion criteria (8 listed)
- biopsy-proved NALD cohort:
- longitudinal cohort
Key exclusion criteria (2 listed)
- (1)consumed excessive alcohol (≥140 g/week for males or ≥ 70 g/week for females) •
- (2) with history of other liver diseases including chronic hepatitis, biliary obstructive diseases or 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.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| 10-year ASCVD risk estimationHigh CVD risk was defined as a history of CVD or a 10-year ASCVD risk ≥10%. The 10-year ASCVD risk estimation was carried out according to 2016 Chinese guidelines for the management of dyslipidemia in adults. | Diagnostic test | biopsy-proved NAFLD cohort, longitudinal physical examination cohort |
Primary outcome
Ischemic heart disease
Time frame: up to 5 years
Objective Findings of Coronary Stenosis (≥ 50%) in at least 2 coronary artery territories (ie, left anterior descending, ramus intermedius, left circumflex, right coronary artery) involving the vain vessel, a major branch, or a bypass graft
Documented heart disease checklist
Time frame: up to 5 years
Documented Myocardial Infarction or Percutaneous Coronary Intervention or Coronary Artery Bypass Grafting
histological cirrhosis checklist
Time frame: up to 5 years
cirrhosis was defined as widespread disruption of normal liver structure by the formation of pseudolobules or Scheuer stage 4 fibrosis in pathological findings.
hepatocellular carcinoma
Time frame: up to 5 years
the diagnosis of hepatocellular carcinoma was based on well-established diagnostic imaging criteria and/or histology.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 21 Jun 2024.
- Individual participant dataSharing planned: No
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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.
Division of Endocrinology, the Affiliated Drum Tower Hospital of Nanjing University
Nanjing, China
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 Non-Alcoholic Fatty Liver Disease and Machine Learning, run by Yan Bi 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 8 inclusion and 2 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: status not confirmed, as of the sponsor's last update on 21 Jun 2024. 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Each site lists its own contact: choose the nearest one under Trial locations. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Ischemic heart disease (time frame: up to 5 years). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 21 Jun 2024.