Population-based Genetic Testing for Precision Prevention
- PMID: 32409595
- DOI: 10.1158/1940-6207.CAPR-20-0002
Population-based Genetic Testing for Precision Prevention
Abstract
Global interest in genetic testing for cancer susceptibility genes (CSG) has surged with falling costs, increasing awareness, and celebrity endorsement. Current access to genetic testing is based on clinical criteria/risk model assessment which uses family history as a surrogate. However, this approach is fraught with inequality, massive underutilization, and misses 50% CSG carriers. This reflects huge missed opportunities for precision prevention. Early CSG identification enables uptake of risk-reducing strategies in unaffected individuals to reduce cancer risk. Population-based genetic testing (PGT) can overcome limitations of clinical criteria/family history-based testing. Jewish population studies show population-based BRCA testing is feasible, acceptable, has high satisfaction, does not harm psychologic well-being/quality of life, and is extremely cost-effective, arguing for changing paradigm to PGT in the Jewish population. Innovative approaches for delivering pretest information/education are needed to facilitate informed decision-making for PGT. Different health systems will need context-specific implementation strategies and management pathways, while maintaining principles of population screening. Data on general population PGT are beginning to emerge, prompting evaluation of wider implementation. Sophisticated risk prediction models incorporating genetic and nongenetic data are being used to stratify populations for ovarian cancer and breast cancer risk and risk-adapted screening/prevention. PGT is potentially cost-effective for panel testing of breast and ovarian CSGs and for risk-adapted breast cancer screening. Further research/implementation studies evaluating the impact, clinical efficacy, psychologic and socio-ethical consequences, and cost-effectiveness of PGT are needed.
©2020 American Association for Cancer Research.
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