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Table 2. Characteristics of Common Models for Estimating the Likelihood of a BRCA1/2 Mutation

 Myriad Prevalence Tables [77] BRCAPRO [80,100] BOADICEA [80,94] Tyrer-Cuzick [113] 
AJ = Ashkenazi Jewish; BOADICEA = Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm; FDR = first-degree relatives; SDR = second-degree relatives.
Method Empiric data from Myriad Genetics based on family and personal history reported on requisition formsStatistical modelStatistical modelStatistical model
Features of the Model Proband may or may not have breast or ovarian cancerProband may or may not have breast or ovarian cancerProband may or may not have breast or ovarian cancerProband must be unaffected
Considers age of breast cancer diagnosis as <50 y, >50 yConsiders exact age at breast and ovarian cancer diagnosisConsiders exact age at breast and ovarian cancer diagnosisAlso includes reproductive factors and body mass index to estimate breast cancer risk
Considers breast cancer in ≥1 affected relative only if diagnosed <50 yConsiders prior genetic testing in family (i.e., BRCA1/BRCA2 mutation–negative relatives)Includes all FDR and SDR with and without cancer
Considers ovarian cancer in ≥1 relative at any ageConsiders oophorectomy statusIncludes AJ ancestry
Includes AJ ancestryIncludes all FDR and SDR with and without cancer
Very easy to useIncludes AJ ancestry
Limitations Simplified/limited consideration of family structureRequires computer software and time-consuming data entryRequires computer software and time-consuming data entryDesigned for individuals unaffected with breast cancer
Incorporates only FDR and SDR; may need to change proband to best capture risk and to account for disease in the paternal lineage
May overestimate risk in bilateral breast cancer [114]
Early age of breast cancer onsetMay perform better in whites than minority populations [104,115]Incorporates only FDR and SDR; may need to change proband to best capture risk
May underestimate risk of BRCA mutation in high-grade serous ovarian cancers but overestimate the risk for other histologies [116]


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  2. Parmigiani G, Berry D, Aguilar O: Determining carrier probabilities for breast cancer-susceptibility genes BRCA1 and BRCA2. Am J Hum Genet 62 (1): 145-58, 1998.  [PUBMED Abstract]

  3. Antoniou AC, Pharoah PP, Smith P, et al.: The BOADICEA model of genetic susceptibility to breast and ovarian cancer. Br J Cancer 91 (8): 1580-90, 2004.  [PUBMED Abstract]

  4. Katki HA: Incorporating medical interventions into carrier probability estimation for genetic counseling. BMC Med Genet 8: 13, 2007.  [PUBMED Abstract]

  5. Kurian AW, Gong GD, John EM, et al.: Performance of prediction models for BRCA mutation carriage in three racial/ethnic groups: findings from the Northern California Breast Cancer Family Registry. Cancer Epidemiol Biomarkers Prev 18 (4): 1084-91, 2009.  [PUBMED Abstract]

  6. Tyrer J, Duffy SW, Cuzick J: A breast cancer prediction model incorporating familial and personal risk factors. Stat Med 23 (7): 1111-30, 2004.  [PUBMED Abstract]

  7. Ready KJ, Vogel KJ, Atchley DP, et al.: Accuracy of the BRCAPRO model among women with bilateral breast cancer. Cancer 115 (4): 725-30, 2009.  [PUBMED Abstract]

  8. Huo D, Senie RT, Daly M, et al.: Prediction of BRCA Mutations Using the BRCAPRO Model in Clinic-Based African American, Hispanic, and Other Minority Families in the United States. J Clin Oncol 27 (8): 1184-90, 2009.  [PUBMED Abstract]

  9. Daniels MS, Babb SA, King RH, et al.: Underestimation of risk of a BRCA1 or BRCA2 mutation in women with high-grade serous ovarian cancer by BRCAPRO: a multi-institution study. J Clin Oncol 32 (12): 1249-55, 2014.  [PUBMED Abstract]