Background and Objectives: Ovarian cancer surgery requires multiple radical resections with a high risk of complications. The aim of this single-centre, retrospective study was to determine the best method for predicting Clavien–Dindo grade ≥ III complications using machine learning techniques. Material and Methods: The study included 179 patients who underwent surgery at the gynaecological oncology department of Antalya Training and Research Hospital between January 2015 and December 2020. The data were randomly split into training set n = 134 (75%) and test set n = 45 (25%). We used 49 predictors to develop the best algorithm. Mean absolute error, root mean squared error, correlation coefficients, Mathew’s correlation coefficient, and F1 score were used to determine the best performing algorithm. Cohens’ kappa value was evaluated to analyse the consistency of the model with real data. The relationship between these predicted values and the actual values were then summarised using a confusion matrix. True positive (TP) rate, False positive (FP) rate, precision, recall, and Area under the curve (AUC) values were evaluated to demonstrate clinical usability and classification skills. Results: 139 patients (77.65%) had no morbidity or grade I-II CDC morbidity, while 40 patients (22.35%) had grade III or higher CDC morbidity. BayesNet was found to be the most effective prediction model. No dominant parameter was observed in the Bayesian net importance matrix plot. The true positive (TP) rate was 76%, false positive (FP) rate was 15.6%, recall rate (sensitivity) was 76.9%, and overall accuracy was 82.2% A receiver operating characteristic (ROC) analysis was performed to estimate CDC grade ≥ III. AUC was 0.863 with a statistical significance of p < 0.001, indicating a high degree of accuracy. Conclusions: The Bayesian network model achieved the highest accuracy compared to all other models in predicting CDC Grade ≥ III complications following epithelial ovarian cancer surgery.

Background: This study aimed to evaluate the outcomes of patients diagnosed with stage IB2/IIA2 cervical squamous cell carcinoma who underwent neoadjuvant chemotherapy (NACT) prior to radical hysterectomy compared to those who did not receive NACT before surgery. Materials and methods: This is a multicenter study including data of 6 gynecological oncology departments. The study is approved from one of the institution’s local ethics committee. Patients were stratified into two cohorts based on the receipt of NACT preceding their surgical intervention. Clinico-pathological factors and progression-free survival were analyzed. Results: Totally 87 patients were included. Lymphovascular space invasion (LVSI) was observed as 40% in the group receiving NACT, while it was 66.1% in the group not receiving NACT (p = 0.036). Deep stromal invasion (> 50%) was 56% in the group receiving NACT and 84.8% in the group not receiving NACT (p = 0.001). In the univariate analysis, application of NACT is statistically significant among the factors that would be associated with disease-free survival. Consequently, a multivariate analysis was conducted for progression-free survival, incorporating factors such as the depth of stromal invasion, the presence of LVSI, and the administration of NACT. Of these, only the administration of NACT emerged as an independent predictor associated with decreased progression-free survival. (RR:5.88; 95% CI: 1.63–21.25; p = 0.07). Conclusions: NACT shouldn’t be used routinely in patients with stage IB2/IIA2 cervical cancer before radical surgery. Presented as oral presentation at National Congress of Gynaecological Oncology & National Congress of Cervical Pathologies and Colposcopy (2022/ TURKEY).

Background/Objectives: This study was designed to investigate the relationship between peripheral hematological inflammation markers, namely, neutrophil/lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte/lymphocyte ratio (MLR), systemic immune inflammation index (SII), and systemic inflammatory response index (SIRI) and high-grade cervical lesions (CIN2+). Methods: A retrospective cohort analysis was conducted on 358 patients who underwent cervical excision procedures. Patients were divided into two groups: <CIN2 and CIN2+. Preoperative complete blood count data were used to calculate the inflammation indices. HPV genotypes were also recorded. Logistic regression and ROC analyses were performed to evaluate the predictive performance. Results: CIN2+ lesions were detected in 69.6% of participants. In the univariate analysis, only age and HPV 16 positivity (p < 0.005) showed a significant association with the presence of CIN2+. NLR, PLR, MLR, SII, and SIRI values did not show significant differences between groups (all p > 0.05). In the multivariate analysis, increasing age was independently associated with a decrease in the risk of CIN2+ (OR = 0.96, 95% CI: 0.94–0.99), while HPV 16 positivity was associated with an increase in risk (OR = 2.44, 95% CI: 1.43–4.18). ROC analysis showed that combining age and HPV 16 status improved the specificity (85.1%) of predicting CIN2+ compared to using age alone (42.2%). Conclusions: Peripheral haematological inflammation markers (NLR, PLR, MLR, SII, and SIRI) did not show predictive value in predicting CIN2+ lesions. However, age and HPV 16 infection were found to be independent predictors. These findings suggest that haematological indices may reflect systemic inflammatory responses but are not sufficient on their own for the detection of CIN2+. HPV genotyping is of critical importance for the early detection of high-grade lesions.

