TY - JOUR
T1 - Dualistic classification of epithelial ovarian cancer: Surgical and survival outcomes in a large retrospective series
AU - Panici, Pierluigi Benedetti
AU - Marchetti, Claudia
AU - Salerno, Laura
AU - Musella, Angela
AU - Vertechy, Laura
AU - Palaia, Innocenza
AU - Perniola, Giorgia
AU - Ruscito, Ilary
AU - Boni, Terenzio
AU - Angioli, Roberto
AU - Muzii, Ludovico
PY - 2014
Y1 - 2014
N2 - Background. Ovarian cancers have been recently categorized into types I and II according to a dualistic model of tumorigenesis. Data on the correlation between this classification and clinical outcome are still scarce and controversial. Methods. A retrospective analysis of patients with ovarian cancer treated from 1998 to 2013 and operated by the same surgeon was conducted. Patients were classified into two groups: type I (125 patients), including low-grade serous, mucinous, endometrioid, and clear cell tumors; and type II (286 patients), including high-grade serous tumors, unspecified adenocarcinomas, and undifferentiated carcinomas. Results. Type II patients had a significantly higher incidence of advanced disease than type I (88.4 vs. 65.6 %, P = 0.0001) and required more aggressive surgical procedures. Rates of optimal tumor debulking were almost similar between groups (92.6 vs. 91.7 %, type I vs. II, P = NS). After a median follow-up of 41 months, 207 patients (50.4 %) were alive and 204 (49.6 %) were dead; 79 type I patients (63.8 %) and 237 type II patients (82.7 %) experienced relapse (P = 0.02). Progression-free survival was significantly different between groups: 25 months for type I vs. 17 months for type II (P = 0.023). Overall survival was not significantly different between groups, with a median overall survival of 75 months for type I vs. 62 months for type II (P = 0.116). Conclusions. The dualistic histotype-based classification into types I and II of ovarian cancer does not seem to correlate with prognosis. Different molecular characteristics of type I and II tumors may have therapeutic implications and should be deeply investigated. © 2014 Society of Surgical Oncology.
AB - Background. Ovarian cancers have been recently categorized into types I and II according to a dualistic model of tumorigenesis. Data on the correlation between this classification and clinical outcome are still scarce and controversial. Methods. A retrospective analysis of patients with ovarian cancer treated from 1998 to 2013 and operated by the same surgeon was conducted. Patients were classified into two groups: type I (125 patients), including low-grade serous, mucinous, endometrioid, and clear cell tumors; and type II (286 patients), including high-grade serous tumors, unspecified adenocarcinomas, and undifferentiated carcinomas. Results. Type II patients had a significantly higher incidence of advanced disease than type I (88.4 vs. 65.6 %, P = 0.0001) and required more aggressive surgical procedures. Rates of optimal tumor debulking were almost similar between groups (92.6 vs. 91.7 %, type I vs. II, P = NS). After a median follow-up of 41 months, 207 patients (50.4 %) were alive and 204 (49.6 %) were dead; 79 type I patients (63.8 %) and 237 type II patients (82.7 %) experienced relapse (P = 0.02). Progression-free survival was significantly different between groups: 25 months for type I vs. 17 months for type II (P = 0.023). Overall survival was not significantly different between groups, with a median overall survival of 75 months for type I vs. 62 months for type II (P = 0.116). Conclusions. The dualistic histotype-based classification into types I and II of ovarian cancer does not seem to correlate with prognosis. Different molecular characteristics of type I and II tumors may have therapeutic implications and should be deeply investigated. © 2014 Society of Surgical Oncology.
KW - ovarian cancer
KW - ovarian cancer
UR - http://hdl.handle.net/10807/203922
U2 - 10.1245/s10434-014-3714-6
DO - 10.1245/s10434-014-3714-6
M3 - Article
SN - 1068-9265
VL - 21
SP - 3036
EP - 3041
JO - Annals of Surgical Oncology
JF - Annals of Surgical Oncology
ER -