Robot-assisted laparoscopy versus laparotomy for infrarenal paraaortic lymphadenectomy in women with high-risk endometrial cancer: A randomised controlled trial

Purpose: To investigate if robot-assisted laparoscopic surgery (RALS) was non-inferior to laparotomy (LT) in harvesting infrarenal paraaortic lymph nodes in patients with presumed stage IeII high-risk endometrial cancer. Patients and methods: Patients with histologically proven endometrial cancer, presumed stage IeII with high-risk tumour features, were randomised to hysterectomy, bilateral salpingo-oophorectomy, pelvic and paraaortic lymphadenectomy by either RALS or LT. Primary outcome was paraaortic lymph node count. Secondary outcomes were perioperative events, postoperative complications and total health care cost. Results: Overall 120 patients were randomised and 96 patients were included in the per protocol analysis. Demographic, clinical and tumour characteristics were evenly distributed between groups. Mean (+/- SD) paraaortic lymph node count was 20.9 (+/- 9.6) for RALS and 22 (+/- 11, p = 0.45) for LT. The difference of means was within the non-inferiority margin (-1.6, 95% CI -5.78, 2.57). Mean pelvic node count was lower after RALS (28 +/- 10 versus 22 +/- 8, p < 0.001). There was no difference in perioperative complications or readmissions between the groups. Operation time was longer (p < 0.001) but total blood loss less (<0.001) and hospital stay shorter (<0.001) in RALS group than LT group. Health care costs for RALS was significantly lower (mean difference $1568 USD/(sic)1225 Euro, p < 0.05). Conclusion: Our results demonstrate non-inferiority in paraaortic lymph node count, comparable complication rates, shorter hospital length and lower total cost for RALS over laparotomy. Generalisability of the latter finding requires a high-volume setting and high surgical proficiency. In women with high-risk endometrial cancer confined to the uterus, RALS is a valid treatment modality. Clinical trials registrations: ClinicalTrials.gov NCT01847703. (C) 2017 Elsevier Ltd. All rights reserved.