Current State of The Problem of Resectability Prediction and Personalized Treatment Selection in Advanced Ovarian Cancer (Literature Review)
DOI:
https://doi.org/10.55640/eijmrms-06-07-07Keywords:
Ovarian cancer, cytoreductive surgery, Bristow indexAbstract
Ovarian cancer remains one of the leading causes of mortality among gynecological malignancies: more than 70% of patients present with FIGO stage III–IV disease, and five-year survival in advanced disease does not exceed 30–40%. Complete (R0) cytoreductive surgery is the strongest independent prognostic factor, whereas current preoperative methods of resectability assessment — computed tomography, diagnostic laparoscopy, and tumor/inflammatory biomarkers — show limited and heterogeneous accuracy. This review summarizes current literature on the epidemiology and clinicopathological features of advanced ovarian cancer, the role of cytoreductive surgery as the principal prognostic factor, radiologic (R.E. Bristow index) and laparoscopic (A. Fagotti Predictive Index Value, PIV; Peritoneal Cancer Index, PCI) methods of resectability assessment, the role of CA-125, HE4 and the ROMA algorithm, systemic inflammatory markers (NLR, PLR, SII), molecular factors of the tumor microenvironment (VEGF, HIF-1α, CD8+, CD68+, PD-L1), the results of randomized trials comparing primary cytoreduction with neoadjuvant chemotherapy (EORTC-NCIC 55971, CHORUS, JCOG0602), and the prospects of machine learning and the TRIPOD framework for multiparametric predictive modeling. Most existing tools rely on a single diagnostic modality, while studies integrating clinical, laboratory, radiologic, endoscopic, morphological and molecular predictors into a single, properly validated quantitative model remain scarce. The development and validation of such multiparametric models is substantiated as a promising direction for personalizing surgical strategy in advanced ovarian cancer.
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