Literature DB >> 7226106

Selected prognostic variables for mammographic parenchymal patterns.

J B Buchanan, B F Weisberg, J P Sandoz, L A Gray, K I Bland.   

Abstract

Conjecture exists about the influence of numerous risk-factors for breast cancer on mammographic parenchymal patterns. To allow more precise documentation of the common variables considered influential in alterations of breast parenchyma, we conducted a randomized retrospective analysis. Of 10,132 women participants in the Louisville Breast Cancer Detection Demonstration Project, every tenth participant was randomly selected for evaluation using SPSS statistical programming. Each accessioned patient had discriminant analysis for the risk factors of age, parity, age at birth of first child, family history, personal history, previous history of breast biopsy, and exogenous estrogen therapy. One-thousand-and-two women were examined for the significance of the selected prognostic variable association with Wolfe mammographic parenchymal patterns (WMPP). Each prognostic factor was tested by chi-square analysis for the low-risk pattern (N1P1) versus the high-risk pattern (P2DY). A high correlation existed between the age of patient and WMPP (P = 0.0002) in the subjects evaluated (50--85 years, mean 60). Similarly, a very significant correlation was evident between WMPP and parity (P = 0.0002), age at birth of first child (P = 0.0014), family history of breast cancer (P = 0.097), and history of previous breast biopsy (P = 0.0066). Little correlation existed between the Wolfe parenchymal pattern classification and a personal history of breast cancer (P = 0.7779) or the use of exogenous estrogens (P = 0.5776).

Entities:  

Mesh:

Substances:

Year:  1981        PMID: 7226106     DOI: 10.1002/1097-0142(19810501)47:9<2135::aid-cncr2820470905>3.0.co;2-b

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  6 in total

Review 1.  Epithelial-mesenchymal transition: general principles and pathological relevance with special emphasis on the role of matrix metalloproteinases.

Authors:  Paola Nisticò; Mina J Bissell; Derek C Radisky
Journal:  Cold Spring Harb Perspect Biol       Date:  2012-02-01       Impact factor: 10.005

Review 2.  Fibrosis and cancer: do myofibroblasts come also from epithelial cells via EMT?

Authors:  Derek C Radisky; Paraic A Kenny; Mina J Bissell
Journal:  J Cell Biochem       Date:  2007-07-01       Impact factor: 4.429

3.  Mammographic changes in postmenopausal women on hormonal replacement therapy.

Authors:  R C Marugg; M J van der Mooren; J H Hendriks; R Rolland; S H Ruijs
Journal:  Eur Radiol       Date:  1997       Impact factor: 5.315

4.  Mammographic density does not differ between unaffected BRCA1/2 mutation carriers and women at low-to-average risk of breast cancer.

Authors:  Gretchen L Gierach; Jennifer T Loud; Catherine K Chow; Sheila A Prindiville; Jennifer Eng-Wong; Peter W Soballe; Claudia Giambartolomei; Phuong L Mai; Claudia E Galbo; Kathryn Nichols; Kathleen A Calzone; Celine Vachon; Mitchell H Gail; Mark H Greene
Journal:  Breast Cancer Res Treat       Date:  2010-02-04       Impact factor: 4.872

Review 5.  Matrix metalloproteinase-induced epithelial-mesenchymal transition in breast cancer.

Authors:  Evette S Radisky; Derek C Radisky
Journal:  J Mammary Gland Biol Neoplasia       Date:  2010-05-05       Impact factor: 2.673

6.  A clinicopathologic correlation of mammographic parenchymal patterns and associated risk factors for human mammary carcinoma.

Authors:  K I Bland; J G Kuhns; J B Buchanan; P A Dwyer; L F Heuser; C A O'Connor; L A Gray; H C Polk
Journal:  Ann Surg       Date:  1982-05       Impact factor: 12.969

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.