The Promise of Population-based Genomic Screening for Selected Hereditary Conditions: Contributions of Cost-Effectiveness Analysis

Posted on by Nandana D. Rao, Lu Shi, Muin J. Khoury, Office of Genomics and Precision Public Health, National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, Georgia

individuals connected with DNA and dollar bills in the backgroundIt is estimated that 3 million people in the United States carry pathogenic variants that increase their risks for heart disease and cancer. If people with such variants are identified, medical interventions are available to significantly reduce morbidity and mortality. However, existing recommendations tend to emphasize family-based or ethnic-specific criteria to determine at-risk individuals for testing, which can miss most of the affected persons in the population. More recently, researchers and public health professionals have been considering population genomic screening, or offering genetic testing to people regardless of their personal or family history of disease, to identify adults who could benefit from early intervention. However, before implementing population genomic screening programs, it is helpful to have data from cost-effectiveness analysis to inform policy and practice decisions.

Cost-Effectiveness Analysis in Public Health Genomics

  • Cost-effectiveness models are used to evaluate the health outcomes and economic costs of interventions.
  • Models can compare a new health intervention to previous standards of care or to no care.
  • Cost-effectiveness analysis depends on the parameters included in models, such as the price of implementing a health intervention and the effect of an intervention on health outcomes. Sensitivity analyses are used to understand how variation in parameters can impact model results.
  • For more information, please attend our October 26 webinar on cost-effectiveness analysis in public health genomics

 

A recent study examined the cost-effectiveness of simultaneous genomic screening of U.S. adults for three CDC Tier 1 genomic applications, hereditary breast and ovarian cancer, Lynch syndrome, and familial hypercholesterolemia, compared to usual care where people receive genetic testing based on personal or family history. Tier 1 genomic applications are those with a significant potential to positively impact public health.

Study models considered factors such as age at screening, prevalence and penetrance of disease associated variants in the population, and uptake and efficacy of risk-reducing interventions if a disease-associated variant is detected through screening. Models also accounted for costs of genetic screening panels and any subsequent care, as well as resultant cascade testing (genetic testing of biological relatives of individuals carrying a disease associated genetic variant).

The study found that population genomic screening focused on pathogenic variants associated with hereditary breast and ovarian cancer, Lynch syndrome, and familial hypercholesterolemia is likely cost-effective compared to usual care in U.S. adults younger than 40 years. This finding assumes a relatively low cost for genomic screening (around $250 for a screening test) and that individuals identified with genetic risk have access to preventive care. Model results also showed that screening per 100,000 unselected 30-year-olds could result in approximately 101 fewer overall cancer cases and 15 fewer cardiovascular events.

Challenges of Cost-Effectiveness Analysis in Public Health Genomics

Cost-effectiveness analyses are highly dependent on model parameters. Accurately quantifying, evaluating, and citing the sources of costs and parameters are essential to assess the validity of cost-effectiveness analysis. In the previously discussed study, variant prevalence and penetrance parameters were primarily based on estimates from cohorts of European ancestry. Therefore, study results may not translate well to populations including more individuals with non-European ancestry. Model inputs related to uptake of risk-reducing interventions or preventive treatments may also not adequately reflect all health care experiences, particularly for individuals or communities that may face economic, insurance, logistic, or other barriers to care. Other factors that influence screening cost, such as provider or genetic counseling time, were not considered in detail in study models.

For population genomic screening cost-effectiveness estimates to reflect real-world costs more accurately, realistic model parameters are needed. Therefore, there is a need for continued research on genetic variation, population genomic screening implementation, and access to care in a diversity of populations and settings.

Public Health Implications

Initial cost-effectiveness research suggests that population genomic screening related to Tier 1 applications can be cost effective and reduce morbidity and mortality if implemented in adults younger than 40 years old, costs of screening tests are low, and those found carrying a pathogenic variant have access to preventive care. As more data are gathered from screening trials about variant penetrance and health behaviors and outcomes after screening, updates to cost-effectiveness model parameters can lead to improved estimates about cost, effects on quality of life, and overall impact on public health. Inclusion of data from populations of a variety of backgrounds and circumstances will make cost-effectiveness estimates more representative and promote equitable implementation of population-based genomic screening.

 


Posted on by Nandana D. Rao, Lu Shi, Muin J. Khoury, Office of Genomics and Precision Public Health, National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, GeorgiaTags ,
Page last reviewed: July 14, 2023
Page last updated: July 14, 2023