Contrast-enhanced CT-based Deep Learning Model for Preoperative Prediction of Disease-free Survival (DFS) in Localized Clear Cell Renal Cell Carcinoma (ccRCC)

Sponsor

Mingzhao Xiao (Other)

Overall Status

Recruiting

CT.gov ID

NCT06088134

Collaborator

(none)

800

Enrollment

Location

Anticipated Duration (Months)

38.1

Patients Per Site Per Month

Study Details

Study Description

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.

Condition or Disease	Intervention/Treatment	Phase
Predictive Ability of Contrast-enhanced CT-based Deep Learning Model in Patients With Localised ccRCC Generalisation of a Deep Learning Prediction Model in Multicentre Data Comparison of Prediction Performance Between Deep Learning Prediction Model and Traditional Prediction Models

Study Design

Study Type:

Observational

Anticipated Enrollment :

800 participants

Observational Model:

Cohort

Time Perspective:

Retrospective

Official Title:

Urology Department of the First Affiliated Hospital of Chongqing Medical University

Actual Study Start Date :

Sep 1, 2022

Anticipated Primary Completion Date :

Dec 25, 2023

Anticipated Study Completion Date :

Jun 1, 2024

Arms and Interventions

Arm	Intervention/Treatment
Non-recurrence group
Recurrence group

Outcome Measures

Primary Outcome Measures

disease-free survival (DFS) [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

Eligibility Criteria

Criteria

Ages Eligible for Study:

N/A and Older

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

Inclusion Criteria:

Patients who underwent partial/radical nephrectomies and histologically diagnosed as ccRCC

Exclusion Criteria:

(1) with incomplete clinic-pathological data; (2) lack of preoperative contrast-enhanced CT images or the image quality was unsuitable for analysis; (3) who received pre-surgery neoadjuvant or adjuvant therapies; (4) with multiple renal tumors or/and had synchronous metastasis

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Yingjie Xv	Chongqing	Chongqing	China	400016

Sponsors and Collaborators

Mingzhao Xiao

Investigators

None specified.

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

Responsible Party:

Mingzhao Xiao, Urology Department, First Affiliated Hospital of Chongqing Medical University

ClinicalTrials.gov Identifier:

NCT06088134

Other Study ID Numbers:

DL-ccRCC

First Posted:

Oct 18, 2023

Last Update Posted:

Oct 18, 2023

Last Verified:

Oct 1, 2023

Individual Participant Data (IPD) Sharing Statement:

Plan to Share IPD:

Studies a U.S. FDA-regulated Drug Product:

Studies a U.S. FDA-regulated Device Product:

Study Results

No Results Posted as of Oct 18, 2023