Evaluating clinician acceptability of the prototype CanRisk tool for predicting risk of breast and ovarian cancer: A multi-methods study

In order to maximise opportunities to both prevent and detect cancer early, there is a need to identify people at higher risk, who may benefit from tailored screening and prevention. The Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) is one example of a cancer risk prediction algorithm, which factors in genetic factors, family history, lifestyle and hormonal factors to calculate future risk of developing breast and ovarian cancer. To implement this algorithm into clinical practice, a new user-friendly web-based tool called CanRisk (CanRisk.org) was developed to apply BOADICEA in clinical settings. Clinicians from primary care and specialist genetics clinics in England, France and Germany were invited to use the CanRisk prototype. Their views on the tool were assessed either through an interview or an open-ended questionnaire. The study found that whilst the CanRisk tool was generally acceptable to most participants, primary care clinicians raised concerns over the amount of time needed to complete. Furthermore, clinicians from both groups were apprehensive about the lack of opportunities to interpret risk scores before sharing them with their patients. Themes surrounding the tool’s impact on clinician-patient interaction; the patients’ understanding of how the tool works; and clinicians’ confidence in using the tool were also found. These findings demonstrate the difficulties surrounding the development of a complex tool for clinical settings and highlights that needs of primary care clinicians and geneticists are different, emphasizing the importance of understanding clinic context when developing cancer risk assessment tools.

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