You are here

  • Home
  • Archive
  • Volume 33, Issue Suppl 4
  • EP138/#520  Prediction of final pathology depending on preoperative myometrial invasion and grade assessment in low risk endometrial cancer patients: a Korean gynecologic oncology group ancillary study

Article Text

Article menu

Download PDFPDF

ePoster Viewing
AS04. Endometrial/Uterine corpus cancers
EP138/#520  Prediction of final pathology depending on preoperative myometrial invasion and grade assessment in low risk endometrial cancer patients: a Korean gynecologic oncology group ancillary study
Free
  1. Bang-Hyun Lee1,
  2. Sokbom Kang2,
  3. Jong-Hyeok Kim3,
  4. Byoung Gie Kim4,
  5. Jae-Weon Kim5,
  6. Moon-Hong Kim6,
  7. Xiaojun Chen7,
  8. Jae-Hong No8,
  9. Jong-Min Lee9,
  10. Jae-Hoon Kim10,
  11. Hidemichi Watari11,
  12. Seok Mo Kim12,
  13. Sunghoon Kim10,
  14. Seok Ju Seong13,
  15. Dae Hoon Jeong14 and
  16. Yun Hwan Kim15
  1. 1Inha University hospital, Inha University School of Medicine, Obstetrics and Gynecology, Incheon, Korea, Republic of
  2. 2National Cancer Center, Gynecologic Oncology Research Branch, Research Institute and Hospital, Goyang, Korea, Republic of
  3. 3University of Ulsan College of Medicine, Asan Medical Center, Department of Obstetrics and Gynecology, seoul, Korea, Republic of
  4. 4Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea, Republic of
  5. 5Seoul National University, Obstetrics and Gynecology, Seoul, Korea, Republic of
  6. 6Korea Cancer Center Hospital, Korea Institute of Radiological and Medical Sciences, Department of Obstetrics and Gynecology, seoul, Korea, Republic of
  7. 7Obstetrics and Gynecology Hospital of Fudan University, Gynecology, Shanghai, China
  8. 8Seoul National University Bundang Hospital, Department of Obstetrics and Gynecology, Seongnam, Korea, Republic of
  9. 9College of Medicine, Kyung Hee University Hospital at Gangdong Kyung Hee University, Department of Obstetrics and Gynecology, seoul, Korea, Republic of
  10. 10Institute of Women’s Life Medical Science, Yonsei University College of Medicine, Department of Obstetrics and Gynecology, Seoul, Korea, Republic of
  11. 11Hokkaido University Hospital, Gynecology, Sapporo, Japan
  12. 12Chonnam National University Medical School, Department of Obstetrics and Gynecology, Gwangju, Korea, Republic of
  13. 13CHA Gangnam Medical Center, CHA University School of Medicine, Department of Obstetrics and Gynecology, Seoul, Korea, Republic of
  14. 14Busan Paik Hospital, College of Medicine, Inje University, Department of Obstetrics and Gynecology, Busan, Korea, Republic of
  15. 15Ewha Womans University Mokdong Hospital, Ewha Womans University College of Medicine, Department of Obstetrics and Gynecology, seoul, Korea, Republic of

Abstract

Introduction Fertility-sparing treatment might be considered option for reproductive women with low risk endometrial cancer (EC). However, in low risk EC patients, concordance rates between preoperative assessment and postoperative pathology are not high enough. We aimed to predict postoperative pathology depending on preoperative myometrial invasion (MI) and grade in low risk EC patients to help extend current criteria for fertility-sparing treatment.

Methods In Korean Gynecologic Oncology Group (KGOG) 2015, a prospective, multicenter study, 529 EC patients underwent preoperative assessment using MRI and endometrial biopsy followed by surgical staging. This ancillary study included patients who had no MI or MI <1/2 on preoperative MRI and endometrioid adenocarcinoma and grade 1 or 2 on endometrial biopsy. Among eligible patients, Groups 1 - 4 were defined with no MI and grade 1, no MI and grade 2, MI <1/2 and grade 1, and MI <1/2 and grade 2, respectively. New prediction model using machine learning was developed.

Results Among 251 eligible patients, Groups 1 - 4 included 106 (42.2%) patients, 41 (16.3%), 74 (29.5%), and 30 (12.0%), respectively. Compared with conventional analysis, new prediction model showed somewhat better prediction values. In new prediction model, NPV, sensitivity, and AUC of preoperative each group to predict postoperative each group were 88.9%, 77.6%, and 0.714 for Group 1, 97.1%, 64.3%, and 0.676 for Group 2, 77.5%, 76.5%, and 0.641 for Group 3, and 92.4%, 64.9%, and 0.691% for Group 4.

Conclusion/Implications In low risk EC patients, prediction of postoperative pathology was ineffective enough. New prediction model might provide better prediction.

https://doi.org/10.1136/ijgc-2023-IGCS.234

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.