Cited by 678Digital Radiography and Breast ImagingAI in cancer detectionGlobal Cancer Incidence and Screening

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Diagnostic Accuracy of Digital Screening Mammography With and Without Computer-Aided Detection

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Lehman, Constance D., Wellman, Robert D., Buist, Diana S. M., Kerlikowske, Karla, Tosteson, Anna N. A., Miglioretti, Diana L.·2015·JAMA Internal Medicine

DOI 10.1001/jamainternmed.2015.5231PMC PMC4836172

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Abstract

IMPORTANCE: After the US Food and Drug Administration (FDA) approved computer-aided detection (CAD) for mammography in 1998, and the Centers for Medicare and Medicaid Services (CMS) provided increased payment in 2002, CAD technology disseminated rapidly. Despite sparse evidence that CAD improves accuracy of mammographic interpretations and costs over $400 million a year, CAD is currently used for most screening mammograms in the United States. OBJECTIVE: To measure performance of digital screening mammography with and without CAD in US community practice. DESIGN, SETTING, AND PARTICIPANTS: We compared the accuracy of digital screening mammography interpreted with (n = 495 818) vs without (n = 129 807) CAD from 2003 through 2009 in 323 973 women. Mammograms were interpreted by 271 radiologists from 66 facilities in the Breast Cancer Surveillance Consortium. Linkage with tumor registries identified 3159 breast cancers in 323 973 women within 1 year of the screening. MAIN OUTCOMES AND MEASURES: Mammography performance (sensitivity, specificity, and screen-detected and interval cancers per 1000 women) was modeled using logistic regression with radiologist-specific random effects to account for correlation among examinations interpreted by the same radiologist, adjusting for patient age, race/ethnicity, time since prior mammogram, examination year, and registry. Conditional logistic regression was used to compare performance among 107 radiologists who interpreted mammograms both with and without CAD. RESULTS: Screening performance was not improved with CAD on any metric assessed. Mammography sensitivity was 85.3% (95% CI, 83.6%-86.9%) with and 87.3% (95% CI, 84.5%-89.7%) without CAD. Specificity was 91.6% (95% CI, 91.0%-92.2%) with and 91.4% (95% CI, 90.6%-92.0%) without CAD. There was no difference in cancer detection rate (4.1 in 1000 women screened with and without CAD). Computer-aided detection did not improve intraradiologist performance. Sensitivity was significantly decreased for mammograms interpreted with vs without CAD in the subset of radiologists who interpreted both with and without CAD (odds ratio, 0.53; 95% CI, 0.29-0.97). CONCLUSIONS AND RELEVANCE: Computer-aided detection does not improve diagnostic accuracy of mammography. These results suggest that insurers pay more for CAD with no established benefit to women.

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Self-citation
Considerations for Evaluating the Introduction of New Cancer Screening Technology: Use of Interval Cancers to Assess Potential Benefits and Harms
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Authors: Lehman, C. D., Wellman, R. D., Buist, D. S. M., Kerlikowske, K., Tosteson, A. N. A., & Miglioretti, D. L.
Affiliations: Massachusetts General Hospital (US)
Kaiser Permanente Washington Health Research Institute (US)
University of California, San Francisco (US)
Dartmouth College (US)
Corresponding author: Lehman, Constance D.
ORCID: Lehman, Constance D.
Wellman, Robert D.
Buist, Diana S. M.
Kerlikowske, Karla
Tosteson, Anna N. A.
Miglioretti, Diana L.
Venue: JAMA Internal Medicine
Publisher: American Medical Association (AMA)
Published: 2015-11-01
Volume: 175
Issue: 11
Pages: 1828
ISSN: 2168-6106 (ISSN-L)
DOI: 10.1001/jamainternmed.2015.5231
PMC: PMC4836172
OpenAlex: W1917647701
Cited by: 678
References: 44
Citations by year: 2026: 38 · 2025: 76 · 2024: 81 · 2023: 92 · 2022: 95 · 2021: 86 · 2020: 72 · 2019: 59 · 2018: 35 · 2017: 27 · 2016: 14 · 2015: 1
FWCI: 20.30
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: JAMA Internal Medicine (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
eScholarship (California Digital Library) (submittedVersion)
Funders: National Cancer Institute (HHSN261201100031C, U54CA163303, P30CA023108, P01CA154292)
Topics: Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Digital Radiography and Breast Imaging
Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
Keywords: computer-aided detection, digital mammography, breast cancer screening, diagnostic accuracy, mammography sensitivity, screen-detected breast cancer, interval breast cancer, Breast Cancer Surveillance Consortium, community practice, radiologist interpretation, breast cancer detection rate, mammography quality assurance
MeSH terms: Adult, Aged, Aged, 80 and over, Breast Neoplasms, Female, Humans, Mammography, Mass Screening, Middle Aged, Radiographic Image Interpretation, Computer-Assisted, Registries, Sensitivity and Specificity, United States, Reproducibility of Results, Logistic Models, Early Detection of Cancer

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Diagnostic Accuracy of Digital Screening Mammography With and Without Computer-Aided Detection

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