Literature DB >> 20427433

Assessing women at high risk of breast cancer: a review of risk assessment models.

Eitan Amir1, Orit C Freedman, Bostjan Seruga, D Gareth Evans.   

Abstract

Women who are at high risk of breast cancer can be offered more intensive surveillance or prophylactic measures, such as surgery or chemoprevention. Central to decisions regarding the level of prevention is accurate and individualized risk assessment. This review aims to distill the diverse literature and provide practicing clinicians with an overview of the available risk assessment methods. Risk assessments fall into two groups: the risk of carrying a mutation in a high-risk gene such as BRCA1 or BRCA2 and the risk of developing breast cancer with or without such a mutation. Knowledge of breast cancer risks, taken together with the risks and benefits of the intervention, is needed to choose an appropriate disease management strategy. A number of models have been developed for assessing these risks, but independent validation of such models has produced variable results. Some models are able to predict both mutation carriage risks and breast cancer risk; however, to date, all are limited by only moderate discriminatory accuracy. Further improvements in the knowledge of how to best integrate both new risk factors and newly discovered genetic variants into these models will allow clinicians to more accurately determine which women are most likely to develop breast cancer. These steady and incremental improvements in models will need to undergo revalidation.

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Year:  2010        PMID: 20427433     DOI: 10.1093/jnci/djq088

Source DB:  PubMed          Journal:  J Natl Cancer Inst        ISSN: 0027-8874            Impact factor:   13.506


  154 in total

1.  Validation of three BRCA1/2 mutation-carrier probability models Myriad, BRCAPRO and BOADICEA in a population-based series of 183 German families.

Authors:  S M Schneegans; A Rosenberger; U Engel; M Sander; G Emons; M Shoukier
Journal:  Fam Cancer       Date:  2012-06       Impact factor: 2.375

2.  Residual confounding after adjustment for age: a minor issue in breast cancer screening effectiveness.

Authors:  Guido van Schoor; Ellen Paap; Mireille J M Broeders; André L M Verbeek
Journal:  Eur J Epidemiol       Date:  2011-04-26       Impact factor: 8.082

3.  An interactive system for computer-aided diagnosis of breast masses.

Authors:  Xingwei Wang; Lihua Li; Wei Liu; Weidong Xu; Dror Lederman; Bin Zheng
Journal:  J Digit Imaging       Date:  2012-10       Impact factor: 4.056

4.  Affective forecasting and medication decision making in breast-cancer prevention.

Authors:  Michael Hoerger; Laura D Scherer; Angela Fagerlin
Journal:  Health Psychol       Date:  2016-02-11       Impact factor: 4.267

5.  Osteoprotective effect of soybean and sesame oils in ovariectomized rats via estrogen-like mechanism.

Authors:  Azza M El Wakf; Hanaa A Hassan; Nermin S Gharib
Journal:  Cytotechnology       Date:  2013-06-08       Impact factor: 2.058

6.  The FMR1 CGG repeat test is not a candidate prescreening tool for identifying women with a high probability of being carriers of BRCA mutations.

Authors:  Maria Teresa Ricci; Loredana Pennese; Viviana Gismondi; Chiara Perfumo; Marina Grasso; Elena Gennaro; Paolo Bruzzi; Liliana Varesco
Journal:  Eur J Hum Genet       Date:  2013-09-25       Impact factor: 4.246

7.  Prediction of near-term breast cancer risk based on bilateral mammographic feature asymmetry.

Authors:  Maxine Tan; Bin Zheng; Pandiyarajan Ramalingam; David Gur
Journal:  Acad Radiol       Date:  2013-12       Impact factor: 3.173

8.  Applying a new bilateral mammographic density segmentation method to improve accuracy of breast cancer risk prediction.

Authors:  Shiju Yan; Yunzhi Wang; Faranak Aghaei; Yuchen Qiu; Bin Zheng
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-07-19       Impact factor: 2.924

Review 9.  Risk-Reducing Options for Women with a Hereditary Breast Cancer Predisposition.

Authors:  Ismail Jatoi
Journal:  Eur J Breast Health       Date:  2018-10-01

10.  Assessing breast cancer risk models in Marin County, a population with high rates of delayed childbirth.

Authors:  Mark Powell; Farid Jamshidian; Kate Cheyne; Joanne Nititham; Lee Ann Prebil; Rochelle Ereman
Journal:  Clin Breast Cancer       Date:  2013-11-22       Impact factor: 3.225

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