Garrido-Estepa et al. BMC Cancer 2010, 10:485 http://www.biomedcentral.com/1471-2407/10/485 mammograms with different results in both readings belonged to these three categories. Taking into account the number of categories and the semi-quantitative nat- ure of the Boyd scale, weighted kappa is a more appro- priate estimator of concordance. Using this statistic, concordance for Boyd’s scale was 0.92. The other classi- fications registered agreement percentages of 82% to 84%, and weighted kappa values of over 0.75. Previous studies using the BI-RADS scale reported moderate agreement, with kappa statistics of 0.43 to 0.59 for intra-observer studies [16,17]. We obtained kappa and weighted kappa values of 0.76 and 0.90 respectively, showing very good agreement. When comparing the different scales, kappa values for distinguishing high-density mammographic patterns ran- ged from 0.79 to 0.86, revealing almost perfect agree- ment. This good correlation among the different scales explains the consistency of results on the relationship between mammographic density and breast cancer obtained from different studies using different scales [1,2]. It is interesting to note, however, that classifica- tions, such as Tabár’s and Wolfe’s, which consider both qualitative and quantitative information on density, dis- played lower concordance with the semi-quantitative scale. A more detailed analysis confirmed that these scales registered the greatest disagreement in mammo- grams in the intermediate dense-tissue percentage cate- gory, i.e., ranging from 25% to 50%. This means that categories associated to high risk of the Wolfe and Tabár scales are classify with a huge variability from 25 to 100% of density using quantitative based scales and some women are classified into low (< 50% of density) or high risk group depending on the method selected. It would have been interesting to ascertain to what extent qualitative information in such cases determined differ- ences in breast cancer risk and the clinical relevance of classifying different population into high and low risk but our study was unable to address this issue directly. Separate comparison between digital and analog images failed to reveal relevant differences, yielding weighted kappa values for analog versus digital of: 0.87 versus 0.78 using Wolfe’s scale; 0.75 versus 0.64 using Tabár’s scale; 0.90 versus 0.90 using the BI-RADS scale; and 0.92 versus 0.91 using Boyd’s scale. Even though these differences did not attain statistical significance, the kappa values were always slightly higher when our reader examined analog images. This may reflect his longer experience with the old technology, since digital mammographic technology has only recently been intro- duced in Spanish screening programs. Limitations are intra-observer design of the study and the lack of comparison with computer-assisted methods, which would result in more objective measurements of breast density, slightly higher agreement values, and the Page 7 of 8 possibility of obtaining a measure of density percentages as a continuous variable. Furthermore, such methods are also dependent on observer experience, since the program has to be given some pointers to enable it to delimit the area in which it must calculate the percen- tage of the breast occupied by dense tissue [1,2]. This technique has not been introduced in Spanish breast cancer screening programs, and no radiologist or techni- cian with the necessary experimental training could be found who was able to use it. Previous studies have shown excellent reproducibility, with an intraclass corre- lation of over 0.9 [11] and a Pearson correlation with r values of over 0.90 [10], when this method was used on previously digitized analog images. Conclusions Visual classification of mammographic density patterns, besides being quick and easy to perform, is a relatively inexpensive method to implement in breast cancer screening programs. Our study confirms that, using an experienced reader, the four scales display very high reproducibility and are extremely consistent in identify- ing women with high-density patterns. Quantitative- based scales are more specific in classifying populations in the high-risk group. Abbreviations BI-RADS: Breast Imaging Reporting and Data System; DDM-Spain study: Determinants of Density in Mammography in Spain Acknowledgements This study was supported by research grant FIS PI060386 from Fondo de Investigación Sanitaria, Spain and by collaboration agreement EPY 1306/06 between Astra-Zeneca and the Carlos III Institute of Health. We should like to thank all the women who participated in the DDM-Spain study for their contribution; the respective regional screening-program staff and the other members of DDM-Spain for their invaluable collaboration and effort: Soledad Abad, Manuela Alcaraz, Nuria Aragonés, Anna Cabanes, Monserrat Corujo, Ana-Belén Fernández, Pablo Fernández-Navarro, Milagros García-López, Marcela Guevara, Soledad Laso-Pablos,, Virginia Lope, Gonzalo López-Abente, Carmen Pedraz, Beatriz Pérez-Gómez, Roberto Pastor, Juana Vidan, Jesús Vioque. Author details 1National Centre for Epidemiology, Instituto de Salud Carlos III, Madrid, Spain. 2Valencia Breast Cancer Screening Programme, General Directorate Public Health, Valencia, Spain. 3Centro Superior de Investigación en Salud Pública(CSISP), Valencia, Spain. 4Navarra Breast Cancer Screening Programme, Public Health Institute, Pamplona, Spain. 5Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Spain. 6Castilla-Leon Breast Cancer Screening Programme, D.G. Salud Pública ID e I, SACYL, Castilla y León, Spain. 7Balearic Islands Breast Cancer Screening Programme, Health Promotion for Women and Childhood, General Directorate Public Health and Participation, Regional Authority of Health and Consumer Affairs, Balearic Islands, Spain. 8Galicia Breast Cancer Screening Programme, Regional Authority of Health, Galicia Regional Government, Spain. 9Aragon Breast Cancer Screening Programme, Health Service of Aragon, Zaragoza, Spain. 10Cancer Prevention and Control Unit, Catalan Institute of Oncology (ICO), Barcelona, Spain.