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NCT06253091Recruiting

Comparison of the Application of Robot-assisted Laparoscopic Pathways in Radical Cystectomy

Comparison of the Application of Robot-assisted Laparoscopic Transperitoneal and Transperitoneal Pathways in Radical Cystectomy
The First Affiliated Hospital with Nanjing Medical UniversityClinicalTrials.govprocedure
Verified
Study focus
Disease/Condition
Bladder Cancer
Drug/Device/Intervention
robit-assist extraperitoneal laparoscopic radical cystectomy
Study type
Interventional
Intervention type
procedure
Sponsor & location
Primary sponsor
The First Affiliated Hospital with Nanjing Medical University
Location
Nanjing, China
Timeline & enrollment
Phase
N/A
Start date
Feb 01, 2024
End date
Dec 30, 2025
Enrollment
50 participants
Primary outcome

Complication rate

Summary

Traditional radical cystectomy (RC) is performed transabdominal. However, it often has high
 postoperative complications. There have been studies on extraperitoneal approach to reduce
 postoperative complications. Investigators divided participants underwent robot-assisted
 radical cystectomy into two groups (1:1) . One group of participants transabdominal, the
 other group extraperitoneal. The incidence of complications and PFS/OS at 3, and 5 years were
 compared.

ICD-10 classifications
Malignant neoplasm of bladderMalignant neoplasm: Bladder, unspecifiedMalignant neoplasm: Dome of bladderMalignant neoplasm: Overlapping lesion of bladderMalignant neoplasm: Lateral wall of bladder
Data source
Registry
ClinicalTrials.gov
Trial ID
NCT06253091
Type
Non-Device Trial
About this record

Access comprehensive clinical trial information for NCT06253091 through Pure Global AI's free database. This phase not specified trial is sponsored by The First Affiliated Hospital with Nanjing Medical University and is currently Recruiting. The study focuses on Bladder Cancer. Target enrollment is 50 participants.

This page provides complete trial specifications, intervention details, outcomes, and location information. Pure Global AI offers free access to ClinicalTrials.gov data, helping medical device and pharmaceutical companies navigate clinical research efficiently.