Affiliation of authors: Division of General Internal Medicine (EZ, KK), Department of Medicine (EZ, JS, RS-B), Department of Radiology (RS-B), Department of Epidemiology and Biostatistics (KK), General Internal Medicine Section (KK), Department of Veterans Affairs, University of California, San Francisco.
Correspondence to: Elad Ziv, MD, University of California, San Francisco Womens Health Clinical Research Center, 1635 Divisadero St., Suite 600, San Francisco, CA 94115 (e-mail: eziv{at}itsa.ucsf.edu)
Eisinger raises an important question about the variability of mammographic density measures and its influence on assessing breast cancer risk. In our study (1), we used the Breast Imaging Reporting and Data System (BI-RADS) (2) breast density categoriesa qualitative measure assessed by radiologists at the time of routine screening mammography. A previous study (3) has demonstrated that there is only moderate agreement among radiologists in BI-RADS density readings (kappa statistic = .59). Thus, differences among radiologists in the qualitative assessment of breast density are probably the main reason for the variability among readings.
Our study (1) assessed the association between breast density and family history of breast cancer in a large cross-sectional study, which allowed us to test for relatively subtle effects, despite using a measure of breast density with only moderate precision. As Eisinger suggests, other means of assessing breast density that would increase precision of the measure would likely provide more accurate assessment of breast cancer risk. In addition, quantitative assessments of breast density may also provide more biologic information about density than a categorical scale and thus be more informative for individual risk prediction. Quantitative mammographic density readings have been shown to be highly predictive of breast cancer risk (4,5) and are likely to be a better approach for clinical risk prediction. Measurement of compositional density using dual x-ray absorptiometry and volumetric methods using screen-film mammograms have been recently shown to be highly reproducible (6,7), and may prove to be useful in clinical risk prediction. We hope that further development of precise and accurate breast density measurements leads to an improvement in clinical risk prediction for women.
REFERENCES
1 Ziv E, Shepherd J, Smith-Bindman R, Kerlikowske K. Mammographic breast density and family history of breast cancer. J Natl Cancer Inst 2003;95: 5568.
2 American College of Radiology. The American College of Radiology Breast Imaging Reporting and Data System (BI-RADS). Reston (VA): American College of Radiology; 1998.
3 Kerlikowske K, Grady D, Barclay J, Frankel SD, Ominsky SH, Sickles EA, et al. Variability and accuracy in mammographic interpretation using the American College of Radiology Breast Imaging Reporting and Data System. J Natl Cancer Inst 1998;90: 18019.
4 Boyd NF, Byng JW, Jong RA, Fishell EK, Little LE, Miller AB, et al. Quantitative classification of mammographic densities and breast cancer risk: results from the Canadian National Breast Screening Study. J Natl Cancer Inst 1995;87: 6705.[Abstract]
5 Prevrhal S, Shepherd JA, Smith-Bindman R, Cummings SR, Kerlikowske K. Accuracy of mammographic breast density analysis: results of formal operator training. Cancer Epidemiol Biomarkers Prev 2002;11: 138993.
6 Shepherd JA, Kerlikowske KM, Smith-Bindman R, Genant HK, Cummings SR. Measurement of breast density with dual X-ray absorptiometry: feasibility. Radiology 2002;223: 5547.
7 Pawluczyk O, Augustine BJ, Yaffe MJ, Rico D, Yang J, Mawdsley GE, Boyd NF. A volumetric method for estimation of breast density on digitized screen-film mammograms. Med Phys 2003;30: 35264.[CrossRef][ISI][Medline]
Related Correspondence
![]() |
||||
|
Oxford University Press Privacy Policy and Legal Statement |