While many cancer risk prediction models have been developed, very few have been externally validated, and almost none are used routinely in clinical practice beyond identification of family risk. To address the gap in translation to practice, Rosner and colleagues simplified a summary of breast cancer risk factors, added mammographic breast density, and a 77 SNP polygenic risk score to predict 10-year risk of breast cancer. This simplified model performed well in external validation in the Mayo Mammography Health Study (AUC=0.687). Adding simplified questionnaire data and polygenic risk each improved performance over mammographic breast density and age. This approach can be easily implemented in routine mammography screening clinics.

Identification and management of cancer patients' financial concerns is essential as cancer care costs rise. McLouth and colleagues aimed to describe the prevalence of financial screening, sources of financial navigation services, and availability of cancer-specific financial navigators within the National Cancer Institute's...

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