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A Web-Based Nomogram Predicting Para-aortic Nodal Metastasis in Incompletely Staged Patients With Endometrial Cancer: A Korean Multicenter Study
  1. Sokbom Kang, MD, PhD*,
  2. Jong-Min Lee, MD, PhD,
  3. Jae-Kwan Lee, MD, PhD,
  4. Jae-Weon Kim, MD, PhD§,
  5. Chi-Heum Cho, MD, PhD,
  6. Seok-Mo Kim, MD, PhD,
  7. Sang-Yoon Park, MD, PhD*,
  8. Chan-Yong Park, MD, PhD# and
  9. Ki-Tae Kim, MD, PhD**
  1. *Center for Uterine Cancer, National Cancer Center, Goyang;
  2. Department of Obstetrics and Gynecology, School of Medicine, Kyung Hee University;
  3. Department of Obstetrics and Gynecology, Korea University College of Medicine;
  4. §Department of Obstetrics and Gynecology, Cancer Research Institute, College of Medicine, Seoul National University, Seoul;
  5. Department of Obstetrics and Gynecology, Dongsan Medical Center, Keimyung University, Daegu;
  6. Department of Obstetrics and Gynecology, Chonnam National University, Gwangju;
  7. #Department of Obstetrics and Gynecology, Gachon University Hospital, Incheon; and
  8. **Department of Obstetrics and Gynecology, Busan Paik Hospital, Inje University, Busan, South Korea.
  1. Address correspondence and reprint requests to Sokbom Kang, MD, PhD, Center for Uterine Cancer, National Cancer Center, Ilsan-gu Ilsan-ro 326, Goyang, 410-769, South Korea. E-mail: sokbom{at}


Objective The purpose of this study is to develop a Web-based nomogram for predicting the individualized risk of para-aortic nodal metastasis in incompletely staged patients with endometrial cancer.

Methods From 8 institutions, the medical records of 397 patients who underwent pelvic and para-aortic lymphadenectomy as a surgical staging procedure were retrospectively reviewed. A multivariate logistic regression model was created and internally validated by rigorous bootstrap resampling methods. Finally, the model was transformed into a user-friendly Web-based nomogram (

Results The rate of para-aortic nodal metastasis was 14.4% (57/397 patients). Using a stepwise variable selection, 4 variables including deep myometrial invasion, non–endometrioid subtype, lymphovascular space invasion, and log-transformed CA-125 levels were finally adopted. After 1000 repetitions of bootstrapping, all of these 4 variables retained a significant association with para-aortic nodal metastasis in the multivariate analysis—deep myometrial invasion (P = 0.001), non–endometrioid histologic subtype (P = 0.034), lymphovascular space invasion (P = 0.003), and log-transformed serum CA-125 levels (P = 0.004). The model showed good discrimination (C statistics = 0.87; 95% confidence interval, 0.82–0.92) and accurate calibration (Hosmer-Lemeshow P = 0.74).

Conclusions This nomogram showed good performance in predicting para-aortic metastasis in patients with endometrial cancer. The tool may be useful in determining the extent of lymphadenectomy after incomplete surgery.

  • Endometrial cancer
  • Lymph node
  • Lymphadenectomy
  • Metastasis
  • Para-aortic
  • Staging

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  • This study was funded by the National Cancer Center in Korea (grant number 1210200).

  • The authors declare no conflicts of interest.