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Towards more effective and equitable genetic testing for BRCA1 and BRCA2 mutation carriers
  1. John L Hopper1,
  2. James G Dowty1,
  3. Carmel Apicella1,
  4. Melissa C Southey2,
  5. Graham G Giles3,
  6. Ingrid Winship4
  1. 1
    Centre for Molecular, Analytic, Genetic and Analytic Epidemiology, University of Melbourne, Melbourne, Australia
  2. 2
    Department of Pathology, University of Melbourne, Melbourne, Australia
  3. 3
    The Cancer Council of Victoria, Victoria, Australia
  4. 4
    Clinical Genetics Department, Royal Melbourne Hospital, Melbourne, Australia
  1. Professor J L Hopper, Department of Public Health, University of Melbourne, Australia; j.hopper{at}

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Cochrane1 proposed that, because resources are always limited, they should be used to provide equitably those forms of health care that have been shown in properly designed evaluations to be effective. Consistently with this suggestion, Antoniou et al2 in this issue of JMG (see page 425), examined the performance of several algorithms for predicting the BRCA1 and BRCA2 mutation status of women attending UK cancer family clinics over the past decade or so. They concluded, not unreasonably, that the widespread use of these models would “improve equity of access and the cost-effectiveness of genetic testing”. However, they did not describe policy changes that would achieve these gains.

Antoniou et al2 showed that the various genotype-prediction models are reasonably well calibrated, in that out of 100 women with a prediction probability of x%, approximately x will be a mutation carrier, at least for women with a reasonably high chance of being a carrier (e.g. x>15 or 20; see tables 3 and 4 of that paper2). There was little difference between the algorithms in terms of ranking women in order of their probability of being a carrier (i.e. they have similar areas under the ROC curve; see table 6 of that paper …

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  • Competing interests: None.