Kathryn P Lowry1, Amy Trentham-Dietz2, Clyde B Schechter3, Oguzhan Alagoz2,4, William E Barlow5, Elizabeth S Burnside6, Emily F Conant7, John M Hampton2, Hui Huang8, Karla Kerlikowske9, Sandra J Lee10, Diana L Miglioretti11,12, Brian L Sprague13, Anna N A Tosteson14, Martin J Yaffe15, Natasha K Stout16. 1. Department of Radiology, University of Washington, Seattle Cancer Care Alliance, Seattle, WA. 2. Carbone Cancer Center and Department of Population Health Sciences. 3. University of Wisconsin-Madison, Madison, WI; Department of Family and Social Medicine, Albert Einstein College of Medicine, Bronx, NY. 4. School of Medicine and Public Health, and Department of Industrial and Systems Engineering. 5. Cancer Research and Biostatistics, University of Washington, Seattle, WA. 6. Department of Radiology. 7. Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA. 8. Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA. 9. Departments of Medicine and Epidemiology and Biostatistics, University of California, San Francisco, CA. 10. Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA. 11. Division of Biostatistics, Department of Public Health Sciences, University of California Davis, Davis, CA. 12. Kaiser Permanente Washington Health Research Institute, Seattle, WA. 13. Departments of Surgery and Radiology, University of Vermont Cancer Center, University of Vermont Larner College of Medicine, Burlington, VT. 14. The Dartmouth Institute for Health Policy and Clinical Practice and Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH. 15. Departments of Medical Biophysics and Medical Imaging, University of Toronto, Toronto, Canada. 16. Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA.
Abstract
BACKGROUND: Digital breast tomosynthesis (DBT) is increasingly being used for routine breast cancer screening. We projected the long-term impact and cost-effectiveness of DBT compared to conventional digital mammography (DM) for breast cancer screening in the United States. METHODS: Three Cancer Intervention and Surveillance Modeling Network breast cancer models simulated US women ages 40 years and older undergoing breast cancer screening with either DBT or DM starting in 2011 and continuing for the lifetime of the cohort. Screening performance estimates were based on observational data; in an alternative scenario, we assumed 4% higher sensitivity for DBT. Analyses used federal payer perspective; costs and utilities were discounted at 3% annually. Outcomes included breast cancer deaths, quality-adjusted life-years (QALYs), false-positive examinations, costs, and incremental cost-effectiveness ratios (ICERs). RESULTS: Compared to DM, DBT screening resulted in a slight reduction in breast cancer deaths (range across models 0-0.21 per 1000 women), small increase in QALYs (1.97-3.27 per 1000 women), and a 24-28% reduction in false-positive exams (237-268 per 1000 women) relative to DM. ICERs ranged from $195 026 to $270 135 per QALY for DBT relative to DM. When assuming 4% higher DBT sensitivity, ICERs decreased to $130 533-$156 624 per QALY. ICERs were sensitive to DBT costs, decreasing to $78 731 to $168 883 and $52 918 to $118 048 when the additional cost of DBT was reduced to $36 and $26 (from baseline of $56), respectively. CONCLUSION: DBT reduces false-positive exams while achieving similar or slightly improved health benefits. At current reimbursement rates, the additional costs of DBT screening are likely high relative to the benefits gained; however, DBT could be cost-effective at lower screening costs.
BACKGROUND: Digital breast tomosynthesis (DBT) is increasingly being used for routine breast cancer screening. We projected the long-term impact and cost-effectiveness of DBT compared to conventional digital mammography (DM) for breast cancer screening in the United States. METHODS: Three Cancer Intervention and Surveillance Modeling Network breast cancer models simulated US women ages 40 years and older undergoing breast cancer screening with either DBT or DM starting in 2011 and continuing for the lifetime of the cohort. Screening performance estimates were based on observational data; in an alternative scenario, we assumed 4% higher sensitivity for DBT. Analyses used federal payer perspective; costs and utilities were discounted at 3% annually. Outcomes included breast cancer deaths, quality-adjusted life-years (QALYs), false-positive examinations, costs, and incremental cost-effectiveness ratios (ICERs). RESULTS: Compared to DM, DBT screening resulted in a slight reduction in breast cancer deaths (range across models 0-0.21 per 1000 women), small increase in QALYs (1.97-3.27 per 1000 women), and a 24-28% reduction in false-positive exams (237-268 per 1000 women) relative to DM. ICERs ranged from $195 026 to $270 135 per QALY for DBT relative to DM. When assuming 4% higher DBT sensitivity, ICERs decreased to $130 533-$156 624 per QALY. ICERs were sensitive to DBT costs, decreasing to $78 731 to $168 883 and $52 918 to $118 048 when the additional cost of DBT was reduced to $36 and $26 (from baseline of $56), respectively. CONCLUSION: DBT reduces false-positive exams while achieving similar or slightly improved health benefits. At current reimbursement rates, the additional costs of DBT screening are likely high relative to the benefits gained; however, DBT could be cost-effective at lower screening costs.
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