Background: It is crucial to predict the response to chemotherapy and identify prognostic markers for recurrence and survival in patients with epithelial ovarian cancer (EOC), in order to effectively manage patient care. The CA-125 elimination rate constant K (KELIM) has recently been developed as a means of assessing the chemotherapy response and has been tested mainly in patients enrolled in randomized controlled trials. The objective of this study was to investigate whether the KELIM score is a prognostic marker for progression-free survival (PFS) and overall survival (OS) in EOC, utilizing its role in predicting the chemotherapy response in real-life settings. Method: Demographic, surgical, and survival data of patients with EOC operated on in Antalya Training and Research Hospital between January 2015 and December 2021 were obtained from the electronic gynecological oncology clinic database system and analyzed retrospectively. Results: A total of 102 patients with EOC were included; 30 patients (29.4%) had a KELIM score ≥ 1 and 72 (70.6%) patients had a KELIM score < 1. In the group with a KELIM score < 1, recurrence and refractory disease occurred in 49 patients, while it was 11 patients in the group with a KELIM score ≥ 1 (p = 0.004). PFS was 12 months and 32 months in the groups with KELIM scores of <1 and ≥1, respectively (p = 0.012). There was no difference between groups regarding OS (p = 0.139). In the whole group, KELIM score (<1 vs. ≥1) and type of surgery (IDS vs. PDS) were found to be independent prognostic factors for PFS (RR = 0.44; 95%CI: 0.22–0.88; p = 0.021 and RR = 2.97; 95%CI: 1.76–5.01; p < 0.001, respectively). Conclusion: We found that a favorable KELIM score was associated with better PFS in all groups of patients undergoing surgery for EOC in a real-life setting. With the increasing number of studies, the KELIM score will play an important role in providing better guidance to clinicians at the initial presentation of patients and in subsequent treatment planning.

Determination of nuclear and/or cytoplasmic expression of β‑catenin by immunohistochemistry in patients with endometrial cancer (EC) may constitute a potential diagnostic method for identifying patients with a catenin β1 (CTNNB1) gene mutation and those at risk of disease recurrence. The present study aimed to investigate β‑catenin expression patterns in hysterectomy specimens of patients with endometrioid type EC using immunohistochemistry, and to examine the prognostic impact of β‑catenin. The study was a single‑institutional, retrospective cohort trial enrolling consecutive patients with a postoperative histopathological diagnosis of endometrioid EC who underwent hysterectomy between January 2015 and December 2018. Histopathology slides from 75 patients were stained with a monoclonal antibody targeting the β‑catenin protein. Any percentage of nuclear staining, whether focal or diffuse, was considered ‘β‑catenin nuclear‑positive’. The cytoplasmic staining reaction of β‑catenin was assessed based on the percentage of stained cells and staining intensity. Immune‑reactivity score (IRS) values were determined by multiplying the scores for the percentage of staining and staining intensity. IRS values 0 to 2 were regarded as negative expression, 3 to 4 as low expression, 6 to 8 as moderate expression, and 9 to 12 as high expression. Recurrence‑free survival (RFS) was used as the prognostic endpoint. Only 2 out of 75 tissue samples (2.7%) exhibited nuclear β‑catenin expression, with a low staining percentage of 5%. By contrast, cytoplasmic staining was observed in all samples (100%). According to the IRS findings, 1.3% of the samples exhibited negative cytoplasmic expression, 42.7% low expression, 38.7% moderate expression and 17.3% high expression. Cox regression analysis revealed that staining with β‑catenin, either nuclear or cytoplasmic, had no impact on RFS, and stage was the sole independent prognostic factor. In conclusion, based on these results, β‑catenin expression in endometrioid EC was revealed to be mostly cytoplasmic, with only 2.7% of tissue samples exhibiting nuclear expression. Overall, β‑catenin expression has no impact on RFS.