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Validity of models for predicting BRCA1 and BRCA2 mutations.

Publication ,  Journal Article
Parmigiani, G; Chen, S; Iversen, ES; Friebel, TM; Finkelstein, DM; Anton-Culver, H; Ziogas, A; Weber, BL; Eisen, A; Malone, KE; Daling, JR ...
Published in: Ann Intern Med
October 2, 2007

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. DESIGN: Cross-sectional validation study, using model predictions and BRCA1 or BRCA2 mutation status of patients different from those used to develop the models. SETTING: Multicenter study across Cancer Genetics Network participating centers. PATIENTS: 3 population-based samples of participants in research studies and 8 samples from genetic counseling clinics. MEASUREMENTS: 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. LIMITATION: 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.

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Published In

Ann Intern Med

DOI

EISSN

1539-3704

Publication Date

October 2, 2007

Volume

147

Issue

7

Start / End Page

441 / 450

Location

United States

Related Subject Headings

  • Sensitivity and Specificity
  • Ovarian Neoplasms
  • Mutation
  • Models, Statistical
  • Middle Aged
  • Male
  • Likelihood Functions
  • Humans
  • Genotype
  • Genetic Carrier Screening
 

Citation

APA
Chicago
ICMJE
MLA
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Parmigiani, G., Chen, S., Iversen, E. S., Friebel, T. M., Finkelstein, D. M., Anton-Culver, H., … Euhus, D. M. (2007). Validity of models for predicting BRCA1 and BRCA2 mutations. Ann Intern Med, 147(7), 441–450. https://doi.org/10.7326/0003-4819-147-7-200710020-00002
Parmigiani, Giovanni, Sining Chen, Edwin S. Iversen, Tara M. Friebel, Dianne M. Finkelstein, Hoda Anton-Culver, Argyrios Ziogas, et al. “Validity of models for predicting BRCA1 and BRCA2 mutations.Ann Intern Med 147, no. 7 (October 2, 2007): 441–50. https://doi.org/10.7326/0003-4819-147-7-200710020-00002.
Parmigiani G, Chen S, Iversen ES, Friebel TM, Finkelstein DM, Anton-Culver H, et al. Validity of models for predicting BRCA1 and BRCA2 mutations. Ann Intern Med. 2007 Oct 2;147(7):441–50.
Parmigiani, Giovanni, et al. “Validity of models for predicting BRCA1 and BRCA2 mutations.Ann Intern Med, vol. 147, no. 7, Oct. 2007, pp. 441–50. Pubmed, doi:10.7326/0003-4819-147-7-200710020-00002.
Parmigiani G, Chen S, Iversen ES, Friebel TM, Finkelstein DM, Anton-Culver H, Ziogas A, Weber BL, Eisen A, Malone KE, Daling JR, Hsu L, Ostrander EA, Peterson LE, Schildkraut JM, Isaacs C, Corio C, Leondaridis L, Tomlinson G, Amos CI, Strong LC, Berry DA, Weitzel JN, Sand S, Dutson D, Kerber R, Peshkin BN, Euhus DM. Validity of models for predicting BRCA1 and BRCA2 mutations. Ann Intern Med. 2007 Oct 2;147(7):441–450.

Published In

Ann Intern Med

DOI

EISSN

1539-3704

Publication Date

October 2, 2007

Volume

147

Issue

7

Start / End Page

441 / 450

Location

United States

Related Subject Headings

  • Sensitivity and Specificity
  • Ovarian Neoplasms
  • Mutation
  • Models, Statistical
  • Middle Aged
  • Male
  • Likelihood Functions
  • Humans
  • Genotype
  • Genetic Carrier Screening