TY - JOUR
T1 - The prognostic value of dividing epithelial ovarian cancer into type I and type II tumors based on pathologic characteristics
AU - Prahm, Kira Philipsen
AU - Karlsen, Mona Aarenstrup
AU - Høgdall, Estrid
AU - Scheller, Nikolai Madrid
AU - Lundvall, Lene
AU - Nedergaard, Lotte
AU - Christensen, Ib Jarle
AU - Høgdall, Claus
N1 - Copyright © 2014 Elsevier Inc. All rights reserved.
PY - 2015/2/1
Y1 - 2015/2/1
N2 - Objective. To investigate the prognostic significance of dividing epithelial ovarian cancer (EOC) in type I and type II tumors based on pathologic variables. Methods. We used the Danish Gynecologic Cancer Database to identify all patients diagnosed with EOC from 2005 to 2012. Information on histologic type and grade were used to classify tumors as either type I or type II. Death, and several prognostic factors were used in the multivariate Cox regression, and Landmark analysis was used to estimate hazard ratios of all-cause mortality. Results. Among 2660 patients diagnosed with EOC, 735 were categorized as type I tumors, and 1925 as type II tumors. Patients with type II EOC were more frequently diagnosed in late FIGO stages (stages III-IV) than patients with type I EOC (78.1% vs. 32.1% respectively; P < 0.001). Time dependent multivariate Cox analysis, adjusted for known prognostic variables, showed no significant difference in survival within the first two years after diagnosis, however, after 730 days of follow-up a significantly increased overall survival for type I tumors was observed (hazard ratio 1.72, 95% confidence interval: 1.28-2.31, P < 0.001). Similarly the Landmark analysis for survival confirmed the increased overall survival for type I tumors after two years of follow-up (hazard ratio: 1.85, 95% confidence interval: 1.35-2.54, P < 0.001). Conclusion. Classification of EOC in type I and type II tumors based on pathologic variables was associated with an increased risk of death for type II tumors after two years of follow-up, while no increased risk was seen during the first two years of follow-up.
AB - Objective. To investigate the prognostic significance of dividing epithelial ovarian cancer (EOC) in type I and type II tumors based on pathologic variables. Methods. We used the Danish Gynecologic Cancer Database to identify all patients diagnosed with EOC from 2005 to 2012. Information on histologic type and grade were used to classify tumors as either type I or type II. Death, and several prognostic factors were used in the multivariate Cox regression, and Landmark analysis was used to estimate hazard ratios of all-cause mortality. Results. Among 2660 patients diagnosed with EOC, 735 were categorized as type I tumors, and 1925 as type II tumors. Patients with type II EOC were more frequently diagnosed in late FIGO stages (stages III-IV) than patients with type I EOC (78.1% vs. 32.1% respectively; P < 0.001). Time dependent multivariate Cox analysis, adjusted for known prognostic variables, showed no significant difference in survival within the first two years after diagnosis, however, after 730 days of follow-up a significantly increased overall survival for type I tumors was observed (hazard ratio 1.72, 95% confidence interval: 1.28-2.31, P < 0.001). Similarly the Landmark analysis for survival confirmed the increased overall survival for type I tumors after two years of follow-up (hazard ratio: 1.85, 95% confidence interval: 1.35-2.54, P < 0.001). Conclusion. Classification of EOC in type I and type II tumors based on pathologic variables was associated with an increased risk of death for type II tumors after two years of follow-up, while no increased risk was seen during the first two years of follow-up.
KW - Aged
KW - Aged, 80 and over
KW - Cohort Studies
KW - Female
KW - Humans
KW - Middle Aged
KW - Neoplasms, Glandular and Epithelial
KW - Ovarian Neoplasms
KW - Prognosis
KW - Survival Analysis
U2 - 10.1016/j.ygyno.2014.12.029
DO - 10.1016/j.ygyno.2014.12.029
M3 - Journal article
C2 - 25546113
SN - 0090-8258
VL - 136
SP - 205
EP - 211
JO - Gynecologic Oncology
JF - Gynecologic Oncology
IS - 2
ER -
