Validation of the BOADICEA model for predicting the likelihood of carrying pathogenic variants in eight breast and ovarian cancer susceptibility genes

Nanna Bæk Møller, Desirée Sofie Boonen, Elisabeth Simone Feldner, Qin Hao, Martin Larsen, Anne Vibeke Lænkholm, Åke Borg, Anders Kvist, Therese Törngren, Uffe Birk Jensen, Susanne Eriksen Boonen, Mads Thomassen*, Thorkild Terkelsen*

*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

1 Citation (Scopus)

Abstract

BOADICEA is a comprehensive risk prediction model for breast and/or ovarian cancer (BC/OC) and for carrying pathogenic variants (PVs) in cancer susceptibility genes. In addition to BRCA1 and BRCA2, BOADICEA version 6 includes PALB2, CHEK2, ATM, BARD1, RAD51C and RAD51D. To validate its predictions for these genes, we conducted a retrospective study including 2033 individuals counselled at clinical genetics departments in Denmark. All counselees underwent comprehensive genetic testing by next generation sequencing on suspicion of hereditary susceptibility to BC/OC. Likelihoods of PVs were predicted from information about diagnosis, family history and tumour pathology. Calibration was examined using the observed-to-expected ratio (O/E) and discrimination using the area under the receiver operating characteristics curve (AUC). The O/E was 1.11 (95% CI 0.97–1.26) for all genes combined. At sub-categories of predicted likelihood, the model performed well with limited misestimation at the extremes of predicted likelihood. Discrimination was acceptable with an AUC of 0.70 (95% CI 0.66–0.74), although discrimination was better for BRCA1 and BRCA2 than for the other genes in the model. This suggests that BOADICEA remains a valid decision-making aid for determining which individuals to offer comprehensive genetic testing for hereditary susceptibility to BC/OC despite suboptimal calibration for individual genes in this population.

Original languageEnglish
Article number8536
JournalScientific Reports
Volume13
Issue1
Number of pages11
ISSN2045-2322
DOIs
Publication statusPublished - Dec 2023

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