Guide for Prioritisation of Patients for Referral to Breast Clinics

Following on from the service evaluation of retrospective TWW cases within The Leeds Teaching Hospitals Trust (between 2011-2018), the aim is to undertake a prospective analysis of a cohort of patients (4000) that have been referred from primary care (via their GP) for possible breast cancer diagnosis in the Leeds area. The analysis will include de-identified routine clinical data and blood tests from patients on the primary care referral cancer diagnosis pathway for cancer risk assessment. This is intended as a non-interventional study, where results from this study will not influence patient care. The study includes 3 phases/workstreams: 1. Validate previously developed prototype algorithm (computer instructions) 2. Update algorithm incorporating additional blood biomarkers and other relevant clinical data 3. Validate diagnostic accuracy of updated algorithm The study will include 4000 patients on TWW pathways. Note: The TWW pathway constitutes part of the urgent cancer referral pathway. This study aims to address a major unmet clinical need for breast cancer services within the NHS by safely combining the wealth of routinely collected clinical data and testing of blood samples within the NHS, with secure IT infrastructure in the NHS and the University of Leeds, to efficiently develop a risk assessment tool (guide) to rule-out cancer within a routine NHS environment. Inclusion criteria are: * Age ≥ 18 years old * Male and female patient must have been referred from primary care for possible breast cancer diagnosis * Patient consented to have blood tests The data sets will be divided into a development and validation data set (50:50 split). A range of statistical approaches will be performed on the training data set. The algorithm parameters will then be 'locked down' and validated on the remaining test data set. Performance will be assessed via ROC (Receiver Operator Characteristic) curves, sensitivity and specificity, Area-Under-Curve, negative/positive predictive values and diagnostic odds ratios. The algorithm generation and data analysis will be conducted at the University of Leeds, specifically within a secure VRE within the Leeds Institute for Data analytics (LIDA). Particular scrutiny will be given to the test set patients most likely to be false negatives in this analysis (i.e. those patients with cancer whose predicted probability is very low). Key to further improvements in this approach will be to characterise this sub-group and identify possible ways in which they might be identified by an improved analysis in a future study. Eligible participants will be observed electronically for 2 years post blood testing to ensure any patients with undetected cancer, who develop cancer within a year, are not missed. The study will end once the consented sample and data retention periods have completed therefore the expected duration of project is 5 years.