Mammographic density defined by higher than conventional brightness thresholds better predicts breast cancer risk

Tuong L. Nguyen, Ye K. Aung, Christopher F. Evans, G.S. Dite, Jennifer Stone, Robert J. MacInnis, James G. Dowty, Adrian Bickerstaffe, K. Aujard, Johanna M. Rommens, Yun-Mi Song, Joohon Sung, Mark Jenkins, Melissa C. Southey, Graham G. Giles, Carmel Apicella, John L. Hopper

Research output: Contribution to journalArticle

17 Citations (Scopus)
Original languageEnglish
Pages (from-to)652-661
Number of pages10
JournalInternational Journal of Epidemiology
Volume46
Issue number2
DOIs
Publication statusPublished - 8 Oct 2016

Cite this

Nguyen, T. L., Aung, Y. K., Evans, C. F., Dite, G. S., Stone, J., MacInnis, R. J., Dowty, J. G., Bickerstaffe, A., Aujard, K., Rommens, J. M., Song, Y-M., Sung, J., Jenkins, M., Southey, M. C., Giles, G. G., Apicella, C., & Hopper, J. L. (2016). Mammographic density defined by higher than conventional brightness thresholds better predicts breast cancer risk. International Journal of Epidemiology, 46(2), 652-661. https://doi.org/10.1093/ije/dyw212