Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.712115
Title: Quantification of the risk of breast, uterine and cervical cancers in symptomatic primary care patients
Author: Walker, Sarah
ISNI:       0000 0004 6062 697X
Awarding Body: Exeter and Plymouth Peninsula Medical School
Current Institution: Exeter and Plymouth Peninsula Medical School
Date of Award: 2017
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Abstract:
This thesis explores the features (symptoms, signs or abnormal investigation results) that women present to primary care before a diagnosis of breast, uterine or cervical cancer. Each of the three studies identifies the features predictive of breast, uterine and cervical cancers. The risk of cancer for these features is then quantified, and expressed as a positive predictive value (PPV) for cancer. Individual case-control studies were carried out using data within the Clinical Practice Research Datalink. This hosts anonymised patient records containing full details of every consultation, prescription, referral, and major illness, such as cancer. Three studies were carried out; cases were women aged 40 or over, with a new diagnosis of breast, uterine or cervical cancer, respectively. For each case, five controls, matched on age, sex and GP practice, were provided. Univariable and multivariable analyses identified those features associated with an increased risk of cancer. Four features were predictive of breast cancer: breast lump (PPV 15% (95% Cl 13 to 18)), nipple retraction (PPV 5.9% (95% Cl 2.8 to 12)), nipple discharge (PPV 3.4% (95% Cl 1.9 to 6.2)) and breast pain (PPV 1.0% (95% Cl 0.77 to 1-3)). Nine features were predictive of uterine cancer: post-menopausal bleeding (PPV 3.8% (95% Cl 3.1 to 5.1)), irregular menstruation (PPV 2.0 (95% Cl 1.5 to 2.6)), excessive menstruation, vaginal discharge, abdominal pain, haematuria, low haemoglobin, raised platelets and raised glucose. All features other than post-menopausal bleeding and irregular menstruation had PPVs below 1% when presented as a single symptom. Nine features were predictive of cervical cancer: post-menopausal bleeding, irregular menstruation, inter-menstrual bleeding, vaginal discharge or vaginitis, abdominal pain, urinary tract infection, haematuria, low haemoglobin and high white cell count. Each of these features had PPVs below 0.5%. The main results can be made available for use in clinical practice, in the form of flip charts and mouse mats, as well as an online tool. The results from the breast and uterine cancer studies were also used in the recent update of NICE clinical guidance for the recognition and referral of suspected cancer. Cancer Research UK have also produced an online ‘symptom desk easel’ summarising the NICE guidance under feature headings, including a section on investigations findings. The action which should be taken within 24 hours, 2 weeks and other actions are given for each feature.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.712115  DOI: Not available
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