Back to Search Start Over

Utility of relative and absolute measures of mammographic densityvsclinical risk factors in evaluating breast cancer risk at time of screening mammography

Authors :
Kaitlyn Tsuruda
Jennifer Payne
Christopher B. Lightfoot
Sian Iles
Mohamed Abdolell
Judy S Caines
Source :
The British Journal of Radiology. 89:20150522
Publication Year :
2016
Publisher :
British Institute of Radiology, 2016.

Abstract

Various clinical risk factors, including high breast density, have been shown to be associated with breast cancer. The utility of using relative and absolute area-based breast density-related measures was evaluated as an alternative to clinical risk factors in cancer risk assessment at the time of screening mammography.Contralateral mediolateral oblique digital mammography images from 392 females with unilateral breast cancer and 817 age-matched controls were analysed. Information on clinical risk factors was obtained from the provincial breast-imaging information system. Breast density-related measures were assessed using a fully automated breast density measurement software. Multivariable logistic regression was conducted, and area under the receiver-operating characteristic (AUROC) curve was used to evaluate the performance of three cancer risk models: the first using only clinical risk factors, the second using only density-related measures and the third using both clinical risk factors and density-related measures.The risk factor-based model generated an AUROC of 0.535, while the model including only breast density-related measures generated a significantly higher AUROC of 0.622 (p 0.001). The third combined model generated an AUROC of 0.632 and performed significantly better than the risk factor model (p 0.001) but not the density-related measures model (p = 0.097).Density-related measures from screening mammograms at the time of screen may be superior predictors of cancer compared with clinical risk factors.Breast cancer risk models based on density-related measures alone can outperform risk models based on clinical factors. Such models may support the development of personalized breast-screening protocols.

Details

ISSN :
1748880X and 00071285
Volume :
89
Database :
OpenAIRE
Journal :
The British Journal of Radiology
Accession number :
edsair.doi.dedup.....22a86e50d6b0724823c483d1c5b9beb6