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Precision Medicine & Health Applications

The growing applications of precision medicine

Working towards treatments and approaches to care that are more targeted, more successful, and more cost-effective

Applying Precision Health Initiatives

Applications of precision medicine can help save lives, proactively inform people about genetic risk, reduce health care costs, and improve quality of life. Awareness of future risk could be fundamental for wellness given that genomics plays a role in 9 of the 10 leading causes of death.1

As we learn how certain exposures (environmental, behavioral, etc.) and socio-economic inequities are exacerbating genomic pre-conditions, we can take action to modify the potential impact. A cohesive strategy combining precision medicine with public health and wellness initiatives can help to reduce disease burden and provide better healthcare outcomes.

Assess Hereditary Cancer Risk

Identifying mutations that predispose individuals to cancer can support prevention to reduce the likelihood of developing cancer. Hereditary mutations play an important role in cancer risk and susceptibility.

  • Nearly 1.5% of the population6 and 20% of patients with advanced cancer7 carry a pathogenic variant
  • Population screening has the potential to reduce variant attributable cancer deaths by 31%8
  • Risk-stratified breast cancer screening could have 71% fewer overdiagnoses and 10% fewer deaths while saving costs9
Learn More About Cancer Risk
Predicting Cancer Predisposition

City of Hope scientists use NGS to understand the polygenicity of cancer, predict hereditary cancer risk, and tailor precision prevention.

Contact us to get help implementing precision health applications in your institution.
References
  1. Wakap SN et al. Estimating cumulative point prevalence of rare diseases: analysis of the Orphanet database. Eur J Hum Genet. 2020;28(2):165-173.
  2. Tabor HK et al. Pathogenic variants for Mendelian and complex traits in exomes of 6,517 European and African Americans: implications for the return of incidental results. Am J Hum Genet. 2014; 95(2):183-93.
  3. Bush WS et al. Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network. Clin Pharmacol Ther. 2016; 100(2):160-9.
  4. The NIH U.S. National Library of Medicine. ClinicalTrials.gov. Accessed June 26, 2020.
  5. US Food & Drug Administration. Table of Pharmacogenomic Biomarkers in Drug Labeling. Fda.gov. Published February 5, 2020.
  6. Geisinger MyCode Project.geisinger.org. (Based on 2/1/2021 data with 62,434 cases analyzed for clinical review.)
  7. Mandelker D et al. Mutation Detection in Patients with Advanced Cancer by Universal Sequencing of Cancer-Related Genes in Tumor and Normal DNA vs Guideline-Based Germline Testing. JAMA. 2017;318(9):825-835.
  8. Zhang L et al. Population genomic screening of all young adults in a health-care system: a cost-effectiveness analysis. Genet Med. 2019;21(9):1958-1968.
  9. Pashayan N et al. Cost-effectiveness and Benefit-to-Harm Ratio of Risk-Stratified Screening for Breast Cancer: A Life-Table Model. JAMA Oncol. 2018; 4(11):1504-1510.
  10. Wakap SN et al. Estimating cumulative point prevalence of rare diseases: analysis of the Orphanet database. Eur J Hum Genet. 2020;28(2):165-173.
  11. Online Mendelian Inheritance in Man® Gene Map Statistics. omim.org. Accessed 3/1/2021.
  12. Tabor HK et al. Pathogenic variants for Mendelian and complex traits in exomes of 6,517 European and African Americans: implications for the return of incidental results. Am J Hum Genet. 2014; 95(2):183-93.
  13. Bush WS et al. Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network. Clin Pharmacol Ther. 2016; 100(2):160-9.
  14. van der Wouder CH et al. Pharmacist-Initiated Pre-Emptive Pharmacogenetic Panel Testing with Clinical Decision Support in Primary Care: Record of PGx Results and Real-World Impact. Genes. 2019;10(6):416.
  15. Fagerness J et al. Pharmacogenetic-guided psychiatric intervention associated with increased adherence and cost savings. Am J Manag Care. 2014;20(5):e146-56.
  16. Watanabe JH et al. Cost of Prescription Drug-Related Morbidity and Mortality. Ann Pharmacother. 2018;52(9):829-837.
  17. CPIC Guidelines. Cpicpgx.org. Accessed August 11, 2020.
  18. Bianchi DW, Parker RL, Wentworth J, et al; for CARE Study Group. DNA sequencing versus standard prenatal aneuploidy screening. N Engl J Med. 2014;370(9):799-808.
  19. Office of Disease Prevention and Health Promotion. Genomics. Healthypeople.gov. Accessed 3/1/2021.
  20. Centers for Disease Control and Prevention. Leading causes of Death. CDC.gov. Accessed 3/1/2021.