The learning curve of da Vinci robot-assisted pulmonary lobectomy by using cumulative sum analysis

Objective This study aims to investigate the learning curve of da Vinci robot-assisted pulmonary lobectomy. Methods A cumulative sum analysis (CUSUM) was performed on the operation time (OT) of the 1st to the 109th patients who underwent da Vinci robot-assisted pulmonary lobectomy from Mar. 2012 to Feb. 2015 in our hospital. A multivariate linear regression was performed, in order to exclude the bias factors on OT. The CUSUM learning curve was modeled by curve fitting and R2 was used to testify the goodness. The different phases of the learing curve was compared on OT, estimated blood loss (EBL), lymph nodes dissecting, complications, drainage time and hospital stay. Results The OT decreased with the accumulation of cases. The CUSUM learning curve was best modeled as a cubic curve with the equation: CUSUM(n)=0.002×n3-0.323×n2+ 13.360×n-18.195, which had a higher R2 value of 0.847. The fitting curve reached the top at the 28th case. As a cut-off point, the 28th case di Vided the learning curve into two phases. There were statistical differences in OT (P=0.022), EBL (P=0.014), numbers of lymph nodes dissected (P=0.022), complications (P=0.015), drainage time (P=0.025) and hospital stay (P=0.005). Conclusions The learning curve of da Vinci robot-assisted pulmonary lobectomy can be defined by CUSUM analysis, which suggested from our data that the surgeons need finish about 28 cases to master the technique. Key words: Robot-assisted pulmonary lobectomy; CUSUM analysis; Learning curve; Multivariate linear regression