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Archives of Gynecology and Obstetrics

, Volume 300, Issue 3, pp 693–701 | Cite as

A nomogram for decision-making of completion surgery in endometrial cancer diagnosed after hysterectomy

  • Selen Bozkurt
  • Tayfun ToptasEmail author
  • Hulya Ayik Aydin
  • Tayup Simsek
  • Yasemin Yavuz
Gynecologic Oncology
  • 22 Downloads

Abstract

Objective

Extrauterine tumor spread is one of the essential determinants of disease outcome in endometrial cancer. However; more than 30% of patients still undergo incomplete surgery at the initial attempt. Strategies regarding the management of patients with incompletely staged early-stage disease or patients with undebulked advanced-stage disease remain controversial. Depending on postoperative uterine features and findings on imaging, patients may be put on observation or receive adjuvant therapy or undergo re-staging or debulking surgery followed by adjuvant therapy. To identify patients who would most benefit from a completion surgery, either for restaging or for cytoreduction, we developed a nomogram for estimation of extrauterine disease based on findings of final hysterectomy specimen.

Methods

Data of 336 patients whose extrauterine disease status was known were analyzed. A nomogram was constructed using patient characteristics including age, grade, myometrial invasion, lymphovascular space involvement, cervical involvement, and peritoneal cytology. The nomogram was internally validated in terms of discrimination, calibration and overall performance.

Results

The nomogram showed good performance accuracy with an area under the receiver operating characteristic curve of 0.870, a specificity of 95.5%, and a positive predictive value of 73.9%. Decision curve analysis revealed that the use of the nomogram in decision-making for completion surgery leads to the equivalent of a net 18 true-positive results per 100 patients without an increase in the number of false-positive results.

Conclusions

Estimation of extrauterine disease from final hysterectomy specimen is possible with high predictive performance using the nomogram developed. The nomogram may help clinicians in decision-making for management of incomplete surgeries.

Keywords

Endometrial cancer Completion surgery Nomogram Decision analysis Extrauterine disease 

Notes

Acknowledgements

This study was funded by Akdeniz University Research Foundation, Antalya, Turkey (Grant number: TSA-2017–2712). The abstract of this work was presented in the 20th International Meeting of the European Society of Gynaecological Oncology (ESGO 2017), 04–07 November 2017, Vienna, Austria.

Author contributions

SB: protocol/project development, data collection or management, data analysis, manuscript writing. TT: protocol/project development, data collection or management, data analysis, manuscript writing. HAA: data collection or management, manuscript editing. TS: manuscript editing, supervision. YY: protocol/project development, methodology, manuscript editing.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest and nothing to disclose.

Ethical approval

This study has been approved by the Ethics Committee of the Akdeniz University School of Medicine. This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Informed consent of patients was not obtained due to the nature of study and the obtained data.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Biomedical Data ScienceStanford University School of MedicineStanfordUSA
  2. 2.Department of Biostatistics and Medical InformaticsAkdeniz University School of MedicineAntalyaTurkey
  3. 3.Department of Gynecologic OncologySaglik Bilimleri University Antalya Research and Training HospitalAntalyaTurkey
  4. 4.Department of Gynecologic OncologyAkdeniz University School of MedicineAntalyaTurkey
  5. 5.Department of BiostatisticsAnkara University School of MedicineAnkaraTurkey

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