OBJECTIVE: An ability to predict survival is of crucial importance in determining the need for cancer therapy. Recent advances in tumor typing of ovarian carcinomas lead to a classification which is more reproducible and reflects underlying biology more accurately than grade. We tested whether updated tumor type predicts outcome for patients with low-stage ovarian carcinoma. METHODS: From a population-based cohort of 1326 women diagnosed with stage I-II ovarian carcinoma between 1984 and 2003, 652 cases were available for central pathological slide review using contemporary criteria. Six hundred thirty cases were confirmed as ovarian carcinoma. Twenty-five ovarian carcinomas of rare types were excluded leaving 605 cases for this study. Recursive partitioning analysis and univariate models were used to identify subsets with an excellent outcome, i.e., disease-specific survival at 10 years (DSS10y) > or =95%. RESULTS: Seventy-seven ovarian carcinomas of endometrioid and mucinous type, stage Ia or Ib, were associated with an excellent outcome [DSS10y=95%]. No subset of the high-grade serous type with an excellent outcome could be identified. Clear cell carcinomas of stage Ia or Ib had a favorable outcome [DSS10y=87%] compared to stage Ic-II [DSS10y=66%]. CONCLUSIONS: A subset of ovarian carcinoma patients with an excellent outcome can be identified based on tumor type (endometrioid or mucinous) and stage (Ia or Ib). Type is more reproducibly assigned than grade and identifies a larger cohort of women with stage I/II ovarian carcinoma with favorable outcomes (12.2% vs. 6.5%), and therefore is superior to grade in estimating risk of death from ovarian carcinoma.
OBJECTIVE: An ability to predict survival is of crucial importance in determining the need for cancer therapy. Recent advances in tumor typing of ovarian carcinomas lead to a classification which is more reproducible and reflects underlying biology more accurately than grade. We tested whether updated tumor type predicts outcome for patients with low-stage ovarian carcinoma. METHODS: From a population-based cohort of 1326 women diagnosed with stage I-II ovarian carcinoma between 1984 and 2003, 652 cases were available for central pathological slide review using contemporary criteria. Six hundred thirty cases were confirmed as ovarian carcinoma. Twenty-five ovarian carcinomas of rare types were excluded leaving 605 cases for this study. Recursive partitioning analysis and univariate models were used to identify subsets with an excellent outcome, i.e., disease-specific survival at 10 years (DSS10y) > or =95%. RESULTS: Seventy-seven ovarian carcinomas of endometrioid and mucinous type, stage Ia or Ib, were associated with an excellent outcome [DSS10y=95%]. No subset of the high-grade serous type with an excellent outcome could be identified. Clear cell carcinomas of stage Ia or Ib had a favorable outcome [DSS10y=87%] compared to stage Ic-II [DSS10y=66%]. CONCLUSIONS: A subset of ovarian carcinomapatients with an excellent outcome can be identified based on tumor type (endometrioid or mucinous) and stage (Ia or Ib). Type is more reproducibly assigned than grade and identifies a larger cohort of women with stage I/II ovarian carcinoma with favorable outcomes (12.2% vs. 6.5%), and therefore is superior to grade in estimating risk of death from ovarian carcinoma.
Authors: Martin Köbel; Steve E Kalloger; Sandra Lee; Máire A Duggan; Linda E Kelemen; Leah Prentice; Kimberly R Kalli; Brooke L Fridley; Daniel W Visscher; Gary L Keeney; Robert A Vierkant; Julie M Cunningham; Christine Chow; Roberta B Ness; Kirsten Moysich; Robert Edwards; Francesmary Modugno; Clareann Bunker; Eva L Wozniak; Elizabeth Benjamin; Simon A Gayther; Aleksandra Gentry-Maharaj; Usha Menon; C Blake Gilks; David G Huntsman; Susan J Ramus; Ellen L Goode Journal: Cancer Epidemiol Biomarkers Prev Date: 2013-07-23 Impact factor: 4.254
Authors: Emily N Prendergast; Marie Holzapfel; Jennifer J Mueller; Mario M Leitao; Camille C Gunderson; Kathleen N Moore; Britt K Erickson; Charles A Leath; Elena S Diaz Moore; Joshua G Cohen; Christine S Walsh Journal: Gynecol Oncol Date: 2016-12-12 Impact factor: 5.482
Authors: John Bliton; Michael Parides; Peter Muscarella; John C McAuliffe; Katia Papalezova; Haejin In Journal: J Surg Res Date: 2020-12-09 Impact factor: 2.192