NCT07332923Active, not recruiting
Predicting HIF-2α Levels in Clear Cell Kidney Cancer Using Machine Learning
Development of a Machine Learning-Based Nomogram for Predicting HIF-2α Expression Levels in Clear Cell Renal Cell Carcinoma
Source: ClinicalTrials.gov · Last updated 12 Jan 2026
Brief summary (registry, in English)
This project aims to conduct a multicenter retrospective study to collect clinical, CT imaging, and pathological data from patients. A comprehensive data management system will be established, and radiomic features will be extracted to integrate and analyze multicenter data. We will develop a predictive model based on CT radiomic features and perform both internal and external cohort validation. The model will predict HIF-2α expression levels and clinically relevant prognostic factors in ccRCC, enabling precise identification of patient populations responsive to the HIF-2α antagonist Belzutifan, thereby facilitating personalized treatment decisions, minimizing unnecessary therapeutic risks, and ultimately improving patient quality of life and clinical outcomes.
- Status (registry)
- Active, not recruiting
- Study type
- Observational
- Enrollment
- 500 (estimated)
- First submitted
- 31 Dec 2025
- Start date
- 1 Aug 2024
- Primary completion date
- 1 Sept 2026
- Lead sponsor
- First Affiliated Hospital of Fujian Medical University
- Diseases
- Kidney cancer, Childhood cancers
- NCT number
- NCT07332923
What you commit to
- Study type: Observational
- Planned participants: 500
- From 1 Aug 2024 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
- Patients with concurrent malignancies, including prior treatment for other cancers or presence of untreated active malignancies
Other illness
- Patients considered ineligible for treatment owing to severe comorbid conditions or inability to undergo any therapeutic intervention
Other
- Patients with inadequate CT image quality or missing imaging data
- Patients with missing or incomplete clinical, pathological, or follow-up information
Who the study is looking for
- Pathologically confirmed clear cell renal cell carcinoma (ccRCC)
- Availability of comprehensive clinical, pathological, and follow-up information
- Access to preoperative non-contrast and contrast-enhanced CT images through the PACS database
- Adequately preserved pathological slides for subsequent immunohistochemical (IHC) or tissue microarray analysis
- Minimum of one post-treatment follow-up with documented treatment response or efficacy evaluation
Sex: All · Does not accept healthy volunteers
Sites (1)
Sites in registry order. Pick your city on the disease page to sort them by distance.
| Site | City | Country | Site status |
|---|---|---|---|
| first hospital affiliated of Fujian medical university Coordinator of this site? Confirm its status | Fuzhou | China | Unknown status |
This page is information, not medical advice. Discuss any trial with your doctor.