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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< or = 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.

Original publication




Journal article


British journal of cancer

Publication Date





944 - 952


ICRF Medical Statistics Group, Centre for Statistics in Medicine, Institute of Health Sciences, Old Road, Headington, Oxford, OX3 7LF, UK.


Humans, Ovarian Neoplasms, Ascites, Alkaline Phosphatase, Serum Albumin, Neoplasm Staging, Prognosis, Regression Analysis, Predictive Value of Tests, Age of Onset, Health Status, Models, Theoretical, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Female