Prospective validation of the breast cancer risk prediction model BOADICEA and a batch-mode version BOADICEACentre

Abstract

Background: Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) is a risk prediction algorithm that can be used to compute estimates of age-specific risk of breast cancer. It is uncertain whether BOADICEA performs adequately for populations outside the United Kingdom.

Methods: Using a batch mode version of BOADICEA that we developed (BOADICEACentre), we calculated the cumulative 10-year invasive breast cancer risk for 4176 Australian women of European ancestry unaffected at baseline from 1601 case and control families in the Australian Breast Cancer Family Registry. Based on 115 incident breast cancers, we investigated calibration, discrimination (using receiver-operating characteristic (ROC) curves) and accuracy at the individual level.

Results: The ratio of expected to observed number of breast cancers was 0.92 (95% confidence interval (CI) 0.76-1.10). The E/O ratios by subgroups of the participant's relationship to the index case and by the reported number of affected relatives ranged between 0.83 and 0.98 and all 95% CIs included 1.00. The area under the ROC curve was 0.70 (95% CI 0.66-0.75) and there was no evidence of systematic under- or over-dispersion (P=0.2).

Conclusion: BOADICEA is well calibrated for Australian women, and had good discrimination and accuracy at the individual level.

Figure 1

Distribution of BOADICEA scores. The white bars denote the distribution of 10-year BOADICEA risk scores for all participants; black bars denote the distribution for participants from index control families.

Figure 2

The receiver operator characteristic (ROC) curve BOADICEA as a predictor of 10-year cumulative risk. The square boxes on the ROC curve denote the cut-points. The area under the ROC curve was 0.70.