Oncology Institute of Vojvodina, Sremska Kamenica, Faculty of Medicine University of Novi Sad, Faculty of Medicine University of Belgrade, Belgrade, Serbia.
Department of Gynecology and Obstetrics, University Clinical Center of Serbia, Clinic for Gynecology and Obstetrics, Faculty of Medicine University of Belgrade, Belgrade, Serbia.
Clinics (Sao Paulo). 2023 May 4;78:100204. doi: 10.1016/j.clinsp.2023.100204. eCollection 2023.
The present study purposed to determine characteristics of ovarian carcinoma and to analyze predictors of survival in patients with ovarian carcinoma.
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.
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.
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.
本研究旨在确定卵巢癌的特征,并分析卵巢癌患者生存的预测因素。
本研究为回顾性队列研究,纳入了 2012 年 1 月至 2016 年 12 月在伏伊伏丁那肿瘤研究所手术肿瘤学诊所接受治疗的确诊为卵巢癌的患者。对 72 例卵巢癌患者进行了分析。使用研究所的数据库(BirPis 21 SRC Infonet DOO - 伏伊伏丁那肿瘤研究所信息系统),回顾性收集了肿瘤组织学类型、疾病分期、治疗、淋巴浸润和手术程序等数据。采用描述性统计和 Cox 比例风险模型进行多变量分析。
单因素 Cox 回归分析确定了组织学、肿瘤分级、FIGO(国际妇产科联合会)分期、新辅助化疗(NACT)、治疗周期数、手术类型和化疗反应是死亡率的独立预测因素。最终,肿瘤类型和化疗反应在多变量 Cox 回归模型中具有更高的死亡风险比。此外,高级别、晚期卵巢癌患者完全缓解、无复发病灶和血管淋巴管间隙侵犯的比例是卵巢癌患者生存的显著预测因素。
本研究提供了关于卵巢癌特征和生存预测因素的重要信息,有助于为患者提供个体化的治疗方案。