Predictive factors for irresectability in advanced ovarian cancer

International Journal of Gynecological Cancer : Official Journal of the International Gynecological Cancer Society
H Martínez-SaídC M López-Graniel

Abstract

Despite advances in surgical modalities and chemotherapeutic agents, the 5-year survival for patients with advanced ovarian cancer is barely 40-50%. At the moment, optimally cytoreductive primary surgery is the best option for patients with advanced ovarian cancer. Predictive factors of primary optimum reduction surgery have been described based on imaging studies and tumor markers and based on the premise to know a priori the weight and tumor volume, with promising results. A retrospective study was conducted based on the hypothesis that it is feasible to identify those patients not susceptible of undergoing optimum primary cytoreductive surgery. The variables associated with a lesser probability of success in this study are the presence of palpable abdominal tumor on physical examination, the presence of tumor in Douglas' cul-de-sac on vaginal exploration, the presence of ascites in any quantity, elevation of CA-125 above 1000 U/l, and the presence of pulmonary and liver metastases. The success rate for cytoreduction was 62% when none or one of these variables was present and 32% when two or more variables were present.

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Citations

Mar 7, 2006·International Journal of Gynecological Cancer : Official Journal of the International Gynecological Cancer Society·A Morán-MendozaD Gallardo-Rincón
May 10, 2006·International Journal of Gynecological Cancer : Official Journal of the International Gynecological Cancer Society·A-A K TentesI H Nikas
Nov 8, 2007·International Journal of Gynecological Cancer : Official Journal of the International Gynecological Cancer Society·A E BlandP T Taylor
Feb 23, 2010·World Journal of Surgical Oncology·Azam-Sadat MousaviSetareh Akhavan
Aug 5, 2011·Journal of Surgical Oncology·Yusuf YildirimEmre Gultekin
Jan 29, 2021·The Journal of Obstetrics and Gynaecology Research·Quan QuanXiaoling Mu

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