Literature DB >> 15809722

Clinical significance of categorisation of mammographic density for breast cancer prognosis.

Mariko Morishita1, Akira Ohtsuru, Tomayoshi Hayashi, Ichiro Isomoto, Noriaki Itoyanagi, Shigeto Maeda, Sumihisa Honda, Hiroshi Yano, Tatsuya Uga, Takeshi Nagayasu, Takashi Kanematsu, Shunichi Yamashita.   

Abstract

Mammographic density reflects comprehensive changes in the mammary gland. The condition of the tumour microenvironment is a possible factor affecting tumour progression, as well as a tumour risk factor. This study aimed to determine whether mammographic density correlates with tumour clinicopathological features and prognosis in breast cancer patients. The analysis involved 163 Japanese women who underwent surgery for breast cancer between 1999 and 2003 in the Nagasaki University Hospital, Japan. Mammographic density was classified according to the breast imaging reporting and data system (BI-RADS) categories 1-4. Age, tumour size, axillary lymph node involvement, steroid receptor (SR) status, histological grade and Nottingham prognostic index (NPI) were analysed by density category and tested for statistically significant differences across categories. A significant difference (P<0.05) by breast-density category was found only for age. SR-negative tumours had significantly worse NPI scores than SR-positive tumours in breast-density categories 2 (P=0.03) and 4 (P<0.001). A high distant-metastasis frequency was observed in category 4 SR negatives (44%) versus category 4 SR positives (4.3%). These findings reveal that although the BI-RADS breast-density category alone is not associated with prognosis in breast cancer, patients who are both category 4 and SR negative have an extremely poor prognosis.

Entities:  

Mesh:

Substances:

Year:  2005        PMID: 15809722

Source DB:  PubMed          Journal:  Int J Oncol        ISSN: 1019-6439            Impact factor:   5.650


  5 in total

Review 1.  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

2.  Benign breast tissue composition in breast cancer patients: association with risk factors, clinical variables, and gene expression.

Authors:  Xuezheng Sun; Rupninder Sandhu; Jonine D Figueroa; Gretchen L Gierach; Mark E Sherman; Melissa A Troester
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2014-09-23       Impact factor: 4.254

Review 3.  Mammographic density and breast cancer risk: current understanding and future prospects.

Authors:  Norman F Boyd; Lisa J Martin; Martin J Yaffe; Salomon Minkin
Journal:  Breast Cancer Res       Date:  2011-11-01       Impact factor: 6.466

4.  Association between mammographic density and basal-like and luminal A breast cancer subtypes.

Authors:  Hilda Razzaghi; Melissa A Troester; Gretchen L Gierach; Andrew F Olshan; Bonnie C Yankaskas; Robert C Millikan
Journal:  Breast Cancer Res       Date:  2013       Impact factor: 6.466

5.  Reliability of the percent density in digital mammography with a semi-automated thresholding method.

Authors:  Guiyun Sohn; Jong Won Lee; Sung Won Park; Jihoon Park; Jiyoung Woo; Hwa Jung Kim; Hee Jung Shin; Hak Hee Kim; Kyung Hae Jung; Joohon Sung; Seung Wook Lee; Byung Ho Son; Sei-Hyun Ahn
Journal:  J Breast Cancer       Date:  2014-06-27       Impact factor: 3.588

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.