Incorporating medical interventions into carrier probability estimation for genetic counseling.
BACKGROUND
Mendelian models for predicting who may carry an inherited deleterious mutation of known disease genes based on family history are used in a variety of clinical and research activities. People presenting for genetic counseling are increasingly reporting risk-reducing medical interventions in their family histories because, recently, a slew of prophylactic interventions have become available for certain diseases. For example, oophorectomy reduces risk of breast and ovarian cancers, and is now increasingly being offered to women with family histories of breast and ovarian cancer. Mendelian models should account for medical interventions because interventions modify mutation penetrances and thus affect the carrier probability estimate.


METHODS
We extend Mendelian models to account for medical interventions by accounting for post-intervention disease history through an extra factor that can be estimated from published studies of the effects of interventions. We apply our methods to incorporate oophorectomy into the BRCAPRO model, which predicts a woman's risk of carrying mutations in BRCA1 and BRCA2 based on her family history of breast and ovarian cancer. This new BRCAPRO is available for clinical use.


RESULTS
We show that accounting for interventions undergone by family members can seriously affect the mutation carrier probability estimate, especially if the family member has lived many years post-intervention. We show that interventions have more impact on the carrier probability as the benefits of intervention differ more between carriers and non-carriers.


CONCLUSIONS
These findings imply that carrier probability estimates that do not account for medical interventions may be seriously misleading and could affect a clinician's recommendation about offering genetic testing. The BayesMendel software, which allows one to implement any Mendelian carrier probability model, has been extended to allow medical interventions, so future Mendelian models can easily account for interventions.
Katki
Hormuzd A
HA
Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, 6120 Executive Blvd, Room 8044 Rockville, MD 20852, USA. katkih@mail.nih.gov
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001499:Bayes Theorem; D001943:Breast Neoplasms / Q000235:genetics / Q000517:prevention & control; D005260:Female; D019398:Genes, BRCA1; D006580:Genetic Carrier Screening; D005817:Genetic Counseling / Q000706:statistics & numerical data*; D006579:Heterozygote; D006801:Humans; D008297:Male; D008875:Middle Aged; D008957:Models, Genetic; D009154:Mutation; D010052:Ovariectomy; D010375:Pedigree; D016016:Proportional Hazards Models