Selen Bozkurt1,2, Tayfun Toptas3, Hulya Ayik Aydin4, Tayup Simsek4, Yasemin Yavuz5. 1. Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA. 2. Department of Biostatistics and Medical Informatics, Akdeniz University School of Medicine, Antalya, Turkey. 3. Department of Gynecologic Oncology, Saglik Bilimleri University Antalya Research and Training Hospital, C-Blok, K:2, 07100, Antalya, Turkey. drttoptas@gmail.com. 4. Department of Gynecologic Oncology, Akdeniz University School of Medicine, Antalya, Turkey. 5. Department of Biostatistics, Ankara University School of Medicine, Ankara, Turkey.
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.
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.