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Title of Journal: Breast Cancer Res Treat

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Abbravation: Breast Cancer Research and Treatment

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Springer US

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DOI

10.1016/j.ajoms.2016.01.008

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1573-7217

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Simplifying clinical use of the genetic risk predi

Authors: Swati Biswas Philamer Atienza Jonathan Chipman Kevin Hughes Angelica M Gutierrez Barrera Christopher I Amos Banu Arun Giovanni Parmigiani
Publish Date: 2013/05/21
Volume: 139, Issue: 2, Pages: 571-579
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Abstract

Health care providers need simple tools to identify patients at genetic risk of breast and ovarian cancers Genetic risk prediction models such as BRCAPRO could fill this gap if incorporated into Electronic Medical Records or other Health Information Technology solutions However BRCAPRO requires potentially extensive information on the counselee and her family history Thus it may be useful to provide simplified versions of BRCAPRO for use in settings that do not require exhaustive genetic counseling We explore four simplified versions of BRCAPRO each using less complete information than the original model BRCAPROLYTE uses information on affected relatives only up to second degree It is in clinical use but has not been evaluated BRCAPROLYTEPlus extends BRCAPROLYTE by imputing the ages of unaffected relatives BRCAPROLYTESimple reduces the data collection burden associated with BRCAPROLYTE and BRCAPROLYTEPlus by not collecting the family structure BRCAPRO1Degree only uses firstdegree affected relatives We use data on 2713 individuals from seven sites of the Cancer Genetics Network and MD Anderson Cancer Center to compare these simplified tools with the Family History Assessment Tool FHAT and BRCAPRO with the latter serving as the benchmark BRCAPROLYTE retains high discrimination however because it ignores information on unaffected relatives it overestimates carrier probabilities BRCAPROLYTEPlus and BRCAPROLYTESimple provide better calibration than BRCAPROLYTE so they have higher specificity for similar values of sensitivity BRCAPROLYTEPlus performs slightly better than BRCAPROLYTESimple The Areas Under the ROC curve are 0783 BRCAPRO 0763 BRCAPROLYTE 0772 BRCAPROLYTEPlus 0773 BRCAPROLYTESimple 0728 BRCAPRO1Degree and 0745 FHAT The simpler versions especially BRCAPROLYTEPlus and BRCAPROLYTESimple lead to only modest loss in overall discrimination compared to BRCAPRO in this dataset Thus we conclude that simplified implementations of BRCAPRO can be used for genetic risk prediction in settings where collection of complete pedigree information is impractical

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