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BJOG. 2007 Jan;114(1):59-64.

Feasibility of screening for ovarian cancer using symptoms as selection criteria.

Author information

1
Department of Gynaecological Oncology, The Royal Marsden NHS Foundation Trust, London, UK. b.d.rufford@qmul.ac.uk

Abstract

OBJECTIVE:

Retrospective studies have reported that 95% of women with ovarian cancer have symptoms prior to diagnosis and that women with these symptoms are at an increased risk of ovarian cancer. Failure to recognise these symptoms may result in a delay in referral and diagnosis. We assess the feasibility of screening for ovarian cancer using symptoms as selection criteria.

DESIGN:

A randomised controlled trial.

SETTING:

General practices in East London.

POPULATION:

Three hundred and ninety GPs.

METHODS:

GPs were randomised by practice, and those in the study group were given rapid access to ultrasound and CA125 test for women, >45 years, suffering from symptoms that may be caused by ovarian cancer.

MAIN OUTCOME MEASURES:

Symptoms leading to referral, ultrasound and CA125 results and ovarian cancer diagnosis.

RESULTS:

Seventy nine practices containing 197 GPs were randomised to the study arm. Three hundred and seventeen women were referred, of which 315 were eligible. Women reported the following symptoms: abdominal 87%, gastrointestinal 41% and constitutional 29%. Twenty-three women had abnormal findings on ultrasound: 20 were managed conservatively and 3 surgically. Histology revealed a mucinous cystadenoma, a Brenner tumour and a serous cystadenoma. Incidental findings included endometrial pathology in 13 women and bladder pathology in 2. Ninety five percent of CA125 results were <35 units/ml.

CONCLUSIONS:

This pilot study confirms the feasibility of screening for ovarian cancer using symptoms as selection criteria. Specificity was high and patient compliance good. Initial concerns about referral volumes and additional investigations and referrals generated were not confirmed. No ovarian cancers were detected in this pilot study, and this may be due to the size of the cohort.

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