Risk-Adjusted Cancer Screening and Prevention (RiskAP): Complementing Screening for Early Disease Detection by a Learning Screening Based on Risk Factors

Breast cancer; Evidence-generating care; Risk-adjusted prevention Cáncer de mama; Atención generadora de evidencia; Prevención ajustada al riesgo Càncer de mama; Atenció generadora d'evidències; Prevenció ajustada al risc Background: Risk-adjusted cancer screening and prevention is a promising and continuously emerging option for improving cancer prevention. It is driven by increasing knowledge of risk factors and the ability to determine them for individual risk prediction. However, there is a knowledge gap between evidence of increased risk and evidence of the effectiveness and efficiency of clinical preventive interventions based on increased risk. This gap is, in particular, aggravated by the extensive availability of genetic risk factor diagnostics, since the question of appropriate preventive measures immediately arises when an increased risk is identified. However, collecting proof of effective preventive measures, ideally by prospective randomized preventive studies, typically requires very long periods of time, while the knowledge about an increased risk immediately creates a high demand for action. Summary: Therefore, we propose a risk-adjusted prevention concept that is based on the best current evidence making needed and appropriate preventive measures available, and which is constantly evaluated through outcome evaluation, and continuously improved based on these results. We further discuss the structural and procedural requirements as well as legal and socioeconomical aspects relevant for the implementation of this concept. The project was funded by the German Federal Ministry of Health (grant No. 2515FSB401 to Rita Schmutzler and Christiane Woopen) for supporting the international expert meetings, and a grant of the EU Horizon 2020 program, BRIDGES (grant No. 634935, PI Peter Devilee, WP5-PI Rita Schmutzler), for the compilation of the most recent findings of genetic risk prediction.