NCT07321288Active, not recruiting
Machine Learning-Based Prediction of Insulin Resistance in Psoriasis Patients Emphasizing Interpretability
Identification of Risk Factors and Development of an Interpretable Machine Learning Model for Predicting Insulin Resistance in Patients With Psoriasis
Source: ClinicalTrials.gov · Last updated 8 May 2026
Brief summary (registry, in English)
Psoriasis is a long-term inflammatory skin disease that can affect overall health. People with psoriasis have a higher risk of developing insulin resistance, a condition in which the body does not respond properly to insulin. Insulin resistance can increase the risk of diabetes, heart disease, and other serious health problems. Because insulin resistance often develops without clear symptoms, many patients are not diagnosed early. The purpose of this study is to identify which patients with psoriasis are more likely to develop insulin resistance and to create a tool that can help doctors estimate this risk for individual patients. The study will use existing medical records from two medical centers. Researchers will analyze information such as age, body weight, psoriasis severity, blood test results, other medical conditions, and medication history. Machine learning methods will be used to analyze these data and build a prediction model. The model will be designed to be easy to understand, so doctors can see which factors contribute most to insulin resistance risk. This study does not involve any new treatments or procedures. All patient information will be anonymized to protect privacy. The results may help doctors identify high-risk patients earlier and support timely monitoring and preventive care.
- Status (registry)
- Active, not recruiting
- Study type
- Observational
- Enrollment
- 1265 (estimated)
- First submitted
- 22 Dec 2025
- Start date
- 1 Sept 2025
- Primary completion date
- 1 Sept 2026
- Lead sponsor
- Chinese PLA General Hospital
- Diseases
- Psoriasis
- NCT number
- NCT07321288
What you commit to
- Study type: Observational
- Planned participants: 1265
- From 1 Sept 2025 to the primary completion date, 1 Sept 2026
- 1 site in 1 country
- Visits and tests: ask the trial team, the registry does not list them
Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.
Who cannot take part
Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.
Prior treatment
- Previous or current diagnosis of diabetes mellitus
Lab values
- Presence of severe systemic diseases that may significantly affect glucose metabolism (such as malignant tumors, hyperthyroidism, or other serious endocrine disorders)
- Current or recent use of systemic medications known to affect insulin sensitivity, including:Systemic corticosteroids,Glucose-lowering medications, or Other medications with known significant effects on insulin resistance
Other
- Pregnant or breastfeeding women
- Medical records with missing key variables required for the assessment of insulin resistance or model development
Who the study is looking for
- Adults aged 18 years or older
- Diagnosed with psoriasis (including plaque psoriasis, pustular psoriasis, erythrodermic psoriasis, or other clinically recognized subtypes), according to established clinical diagnostic guidelines
- Received medical care at Chinese PLA General Hospital (First Medical Center) or the collaborating center (Fourth Medical Center) during the study period
- Availability of complete medical records, including demographic information, relevant clinical characteristics, and laboratory data required to assess insulin resistance
Age in the registry: 18 years to - · Sex: All · Does not accept healthy volunteers
Sites (1)
Sites in registry order. Save your city in your profile to sort them by distance.
| Site | City | Country | Site status |
|---|---|---|---|
| Chinese PLA General Hosptial Coordinator of this site? Confirm its status | Beijing | China | Unknown status |
This page is information, not medical advice. Discuss any trial with your doctor.