BACKGROUND: Countries with centralized, high-volume mammography screening programs, such as the U.K. and Sweden, emphasize high specificity (low percentage of false positives) and high sensitivity (high percentage of true positives). By contrast, the United States does not have centralized, high-volume screening programs, emphasizes high sensitivity, and has lower average specificity. We investigated whether high sensitivity can be achieved in the context of high specificity and whether the number of mammograms read per radiologist (reader volume) drives both sensitivity and specificity. METHODS: The U.K.'s National Health Service Breast Screening Programme uses the PERFORMS 2 test as a teaching and assessment tool for radiologists. The same 60-film PERFORMS 2 test was given to 194 high-volume U.K. radiologists and to 60 U.S. radiologists, who were assigned to low-, medium-, or high-volume groups on the basis of the number of mammograms read per month. The standard binormal receiver-operating characteristic (ROC) model was fitted to the data of individual readers. Detection accuracy was measured by the sensitivity at specificity = 0.90, and differences among sensitivities were determined by analysis of variance. RESULTS: The average sensitivity at specificity = 0.90 was 0.785 for U.K. radiologists, 0.756 for high-volume U.S. radiologists, 0.702 for medium-volume U.S. radiologists, and 0.648 for low-volume U.S. radiologists. At this specificity, low-volume U.S. radiologists had statistically significantly lower sensitivity than either high-volume U.S. radiologists or U.K. radiologists, and medium-volume U.S. radiologists had statistically significantly lower sensitivity than U.K. radiologists (P<.001, for all comparisons). CONCLUSIONS: Reader volume is an important determinant of mammogram sensitivity and specificity. High sensitivity (high cancer detection rate) can be achieved with high specificity (low false-positive rate) in high-volume centers. This study suggests that there is great potential for optimizing mammography screening.
BACKGROUND: Countries with centralized, high-volume mammography screening programs, such as the U.K. and Sweden, emphasize high specificity (low percentage of false positives) and high sensitivity (high percentage of true positives). By contrast, the United States does not have centralized, high-volume screening programs, emphasizes high sensitivity, and has lower average specificity. We investigated whether high sensitivity can be achieved in the context of high specificity and whether the number of mammograms read per radiologist (reader volume) drives both sensitivity and specificity. METHODS: The U.K.'s National Health Service Breast Screening Programme uses the PERFORMS 2 test as a teaching and assessment tool for radiologists. The same 60-film PERFORMS 2 test was given to 194 high-volume U.K. radiologists and to 60 U.S. radiologists, who were assigned to low-, medium-, or high-volume groups on the basis of the number of mammograms read per month. The standard binormal receiver-operating characteristic (ROC) model was fitted to the data of individual readers. Detection accuracy was measured by the sensitivity at specificity = 0.90, and differences among sensitivities were determined by analysis of variance. RESULTS: The average sensitivity at specificity = 0.90 was 0.785 for U.K. radiologists, 0.756 for high-volume U.S. radiologists, 0.702 for medium-volume U.S. radiologists, and 0.648 for low-volume U.S. radiologists. At this specificity, low-volume U.S. radiologists had statistically significantly lower sensitivity than either high-volume U.S. radiologists or U.K. radiologists, and medium-volume U.S. radiologists had statistically significantly lower sensitivity than U.K. radiologists (P<.001, for all comparisons). CONCLUSIONS: Reader volume is an important determinant of mammogram sensitivity and specificity. High sensitivity (high cancer detection rate) can be achieved with high specificity (low false-positive rate) in high-volume centers. This study suggests that there is great potential for optimizing mammography screening.
Authors: Jacqueline R Halladay; Bonnie C Yankaskas; J Michael Bowling; Camille Alexander Journal: AJR Am J Roentgenol Date: 2010-09 Impact factor: 3.959
Authors: William E Barlow; Chen Chi; Patricia A Carney; Stephen H Taplin; Carl D'Orsi; Gary Cutter; R Edward Hendrick; Joann G Elmore Journal: J Natl Cancer Inst Date: 2004-12-15 Impact factor: 13.506
Authors: Laura J Esserman; Ian M Thompson; Brian Reid; Peter Nelson; David F Ransohoff; H Gilbert Welch; Shelley Hwang; Donald A Berry; Kenneth W Kinzler; William C Black; Mina Bissell; Howard Parnes; Sudhir Srivastava Journal: Lancet Oncol Date: 2014-05 Impact factor: 41.316