Abstract
Objective:
The present study purposed to determine characteristics of ovarian carcinoma and to analyze predictors of survival in patients with ovarian carcinoma.
Method:
A retrospective cohort study was conducted including the patients with diagnosed ovarian carcinoma treated at the Clinic for Operative Oncology, Oncology Institute of Vojvodina in the period from January 2012 to December 2016. Seventy-two women with ovarian carcinoma were included in the analysis. The data about the histological type of tumor, disease stage, treatment, lymphatic infiltration, and surgical procedure were collected retrospectively, using the database of the institution where the research was conducted (BirPis 21 SRC Infonet DOO – Information System Oncology Institute of Vojvodina). Descriptive statistics and multivariate analysis using Cox proportional hazards model were performed.
Results:
The univariate Cox regression analysis identified histology, tumor grade, FIGO (International Federation of Gynecology and Obstetrics) stage, NACT (Neoadjuvant Chemotherapy), number of therapy cycles, type of surgery, and chemotherapy response as independent predictors of mortality. Finally, the type of tumor and chemotherapy response had an increased hazard ratio for mortality in the multivariate Cox regression model. Herewith, the percentage of high-grade, advanced-stage ovarian cancer patients with complete response to chemotherapy, absence of recurrent disease, and lymphovascular space invasion were significant predictors of survival in patients with ovarian carcinoma.
Conclusions:
Herein, emerging data regarding precision medicine and molecular-based personalized treatments are promising and will likely modify the way the authors provide multiple lines of treatments in the near future.
Keywords:
Surgery; Ovary; Carcinoma; Oncology; Histopathology; Pathology
HIGHLIGHTS
Analyzing predictors of survival in patients with ovarian carcinoma is crucial.
Independent estimators of mortality in ovarian carcinoma, are more precise by identifying histopathologic tumor grade, FIGO, and NACT.
The aforementioned predictors also involve the number of therapeutic cycles, type of surgery, and chemotherapy response.
Poor chemotherapy response increases the hazard ratio for mortality.
Significant predictors of survival in ovarian carcinoma are the absence of recurrent disease and lymphovascular space invasion.