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Last Posted: Jun 27, 2024
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Harnessing population-wide health data to predict cancer risk

From the article: "In an era of big data and efficient computing, the development of complex risk models has become substantially easier than assessing whether, how, and in what context they are useful. The 1976 observation by George E P Box that “All models are wrong but some are useful remains equally true nearly 50 years later. Only time will tell whether the impressive advances since Box's observation in our ability to build risk models will ultimately prove useful for cancer prevention. "

Challenges and opportunities for Lynch syndrome cascade testing in the United States.
Lauren E Passero et al. Fam Cancer 2024 3

From the abstract: " Lynch syndrome is an underdiagnosed genetic condition that increases lifetime colorectal, endometrial, and other cancer risk. Cascade testing in relatives is recommended to increase diagnoses and enable access to cancer prevention services, yet uptake is limited due to documented multi-level barriers. Individual barriers such as feelings of fear, guilt, and anxiety and limited knowledge about Lynch syndrome as well as interpersonal barriers including complex family dynamics and language barriers limit family communication about Lynch syndrome and prevent uptake of genetic screening for relatives. Organizational and environmental barriers including a shortage of genetics professionals, high costs, and fears of discrimination also reduce cascade testing. These multi-level barriers may disproportionately impact underserved populations in the United States,"

Cost-Effectiveness of Population-Based Multigene Testing for Breast and Ovarian Cancer Prevention.
Fangjian Guo et al. JAMA Netw Open 2024 2 (2) e2356078

From the abstract: "Is a population-wide genetic testing strategy more cost-effective than the current family history–based testing strategy for breast and ovarian cancer prevention? This economic evaluation found that population-based BRCA1, BRCA2, and PALB2 testing among unselected women was cost-effective for the prevention of breast and ovarian cancer and remained cost-effective in extensive 1-way sensitivity analyses. Population-wide genetic testing was 100% cost-effective for all the simulations in probabilistic sensitivity analyses; it became cost-inefficient only when the cost of the test exceeded a certain threshold ($825). The findings support the need for a shift toward more comprehensive genetic testing strategies to identify pathogenic variant carriers and enable informed decision-making for personalized risk management. "

A population-level digital histologic biomarker for enhanced prognosis of invasive breast cancer.
Mohamed Amgad et al. Nat Med 2023 11

From the abstract: " Here we present the Histomic Prognostic Signature (HiPS), a comprehensive, interpretable scoring of the survival risk incurred by breast tumor microenvironment morphology. HiPS uses deep learning to accurately map cellular and tissue structures to measure epithelial, stromal, immune, and spatial interaction features. It was developed using a population-level cohort from the Cancer Prevention Study-II and validated using data from three independent cohorts."

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Disclaimer: Articles listed in the Public Health Genomics and Precision Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.

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