Abstract PD1-07: Mammographic density and SNPs add to Tyrer-Cuzick and Gail model breast cancer risk in a UK screening cohort

Abstract

Abstract Background: The predicting risk of cancer at screening study (PROCAS) in Manchester UK is a prospective study of breast cancer risk estimation. This article considers whether mammographic density and SNPs in PROCAS may help refine breast cancer risk estimation using the Gail (BCRAT) and Tyrer-Cuzick (TC, or IBIS) models, based on incident and prevalent breast cancers identified between two three-yearly screening rounds. Methods: Mammographic density was measured at entry as a percentage using the average visual assessment from two trained readers. Tyrer-Cuzick and Gail risks were based on a questionnaire completed at the same time. The contribution of density to risk models was assessed after adjustment for age and body mass index (BMI) using odds ratios (ORs) and profile likelihood confidence intervals (CIs). A secondary analysis compared cancer pathology characteristics using a two-sided Wilcoxon test. Eighteen breast cancer risk variants (SNP18) were assessed with a polygenic risk score (PRS) alongside TC and density in a subset of 8870 women with 341 prospective cancers. Results: Analysis included 50628 women of routine screening age (47-73 yrs), recruited between Aug 2009 and Jul 2014. 697 had a breast cancer diagnosed after enrolment. Median follow-up was 3.2 years. Visually assessed percentage breast density (inter-quartile range odds ratio (IQR OR) 1.48 (95%CI 1.34-1.63)) was a slightly stronger univariate risk factor than TC (IQR OR 1.36 (1.25-1.48)) or Gail (IQR OR 1.22 (1.12-1.33)). It continued to add information after allowing for TC (IQR OR 1.47 (1.33-1.62)) or Gail (IQR OR 1.45 (1.32-1.60)). 36472/50628 (72%) women had less than 3.5% 10-yr risk from the TC model and breast density combined. Women with dense breasts were more likely to have a higher stage breast cancer (P <.001). SNP18 showed a 2 fold relative breast cancer risk between the top and bottom quintile. Using a combined analysis of SNP18, TC and density there was a 5.6 fold risk between those identified at NICE defined high risk compared to low risk. Conclusion: Breast density and SNPs when combined with the TC or Gail risk model identify a larger number of high risk women at screening, and it is associated with higher stage of disease. Approximately 70% of women are identified with a combined TC and density risk assessment of less than 3.5% 10-yr risk (average or less than average risk), for whom three-yearly screening might be effective. SNP18 adds further precision and addition of further newly identified SNPs is likely to add greater discrimination. Citation Format: Evans DG, Astley SM, Brentnall A, Howell A, Cuzick J. Mammographic density and SNPs add to Tyrer-Cuzick and Gail model breast cancer risk in a UK screening cohort. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr PD1-07.