Editorial: [Insights, Controversies, and New Developments in the Initial Treatment Decisions for Advanced Epithelial Ovarian Cancer]

JIANFENG GUO ^1,2*

• ¹ Department of Obstetrics and Gynecology, People’s Hospital of Longhua, Shenzhen, China, shenzhen, China
• ² Longhua District Key Laboratory of Perinatal Population Medicine, Shenzhen, China, shenzhen, China

practice. Here is a brief overview of a few representative articles:1. Machine learning for epithelial ovarian cancer platinum resistance recurrence identification using routine clinical data This study developed machine learning models to predict platinumresistant recurrence in epithelial ovarian cancer (EOC) using clinical and laboratory data from 1,392 patients. Five algorithms (DTA, KNN, SVM, RF, XGBoost) were compared, with XGBoost based on multiple logistic regression showing the best performance (AUC: 0.784, accuracy: 80.4%). Key variables influencing recurrence were identified, and models were visualized via nomograms for clinical use. The findings highlight the potential of machine learning in improving EOC recurrence prediction, though continuous model updates are needed to adapt to evolving clinical contexts.This study compared surgical and oncological outcomes in patients with incidental borderline ovarian tumors or ovarian cancer treated with a two-stage surgical procedure versus those with suspected malignancy undergoing a single-stage procedure. Among 223 patients, those with incidental diagnoses had more surgeries and longer intervals to chemotherapy and cytoreduction completion.However, there were no significant differences in complete cytoreduction rates, complication rates, hospitalization days, recurrence risk, or survival. Despite delays, incidental diagnosis and two-stage treatment did not negatively impact oncological outcomes, supporting their feasibility in clinical practice. This study evaluated the diagnostic performance of 3D ultrasonography (3DUS), 3D power Doppler (3DPD), and their combination in ovarian cancer (OC). Analyzing 18 studies (2,548 cases), 3DUS showed sensitivity of 0.89 and specificity of 0.93, while 3DPD had sensitivity of 0.90 and specificity of 0.85. Combining 3DUS and 3DPD achieved superior diagnostic efficiency, with sensitivity of 0.99, specificity of 0.95, and AUC of 0.99. The findings suggest that 3DUS and 3DPD, particularly when combined, are highly effective diagnostic tools for OC, offering improved accuracy and clinical utility.Although the articles on this topic have provided us with a wealth of insights, there are still many disputes that need to be resolved. For example, how can we better integrate targeted therapy with immunotherapy in the initial treatment? How to further optimize individual treatment strategies through multi-omics analysis? In addition, with the accumulation of real-world data, how to translate these data into decision support tools in clinical practice is also an important direction for future research. conclusion Overall, this topic provides new ideas and evidence for the initial treatment decision of advanced epithelial ovarian cancer through multi-angle discussion. We expect these findings to provide additional references for clinicians and ultimately improve patient outcomes and quality of life." In the future, with more high-quality research, we believe that the treatment of advanced EOC will have a brighter future.