A prognostic model for ovarian cancer
File(s)
Published version
Author(s)
Clark, TG
Stewart, ME
Altman, DG
Gabra, H
Smyth, JF
Type
Journal Article
Abstract
About 6000 women in the United Kingdom develop ovarian cancer each year and about two-thirds of the women will die from the disease. Establishing the prognosis of a woman with ovarian cancer is an important part of her evaluation and treatment. Prognostic models and indices in ovarian cancer should be developed using large databases and, ideally, with complete information on both prognostic indicators and long-term outcome. We developed a prognostic model using Cox regression and multiple imputation from 1189 primary cases of epithelial ovarian cancer (with median follow-up of 4.6 years). We found that the significant (P≤ 0.05) prognostic factors for overall survival were age at diagnosis, FIGO stage, grade of tumour, histology (mixed mesodermal, clear cell and endometrioid versus serous papillary), the presence or absence of ascites, albumin, alkaline phosphatase, performance status on the ZUBROD-ECOG-WHO scale, and debulking of the tumour. This model is consistent with other models in the ovarian cancer literature; it has better predictive ability and, after simplification and validation, could be used in clinical practice.
Date Issued
2001-10-02
Date Acceptance
2001-07-05
Citation
British Journal of Cancer, 2001, 85 (7), pp.944-952
ISSN
0007-0920
Publisher
Springer Nature
Start Page
944
End Page
952
Journal / Book Title
British Journal of Cancer
Volume
85
Issue
7
Copyright Statement
© 2001, Springer Nature. From twelve months after its original publication, this work is licensed under the Creative Commons Attribution-NonCommercial-Share Alike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/.
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000171685300003&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Life Sciences & Biomedicine
Oncology
ovarian cancer
prognostic model
overall survival
FIGO STAGE
SURVIVAL
CARCINOMA
REGRESSION
HISTOLOGY
CA-125
GRADE
AGE
Publication Status
Published
Date Publish Online
2001-10-02