Robot-assisted Surgery for Colorectal Cancer Resection: A Population-based Analysis of Prevalence, Trends and Outcomes

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 pot