Evaluation of widely used models for predicting BRCA1 and BRCA2 mutations

Deleterious mutations of the BRCA1 and BRCA2 genes are a major risk factor for the development of breast and ovarian cancers.1–4 Mutation tests for these two genes commonly are now offered in specialised clinics.5,6 As a result, a large number of women with personal or family histories of breast or ovarian cancer seek genetic counselling. Accurate evaluation of the probability that a woman carries a germline pathogenic mutation at BRCA1 or BRCA2 therefore is essential to help counsellors and those being counselled to decide whether testing is appropriate. In this context, the questions of practical interest are: Given the pedigree, what is the chance of a mutation being present? and What is the chance of the DNA laboratory finding a mutation? After testing became available, several models were developed to assess the pre-test probability of identifying carriers of mutations. Broadly speaking, two different approaches have been used to develop predictive models: the “empirical approach” and the “Mendelian approach”.7 In empirical models, families are stratified according to variables that describe their family history; regression or other approaches are used to predict the results of Mendelian testing. In some cases, this approach simply consists of observing the proportion of mutations found in different strata. Mendelian models, in contrast, address the probability that a proband is a mutation carrier on the basis of explicit assumptions about the genetic parameters (allele frequencies and cancer penetrances in carriers and non-carriers) and the Mendelian rules of gene transmission. A consequence of the two different strategies is that the Mendelian models evaluate the probability that a proband is a gene carrier, whereas the empirical models evaluate the probability of identifying a mutation. The main purpose of this study was to compare the performances of published models in predicting mutation test results in …