Skip to main navigation Skip to search Skip to main content

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

  • R. J. MacInnis
  • , A. Bickerstaffe
  • , Carmel Apicella
  • , Gillian S Dite
  • , James G Dowty
  • , Kelly Aujard
  • , K. A. Phillips
  • , Prue Weideman
  • , A. Lee
  • , Mary Beth Terry
  • , G. G. Giles
  • , M. C. Southey
  • , Antonis C Antoniou
  • , J. L. Hopper

Research output: Contribution to journalArticleResearchpeer-review

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.

Original languageEnglish
Pages (from-to)1296-1301
Number of pages6
JournalBritish Journal of Cancer
Volume109
Issue number5
DOIs
Publication statusPublished - Sept 2013
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • breast cancer incidence; validation; risk prediction model

Cite this