A prognostic model for ovarian cancer

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...

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Bibliographic Details
Published in:British journal of cancer 2001-09, Vol.85 (7), p.944-952
Main Authors: Clark, T G, Stewart, M E, Altman, D G, Gabra, H, Smyth, J F
Format: Article
Language:English
Subjects:
Adolescent
Adult
Age of Onset
Aged
Aged, 80 and over
Alkaline Phosphatase - blood
Ascites - pathology
Biological and medical sciences
Biomedical and Life Sciences
Biomedicine
Cancer Research
Drug Resistance
Epidemiology
Female
Female genital diseases
Gynecology. Andrology. Obstetrics
Health Status
Humans
Medical sciences
Middle Aged
Models, Theoretical
Molecular Medicine
Neoplasm Staging
Oncology
Ovarian Neoplasms - pathology
Ovarian Neoplasms - therapy
Predictive Value of Tests
Prognosis
Regression Analysis
Regular
regular-article
Serum Albumin
Tumors
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Summary: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. © 2001 Cancer Research Campaign http://www.bjcancer.com
ISSN:0007-0920
1532-1827
DOI:10.1054/bjoc.2001.2030