Experiences of implementation of personalised risk estimates for breast cancer in clinical practice: a systematic review and qualitative synthesis

Le résumé fourni par la source

Breast cancer risk prediction tools are increasingly used in clinical practice to guide early detection, prevention, and shared decision-making. Unlike population-level screening, personalised risk estimates incorporate individual factors (family history, genetics, lifestyle, breast density), providing tailored assessments. These tools show promise for improving patient engagement and targeted prevention, but require effective implementation to ensure they enhance rather than complicate care. This review explores healthcare professionals' experiences with providing personalised breast cancer risk estimates and women's experiences of receiving them in clinical settings. Four online databases were searched for qualitative studies on the use of personalised risk estimates in clinical practice. Data were analysed using inductive thematic analysis. Seven papers were included; the majority based in the UK screening setting. Most used interview and focus-groups, with thematic analysis. Both healthcare professionals and women expressed high acceptance of personalised risk estimates. Women found the information empowering and useful for future health planning. Effective communication and prompt follow-up from healthcare professionals were crucial for positive experiences. Professionals highlighted challenges in implementation, including the need for additional healthcare professionals, safe care pathways, and technology. The studies focused on stratified breast screening, raising questions about offering less frequent screening to lower-risk women. This approach must be supported by strong evidence, and women should retain choice in screening intervals. Personalised risk estimates are favourably viewed in clinical practice, but studies mainly examined research settings. Further research is needed to understand real-world implementation, identify barriers, and optimise use across diverse clinical environments.

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