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Cost-Effectiveness of Digital Mammography Breast Cancer Screening

Anna N.A. Tosteson, ScD; Natasha K. Stout, PhD; Dennis G. Fryback, PhD; Suddhasatta Acharyya, PhD; Benjamin A. Herman, SM; Lucy G. Hannah, MS, MAT; Etta D. Pisano, MD, DMIST Investigators
[+] Article, Author, and Disclosure Information

For a list of the DMIST clinical sites, principal investigators, and lead physicists, see the Appendix.

From The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth Medical School, Lebanon, New Hampshire; Harvard School of Public Health, Boston, Massachusetts; University of Wisconsin, Madison, Wisconsin; Brown University, Providence, Rhode Island; and University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.

Grant Support: By National Cancer Institute grants CA80098, CA79778, and CA88211.

Potential Financial Conflicts of Interest:Consultancies: D.G. Fryback (Dartmouth College). Grants received: D.G. Fryback (ACRIN). Institutional: D.G. Fryback (University of Wisconsin, which offers digital mammography services); E.D. Pisano (University of North Carolina, which receives research support from GE).

Reproducible Research Statement: DMIST contact personnel: http://www.acrin.org/PROTOCOLSUMMARYTABLE/PROTOCOL6652/6652ContactPersonnel/tabid/393/Default.aspx. Study protocol: Partial protocol (with information on how to obtain the full protocol) is available at http://www.acrin.org/Portals/0/Protocols/6652/A6652partial_summary.pdf. Statistical code and data set: Available with restriction in accordance with the ACRIN data-sharing policies at http://www.acrin.org/RESEARCHERS/POLICIES/DATAANDIMAGESHARINGPOLICY/DATAACCESSPOLICYDOCUMENT/tabid/475/Default.aspx.

Requests for Single Reprints: Anna N.A. Tosteson, ScD, Clinical Research HB7505, Dartmouth Medical School, One Medical Center Drive, Lebanon, NH 03756; e-mail, anna.tosteson@dartmouth.edu.

Current Author Addresses: Dr. Tosteson: Dartmouth Medical School, One Medical Center Drive, Lebanon, NH 03756.

Dr. Stout: Program in Health Decision Science, Department of Health Policy and Management, 718 Huntington Avenue, Harvard School of Public Health, Boston, MA 02115.

Dr. Fryback: Departments of Population Health Sciences and of Industrial and Systems Engineering, University of Wisconsin, 610 Walnut Street, Room 685, Madison, WI 53726.

Dr. Acharyya, Mr. Herman, and Ms. Hannah: Statistical Sciences Center, Brown University, Box G-121-7, 121 South Main Street, Providence, RI 02912.

Dr. Pisano: Department of Radiology and Biomedical Engineering of the Lineberger Comprehensive Cancer Center and Biomedical Research Imaging Center, CB700, 4th Floor, Bondurant Hall, Dean's Office, University of North Carolina School of Medicine, Chapel Hill, NC 27599.

Author Contributions: Conception and design: A.N.A. Tosteson, D.G. Fryback, E.D. Pisano.

Analysis and interpretation of the data: A.N.A. Tosteson, N.K. Stout, D.G. Fryback, S. Acharyya, B.A. Herman, L. Hannah, E.D. Pisano.

Drafting of the article: A.N.A. Tosteson, N.K. Stout, D.G. Fryback, S. Acharyya, B.A. Herman.

Critical revision of the article for important intellectual content: A.N.A. Tosteson, N.K. Stout, D.G. Fryback, S. Acharyya, B.A. Herman, E.D. Pisano.

Final approval of the article: A.N.A. Tosteson, N.K. Stout, D.G. Fryback, S. Acharyya, B.A. Herman, L. Hannah, E.D. Pisano.

Provision of study materials or patients: E.T. Pisano.

Statistical expertise: A.N.A. Tosteson, D.G. Fryback, S. Acharyya, B.A. Herman, L. Hannah.

Obtaining of funding: A.N.A. Tosteson, E.D. Pisano.

Administrative, technical, or logistic support: A.N.A. Tosteson, N.K. Stout, D.G. Fryback, B.A. Herman.

Collection and assembly of data: B.A. Herman, L. Hannah.

Ann Intern Med. 2008;148(1):1-10. doi:10.7326/0003-4819-148-1-200801010-00002
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We used a validated, computer-based breast cancer natural history model (7) to project the probable effect that breast cancer detection with digital mammography would have on U.S. women age 40 years or older in 2000. The model incorporated DMIST data on mammography performance characteristics and work-up resource use. The strategies considered among women undergoing screening were all-film mammography (done in all women); targeted digital mammography, which includes age-targeted (digital for women <50 years of age and film for women ≥50 years of age) and age- and density-targeted mammography (digital for women <50 years of age or those ≥50 years of age with radiographically dense breasts and film for all others); and all-digital mammography (done in all women) (Figure 1). For women age 65 years or older (the Medicare population subgroup), the analysis was repeated for all-film mammography, density-targeted mammography (digital for women with dense breasts and film for others), and all-digital mammography screening. To evaluate digital mammography, each digital screening strategy was substituted for all-film screening in 2000 and applied to future years until all women age 40 years or older in 2000 died. Simulated years beyond 2000 included breast cancer risk, mammography use, and adjuvant therapy and were maintained at patterns from 2000 because the natural history model was validated on the basis of data available through this period (7). For each screening strategy, each woman's costs and health outcomes were counted from 2000 until her death at a 3% annual discount rate (8). Simulations computing total costs and quality-adjusted life-years (QALYs) by using the same period and population were completed for each screening scenario. Screening strategies were ranked according to increasing mean total costs and incremental costs and then changes in QALYs, and incremental cost-effectiveness ratios were computed for each more costly strategy (8). Mean cost per QALY gained and 95% CIs were computed from 50 independent simulations. The implications of alternative assumptions about mammography sensitivity, breast density, and the cost of digital mammography on the cost-effectiveness of the screening strategies were evaluated in sensitivity analyses.

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Figure 1.
Flow diagram of screening strategies evaluated.

Each year, women enter a film or digital simulation on the basis of breast density and current age.

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Figure 2.
Effect of digital mammography cost on the incremental cost-effectiveness ratio (ICER).

The cost of digital mammography may be interpreted as a premium compared with film mammography, in which $98 represents a $12 premium and $135 represents a $50 premium over film mammography. The ICER for age- and density-targeted screening is computed relative to age-targeted screening. The ICERs for all other strategies are computed relative to film mammography screening. QALY = quality-adjusted life-year.

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