Clear Cell Renal Cell CarcinomaNCT06088134
Contrast-enhanced CT-based Deep Learning Model for Preoperative Prediction of Disease-free Survival (DFS) in Localized Clear Cell Renal Cell Carcinoma (ccRCC)
An observational study of Clear Cell Renal Cell Carcinoma and Prognostic Cancer Model, run by Mingzhao Xiao at 1 site in China.
Trial summary
This study aims to preoperatively predict DFS of patients with localised ccRCC using a deep learning prognostic model based on enhanced contrast CT images, validate it's predictive ability in multicentre data and compare it's predictive ability with traditional models. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Clear Cell Renal Cell Carcinoma, Prognostic Cancer Model, Recurrent Renal Cell Cancer
- How many people
- 800 participants
- Where
- 1 siteChina
- Study dates
- 1 Sep 2022to 1 Aug 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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: Patients admitted to urology departments at participating medical centres
Who may be able to join
- underwent partial/radical nephrectomies
- histologically diagnosed as ccRCC
- with complete clinical data and preoperative CT image data
Who cannot join
- with incomplete clinic-pathological data
- lack of preoperative contrast-enhanced CT images or the image quality was unsuitable for analysis
- who received pre-surgery neoadjuvant or adjuvant therapies
- with multiple renal tumors or/and had synchronous metastasis
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
Yingjie Xv
Chongqing, Chongqing Municipality, 400016
Yingjie Xv, 83-18725891425, xvyingjiecq@qq.com
About this study
Official title: Urology Department of the First Affiliated Hospital of Chongqing Medical University
This study aims to preoperatively predict DFS of patients with localised ccRCC using a deep learning prognostic model based on enhanced contrast CT images, validate it's predictive ability in multicentre data and compare it's predictive ability with traditional models.
- Medical subject headings
- Carcinoma, Renal Cell
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 |
|---|---|---|
| Non-recurrence group | Not described | |
| Recurrence group | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
disease-free survival (DFS)
the interval from the date of surgery to disease recurrence, all-cause mortality or the last visit
Measured: recruitment occurred between June 2013 and March 2020
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted18 Oct 2023
- Study start1 Sep 2022
- Primary completion1 Jun 2025 (estimated)
- Study completion1 Aug 2025 (estimated)
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 Clear Cell Renal Cell CarcinomaStudies 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
- 800 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Mingzhao Xiao
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Mingzhao Xiao, First Affiliated Hospital of Chongqing Medical University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06088134
- Sponsor's protocol ID
- DL-ccRCC
- Status last verified
- May 2025
- First submitted
- 12 Oct 2023
- Last updated
- 31 May 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Xv Y, Wei Z, Jiang Q, Zhang X, Chen Y, Xiao B, Yin S, Xia Z, Qiu M, Li Y, Tan H, Xiao M. Three-dimensional deep learning model complements existing models for preoperative disease-free survival prediction in localized clear cell renal cell carcinoma: a multicenter retrospective cohort study. Int J Surg. 2024 Nov 1;110(11):7034-7046. doi: 10.1097/JS9.0000000000001808.
PubMed 38896853
Study at a glance
From the registry record, last updated by the sponsor on 31 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Urology Department of the First Affiliated Hospital of Chongqing Medical University
- ClinicalTrials.gov ID
- NCT06088134
- Acronym / sponsor ID
- DL-ccRCC
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 800 participants (estimated)
- Lead sponsor
- Mingzhao XiaoUniversity, hospital or other
- Study start
- 1 Sep 2022 (actual)
- Primary completion
- 1 Jun 2025 (estimated)
- Study completion
- 1 Aug 2025 (estimated)
- First posted
- 18 Oct 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 study aims to preoperatively predict DFS of patients with localised ccRCC using a deep learning prognostic model based on enhanced contrast CT images, validate it's predictive ability in multicentre data and compare it's predictive ability with traditional models.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Non-recurrence group | – | – |
| Recurrence group | – | – |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Patients admitted to urology departments at participating medical centres
Key inclusion criteria (3 listed)
- underwent partial/radical nephrectomies
- histologically diagnosed as ccRCC
- with complete clinical data and preoperative CT image data
Key exclusion criteria (4 listed)
- with incomplete clinic-pathological data
- lack of preoperative contrast-enhanced CT images or the image quality was unsuitable for analysis
- who received pre-surgery neoadjuvant or adjuvant therapies
- with multiple renal tumors or/and had synchronous metastasis
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
disease-free survival (DFS)
Time frame: recruitment occurred between June 2013 and March 2020
the interval from the date of surgery to disease recurrence, all-cause mortality or the last visit
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 31 May 2025.
- Derived from this study: PubMed 38896853Xv Y, Wei Z, Jiang Q, Zhang X, Chen Y, Xiao B, Yin S, Xia Z, Qiu M, Li Y, Tan H, Xiao M. Three-dimensional deep learning model complements existing models for preoperative disease-free survival prediction in localized clear cell renal cell carcinoma: a multicenter retrospective cohort study. Int J Surg. 2024 Nov 1;110(11):7034-7046. doi: 10.1097/JS9.0000000000001808.
- 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.
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 Clear Cell Renal Cell Carcinoma and Prognostic Cancer Model, run by Mingzhao Xiao 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 3 inclusion and 4 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: looking for participants now, as of the sponsor's last update on 31 May 2025. 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?
This study is still under way. Results are not available in the source record yet.
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?
disease-free survival (DFS) (time frame: recruitment occurred between June 2013 and March 2020). 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 NCT06088134, 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 31 May 2025.