Julie A Lynch1,2, Brygida Berse2,3,4, Valentina Petkov5, Kelly Filipski5, Yingjun Zhou5, Muin J Khoury6,7, Michael Hassett8, Andrew N Freedman5. 1. VA Salt Lake City Health Care System, Salt Lake City, Utah, USA. 2. RTI International, Research Triangle Park, Durham, North Carolina, USA. 3. Boston University School of Medicine, Boston, Massachusetts, USA. 4. Veterans Health Administration, Bedford, Massachusetts, USA. 5. National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA. 6. Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, Georgia, USA. 7. Epidemiology and Genomics Research Program, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA. 8. Dana Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA.
Abstract
PURPOSE: We examined hospital use of the 21-gene breast cancer test in the United States. We report state-level differences in utilization and propose a model for predicting implementation of guideline-recommended genomic testing. METHODS: Genomic Health provided test orders for calendar year 2011.We summarized utilization at the hospital and state levels. Using logistic regression, we analyzed the association between the likelihood to order the test and the hospital's institutional and regional characteristics. RESULTS: In 2011, 45% of 4,712 acute-care hospitals ordered the test, which suggests that 25% of newly diagnosed invasive female breast cancer cases were tested. Significant predictors of testing included participation in National Cancer Institute (NCI) clinical research cooperative groups (odds ratio (OR) 3.73; 95% confidence interval, 2.96-4.70), advanced imaging (OR, 2.19; CI, 1.78-2.68), high-complexity laboratory (OR, 2.15; CI, 1.24-3.70), affiliation with a medical school (OR, 1.57; CI, 1.31-1.88), and reconstructive surgery (OR, 1.23; CI, 1.01-1.50). Significant regional predictors included metropolitan county (OR, 3.77; CI, 2.83-5.03), above-mean income (OR, 1.37; CI, 1.11-1.69), and education (OR, 1.26; CI, 1.03-1.54). Negative predictors included designation as a critical-access hospital (OR, 0.10; CI, 0.07-0.14) and distance from an NCI cancer center (OR, 0.998; CI, 0.997-0.999), with a 15% decrease in likelihood for every 100 miles. CONCLUSION: Despite considerable market penetration of the test, there are significant regional and site-of-care differences in implementation, particularly in rural states.Genet Med 18 10, 982-990.
PURPOSE: We examined hospital use of the 21-gene breast cancer test in the United States. We report state-level differences in utilization and propose a model for predicting implementation of guideline-recommended genomic testing. METHODS: Genomic Health provided test orders for calendar year 2011.We summarized utilization at the hospital and state levels. Using logistic regression, we analyzed the association between the likelihood to order the test and the hospital's institutional and regional characteristics. RESULTS: In 2011, 45% of 4,712 acute-care hospitals ordered the test, which suggests that 25% of newly diagnosed invasive female breast cancer cases were tested. Significant predictors of testing included participation in National Cancer Institute (NCI) clinical research cooperative groups (odds ratio (OR) 3.73; 95% confidence interval, 2.96-4.70), advanced imaging (OR, 2.19; CI, 1.78-2.68), high-complexity laboratory (OR, 2.15; CI, 1.24-3.70), affiliation with a medical school (OR, 1.57; CI, 1.31-1.88), and reconstructive surgery (OR, 1.23; CI, 1.01-1.50). Significant regional predictors included metropolitan county (OR, 3.77; CI, 2.83-5.03), above-mean income (OR, 1.37; CI, 1.11-1.69), and education (OR, 1.26; CI, 1.03-1.54). Negative predictors included designation as a critical-access hospital (OR, 0.10; CI, 0.07-0.14) and distance from an NCI cancer center (OR, 0.998; CI, 0.997-0.999), with a 15% decrease in likelihood for every 100 miles. CONCLUSION: Despite considerable market penetration of the test, there are significant regional and site-of-care differences in implementation, particularly in rural states.Genet Med 18 10, 982-990.
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