Mammography Facility Characteristics Associated With Interpretive Accuracy of Screening Mammography
Stephen Taplin, Linn Abraham, William E. Barlow, Joshua J. Fenton, Eric A. Berns, Patricia A. Carney, Gary R. Cutter, Edward A. Sickles, D'Orsi Carl, and Joann G. Elmore
J. Natl. Cancer Inst. 2008 100: 876-887
Link to Journal (Open Access Article)
Previous studies have suggested that patient characteristics, such as age, are associated with variations in the accuracy of screening mammograms. Similarly, characteristics of the radiologist who interprets the mammograms, such as his or her reading experience, are associated with variations in accuracy.
Stephen Taplin, M.D., of the National Cancer Institute in Bethesda, Md., and colleagues surveyed 53 mammography facilities between 1992 and 2002 to look for associations between facility characteristics and interpretive accuracy. The researchers were able to analyze data from 44 facilities, which altogether performed 484,463 screening mammograms on 237,669 women. Of those, 2,686 women were diagnosed with breast cancer.
Several facility characteristics were associated with a higher measure of accuracy that combines sensitivity and specificity, including those that offered screening mammograms alone versus those that offered diagnostic and screening mammograms, and those that had a breast imaging specialist reading the mammograms versus those that did not.
The facilities varied statistically significantly in specificity (P < .001), PPV1 (P < .001), and PPV2 (P = .002) but not in sensitivity (P = .99). AUC was higher among facilities that offered screening mammograms alone vs those that offered screening and diagnostic mammograms (0.943 vs 0.911, P = .006), had a breast imaging specialist interpreting mammograms vs not (0.932 vs 0.905, P = .004), did not perform double reading vs independent double reading vs consensus double reading (0.925 vs 0.915 vs 0.887, P = .034), or conducted audit reviews two or more times per year vs annually vs at an unknown frequency (0.929 vs 0.904 vs 0.900, P = .018).
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