6th International Workshop on Breast Densitometry and Breast ...

P6
6 th <strong>International</strong> <strong>Workshop</strong> on Breast Densitometry
and Breast Cancer Risk Assessment
ASSOCIATIONS OF MAMMOGRAPHIC DENSE AND NON-DENSE AREA AND BODY
MASS INDEX WITH RISK OF BREAST CANCER
Laura Baglietto 1,2 ; Kavitha Krishnan 1,2 ; Jennifer Stone 2 ; Carmel Apicella 2 ; Melissa C. Southey 1,3 ; Dallas
R. English 1,2 ; John L. Hopper 2 ; Graham G. Giles 1,2,4 .
1 Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia (2) Centre for Molecular,
Environmental, Genetic and Analytical Epidemiology, The University of Melbourne, Australia (3)
Department of Pathology, The University of Melbourne, Australia; (4) Department of Epidemiology and
Preventive Medicine, Monash University, Melbourne, Australia
Mammographic density measures are associated with risk of breast cancer. Traditionally mammographic
density has been quantified as percent mammographic density (PMD), and few studies have investigated
the concurrent roles of absolute dense and non-dense mammographic areas, body mass index (BMI), age
at mammogram and diagnosis on breast cancer risk.
ABSTRACTS
We conducted a matched case-control study nested within the Melbourne Collaborative Cohort Study
(MCCS) to estimate the associations of dense area, non-dense area, and BMI with breast cancer risk under
alternative causal models.
Dense area was positively associated with risk and the strength of this association was only slightly
influenced by the choice of the causal model. The association between non-dense area and breast cancer
risk was negative under a direct causal relation and null otherwise. The choice of causal model affected
the individual risk predictions, especially for women with extreme values of non-dense area. It also
impacted on the estimates of the associations, interpretations, and the risk predictions which might vary
considerably whether it is assumed that the risk factor is PMD or a linear combination of dense and nondense
area.
An alternative explanation for the negative association observed between non-dense area and breast
cancer risk could be the intrinsic collinearity between dense and non-dense area, whose sum is
constrained to be equal to the total breast area. The presence of two negatively correlated predictors in the
same model could lead to biased estimates of their associations, resulting in a spurious negative
association of non-dense area and an under-estimate of the association of dense-area.
With our data we have not been able to choose whether a model based on PMD or on a linear
combination of dense and non-dense areas provides a better fit. We have shown that, for non-dense area
close to the population median, the two models are similar in their predictions, whereas for more extreme
values of non-dense area they provide quite different predictions. A validation study conducted on a
sample of women with more extreme values of non-dense area might help to determine which of these
two models provide a better fit to the data.
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