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EP407 Learning curve could affect the surgical outcome of radical hysterectomy in cervical cancer
  1. S Kim1,
  2. S Lee1,
  3. JY Song1,
  4. JW Shin2,
  5. JK Lee1 and
  6. NW Lee1
  1. 1Obstetrics and Gynecology, Korea University College of Medicine, Seoul
  2. 2Gachon University Gil Medical Center, Gachon University College of Medicine, Incheon, Republic of Korea


Introduction/Background Minimally invasive surgery has become essential technology in field of gynecologic malignancies including cervical cancer. We reviewed our experience and evaluated the results of radical hysterectomy in patients with early stage cervical cancer.

Methodology This retrospective study included patients with early stage cervical cancer (Ia1–IIa2) who were treated with radical hysterectomy from May 2006 to April 2018. Patients were divided into three groups according to the approach of surgery: open laparotomy (ARH), laparoscopic radical hysterectomy (LRH), and robotic-assisted radical hysterectomy (RRH). The type of hysterectomy included Piver type II and III hysterectomy. Learning curves of each type of surgery were obtained using cumulative sum (CUSUM) method. The survivals were compared using Kaplan-Meier curves.

Results Learning curves of each groups showed two distinct phases. The minimal cases required to achieve surgical improvement were 16 in ARH, 14 in LRH, and 15 in RRH. Progression-free survival and overall survival were not different between 3 groups (p=0.556 and p=0.273, respectively). But when the groups were stratified by the phases of the learning curves, the patients included in early phase showed poor PFS in RRH (p=0.043).

Conclusion The learning curve could significantly affect the oncologic outcome in robotic-assisted radical hysterectomy. Enough experience is necessary to improve surgical outcome in RRH. Further, a prospective randomized study regarding sufficient surgical competence is necessary for elaborate analysis of feasibility of minimally invasive radical hysterectomy.

Disclosure Nothing to disclose.

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