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© 2004 Oxford University Press
CORRESPONDENCE |
Re: Changes in Breast Cancer Detection and Mammography Recall Rates After the Introduction of a Computer-Aided Detection System
Affiliations of authors: Department of Radiology, Mount Sinai School of Medicine of New York University, New York, NY (SAF); Department of Radiology, University of California, San Francisco (EAS); Department of Radiology, University of Texas Southwestern Medical Center, Dallas (WPE); X-Ray Associates of New Mexico, Albuquerque (MNL)
Correspondence to: Stephen A. Feig, MD, Department of Radiology, The Mount Sinai Hospital, 1178 Fifth Ave., New York, NY 10029-6574 (e-mail: stephen.feig{at}mountsinai.org)
In their recent article, Gur et al. (1) concluded that "The introduction of computer-aided detection...was not associated with statistically significant changes in recall and breast cancer detection rates for the entire group of radiologists as well as for the subset of seven radiologists who interpreted high volumes of mammograms." Three important points must be made regarding this conclusion.
First, the 95% confidence intervals (–11% to 19%) reported by Gur et al. allow for a wide range of detection rate changes. Even a 19% increase in detection rate would be consistent with their findings. The source of this large variation is not clear but may be a result of variability among readers.
Second, we show that the use of computer-aided detection was associated with a substantial, but not statistically significant, increase in cancer detection rates for the subgroup of 17 low-volume radiologists in the Gur et al. study (Table 1). Among the 24 radiologists in their study, the seven high-volume radiologists each read more than 8000 mammograms during this 3-year study and the 17 low-volume radiologists interpreted an average of 1967 mammograms during the same period [table 1 in Gur et al. (1)]. The authors analyzed the combined performance of all 24 radiologists and separately analyzed the performance of the seven high-volume radiologists [table 2 in Gur et al. (1)]. However, they did not similarly analyze the performance of the 17 low-volume radiologists.
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As shown in Table 1, we used the data reported by Gur et al. (1) to address this issue. We subtracted their data for high-volume radiologists from that for all radiologists and found that use of computer-aided detection by the low-volume radiologists was associated with a 19.7% increase in their detection rate (from 3.05 cancers per 1000 mammograms without computer-aided detection to 3.65 cancers per 1000 mammograms with computer-aided detection). Thus, use of computer-aided detection allowed the low-volume radiologists to increase their collective detection rate to a rate equal to that of the high-volume radiologists. However, because of the small sample size, this improvement was not statistically significant (P = .37, chi-squared test). A sample size approximately five times larger than the one in the Gur et al. study would be needed to demonstrate that the nearly 20% increase in detection rate was statistically significant. Nevertheless, the increase we calculated using data reported by Gur et al. is similar to the 19.5% increase in cancer detection reported by Freer and Ulissey (2) in 2001 in their prospective study of computer-aided detection.
Our third point relates to the authors' acknowledgement that during the study period, the percentage of women who were screened for the first time decreased from approximately 40% to 30%. This observation is clinically significant because a population undergoing periodic mammographic screening typically has lower cancer detection rates on second and third (i.e., incidence) screens than on the first (i.e., prevalence) screen (3). Gur et al. did not adjust for this confounding factor, which could obscure any evidence of benefit from computer-aided detection.
Results of previous studies suggest that computer-aided detection should improve breast cancer detection rates and that the value of computer-aided detection may vary among different readers (4,5). The article by Gur et al. and the editorial by Elmore and Carney (6) should have mentioned that the breast cancer detection rates of low-volume radiologists benefited from computer-aided detection. The article by Gur et al. indicates that additional studies will be helpful to provide more insight into the benefits of computer-aided detection in different clinical settings.
NOTES
S. A. Feig, E. A. Sickles, and W. Phil Evans hold minor stock interests in R2 Technology, Inc., the manufacturer of the ImageChecker computer-aided detection system. S. A. Feig and E. A. Sickles are members of the Mammography Advisory Board of R2 Technology, Inc.
REFERENCES
1 Gur D, Sumkin JH, Rockette HE, Gannot M, Hakim C, Hardesty L, et al. Changes in breast cancer detection and mammography recall rates after the introduction of a computer-aided detection system. J Natl Cancer Inst 2004;96;185–90.
2 Freer TW, Ulissey MJ. Screening mammography with computer-aided detection: prospective study of 12,860 patients in a community breast center. Radiology 2001;220:781–6.
3 Feig, SA. Age-related accuracy of screening mammography: How should it be measured? Radiology 2000;214:633–40.
4 Warren Burhenne LJ, Wood SA, D'Orsi CJ, Feig SA, Kopans DB, O'Shaughnessy KF, et al. Potential contribution of computer-aided detection to the sensitivity of screening mammography [Erratum in: Radiology 2000;216:306]. Radiology 2000;215:554–62.
5 Thurfjell E, Thurfjell MG, Egge E, Bjurstam N. Sensitivity and specificity of computer-assisted breast cancer detection in mammography screening. Acta Radiol 1998;39:384–8.[Medline]
6 Elmore JG, Carney PA. Computer-aided detection of breast cancer: has promise outstripped performance? [Erratum in: J Natl Cancer Inst 2004;96:719]. J Natl Cancer Inst 2004;96:162–3.
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J Natl Cancer Inst 2004 96: 1261.
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