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Long-Term Outcomes and Cost-Effectiveness of Breast Cancer Screening With Digital Breast Tomosynthesis in the United States

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.

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References
1.
Schechter C, Near A, Jayasekera J, Chandler Y, Mandelblatt J . Structure, Function, and Applications of the Georgetown-Einstein (GE) Breast Cancer Simulation Model. Med Decis Making. 2018; 38(1_suppl):66S-77S. PMC: 5862062. DOI: 10.1177/0272989X17698685. View

2.
Rose S, Tidwell A, Bujnoch L, Kushwaha A, Nordmann A, Sexton Jr R . Implementation of breast tomosynthesis in a routine screening practice: an observational study. AJR Am J Roentgenol. 2013; 200(6):1401-8. DOI: 10.2214/AJR.12.9672. View

3.
Alagoz O, Ergun M, Cevik M, Sprague B, Fryback D, Gangnon R . The University of Wisconsin Breast Cancer Epidemiology Simulation Model: An Update. Med Decis Making. 2018; 38(1_suppl):99S-111S. PMC: 5862066. DOI: 10.1177/0272989X17711927. View

4.
Zuckerman S, Conant E, Keller B, Maidment A, Barufaldi B, Weinstein S . Implementation of Synthesized Two-dimensional Mammography in a Population-based Digital Breast Tomosynthesis Screening Program. Radiology. 2016; 281(3):730-736. PMC: 5131829. DOI: 10.1148/radiol.2016160366. View

5.
Mandelblatt J, Near A, Miglioretti D, Munoz D, Sprague B, Trentham-Dietz A . Common Model Inputs Used in CISNET Collaborative Breast Cancer Modeling. Med Decis Making. 2018; 38(1_suppl):9S-23S. PMC: 5862072. DOI: 10.1177/0272989X17700624. View