NCT06959849

Brief Summary

The objective of this research project is to conduct a comparative analysis of short- and long-term outcomes between conventional laparoscopic and robot-assisted resection procedures for colorectal cancer. The analysis will utilize population-based DRG data and clinical cancer registry data from Germany. The rationale behind this project is that the number of conversions to open surgery in robotic procedures is approximately half that observed in laparoscopic procedures. Furthermore, it has been demonstrated that conversions are associated with a markedly elevated risk of postoperative complications. The aim of this project is to estimate the number of avoidable adverse outcomes resulting from the use of robot-assisted surgery. Multiple studies have shown, that the conversion rate for robot-assisted surgery (RAS) is consistently lower than that for conventional laparoscopic (LAP) surgery. Additionally, conversions have been reported to be associated with an increased risk of adverse surgical outcomes. However, most studies have not achieved statistical significance, due to limited sample sizes and insufficient statistical power. A comprehensive review of the existing literature reveals three key findings. First, the conversion rate for RAS procedures is approximately half that of LAP procedures. Second, conversions are associated with a significantly higher incidence of adverse short-term outcomes, including increased morbidity and mortality, as well as prolonged hospitalization. Third, although not significant due to low case numbers, there is some evidence suggesting improved long-term survival with RAS. The hypothesis is that the lower conversion rate in RAS for colorectal surgery is associated with fewer adverse outcomes compared to LAP procedures. This study aims to estimate the number of short-term adverse outcomes that could be prevented through avoided conversions when surgeries are performed using RAS rather than LAP. Furthermore, it will estimate the potential life years saved due to improved survival resulting from fewer conversions. To analyze avoidable short-term adverse outcomes, Germany's nationwide diagnosis-related group (DRG) data for the years 2016-2023 will be used. Multiple logistic regression analyses will be conducted, and estimated marginal means will be computed to provide population-based estimates. To estimate potential life years saved, clinical cancer registry data will be analyzed using Cox proportional hazards regression models. Long-term survival curves (three-year overall and disease-free survival) will be computed and compared between RAS and LAP surgeries, with a focus on converted operations. The quality of surgical outcomes (perioperative and short-term postoperative outcomes) for RAS and LAP colorectal surgery will compared using DRG data. This study will analyze the factors that moderate the difference in conversion rates and their relationship to outcome quality. Inclusion criteria will comprise patients who underwent elective resection for a primary malignant colorectal neoplasm. The study further aims to compare long-term overall survival (OS) and disease-free survival (DFS) between RAS and laparoscopic surgery using clinical cancer registry data. This project represents the first comprehensive analysis in Germany of the use of robotic assistance systems in colorectal surgery based on routine data. A key objective is to assess the prevalence of robotic assistance systems in clinical practice and to estimate the number of conversions-and corresponding adverse outcomes-that could be avoided through their use.

Trial Health

53
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Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
128,000

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started Jan 2016

Longer than P75 for all trials

Status
active not recruiting

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

January 1, 2016

Completed
8 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

December 31, 2023

Completed
1.3 years until next milestone

First Submitted

Initial submission to the registry

April 24, 2025

Completed
13 days until next milestone

First Posted

Study publicly available on registry

May 7, 2025

Completed
10 months until next milestone

Study Completion

Last participant's last visit for all outcomes

February 28, 2026

Completed
Last Updated

September 5, 2025

Status Verified

May 1, 2025

Enrollment Period

8 years

First QC Date

April 24, 2025

Last Update Submit

August 29, 2025

Conditions

Keywords

Resection for colorectal cancerrobot-assisted surgeryclinical outcome research

Outcome Measures

Primary Outcomes (4)

  • Proportion of procedures performed with robotic assistance systems

    Change in the proportion of surgical resection procedures across time, stratified by procedure type and indication at the patient level (Study-Part I)

    During surgery (intraoperative)

  • Conversion rate

    Rate of conversions to open surgery for laparoscopic procedures and robot-assisted procedures (Study-Part II)

    During surgery (intraoperative)

  • Mortality rate

    Proportion of patients that died after surgical intervention (Study-Part II)

    30 days

  • 3-year overall survival rates

    Death from any cause within three years after the operation (Study-Part III)

    3 years after index operation

Secondary Outcomes (6)

  • Patient characteristics

    At the beginning of the index operation

  • Length-of-stay

    From the day of the index operation to hospital discharge (up to 90 days post-operation, on average)

  • Postoperative complications

    30 days postoperatively

  • Revision surgery

    30 days postoperatively

  • Stay in intensive care unit

    30 days postoperatively

  • +1 more secondary outcomes

Other Outcomes (2)

  • Number of hospitals using robot-assistance systems

    During surgery (intraoperative)

  • Characteristics of hospitals which use robot-assistance systems

    During surgery (intraoperative)

Study Arms (4)

Surgery performed and completed laparoscopically (LF)

Surgery started laparoscopically with conversion (LC)

Surgery performed and completed robotically (RF)

Device: Use of robot surgical system

Surgery started robotically with conversion (RC)

Device: Use of robot surgical system

Interventions

Surgery performed and completed robotically (RF)Surgery started robotically with conversion (RC)

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

Population-based analysis for all hospitalised patients in Germany (Study-Part I and II); Population-based analysis for all hospitalised patients in the German Federal States of Brandenburg and Berlin (Study-Part III)

You may qualify if:

  • malignant neoplasm of the colon or rectum (ICD-10: C18 - C20)
  • surgical resection for cancer

You may not qualify if:

  • emergent procedures

Contact the study team to confirm eligibility.

Sponsors & Collaborators

MeSH Terms

Conditions

Colorectal Neoplasms

Condition Hierarchy (Ancestors)

Intestinal NeoplasmsGastrointestinal NeoplasmsDigestive System NeoplasmsNeoplasms by SiteNeoplasmsDigestive System DiseasesGastrointestinal DiseasesColonic DiseasesIntestinal DiseasesRectal Diseases

Study Design

Study Type
observational
Observational Model
CASE CONTROL
Time Perspective
RETROSPECTIVE
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Head of General Surgery

Study Record Dates

First Submitted

April 24, 2025

First Posted

May 7, 2025

Study Start

January 1, 2016

Primary Completion

December 31, 2023

Study Completion

February 28, 2026

Last Updated

September 5, 2025

Record last verified: 2025-05

Data Sharing

IPD Sharing
Will not share

The dissemination of Diagnosis-Related Group (DRG) statistics is not a viable option due to the centralised management of such data by the Federal Statistical Office of Germany, which restricts accessibility and analysis to remote mechanisms. The dissemination of data from the cancer registry is strictly prohibited by law.