Precision Medicine Policy and Treatment (PreEMPT) Model II

项目总结/文摘

PROJECT SUMMARY/ABSTRACT Integration of genomic sequencing into everyday medical practice has already begun. In our first funding period, Precision Medicine Policy and Treatment Model (PreEMPT) I, we began exploring the benefits and risks associated with genomic sequencing in newborns, which has compelling logic: It can provide clinically actionable insights to prevent illness altogether or to facilitate early detection of illnesses in childhood or adulthood. Notwithstanding the clinical utility of newborn genomic sequencing and cascade testing of family members, questions remain: cost-effectiveness of newborn genomic sequencing, long-term effects on disease morbidity and mortality, and diagnostic and treatment-related costs. These knowledge gaps are important to fill, given expectations about widespread applications of genomic sequencing. Our proposed research will create PreEMPT II by extending our existing computer microsimulation model developed in PreEMPT I to reflect the impact of newborn genomic sequencing on a wider array of childhood- onset diseases and their long-term consequences into adulthood. Additionally, we will refine our approach to considering the impact of targeted screening of siblings of children with pathogenic variants. Previously, we developed a framework to evaluate newborn genomic sequencing for pediatric cancer and cardiac diseases. In this renewal, we will extend this framework to evaluate the clinical benefits and cost-effectiveness for metabolic diseases such as Pompe disease and biotinidase deficiency, and other diseases such as malignant hyperthermia. To highlight critical knowledge gaps, we will use value of information analysis to identify high- priority research studies within the rapidly evolving area of genomic medicine with a focus on addressing race- based health disparities. We will enhance our existing simulation model to synthesize the best available clinical, epidemiologic and economic data, and use our analytic framework to project both short- and long-term outcomes associated with alternative screening strategies and assess the potential value of genomic sequencing in reducing racial disparities in disease outcomes. Our interdisciplinary team includes experts in simulation modeling, health economics, genomics, pediatrics, predictive modeling, health policy, and health systems research. We propose a highly innovative application of modeling methods to genomic technologies with the goal of synthesizing available clinical and epidemiological data into a unified modeling effort. The goal is to project long-term outcomes by incorporating evolving data in the area of genomic sequencing for newborns, permitting ready evaluation and guidance for clinical care in the United States over the next decades.