Abstract IA40: Maximizing the benefits of precision medicine for cancer disparities

Abstract

Abstract Disparities, defined as differences that are unnecessary and avoidable, exist in cancer incidence, mortality, and survival. They occur by race/ethnicity, socioeconomic status, geography (rural versus urban), and other factors. Although cancer deaths for all types of cancer decreased for both African-Americans and whites in the United States between 1999 and 2011, for example, African-American males and females had both higher cancer incidence and cancer mortality than white males and females and showed less marked improvement over that time period. Warnecke and colleagues published a multi-level framework of the determinants of cancer disparities that included three basic levels, namely distal, intermediate, and proximal.1 Distal determinants include population-level social conditions such as variation in rates of disease or poverty. Their roots are embedded in shared social norms or social practices and socioeconomic disadvantage. Intermediate determinants include the immediate social and physical contexts and social relationships in which distal effects are experienced, such as neighborhoods. Proximal determinants include biological and genetic factors and individual-level factors like health behavior. The sequencing of the human genome and increased understanding of its function have allowed the identification of genetic variants that lead to common diseases like cancer. Yet, awareness is growing, too, that genetic variants alone cannot account for cancer expression and outcomes. Consistent with the Warnecke et al. framework, it seems to be the case that social, environmental, and behavioral factors interact with genetic predisposition to produce disease, and that differential exposures and behaviors across populations and subpopulations might help to explain cancer disparities. Both the genetic variants and the exposures and behaviors must be present to produce cancers. The Precision Medicine Initiative (PMI), announced by President Obama on January 30, 2015 seeks to advance our understanding of genetic variations within diseases and develop treatments for them, beginning with cancer. President Obama requested $215 million in the next fiscal year to collect genetic data and data from electronic medical records, lab test results, and information about diet, tobacco use, lifestyle, and environment on 1,000,000 Americans. In this presentation, we argue that while the PMI has the potential to reduce cancer disparities: (1) preventing cancer and reducing death rates for everyone in the population requires collecting and analyzing consistent, accurate, reliable, and sufficiently detailed data that represent all segments of the population and that (2) developing risk assessments and interventions that are effective for everyone requires evidence on the distribution and impact of causes across subpopulations. Collecting and analyzing data that represents all segments of the population poses significant challenges essential for the PMI to contribute to decreasing disparities in cancer and other common diseases. Minority groups historically have had low participation in research, such as in clinical research trials. The 1993 NIH Revitalization Act (http://orwh.od.nih.gov/about/pdf/NIH-Revitalization-Act-1993.pdf) established a mandate that funded research would be based on valid analysis of whether the variables being studied in the trial affect minority groups. Yet a 2014 review found that only 20% of randomized controlled studies in a major cancer journal reported analyzing results by race/ethnicity.2 Likewise, a survey of its members and the general public by the American Association for the Advancement of Science (AAAS) found that while 92% of AAAS scientists considered US scientific achievement to be the best in the world or above average, only 54% of the public endorsed this ranking.3 The presentation will conclude with two recommendations for improving the PMI's role in eliminating cancer and other disparities. First, make the effort to recruit a cohort that reflects the US population in terms of race/ethnicity, socioeconomic status, and geography. Second, do not recruit entirely from clinic populations or rely entirely on electronic medical records for social data, because this will miss those most without consistent health care, a group for whom disparities are rife. In addition, for Precision Medicine practice to contribute to the elimination of disparities, it will be important that: (1) the cost of genetic testing is covered under Medicaid, other public insurance, and less generous marketplace insurance plans; (2) the collection of social variables be systematized so that they capture the lives of minority groups; and (3) the capacity of genetic counseling is increased and that counseling services are available to all who have genetic testing.