• EvansD Gareth RDGRhttp://orcid.org/0000-0002-8482-5784Division of Evolution and Genomic Sciences, Faculty of Biology, Medicine and Health, University of Manchester, MAHSC, Manchester, UK. gareth.evans@mft.nhs.uk.Prevention Breast Cancer Unit and Nightinga, Elaine F Harkness, Adam R Brentnall, Elke M van Veen, Susan M Astley, Helen Byers, Sarah Sampson, Jake Southworth, Paula Stavrinos, Sacha J Howell, Anthony J Maxwell, Anthony Howell, William G Newman, and Jack Cuzick.
• Division of Evolution and Genomic Sciences, Faculty of Biology, Medicine and Health, University of Manchester, MAHSC, Manchester, UK. gareth.evans@mft.nhs.uk.
• Breast Cancer Res. Treat. 2019 Jul 1; 176 (1): 141-148.

PurposeTo improve breast cancer risk stratification to enable more targeted early detection/prevention strategies that will better balance risks and benefits of population screening programmes.Methods9362 of 57,902 women in the Predicting-Risk-Of-Cancer-At-Screening (PROCAS) study who were unaffected by breast cancer at study entry and provided DNA for a polygenic risk score (PRS). The PRS was analysed alongside mammographic density (density-residual-DR) and standard risk factors (Tyrer-Cuzick-model) to assess future risk of breast cancer based on tumour stage receptor expression and pathology.Results195 prospective incident breast cancers had a prediction based on TC/DR/PRS which was informative for subsequent breast cancer overall [IQ-OR 2.25 (95% CI 1.89-2.68)] with excellent calibration-(0.99). The model performed particularly well in predicting higher stage stage 2+ IQ-OR 2.69 (95% CI 2.02-3.60) and ER + BCs (IQ-OR 2.36 (95% CI 1.93-2.89)). DR was most predictive for HER2+ and stage 2+ cancers but did not discriminate as well between poor and extremely good prognosis BC as either Tyrer-Cuzick or PRS. In contrast, PRS gave the highest OR for incident stage 2+ cancers, [IQR-OR 1.79 (95% CI 1.30-2.46)].ConclusionsA combined approach using Tyrer-Cuzick/DR/PRS provides accurate risk stratification, particularly for poor prognosis cancers. This provides support for reducing the screening interval in high-risk women and increasing the screening interval in low-risk women defined by this model.

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