Literature DB >> 17639036

Critical assessment of new risk factors for breast cancer: considerations for development of an improved risk prediction model.

Richard J Santen1, Norman F Boyd, Rowan T Chlebowski, Steven Cummings, Jack Cuzick, Mitch Dowsett, Douglas Easton, John F Forbes, Tim Key, Susan E Hankinson, Anthony Howell, James Ingle.   

Abstract

The majority of candidates for breast cancer prevention have not accepted tamoxifen because of the perception of an unfavorable risk/benefit ratio and the acceptance of raloxifene remains to be determined. One means of improving this ratio is to identify women at very high risk of breast cancer. Family history, age, atypia in a benign biopsy, and reproductive factors are the main parameters currently used to determine risk. The most powerful risk factor, mammographic density, is not presently employed routinely. Other potentially important factors are plasma estrogen and androgen levels, bone density, weight gain, age of menopause, and fracture history, which are also not currently used in a comprehensive risk prediction model because of lack of prospective validation. The Breast Cancer Prevention Collaborative Group (BCPCG) met to critically examine and prioritize risk factors that might be selected for further testing by multivariate analysis using existing clinical material. The BCPCG reached a consensus that quantitative breast density, state of the art plasma estrogen and androgen measurements, history of fracture and height loss, BMI, and waist-hip ratio had sufficient priority for further testing. As a practical approach, these parameters could be added to the existing Tyrer-Cuzick model which encompasses factors included in both the Claus and Gail models. The BCPCG analyzed potentially available clinical material from previous prospective studies and determined that a large case/control study to evaluate these new factors might be feasible at this time.

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Year:  2007        PMID: 17639036     DOI: 10.1677/ERC-06-0045

Source DB:  PubMed          Journal:  Endocr Relat Cancer        ISSN: 1351-0088            Impact factor:   5.678


  80 in total

Review 1.  Estrogen and ERalpha: culprits in cervical cancer?

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Journal:  Trends Endocrinol Metab       Date:  2010-04-22       Impact factor: 12.015

2.  Consistency of breast density measured from the same women using different MR scanners.

Authors:  J-H Chen; S Chan; D H-E Chang; M Lin; M-Y Su
Journal:  Ann Oncol       Date:  2011-10-19       Impact factor: 32.976

3.  Comparison of breast density measured on MR images acquired using fat-suppressed versus nonfat-suppressed sequences.

Authors:  Daniel H-E Chang; Jeon-Hor Chen; Muqing Lin; Shadfar Bahri; Hon J Yu; Rita S Mehta; Ke Nie; David J B Hsiang; Orhan Nalcioglu; Min-Ying Su
Journal:  Med Phys       Date:  2011-11       Impact factor: 4.071

Review 4.  Analysis of estrogens and androgens in postmenopausal serum and plasma by liquid chromatography-mass spectrometry.

Authors:  Qingqing Wang; Lisa Bottalico; Clementina Mesaros; Ian A Blair
Journal:  Steroids       Date:  2014-08-20       Impact factor: 2.668

5.  Breast density quantification using magnetic resonance imaging (MRI) with bias field correction: a postmortem study.

Authors:  Huanjun Ding; Travis Johnson; Muqing Lin; Huy Q Le; Justin L Ducote; Min-Ying Su; Sabee Molloi
Journal:  Med Phys       Date:  2013-12       Impact factor: 4.071

6.  Consistency of breast density measured from the same women in four different MR scanners.

Authors:  Jeon-Hor Chen; Siwa Chan; Yi-Jui Liu; Dah-Cherng Yeh; Chih-Kai Chang; Li-Kuang Chen; Wei-Fan Pan; Chih-Chen Kuo; Muqing Lin; Daniel H E Chang; Peter T Fwu; Min-Ying Su
Journal:  Med Phys       Date:  2012-08       Impact factor: 4.071

7.  Obesity and Breast Cancer: A Complex Relationship.

Authors:  Victoria M Gershuni; Rexford S Ahima; Julia Tchou
Journal:  Curr Surg Rep       Date:  2016-03-21

8.  Overall and Estrogen Receptor-Positive Breast Cancer Incidences Are Decreased Following Bariatric Surgery.

Authors:  Taryn E Hassinger; J Hunter Mehaffey; Robert B Hawkins; Bruce D Schirmer; Peter T Hallowell; Anneke T Schroen; Shayna L Showalter
Journal:  Obes Surg       Date:  2019-03       Impact factor: 4.129

Review 9.  Stable-isotope dilution LC–MS for quantitative biomarker analysis.

Authors:  Eugene Ciccimaro; Ian A Blair
Journal:  Bioanalysis       Date:  2010-02       Impact factor: 2.681

10.  Quantitative analysis of breast parenchymal patterns using 3D fibroglandular tissues segmented based on MRI.

Authors:  Ke Nie; Daniel Chang; Jeon-Hor Chen; Chieh-Chih Hsu; Orhan Nalcioglu; Min-Ying Su
Journal:  Med Phys       Date:  2010-01       Impact factor: 4.071

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