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Mammographic density parameters and breast cancer tumor characteristics among postmenopausal women

Authors Velásquez García HA, Gotay CC, Wilson CM, Lohrisch CA, Lai AS, Aronson KJ, Spinelli JJ

Received 30 October 2018

Accepted for publication 18 February 2019

Published 16 August 2019 Volume 2019:11 Pages 261—271

DOI https://doi.org/10.2147/BCTT.S192766

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Cristina Weinberg

Peer reviewer comments 2

Editor who approved publication: Professor Pranela Rameshwar


Héctor A Velásquez García,1,2 Carolyn C Gotay,1 Christine M Wilson,3 Caroline A Lohrisch,4 Agnes S Lai,2 Kristan J Aronson,5 John J Spinelli1,2

1School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada; 2Population Oncology, BC Cancer, Vancouver, BC, Canada; 3Screening Mammography Program, BC Cancer, Vancouver, BC, Canada; 4Department of Medical Oncology, BC Cancer, Vancouver, BC, Canada; 5Department of Public Health Sciences and Division of Cancer Care and Epidemiology, Cancer Research Institute, Queen’s University, Kingston, ON, Canada

Correspondence: Héctor A Velásquez García
Population Oncology, BC Cancer, 8 th floor, 686 West Broadway, Vancouver, BC V5Z 1G1, Canada
Tel +1604 877 6068
Fax +1 604 877 6212
Email hector.velasquezgarcia@alumni.ubc.ca

Purpose: Mammographic density is an important breast cancer risk factor, although it is not clear whether the association differs across breast cancer tumor subtypes. We examined the association between indicators of mammographic density and breast cancer risk by tumor subtype among postmenopausal women by investigating heterogeneity across tumor characteristics.
Methods: Mammographic density measures were determined for 477 breast cancer cases and 588 controls, all postmenopausal, in Vancouver, British Columbia, using digitized screening mammograms and Cumulus software. Mammographic dense (DA), non-dense (NDA), and percent dense (PDA) areas were treated as continuous covariates and categorized into quartiles according to the distribution in controls. For cases only, tests for heterogeneity between tumor subtypes were assessed by multinomial logistic regression. Associations between mammographic density and breast cancer risk were modeled for each subtype separately through unconditional logistic regression.
Results: Heterogeneity was apparent for the association of PDA with tumor size (p-heterogeneity=0.04). Risk did not differ across the other assessed tumor characteristics (p-heterogeneity values >0.05).
Conclusion: These findings do not provide strong evidence that mammographic density parameters differentially affect specific breast cancer tumor characteristics.

Keywords: mammographic density, breast cancer, tumor characteristics, heterogeneity, multinomial logistic regression

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