Metabolic Dysfunction-associated Fatty Liver DiseaseNCT06061640
The Potential Value and Impact of Diagnostic Biomarkers for MAFLD Using Machine Learning Methods
An observational study of Metabolic Dysfunction-associated Fatty Liver Disease, run by The First Affiliated Hospital of Zhejiang Chinese Medical University at 1 site in China.
Trial summary
This is a case-control study that aims to build a predictive model for MAFLD based on machine learning. Read more about this study
- Who is it for?
- Ages 18 to 75 yearsHealthy volunteers can take part
- Conditions the study is for
- Metabolic Dysfunction-associated Fatty Liver Disease
- How many people
- 500 participants
- Where
- 1 siteChina
- Study dates
- 1 Jun 2023to 31 Dec 2024
- 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: Chinese participants age 18 years or older diagnosed with MAFLD on imaging and healthy volunteers without MAFLD.
Who may be able to join
- aged 18 to 75 years;
- meeting the diagnostic criteria of MAFLD;
- no other organic lesions were found in imaging examination;
- willing and able to sign informed consent.
Who cannot join
- significant drinking history (weekly alcohol consumption ≥ 140g for male, or weekly alcohol consumption ≥ 70g for female);
- presence of evidence for having hepatic steatosis, viral hepatitis, history of hepatic cancer, drug-induced liver injury, liver cirrhosis and other liver and biliary tract diseases;
- major organ malfunction, severe systemic illnesses, mental health issues, or inability to complete examination;
- pregnant or pregnancy planning female;
- missing of important clinical data.
Trial locations and contacts
1 site in 1 country.
China1 site
The First Clinical Medical College of Zhejiang Chinese Medical University
Hangzhou, Zhejiang, 310003
About this study
This is a case-control study that aims to build a predictive model for MAFLD based on machine learning.
Read the detailed description
Metabolic dysfunction-associated fatty liver disease (MAFLD) also known as non-alcoholic fatty liver disease (NAFLD), is one of the most prevalent liver diseases worldwide with high prevalence and economic burden, which affects 25% of global adult population. Despite extensive research on understanding the inner pathophysiology of MAFLD, it still keep growing with no approval therapy. Therefore, preventive measures are particularly important in diagnosing MAFLD. So far the liver biopsy is still the gold standard for diagnosis of MAFLD, however considering the invasive process and potential risks, it still has low acceptance for asymptomatic patients, thus non-invasive methods are necessary for this reason.
The purpose of this study is to establish a prediction model to identify MAFLD patients, which can accurately predict whether the participants have MAFLD according to the relevant metabolic indicators of the participants, without the need for invasive examinations such as tissue biopsy.
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 |
|---|---|---|
| case group | MAFLD patients | |
| control group | health people |
What is being measured
The primary outcome is the main question the study is designed to answer.
Area under cure
Area under cure(AUC) was defined as the area enclosed by the coordinate axis under the receiver operating characteristic curve, with values ranging from 0.5 to 1.0. The closer the AUC is to 1.0, the higher the authenticity of the detection method; the closer to 0.5, the lower the authenticity of the detection method; when equal to 0.5, the authenticity is the lowest and has no application value.
Measured: 2022-2024
Secondary outcomes (2)
Accuracy
The proportion of the number of correctly classified samples to the total number of samples.
Measured: 2022-2024
Precision
The proportion of data that is actually positive among the data that is determined to be positive.
Measured: 2022-2024
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Sep 2023
- Study start1 Jun 2023
- Primary completion30 Jun 2024 (estimated)
- Study completion31 Dec 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Metabolic Dysfunction-associated 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
- Case-control
- Time perspective
- Prospective
- Enrolment
- 500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- The First Affiliated Hospital of Zhejiang Chinese Medical University
- Sponsor type
- University, hospital or other
- Collaborators
- Zhejiang Chinese Medical University
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06061640
- Sponsor's protocol ID
- 2021-KL-202-01
- Status last verified
- Sep 2023
- First submitted
- 25 Sep 2023
- Last updated
- 29 Sep 2023
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 29 Sep 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Potential Value and Impact of Diagnostic Biomarkers for MAFLD Using Machine Learning Methods
- ClinicalTrials.gov ID
- NCT06061640
- Acronym / sponsor ID
- 2021-KL-202-01
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 500 participants (estimated)
- Lead sponsor
- The First Affiliated Hospital of Zhejiang Chinese Medical UniversityUniversity, hospital or other
- Collaborators
- Zhejiang Chinese Medical University
- Study start
- 1 Jun 2023 (actual)
- Primary completion
- 30 Jun 2024 (estimated)
- Study completion
- 31 Dec 2024 (estimated)
- First posted
- 29 Sep 2023 (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.
This is a case-control study that aims to build a predictive model for MAFLD based on machine learning.
Detailed description
Metabolic dysfunction-associated fatty liver disease (MAFLD) also known as non-alcoholic fatty liver disease (NAFLD), is one of the most prevalent liver diseases worldwide with high prevalence and economic burden, which affects 25% of global adult population. Despite extensive research on understanding the inner pathophysiology of MAFLD, it still keep growing with no approval therapy. Therefore, preventive measures are particularly important in diagnosing MAFLD. So far the liver biopsy is still the gold standard for diagnosis of MAFLD, however considering the invasive process and potential risks, it still has low acceptance for asymptomatic patients, thus non-invasive methods are necessary for this reason.
The purpose of this study is to establish a prediction model to identify MAFLD patients, which can accurately predict whether the participants have MAFLD according to the relevant metabolic indicators of the participants, without the need for invasive examinations such as tissue biopsy.
Study design
- Observational model
- Case-control
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| case group | – | –MAFLD patients |
| control group | – | –health people |
Who may qualify
- Ages
- 18 to 75 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Chinese participants age 18 years or older diagnosed with MAFLD on imaging and healthy volunteers without MAFLD.
Key inclusion criteria (4 listed)
- aged 18 to 75 years;
- meeting the diagnostic criteria of MAFLD;
- no other organic lesions were found in imaging examination;
- willing and able to sign informed consent.
Key exclusion criteria (5 listed)
- significant drinking history (weekly alcohol consumption ≥ 140g for male, or weekly alcohol consumption ≥ 70g for female);
- presence of evidence for having hepatic steatosis, viral hepatitis, history of hepatic cancer, drug-induced liver injury, liver cirrhosis and other liver and biliary tract diseases;
- major organ malfunction, severe systemic illnesses, mental health issues, or inability to complete examination;
- pregnant or pregnancy planning female;
- missing of important clinical data.
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
Area under cure
Time frame: 2022-2024
Area under cure(AUC) was defined as the area enclosed by the coordinate axis under the receiver operating characteristic curve, with values ranging from 0.5 to 1.0. The closer the AUC is to 1.0, the higher the authenticity of the detection method; the closer to 0.5, the lower the authenticity of the detection method; when equal to 0.5, the authenticity is the lowest and has no application value.
2 secondary outcomes
Accuracy
Time frame: 2022-2024
Precision
Time frame: 2022-2024
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 Sep 2023.
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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.
The record lists no contact. Use the official record to reach the sponsor.
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 Metabolic Dysfunction-associated Fatty Liver Disease, run by The First Affiliated Hospital of Zhejiang Chinese Medical University 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 4 inclusion and 5 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 29 Sep 2023. 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?
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?
Area under cure (time frame: 2022-2024). 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 29 Sep 2023.