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

Mingzhao Xiao800 enrolled

Overview

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 Type

OBSERVATIONAL

Enrollment

800

Conditions

Clear Cell Renal Cell Carcinoma Prognostic Cancer Model Recurrent Renal Cell Cancer

Eligibility

Sex: ALL

Medical Language ↔ Plain English

Inclusion Criteria: * underwent partial/radical nephrectomies * histologically diagnosed as ccRCC * with complete clinical data and preoperative CT image data Exclusion Criteria: * 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

Locations (1)

Outcomes

Primary Outcomes

disease-free survival (DFS)

the interval from the date of surgery to disease recurrence, all-cause mortality or the last visit

Time frame: recruitment occurred between June 2013 and March 2020