Mammographic density adds accuracy to both the Tyrer-Cuzick and Gail breast cancer risk models in a prospective UK screening cohort

Abstract

Introduction: The Predicting Risk of Cancer at Screening study in Manchester, UK, is a prospective study of breast cancer risk estimation. It was designed to assess whether mammographic density may help in refinement of breast cancer risk estimation using either the Gail model (Breast Cancer Risk Assessment Tool) or the Tyrer-Cuzick model (International Breast Intervention Study model).

Methods: Mammographic density was measured at entry as a percentage visual assessment, adjusted for age and body mass index. Tyrer-Cuzick and Gail 10-year risks were based on a questionnaire completed contemporaneously. Breast cancers were identified at the entry screen or shortly thereafter. The contribution of density to risk models was assessed using odds ratios (ORs) with profile likelihood confidence intervals (CIs) and area under the receiver operating characteristic curve (AUC). The calibration of predicted ORs was estimated as a percentage [(observed vs expected (O/E)] from logistic regression.

Results: The analysis included 50,628 women aged 47-73 years who were recruited between October 2009 and September 2013. Of these, 697 had breast cancer diagnosed after enrolment. Median follow-up was 3.2 years. Breast density [interquartile range odds ratio (IQR-OR) 1.48, 95 % CI 1.34-1.63, AUC 0.59] was a slightly stronger univariate risk factor than the Tyrer-Cuzick model [IQR-OR 1.36 (95 % CI 1.25-1.48), O/E 60 % (95 % CI 44-74), AUC 0.57] or the Gail model [IQR-OR 1.22 (95 % CI 1.12-1.33), O/E 46 % (95 % CI 26-65 %), AUC 0.55]. It continued to add information after allowing for Tyrer-Cuzick [IQR-OR 1.47 (95 % CI 1.33-1.62), combined AUC 0.61] or Gail [IQR-OR 1.45 (95 % CI 1.32-1.60), combined AUC 0.59].

Conclusions: Breast density may be usefully combined with the Tyrer-Cuzick model or the Gail model.

Fig. 1

Calibration and spread of risk from the models and density. The predicted and observed odds ratios from (a) the Tyrer-Cuzick model and (b) the Gail model in the cohort are shown. c Histogram of observed risk. O vs E is the estimate from a logistic regression of the logarithmic predicted odds ratio. TC Tyrer-Cuzick 10-year risk, DR density residual

Fig. 2

Breast density and residual by time of diagnosis since enrolment. a and c Histograms and empirical cumulative distribution functions for breast density. b and d Histograms and empirical cumulative distribution functions for age, body mass index and type of image adjusted residual. The cancers are split into those diagnosed within 100 days of entry (<100-d) and more than 100 days (100-d+). A Wilcoxon test for the difference between <100 days and 100+ days yielded P = 0.34 for visual analogue scale (VAS) and P = 0.98 for the residual.