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Int J Gynecol Cancer. 2014 Oct;24(8):1493-8. doi: 10.1097/IGC.0000000000000224.

The safety and feasibility of robotic-assisted lymph node staging in early-stage ovarian cancer.

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*Gynecologic Oncology Associates, Hoag Memorial Hospital Cancer Center; and †The Nancy Yeary Women's Cancer Research Foundation, Newport Beach, CA.



The purpose of this study was to report on the safety and feasibility of robotic-assisted systematic lymph node staging in the management of early-stage ovarian cancer.


We retrospectively reviewed the charts of presumed early-stage (International Federation of Gynecology and Obstetrics (FIGO) stages I and II) ovarian cancer patients who underwent robotic-assisted surgery that incorporated a systematic pelvic and para-aortic lymphadenectomy from January 2009 until December 2013. Patient demographics, operative characteristics, pathology, lymph node counts, surgical complications, and hospital stay were evaluated.


A total of 26 early-stage ovarian cancer patients were identified. The mean operating time was 2.90 hours, and the estimated blood loss was 63 mL; there were no intraoperative complications although 1 patient's surgery was significantly prolonged due to pelvic adhesions. The mean number of pelvic and para-aortic lymph nodes removed was 14.6 (2.3% incidence of pelvic lymph node metastases) and 5.8 (3.3% incidence of para-aortic lymph node metastases), respectively. The patients' mean duration of hospital stay was 18.4 hours, and 2 patients were readmitted for either a postoperative wound infection or vaginal dehiscence.


The results from this study suggest that robotic-assisted surgical staging in the management of presumed early-stage ovarian cancer is both feasible and associated with a minimal patient complication rate. We encountered a low incidence of lymph node metastases, and the readmission rate was favorable. Nevertheless, because the prevalence of lymph node metastases can approach 20% in select patients, physicians should consider a systematic lymph node resection to confer an optimal clinical assessment.

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