Cumulative summation graphs are a useful tool for monitoring positive surgical margin rates in robot‐assisted radical prostatectomy

摘要

Study Type – Therapy (case series) Level of Evidence 4 What’s known on the subject? and What does the study add? Whilst the technique of robot‐assisted radical prostatectomy has rapidly been adopted by surgeons there is little information on techniques used for quality control when a surgeon is learning this new surgical technique. Cummulative summation graphs have been used in cardiothoracic surgery to monitor complications with good effect and have been shown to be useful in monitoring outcomes from cystectomy. We demonstrate that using the technique of cumulative summation graphs a surgeon can monitor their progress prospectively through a learning curve without having to wait to perform a retrospective analysis. This study demonstrates that margin positive rates in radical prostatectomy can be monitored in real time and adjustments in technique applied to allow a surgeon to continually monitor and improve their surgical results. OBJECTIVE • To explore the usefulness of cumulative summation (CUSUM) graphs for monitoring positive surgical margin (PSM) rates during a surgeon’s transition from open to robot‐assisted radical prostatectomy (RARP). PATIENTS AND METHODS • Data were prospectively collected from patients undergoing RARP by a single surgeon. • Preoperatively all patients were either low or moderate risk under the D’Amico classification system. • A CUSUM graph was charted retrospectively to analyse the PSM rate in patients undergoing RARP for pathological stage T2 (pT2) disease. • Acceptable and unacceptable PSM rates were set at 10% and 15% respectively. RESULTS • From a cohort of 226 patients, 158 patients with pT2 disease were selected. The mean (range) age of these patients was 59.2 (39–73) years, the median (range) Gleason score was 6 (4–9), the mean (range) PSA was 6.43 (0.52–17.5) ng/mL and the mean (range) prostate volume was 44 (18–120) cm 3 . In all, 21 patients had PSMs (13%). • CUSUM graphs were produced and clearly demonstrated the change in PSM rate over time. CONCLUSION • CUSUM graphs are a novel and useful visual representation of the learning curve for surgeons. • PSM rates in patients with pT2 disease are a good outcome to monitor using CUSUM graphs as they are binary and lack the confounding factors associated with other outcomes such as continence and erectile dysfunction. • We advocate the use of CUSUM graphs as a method of quality assurance with the introduction of a robotics programme.