Validity of models for predicting BRCA1 and BRCA2 mutations.
BACKGROUND
Deleterious mutations of the BRCA1 and BRCA2 genes confer susceptibility to breast and ovarian cancer. At least 7 models for estimating the probabilities of having a mutation are used widely in clinical and scientific activities; however, the merits and limitations of these models are not fully understood.


OBJECTIVE
To systematically quantify the accuracy of the following publicly available models to predict mutation carrier status: BRCAPRO, family history assessment tool, Finnish, Myriad, National Cancer Institute, University of Pennsylvania, and Yale University.


METHODS
Cross-sectional validation study, using model predictions and BRCA1 or BRCA2 mutation status of patients different from those used to develop the models.


METHODS
Multicenter study across Cancer Genetics Network participating centers.


METHODS
3 population-based samples of participants in research studies and 8 samples from genetic counseling clinics.


METHODS
Discrimination between individuals testing positive for a mutation in BRCA1 or BRCA2 from those testing negative, as measured by the c-statistic, and sensitivity and specificity of model predictions.


RESULTS
The 7 models differ in their predictions. The better-performing models have a c-statistic around 80%. BRCAPRO has the largest c-statistic overall and in all but 2 patient subgroups, although the margin over other models is narrow in many strata. Outside of high-risk populations, all models have high false-negative and false-positive rates across a range of probability thresholds used to refer for mutation testing.


CONCLUSIONS
Three recently published models were not included.


CONCLUSIONS
All models identify women who probably carry a deleterious mutation of BRCA1 or BRCA2 with adequate discrimination to support individualized genetic counseling, although discrimination varies across models and populations.
Parmigiani
Giovanni
G
The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland 21205-2011, USA. gp@jhu.edu
Chen
Sining
S
Iversen
Edwin S
ES
Friebel
Tara M
TM
Finkelstein
Dianne M
DM
Anton-Culver
Hoda
H
Ziogas
Argyrios
A
Weber
Barbara L
BL
Eisen
Andrea
A
Malone
Kathleen E
KE
Daling
Janet R
JR
Hsu
Li
L
Ostrander
Elaine A
EA
Peterson
Leif E
LE
Schildkraut
Joellen M
JM
Isaacs
Claudine
C
Corio
Camille
C
Leondaridis
Leoni
L
Tomlinson
Gail
G
Amos
Christopher I
CI
Strong
Louise C
LC
Berry
Donald A
DA
Weitzel
Jeffrey N
JN
Sand
Sharon
S
Dutson
Debra
D
Kerber
Rich
R
Peshkin
Beth N
BN
Euhus
David M
DM
D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000175:diagnosis / Q000235:genetics*; D003430:Cross-Sectional Studies; D005260:Female; D019398:Genes, BRCA1; D024522:Genes, BRCA2; D006580:Genetic Carrier Screening; D005838:Genotype; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009154:Mutation; D010051:Ovarian Neoplasms / Q000175:diagnosis / Q000235:genetics*; D012680:Sensitivity and Specificity