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Eur J Cancer Care (Engl). 2013 Jul;22(4):423-9. doi: 10.1111/ecc.12015. Epub 2012 Nov 1.

Identifying women with undetected ovarian cancer: independent and external validation of QCancer(®) (Ovarian) prediction model.

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1
Centre for Statistics in Medicine, Wolfson College Annexe, University of Oxford, Oxford, UK. gary.collins@csm.ox.ac.uk

Abstract

Early identification of ovarian cancer is an unresolved challenge and the predictive value of single symptoms is limited. We evaluated the performance of QCancer(®) (Ovarian) prediction model for predicting the risk of ovarian cancer in a UK cohort of general practice patients. A total of 1.1 million patients registered with a general practice surgery between 1 January 2000 and 30 June 2008, aged 30-84 years with 735 ovarian cancer cases, were included in the analysis. Ovarian cancer was defined as incident diagnosis of ovarian cancer during the 2 years after study entry. The results from this independent and external validation of QCancer(®) (Ovarian) prediction model demonstrated good performance on a large cohort of general practice patients. QCancer(®) (Ovarian) had very good discrimination with an area under the receiver operating characteristic curve of 0.86 and explained 59.9% of the variation. QCancer(®) (Ovarian) was well calibrated across all tenths of risk and over all age. The 10% of women with the highest predicted risks included 64% of all ovarian cancer diagnoses over the next 2 years. QCancer(®) (Ovarian) appears to be a useful tool for identifying undetected cases of ovarian cancer in primary care in the UK for early referral and investigation.

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PMID:
23121234
DOI:
10.1111/ecc.12015
[Indexed for MEDLINE]
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