Literature DB >> 32976625

Mammography features for early markers of aggressive breast cancer subtypes and tumor characteristics: A population-based cohort study.

Pui San Tan1, Maya Alsheh Ali1,2, Mikael Eriksson1, Per Hall1,3, Keith Humphreys1,2, Kamila Czene1.   

Abstract

Current breast cancer risk models identify mostly less aggressive tumors, although only women developing fatal breast cancer will greatly benefit from early identification. Here, we evaluated the use of mammography features (microcalcification clusters, computer-generated Breast Imaging Reporting and Data System [cBIRADS] density and lack of breast density reduction) as early markers of aggressive subtypes and tumor characteristics. Mammograms were retrieved from a population-based cohort of women that were diagnosed with breast cancer from 2001 to 2008 in Stockholm-Gotland County, Sweden. Tumor and patient characteristics were obtained from Stockholm Breast Cancer Quality Register and the Swedish Cancer Registry. Multinomial logistic regression was used to individually model each mammographic feature as a function of molecular subtypes, tumor characteristics and detection mode. A total of 4546 women with invasive breast cancer were included in the study. Women with microcalcification clusters in the affected breast were more likely to have human epidermal growth factor receptor 2 subtype (odds ratio [OR] 1.78; 95% confidence interval [CI] 1.24-2.54) and potentially less likely to have basal subtype (OR 0.54; 0.30-0.96) compared to Luminal A subtype. High mammographic cBIRADS showed association with larger tumor size and interval vs screen-detected cancers. Lack of density reduction was associated with interval vs screen-detected cancers (OR 1.43; 1.11-1.83) and potentially of Luminal B subtype vs Luminal A subtype (OR 1.76; 1.04-2.99). In conclusion, microcalcification clusters, cBIRADS density and lack of breast density reduction could serve as early markers of particular subtypes and tumor characteristics of breast cancer. This information has the potential to be integrated into risk models to identify women at risk for developing aggressive breast cancer in need of supplemental screening.
© 2020 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of Union for International Cancer Control.

Entities:  

Keywords:  BIRADS; breast cancer; density change; mammography; microcalcification

Year:  2020        PMID: 32976625      PMCID: PMC7891615          DOI: 10.1002/ijc.33309

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  37 in total

1.  Breast imaging reporting and data system (BI-RADS).

Authors:  Laura Liberman; Jennifer H Menell
Journal:  Radiol Clin North Am       Date:  2002-05       Impact factor: 2.303

2.  Breast screening benefits have been overstated, Danish study finds.

Authors:  Jacqui Wise
Journal:  BMJ       Date:  2017-01-10

3.  Projecting individualized probabilities of developing breast cancer for white females who are being examined annually.

Authors:  M H Gail; L A Brinton; D P Byar; D K Corle; S B Green; C Schairer; J J Mulvihill
Journal:  J Natl Cancer Inst       Date:  1989-12-20       Impact factor: 13.506

4.  Breast Cancer Screening Program in Stockholm County, Sweden - Aspects of Organization and Quality Assurance.

Authors:  Helena Lind; Gunilla Svane; Levent Kemetli; Sven Törnberg
Journal:  Breast Care (Basel)       Date:  2010-10-19       Impact factor: 2.860

5.  A breast cancer prediction model incorporating familial and personal risk factors.

Authors:  Jonathan Tyrer; Stephen W Duffy; Jack Cuzick
Journal:  Stat Med       Date:  2004-04-15       Impact factor: 2.373

6.  Invasive cancers detected after breast cancer screening yielded a negative result: relationship of mammographic density to tumor prognostic factors.

Authors:  Marilyn A Roubidoux; Janet E Bailey; Linda A Wray; Mark A Helvie
Journal:  Radiology       Date:  2004-01       Impact factor: 11.105

7.  A clinical model for identifying the short-term risk of breast cancer.

Authors:  Mikael Eriksson; Kamila Czene; Yudi Pawitan; Karin Leifland; Hatef Darabi; Per Hall
Journal:  Breast Cancer Res       Date:  2017-03-14       Impact factor: 6.466

Review 8.  Detection of potential microcalcification clusters using multivendor for-presentation digital mammograms for short-term breast cancer risk estimation.

Authors:  Maya Alsheh Ali; Mikael Eriksson; Kamila Czene; Per Hall; Keith Humphreys
Journal:  Med Phys       Date:  2019-03-07       Impact factor: 4.071

9.  Changes in mammographic density over time in breast cancer cases and women at high risk for breast cancer.

Authors:  Meghan E Work; Laura L Reimers; Anne S Quante; Katherine D Crew; Amy Whiffen; Mary Beth Terry
Journal:  Int J Cancer       Date:  2014-03-17       Impact factor: 7.396

10.  Mammography features for early markers of aggressive breast cancer subtypes and tumor characteristics: A population-based cohort study.

Authors:  Pui San Tan; Maya Alsheh Ali; Mikael Eriksson; Per Hall; Keith Humphreys; Kamila Czene
Journal:  Int J Cancer       Date:  2020-10-06       Impact factor: 7.396

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  3 in total

1.  Association between quantitative and qualitative image features of contrast-enhanced mammography and molecular subtypes of breast cancer.

Authors:  Simin Wang; Zhenxun Wang; Ruimin Li; Chao You; Ning Mao; Tingting Jiang; Zhongyi Wang; Haizhu Xie; Yajia Gu
Journal:  Quant Imaging Med Surg       Date:  2022-02

Review 2.  The Role of PTX3 in Mineralization Processes and Aging-Related Bone Diseases.

Authors:  Umberto Tarantino; Chiara Greggi; Ida Cariati; Virginia Veronica Visconti; Monica Gasparini; Marco Cateni; Elena Gasbarra; Annalisa Botta; Antonietta Salustri; Manuel Scimeca
Journal:  Front Immunol       Date:  2021-01-29       Impact factor: 7.561

3.  Mammography features for early markers of aggressive breast cancer subtypes and tumor characteristics: A population-based cohort study.

Authors:  Pui San Tan; Maya Alsheh Ali; Mikael Eriksson; Per Hall; Keith Humphreys; Kamila Czene
Journal:  Int J Cancer       Date:  2020-10-06       Impact factor: 7.396

  3 in total

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