Methods for assessing and representing mammographic density: An analysis of 4 case-control studies

Christy G. Woolcott, Shannon M. Conroy, Chisato Nagata, Giske Ursin, Celine M. Vachon, Martin J. Yaffe, Ian S. Pagano, Celia Byrne, Gertraud Maskarinec*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


To maximize statistical power in studies of mammographic density and breast cancer, it is advantageous to combine data from several studies, but standardization of the density assessment is desirable. Using data from 4 case-control studies, we describe the process of reassessment and the resulting correlation between values, identify predictors of differences in density readings, and evaluate the strength of the association between mammographic density and breast cancer risk using different representations of density values. The pooled analysis included 1,699 cases and 2,422 controls from California (1990-1998), Hawaii (1996-2003), Minnesota (1992-2001), and Japan (1999-2003). In 2010, a single reader reassessed all images for mammographic density using Cumulus software (Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada). The mean difference between original and reassessed percent density values was -0.7% (95% confidence interval: -1.1, -0.3), with a correlation of 0.82 that varied by location (r = 0.80-0.89). Case status, weight status, age, parity, density assessment method, mammogram view, and race/ethnicity were significant determinants of the difference between original and reassessed values; in combination, these factors explained 9.2% of the variation. The associations of mammographic density with breast cancer and the model fits were similar using the original values and the reassessed values but were slightly strengthened when a calibrated value based on 100 reassessed radiographs was used.

Original languageEnglish
Pages (from-to)236-244
Number of pages9
JournalAmerican Journal of Epidemiology
Issue number2
StatePublished - 15 Jan 2014
Externally publishedYes


  • breast cancer
  • epidemiologic methods
  • ethnicity
  • mammographic density
  • pooling
  • risk


Dive into the research topics of 'Methods for assessing and representing mammographic density: An analysis of 4 case-control studies'. Together they form a unique fingerprint.

Cite this