Literature DB >> 24891549

Recent BRCAPRO upgrades significantly improve calibration.

Emanuele Mazzola1, Jonathan Chipman2, Su-Chun Cheng2, Giovanni Parmigiani2.   

Abstract

The recent release of version 2.0-8 of the BayesMendel package contains an updated BRCAPRO risk prediction model, which includes revised modeling of contralateral breast cancer (CBC) penetrance, provisions for pedigrees of mixed ethnicity and an adjustment for mastectomies among family members. We estimated penetrance functions for CBC by a combination of parametric survival modeling of literature data and deconvolution of SEER9 data. We then validated the resulting updated model of CBC in BRCAPRO by comparing it with the previous release (BayesMendel 2.0-7), using pedigrees from the Cancer Genetics Network (CGN) Model Validation Study. Version 2.0-8 of BRCAPRO discriminates BRCA1/BRCA2 carriers from noncarriers with similar accuracy compared with the previous version (increase in AUC, 0.0043), is slightly more precise in terms of the root-mean-square error (decrease in RMSE, 0.0108), and it significantly improves calibration (ratio of observed to expected events of 0.9765 in version 2.0-8, compared with 0.8910 in version 2.0-7). We recommend that the new version be used in clinical counseling, particularly in settings where families with CBC are common. ©2014 American Association for Cancer Research.

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Year:  2014        PMID: 24891549      PMCID: PMC4119541          DOI: 10.1158/1055-9965.EPI-13-1364

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  19 in total

1.  Assessing the added value of breast tumor markers in genetic risk prediction model BRCAPRO.

Authors:  Swati Biswas; Neelam Tankhiwale; Amanda Blackford; Angelica M Gutierrez Barrera; Kaylene Ready; Karen Lu; Christopher I Amos; Giovanni Parmigiani; Banu Arun
Journal:  Breast Cancer Res Treat       Date:  2012-01-21       Impact factor: 4.872

2.  ROCR: visualizing classifier performance in R.

Authors:  Tobias Sing; Oliver Sander; Niko Beerenwinkel; Thomas Lengauer
Journal:  Bioinformatics       Date:  2005-08-11       Impact factor: 6.937

3.  Interpreting incremental value of markers added to risk prediction models.

Authors:  Michael J Pencina; Ralph B D'Agostino; Karol M Pencina; A Cecile J W Janssens; Philip Greenland
Journal:  Am J Epidemiol       Date:  2012-08-08       Impact factor: 4.897

Review 4.  Epidemiology of contralateral breast cancer.

Authors:  Y Chen; W Thompson; R Semenciw; Y Mao
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  1999-10       Impact factor: 4.254

5.  Providing access to risk prediction tools via the HL7 XML-formatted risk web service.

Authors:  Jonathan Chipman; Brian Drohan; Amanda Blackford; Giovanni Parmigiani; Kevin Hughes; Phil Bosinoff
Journal:  Breast Cancer Res Treat       Date:  2013-06-23       Impact factor: 4.872

6.  Tailoring BRCAPRO to Asian-Americans.

Authors:  Sining Chen; Amanda L Blackford; Giovanni Parmigiani
Journal:  J Clin Oncol       Date:  2008-12-15       Impact factor: 44.544

7.  Contralateral breast cancer in BRCA1 and BRCA2 mutation carriers.

Authors:  Kelly Metcalfe; Henry T Lynch; Parviz Ghadirian; Nadine Tung; Ivo Olivotto; Ellen Warner; Olufunmilayo I Olopade; Andrea Eisen; Barbara Weber; Jane McLennan; Ping Sun; William D Foulkes; Steven A Narod
Journal:  J Clin Oncol       Date:  2004-06-15       Impact factor: 44.544

8.  Accuracy of the BRCAPRO model among women with bilateral breast cancer.

Authors:  Kaylene J Ready; Kristen J Vogel; Deann P Atchley; Kristine R Broglio; Kimberly K Solomon; Christopher Amos; Karen H Lu; Gabriel N Hortobagyi; Banu Arun
Journal:  Cancer       Date:  2009-02-15       Impact factor: 6.860

9.  Incorporating medical interventions into carrier probability estimation for genetic counseling.

Authors:  Hormuzd A Katki
Journal:  BMC Med Genet       Date:  2007-03-22       Impact factor: 2.103

10.  Relation of risk of contralateral breast cancer to the interval since the first primary tumour.

Authors:  C Rubino; R Arriagada; S Delaloge; M G Lê
Journal:  Br J Cancer       Date:  2009-11-17       Impact factor: 7.640

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  7 in total

Review 1.  Mutations in context: implications of BRCA testing in diverse populations.

Authors:  Gabriela E S Felix; Yonglan Zheng; Olufunmilayo I Olopade
Journal:  Fam Cancer       Date:  2018-10       Impact factor: 2.375

2.  Simpson's paradox in the integrated discrimination improvement.

Authors:  J Chipman; D Braun
Journal:  Stat Med       Date:  2016-01-05       Impact factor: 2.373

3.  A Pragmatic Testing-Eligibility Framework for Population Mutation Screening: The Example of BRCA1/2.

Authors:  Ana F Best; Margaret A Tucker; Megan N Frone; Mark H Greene; June A Peters; Hormuzd A Katki
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-01-28       Impact factor: 4.254

Review 4.  Breast cancer risks and risk prediction models.

Authors:  Christoph Engel; Christine Fischer
Journal:  Breast Care (Basel)       Date:  2015-02       Impact factor: 2.860

5.  Breast Cancer Risk Prediction Using Clinical Models and 77 Independent Risk-Associated SNPs for Women Aged Under 50 Years: Australian Breast Cancer Family Registry.

Authors:  Gillian S Dite; Robert J MacInnis; Adrian Bickerstaffe; James G Dowty; Richard Allman; Carmel Apicella; Roger L Milne; Helen Tsimiklis; Kelly-Anne Phillips; Graham G Giles; Mary Beth Terry; Melissa C Southey; John L Hopper
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2015-12-16       Impact factor: 4.254

Review 6.  Recent Enhancements to the Genetic Risk Prediction Model BRCAPRO.

Authors:  Emanuele Mazzola; Amanda Blackford; Giovanni Parmigiani; Swati Biswas
Journal:  Cancer Inform       Date:  2015-05-10

7.  Uncertainty quantification in breast cancer risk prediction models using self-reported family health history.

Authors:  Lance T Pflieger; Clinton C Mason; Julio C Facelli
Journal:  J Clin Transl Sci       Date:  2017-01-20
  7 in total

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