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Updated: May 8, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Prospective validation of the breast cancer risk prediction model BOADICEA and a batch-mode version BOADICEACentre
R J MacInnis1, A Bickerstaffe, C Apicella
1Cancer Epidemiology Centre, Cancer Council Victoria, Victoria, Melbourne, Australia.
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.
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