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    Endometrial Cancer Individualized Scoring System (ECISS): A machine learning-based prediction model of endometrial cancer prognosis
    (Wiley, 2023) Shazly, Sherif A.; Coronado, Pluvio J.; Yilmaz, Ercan; Melekoglu, Rauf; Sahin, Hanifi; Giannella, Luca; Ciavattini, Andrea
    ObjectiveTo establish a prognostic model for endometrial cancer (EC) that individualizes a risk and management plan per patient and disease characteristics. MethodsA multicenter retrospective study conducted in nine European gynecologic cancer centers. Women with confirmed EC between January 2008 to December 2015 were included. Demographics, disease characteristics, management, and follow-up information were collected. Cancer-specific survival (CSS) and disease-free survival (DFS) at 3 and 5 years comprise the primary outcomes of the study. Machine learning algorithms were applied to patient and disease characteristics. Model I: pretreatment model. Calculated probability was added to management variables (model II: treatment model), and the second calculated probability was added to perioperative and postoperative variables (model III). ResultsOf 1150 women, 1144 were eligible for 3-year survival analysis and 860 for 5-year survival analysis. Model I, II, and III accuracies of prediction of 5-year CSS were 84.88%/85.47% (in train and test sets), 85.47%/84.88%, and 87.35%/86.05%, respectively. Model I predicted 3-year CSS at an accuracy of 91.34%/87.02%. Accuracies of models I, II, and III in predicting 5-year DFS were 74.63%/76.72%, 77.03%/76.72%, and 80.61%/77.78%, respectively. ConclusionThe Endometrial Cancer Individualized Scoring System (ECISS) is a novel machine learning tool assessing patient-specific survival probability with high accuracy.
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    Risk factors for cervical stromal involvement in endometrioid-type endometrial cancer
    (Wiley, 2021) Toprak, Serhat; Sahin, Eda Adeviye; Sahin, Hanifi; Tohma, Yusuf Aytac; Yilmaz, Ercan; Meydanli, Mehmet Mutlu
    ObjectiveThe aim of this study was to identify predictors of cervical stromal involvement in women with endometrioid-type endometrial cancer (EEC). MethodsA total of 795 patients with EEC who underwent comprehensive surgical staging including pelvic and para-aortic lymph node dissection between January 2007 and December 2018 were retrospectively analyzed. Data including age, menopausal status, serum CA-125 levels, tumor size, lymphovascular space invasion (LVSI), depth of myometrial invasion, positive peritoneal cytology, cervical stromal involvement, histologic grade, recurrence, and follow-up duration were recorded. ResultsMedian follow up was 49 months. Cervical stromal invasion was found in 88 patients. Multivariate analysis revealed that presence of LVSI (hazard ratio [HR] 2, 95% confidence interval [CI] 1.02-4.25, P = 0.045), a primary tumor diameter of at least 3 cm (HR 3, 95% CI 1.31-7.25, P = 0.010), and at least 50% deep myometrial invasion (HR 2.7, 95% CI 1.37-5.41, P = 0.004) were independent risk factors for cervical stromal involvement in patients with EEC. ConclusionOur study results suggest that presence of LVSI, a primary tumor diameter of at least 3 cm, and LVSI of at least 50% seem to be independent predictors of cervical involvement in women with EEC. Tumor diameter of >= 3 cm, and lymphovascular space invasion >= 50% seem to be independent predictors of cervical involvement in patients with endometrioid-type endometrial cancer.
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    YKL-40 and fibronectin levels in patients with placental invasion anomaly
    (2021) Soylu Karapinar, Oya; Sahin, Hanifi; Gozukara, Ilay; Adeviye Sahin, Eda; Ozcan, Oguzhan; Sezgin, Burak; Gungoren, Arif
    Aim: To investigate the level of YKL-40 and fibronectin in patients with total placenta previa and to evaluate the presence of placental invasion anomaly such as accreta. Materials and Methods: A total of 60 patients were included in this prospective study. The patients were classified according to the placental localization as assessed through ultrasound. The study group consisted of 33 patients diagnosed with placenta previa or accreta with previous cesarean section. These patients were also subdivided into two groups according to the histopathological examination results as invasion-positive group and invasion-negative group. The control group consisted of 27 patients who were admitted to the gynecology clinic with previous cesarean deliveries and had normal placental localization. Serum YKL-40 and fibronectin levels were measured in two groups via human chitinase-3-like protein 1 (Ykl-40/CHI3L1) and fibronectin enzyme-linked immunosorbent assay kits. Results: Mean serum levels for YKL-40 and fibronectin were similar between the study and control groups. In the subgroup analysis according to invasion anomaly, the level of YKL-40 in invasion-positive group (n=11) was higher than invasion-negative group (n=22), indicating a statistically significant difference. Conclusion: Outcomes of this research indicates that YKL-40 can be used as a marker for identifying placental invasion anomalies.