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Published on: October 16, 2010
Mammographic density and risk of breast cancer by tumor characteristics: a case-control study
Kavitha Krishnan1, Laura Baglietto1,2,3,4, Jennifer Stone1,5
1Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Level 3, 207 Bouverie Street, Carlton, VIC, 3053, Australia.
Background:
In a previous paper, we had assumed that the risk of screen-detected breast cancer mostly reflects inherent risk, and the risk of whether a breast cancer is interval versus screen-detected mostly reflects risk of masking. We found that inherent risk was predicted by body mass index (BMI) and dense area (DA) or percent dense area (PDA), but not by non-dense area (NDA). Masking, however, was best predicted by PDA but not BMI. In this study, we aimed to investigate if these associations vary by tumor characteristics and mode of detection.
Methods:
We conducted a case-control study nested within the Melbourne Collaborative Cohort Study of 244 screen-detected cases matched to 700 controls and 148 interval cases matched to 446 controls. DA, NDA and PDA were measured using the Cumulus software. Tumor characteristics included size, grade, lymph node involvement, and ER, PR, and HER2 status. Conditional and unconditional logistic regression were applied as appropriate to estimate the Odds per Adjusted Standard Deviation (OPERA) adjusted for age and BMI, allowing the association with BMI to be a function of age at diagnosis.
Results:
For screen-detected cancer, both DA and PDA were associated to an increased risk of tumors of large size (OPERA ~ 1.6) and positive lymph node involvement (OPERA ~ 1.8); no association was observed for BMI and NDA. For risk of interval versus screen-detected breast cancer, the association with risk for any of the three mammographic measures did not vary by tumor characteristics; an association was observed for BMI for positive lymph nodes (OPERA ~ 0.6). No associations were observed for tumor grade and ER, PR and HER2 status of tumor.
Conclusions:
Both DA and PDA were predictors of inherent risk of larger breast tumors and positive nodal status, whereas for each of the three mammographic density measures the association with risk of masking did not vary by tumor characteristics. This might raise the hypothesis that the risk of breast tumours with poorer prognosis, such as larger and node positive tumours, is intrinsically associated with increased mammographic density and not through delay of diagnosis due to masking.
