Literature DB >> 24771910

Mammographic Density and Prediction of Nodal Status in Breast Cancer Patients.

C C Hack1, L Häberle1, K Geisler1, R Schulz-Wendtland2, A Hartmann3, P A Fasching1, M Uder2, D L Wachter3, S M Jud1, C R Loehberg1, M P Lux1, C Rauh1, M W Beckmann1, K Heusinger1.   

Abstract

Aim: Nodal status remains one of the most important prognostic factors in breast cancer. The cellular and molecular reasons for the spread of tumor cells to the lymph nodes are not well understood and there are only few predictors in addition to tumor size and multifocality that give an insight into additional mechanisms of lymphatic spread. Aim of our study was therefore to investigate whether breast characteristics such as mammographic density (MD) add to the predictive value of the presence of lymph node metastases in patients with primary breast cancer.
Methods: In this retrospective study we analyzed primary, metastasis-free breast cancer patients from one breast center for whom data on MD and staging information were available. A total of 1831 patients were included into this study. MD was assessed as percentage MD (PMD) using a semiautomated method and two readers for every patient. Multiple logistic regression analyses with nodal status as outcome were used to investigate the predictive value of PMD in addition to age, tumor size, Ki-67, estrogen receptor (ER), progesterone receptor (PR), grading, histology, and multi-focality.
Results: Multifocality, tumor size, Ki-67 and grading were relevant predictors for nodal status. Adding PMD to a prediction model which included these factors did not significantly improve the prediction of nodal status (p = 0.24, likelihood ratio test).
Conclusion: Nodal status could be predicted quite well with the factors multifocality, tumor size, Ki-67 and grading. PMD does not seem to play a role in the lymphatic spread of tumor cells. It could be concluded that the amount of extracellular matrix and stromal cell content of the breast which is reflected by MD does not influence the probability of malignant breast cells spreading from the primary tumor to the lymph nodes.

Entities:  

Keywords:  Ki-67; breast cancer; estrogen receptor; mammographic density; nodal status; progesterone receptor

Year:  2013        PMID: 24771910      PMCID: PMC3858989          DOI: 10.1055/s-0032-1328291

Source DB:  PubMed          Journal:  Geburtshilfe Frauenheilkd        ISSN: 0016-5751            Impact factor:   2.915


  38 in total

1.  Effect of baseline breast density on breast cancer incidence, stage, mortality, and screening parameters: 25-year follow-up of a Swedish mammographic screening.

Authors:  Sherry Yueh-Hsia Chiu; Stephen Duffy; Amy Ming-Fang Yen; Laszlo Tabár; Robert A Smith; Hsiu-Hsi Chen
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2010-04-20       Impact factor: 4.254

2.  The association of measured breast tissue characteristics with mammographic density and other risk factors for breast cancer.

Authors:  Tong Li; Limei Sun; Naomi Miller; Trudey Nicklee; Jennifer Woo; Lee Hulse-Smith; Ming-Sound Tsao; Rama Khokha; Lisa Martin; Norman Boyd
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2005-02       Impact factor: 4.254

3.  A bootstrap resampling procedure for model building: application to the Cox regression model.

Authors:  W Sauerbrei; M Schumacher
Journal:  Stat Med       Date:  1992-12       Impact factor: 2.373

4.  Quality assured health care in certified breast centers and improvement of the prognosis of breast cancer patients.

Authors:  Matthias W Beckmann; Cosima Brucker; Volker Hanf; Claudia Rauh; Mayada R Bani; Stefanie Knob; Sabrina Petsch; Stefan Schick; Peter A Fasching; Arndt Hartmann; Michael P Lux; Lothar Häberle
Journal:  Onkologie       Date:  2011-06-15

5.  Association of mammographic density with the proliferation marker Ki-67 in a cohort of patients with invasive breast cancer.

Authors:  Katharina Heusinger; Sebastian M Jud; Lothar Häberle; Carolin C Hack; Peter A Fasching; Martina Meier-Meitinger; Michael P Lux; Carsten Hagenbeck; Christian R Loehberg; Thomas Wittenberg; Claudia Rauh; Florian Wagner; Michael Uder; Arndt Hartmann; Rüdiger Schulz-Wendtland; Matthias W Beckmann; David L Wachter
Journal:  Breast Cancer Res Treat       Date:  2012-08-31       Impact factor: 4.872

6.  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

7.  Mammographic density and hormone receptor expression in breast cancer: the Multiethnic Cohort Study.

Authors:  Shannon M Conroy; Ian Pagano; Laurence N Kolonel; Gertraud Maskarinec
Journal:  Cancer Epidemiol       Date:  2011-01-17       Impact factor: 2.984

8.  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

9.  Interstitial hypertension in human breast and colorectal tumors.

Authors:  J R Less; M C Posner; Y Boucher; D Borochovitz; N Wolmark; R K Jain
Journal:  Cancer Res       Date:  1992-11-15       Impact factor: 12.701

10.  Is there a difference in the association between percent mammographic density and subtypes of breast cancer? Luminal A and triple-negative breast cancer.

Authors:  Huiyan Ma; Jianning Luo; Michael F Press; Yaping Wang; Leslie Bernstein; Giske Ursin
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2009-02-03       Impact factor: 4.254

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  1 in total

1.  Biomarkers in Patients with Metastatic Breast Cancer and the PRAEGNANT Study Network.

Authors:  P A Fasching; S Y Brucker; T N Fehm; F Overkamp; W Janni; M Wallwiener; P Hadji; E Belleville; L Häberle; F-A Taran; D Lüftner; M P Lux; J Ettl; V Müller; H Tesch; D Wallwiener; A Schneeweiss
Journal:  Geburtshilfe Frauenheilkd       Date:  2015-01       Impact factor: 2.915

  1 in total

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