Literature DB >> 10663736

Size, node status and grade of breast tumours: association with mammographic parenchymal patterns.

E Sala1, L Solomon, R Warren, J McCann, S Duffy, R Luben, N Day.   

Abstract

A case-control study was designed to assess the association of mammographic parenchymal patterns with the risk of in-situ and invasive breast cancer. In addition, the relationship between tumour characteristics and mammographic patterns were also investigated. A total of 875 patients with breast cancer were selected and matched with 2601 controls. Mammographic parenchymal patterns of breast tissue were assessed according to Wolfe's classification, and statistical analysis was by conditional logistic regression. Relative to the N1 pattern, the odds ratios of having an invasive breast cancer associated with the P2 and DY patterns were 1.8 and 1. 4, respectively. In addition, the odd ratios of having an invasive grade 3 breast cancer associated with the P2 and DY patterns were 2. 8 and 3.9, respectively. Relative to the combined N1/P1 pattern, the odd ratios of having a breast cancer smaller than 14 mm, 15-29 mm, or larger than 30 mm associated with the combined high-risk P2/DY pattern (P2 + DY) were 1.2, 1.6, and 2.0, respectively. Finally, women with the P2/DY pattern were twice as likely to have a breast cancer which had already spread to the axillary nodes, compared to women with women with the N1/P1 pattern (odds ratios of 2.1 and 1.4, respectively). Our results confirm previous findings suggesting that mammographic parenchymal patterns may serve as indicators of risk for breast cancer. Our results also suggest that mammographic parenchymal patterns are associated with the stage at which breast cancer is detected.

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Year:  2000        PMID: 10663736     DOI: 10.1007/s003300050025

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  26 in total

1.  Breast cancer risk by breast density, menopause, and postmenopausal hormone therapy use.

Authors:  Karla Kerlikowske; Andrea J Cook; Diana S M Buist; Steve R Cummings; Celine Vachon; Pamela Vacek; Diana L Miglioretti
Journal:  J Clin Oncol       Date:  2010-07-19       Impact factor: 44.544

2.  Breast density influences tumor subtypes and tumor aggressiveness.

Authors:  Karla Kerlikowske; Amanda I Phipps
Journal:  J Natl Cancer Inst       Date:  2011-07-27       Impact factor: 13.506

Review 3.  A review of the influence of mammographic density on breast cancer clinical and pathological phenotype.

Authors:  Michael S Shawky; Cecilia W Huo; Kara Britt; Erik W Thompson; Michael A Henderson; Andrew Redfern
Journal:  Breast Cancer Res Treat       Date:  2019-06-08       Impact factor: 4.872

4.  Interaction of mammographic breast density with menopausal status and postmenopausal hormone use in relation to the risk of aggressive breast cancer subtypes.

Authors:  Lusine Yaghjyan; Rulla M Tamimi; Kimberly A Bertrand; Christopher G Scott; Matthew R Jensen; V Shane Pankratz; Kathy Brandt; Daniel Visscher; Aaron Norman; Fergus Couch; John Shepherd; Bo Fan; Yunn-Yi Chen; Lin Ma; Andrew H Beck; Steven R Cummings; Karla Kerlikowske; Celine M Vachon
Journal:  Breast Cancer Res Treat       Date:  2017-06-17       Impact factor: 4.872

5.  Mammographic breast density and subsequent risk of breast cancer in postmenopausal women according to tumor characteristics.

Authors:  Lusine Yaghjyan; Graham A Colditz; Laura C Collins; Stuart J Schnitt; Bernard Rosner; Celine Vachon; Rulla M Tamimi
Journal:  J Natl Cancer Inst       Date:  2011-07-27       Impact factor: 13.506

6.  Very low mammographic breast density predicts poorer outcome in patients with invasive breast cancer.

Authors:  Amro Masarwah; Päivi Auvinen; Mazen Sudah; Suvi Rautiainen; Anna Sutela; Outi Pelkonen; Sanna Oikari; Veli-Matti Kosma; Ritva Vanninen
Journal:  Eur Radiol       Date:  2015-03-04       Impact factor: 5.315

7.  Relationship between mammographic density and breast cancer death in the Breast Cancer Surveillance Consortium.

Authors:  Gretchen L Gierach; Laura Ichikawa; Karla Kerlikowske; Louise A Brinton; Ghada N Farhat; Pamela M Vacek; Donald L Weaver; Catherine Schairer; Stephen H Taplin; Mark E Sherman
Journal:  J Natl Cancer Inst       Date:  2012-08-21       Impact factor: 13.506

8.  Outcomes of screening mammography by frequency, breast density, and postmenopausal hormone therapy.

Authors:  Karla Kerlikowske; Weiwei Zhu; Rebecca A Hubbard; Berta Geller; Kim Dittus; Dejana Braithwaite; Karen J Wernli; Diana L Miglioretti; Ellen S O'Meara
Journal:  JAMA Intern Med       Date:  2013-05-13       Impact factor: 21.873

9.  Association of mammographic density with the pathology of subsequent breast cancer among postmenopausal women.

Authors:  Karthik Ghosh; Kathleen R Brandt; Thomas A Sellers; Carol Reynolds; Christopher G Scott; Shaun D Maloney; Michael J Carston; V Shane Pankratz; Celine M Vachon
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2008-04       Impact factor: 4.254

10.  Prediction of neoadjuvant chemotherapy response in high-grade osteosarcoma: added value of non-tumorous bone radiomics using CT images.

Authors:  Lei Xu; Pengfei Yang; Kun Hu; Yan Wu; Meng Xu-Welliver; Yidong Wan; Chen Luo; Jing Wang; Jinhua Wang; Jiale Qin; Yi Rong; Tianye Niu
Journal:  Quant Imaging Med Surg       Date:  2021-04
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