Contrast-enhanced CT-based Deep Learning Model for Preoperative Prediction of Disease-free Survival (DFS) in Localized Clear Cell Renal Cell Carcinoma (ccRCC)
Urology Department of the First Affiliated Hospital of Chongqing Medical University
1 other identifier
observational
800
1 country
1
Brief 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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Sep 2022
Typical duration for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
September 1, 2022
CompletedFirst Submitted
Initial submission to the registry
October 12, 2023
CompletedFirst Posted
Study publicly available on registry
October 18, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
June 1, 2025
CompletedStudy Completion
Last participant's last visit for all outcomes
August 1, 2025
CompletedMay 31, 2025
May 1, 2025
2.8 years
October 12, 2023
May 27, 2025
Conditions
Outcome Measures
Primary Outcomes (1)
disease-free survival (DFS)
the interval from the date of surgery to disease recurrence, all-cause mortality or the last visit
recruitment occurred between June 2013 and March 2020
Study Arms (2)
Non-recurrence group
Recurrence group
Eligibility Criteria
Patients admitted to urology departments at participating medical centres
You may qualify if:
- underwent partial/radical nephrectomies
- histologically diagnosed as ccRCC
- with complete clinical data and preoperative CT image data
You may not qualify if:
- 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
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Mingzhao Xiaolead
Study Sites (1)
Yingjie Xv
Chongqing, Chongqing Municipality, 400016, China
Related Publications (1)
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.
PMID: 38896853DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- RETROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR INVESTIGATOR
- PI Title
- Urology Department
Study Record Dates
First Submitted
October 12, 2023
First Posted
October 18, 2023
Study Start
September 1, 2022
Primary Completion
June 1, 2025
Study Completion
August 1, 2025
Last Updated
May 31, 2025
Record last verified: 2025-05
Data Sharing
- IPD Sharing
- Will not share