Context
Models have been developed to predict the probability that a person carries a detectable germline mutation in the BRCA1 or BRCA2 genes. Their relative performance in a clinical setting is unclear.
Objective
To compare the performance characteristics of four BRCA1/BRCA2 gene mutation prediction models: LAMBDA, based on a checklist and scores developed from data on Ashkenazi Jewish (AJ) women;
BRCAPRO, a Bayesian computer program; modified Couch tables based on regression analyses; and Myriad II tables collated by
Myriad Genetics Laboratories.
Design and setting
Family cancer history data were analyzed from 200 probands from the Mayo Clinic Familial Cancer Program, in a multispecialty
tertiary care group practice. All probands had clinical testing for BRCA1 and BRCA2 mutations conducted in a single laboratory.
Main outcomes measures
For each model, performance was assessed by the area under the receiver operator characteristic curve (ROC) and by tests of
accuracy and dispersion. Cases “missed” by one or more models (model predicted less than 10% probability of mutation when
a mutation was actually found) were compared across models.
Results
All models gave similar areas under the ROC curve of 0.71 to 0.76. All models except LAMBDA substantially under-predicted
the numbers of carriers. All models were too dispersed.
Conclusions
In terms of ranking, all prediction models performed reasonably well with similar performance characteristics. Model predictions
were widely discrepant for some families. Review of cancer family histories by an experienced clinician continues to be vital
to ensure that critical elements are not missed and that the most appropriate risk prediction figures are provided.
Keywords Ashkenazi Jewish - Bayesian -
BRCA1
-
BRCA2
- Breast cancer - Risk prediction