Literature DB >> 17661812

Validation study of the LAMBDA model for predicting the BRCA1 or BRCA2 mutation carrier status of North American Ashkenazi Jewish women.

C Apicella1, J G Dowty, G S Dite, M A Jenkins, R T Senie, M B Daly, I L Andrulis, E M John, S S Buys, F P Li, G Glendon, W Chung, H Ozcelik, A Miron, K Kotar, M C Southey, W D Foulkes, J L Hopper.   

Abstract

LAMBDA is a model that estimates the probability an Ashkenazi Jewish (AJ) woman carries an ancestral BRCA1 or BRCA2 mutation from her personal and family cancer history. LAMBDA is relevant to clinical practice, and its implementation does not require a computer. It was developed principally from Australian and UK data. We conducted a validation study using 1286 North American AJ women tested for the mutations 185delAG and 5382insC in BRCA1 and 6174delT in BRCA2. Most had a personal or family history of breast cancer. We observed 197 carriers. The area under the receiver operator characteristic (ROC) curve (a measure of ranking) was 0.79 [95% confidence interval (CI) = 0.77-0.81], similar to that for the model-generating data (0.78; 95% CI = 0.75-0.82). LAMBDA predicted 232 carriers (18% more than observed; p = 0.002) and was overdispersed (p = 0.009). The Bayesian computer program BRCAPRO gave a similar area under the ROC curve (0.78; 95% CI = 0.76-0.80), but predicted 367 carriers (86% more than observed; p < 0.0001), and was substantially overdispersed (p < 0.0001). Therefore, LAMBDA is comparable to BRCAPRO for ranking AJ women according to their probability of being a BRCA1 or BRCA2 mutation carrier and is more accurate than brcapro which substantially overpredicts carriers in this population.

Entities:  

Mesh:

Year:  2007        PMID: 17661812     DOI: 10.1111/j.1399-0004.2007.00841.x

Source DB:  PubMed          Journal:  Clin Genet        ISSN: 0009-9163            Impact factor:   4.438


  7 in total

1.  Prediction of BRCA Mutations Using the BRCAPRO Model in Clinic-Based African American, Hispanic, and Other Minority Families in the United States.

Authors:  Dezheng Huo; Ruby T Senie; Mary Daly; Saundra S Buys; Shelly Cummings; Jacqueline Ogutha; Kisha Hope; Olufunmilayo I Olopade
Journal:  J Clin Oncol       Date:  2009-02-02       Impact factor: 44.544

2.  Genome-wide DNA methylation assessment of 'BRCA1-like' early-onset breast cancer: Data from the Australian Breast Cancer Family Registry.

Authors:  Cameron M Scott; Ee Ming Wong; JiHoon Eric Joo; Pierre-Antoine Dugué; Chol-Hee Jung; Neil O'Callaghan; James Dowty; Graham G Giles; John L Hopper; Melissa C Southey
Journal:  Exp Mol Pathol       Date:  2018-11-10       Impact factor: 3.362

3.  Predictive accuracy of the Liverpool Lung Project risk model for stratifying patients for computed tomography screening for lung cancer: a case-control and cohort validation study.

Authors:  Olaide Y Raji; Stephen W Duffy; Olorunshola F Agbaje; Stuart G Baker; David C Christiani; Adrian Cassidy; John K Field
Journal:  Ann Intern Med       Date:  2012-08-21       Impact factor: 25.391

4.  Performance of prediction models for BRCA mutation carriage in three racial/ethnic groups: findings from the Northern California Breast Cancer Family Registry.

Authors:  Allison W Kurian; Gail D Gong; Esther M John; Alexander Miron; Anna Felberg; Amanda I Phipps; Dee W West; Alice S Whittemore
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2009-03-31       Impact factor: 4.254

5.  Morphological predictors of BRCA1 germline mutations in young women with breast cancer.

Authors:  M C Southey; S J Ramus; J G Dowty; L D Smith; A A Tesoriero; E E M Wong; G S Dite; M A Jenkins; G B Byrnes; I Winship; K-A Phillips; G G Giles; J L Hopper
Journal:  Br J Cancer       Date:  2011-02-22       Impact factor: 7.640

6.  Methylation of Breast Cancer Predisposition Genes in Early-Onset Breast Cancer: Australian Breast Cancer Family Registry.

Authors:  Cameron M Scott; JiHoon Eric Joo; Neil O'Callaghan; Daniel D Buchanan; Mark Clendenning; Graham G Giles; John L Hopper; Ee Ming Wong; Melissa C Southey
Journal:  PLoS One       Date:  2016-11-30       Impact factor: 3.240

7.  Increased genomic burden of germline copy number variants is associated with early onset breast cancer: Australian breast cancer family registry.

Authors:  Logan C Walker; John F Pearson; George A R Wiggins; Graham G Giles; John L Hopper; Melissa C Southey
Journal:  Breast Cancer Res       Date:  2017-03-16       Impact factor: 6.466

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.