Breast cancer (BC) is the most common cancer in UK females, with about 1 in 8 developing it. Ovarian cancer (OC), although less prevalent, has worse survival rates as it is often not diagnosed until an advanced stage. For both, survival rates increase with earlier diagnosis. Risk models allow identification of women at highest and lowest risk, and so those most likely to benefit from alternative screening modalities and/or preventative treatments. BC and OC risks are multifactorial, depending on genetic, family history and other lifestyle/hormonal/reproductive risk factors. We have developed comprehensive BC (BOADICEA) and OC risk models. As risk prediction is computationally intensive, they have been optimised for real-time clinical use. The models will be accessible for clinical use via a new online tool (www.canrisk.org), developed by a team of software developers, clinicians and scientists following a standard framework and using established software engineering practices. Since such tools are classified as medical devices they must adhere to medical device regulations for safety, quality and efficacy (CE marking). We are currently undertaking the necessary additional risk/quality management and software engineering work.
