Literature DB >> 9934652

Mammographic parenchymal patterns and mode of detection: implications for the breast screening programme.

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

Abstract

OBJECTIVES: To assess the effects of mammographic parenchymal patterns on the risk of breast cancer detected at first screen, second screen, and in the interval between these two screens. SETTINGS: A nested case-control study within a screening cohort in East Anglia was designed. The study group comprised 502 patients with cancer at the prevalence screening round, 198 patients with interval cancer, and 175 with cancer at the first incidence screen. These patients were matched with 2601 controls.
METHODS: The mammographic parenchymal patterns of breast tissue were assessed according to Wolfe's classification. Statistical analysis was by conditional logistic regression.
RESULTS: Overall, 67% of patients and 59% of controls were considered to have high risk pattern (P2 + DY) mammogram. The risk associated with P2 or DY mammographic patterns compared with N1 was higher for interval cancers (odds ratios (ORs) 2.2 and 2.4 respectively) than for screen detected cancers (ORs 1.7 and 1.1 respectively). For interval cancers in the first 18 months after the last negative mammogram, the risk was particularly high (ORs 3.8 for P2 and 4.1 for DY compared with N1). The high risk associated with P2 and DY patterns was concentrated on invasive ductal grade III cancers (ORs 2.7 and 3.8) rather than grade I or II cancers (ORs 1.6 and 1.2).
CONCLUSIONS: The study strongly suggests that screening effectiveness is reduced for high risk parenchymal patterns which are associated with high grade cancers. Changes should aim at improving screening sensitivity for dense parenchymal patterns, and the diagnosis of high grade tumours.

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Year:  1998        PMID: 9934652     DOI: 10.1136/jms.5.4.207

Source DB:  PubMed          Journal:  J Med Screen        ISSN: 0969-1413            Impact factor:   2.136


  28 in total

Review 1.  Clinical and epidemiological issues in mammographic density.

Authors:  Valentina Assi; Jane Warwick; Jack Cuzick; Stephen W Duffy
Journal:  Nat Rev Clin Oncol       Date:  2011-12-06       Impact factor: 66.675

Review 2.  Breast tissue composition and susceptibility to breast cancer.

Authors:  Norman F Boyd; Lisa J Martin; Michael Bronskill; Martin J Yaffe; Neb Duric; Salomon Minkin
Journal:  J Natl Cancer Inst       Date:  2010-07-08       Impact factor: 13.506

3.  Annual vs Biennial Screening: Diagnostic Accuracy Among Concurrent Cohorts Within the Ontario Breast Screening Program.

Authors:  Anna M Chiarelli; Kristina M Blackmore; Lucia Mirea; Susan J Done; Vicky Majpruz; Ashini Weerasinghe; Linda Rabeneck; Derek Muradali
Journal:  J Natl Cancer Inst       Date:  2020-04-01       Impact factor: 13.506

4.  Evaluation of the kinetic properties of background parenchymal enhancement throughout the phases of the menstrual cycle.

Authors:  Alana R Amarosa; Jason McKellop; Ana Paula Klautau Leite; Melanie Moccaldi; Tess V Clendenen; James S Babb; Anne Zeleniuch-Jacquotte; Linda Moy; Sungheon Kim
Journal:  Radiology       Date:  2013-05-08       Impact factor: 11.105

5.  Radiologic findings of screen-detected cancers in an organized population-based screening mammography program in Turkey.

Authors:  Arda Kayhan; Erkin Arıbal; Cennet Şahin; Ömür Can Taşçı; Sibel Özkan Gürdal; Enis Öztürk; Hayat Halide Hatipoğlu; Nilüfer Özaydın; Neslihan Cabioğlu; Beyza Özçınar; Vahit Özmen
Journal:  Diagn Interv Radiol       Date:  2016 Nov-Dec       Impact factor: 2.630

6.  Validation of a method for measuring the volumetric breast density from digital mammograms.

Authors:  O Alonzo-Proulx; N Packard; J M Boone; A Al-Mayah; K K Brock; S Z Shen; M J Yaffe
Journal:  Phys Med Biol       Date:  2010-05-12       Impact factor: 3.609

7.  Influence of personal characteristics of individual women on sensitivity and specificity of mammography in the Million Women Study: cohort study.

Authors:  Emily Banks; Gillian Reeves; Valerie Beral; Diana Bull; Barbara Crossley; Moya Simmonds; Elizabeth Hilton; Stephen Bailey; Nigel Barrett; Peter Briers; Ruth English; Alan Jackson; Elizabeth Kutt; Janet Lavelle; Linda Rockall; Matthew G Wallis; Mary Wilson; Julietta Patnick
Journal:  BMJ       Date:  2004-08-28

8.  Mammographic density and markers of socioeconomic status: a cross-sectional study.

Authors:  Zoe Aitken; Kate Walker; Bernardine H Stegeman; Petra A Wark; Sue M Moss; Valerie A McCormack; Isabel dos Santos Silva
Journal:  BMC Cancer       Date:  2010-02-09       Impact factor: 4.430

9.  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

Review 10.  Mammographic density.

Authors:  Norman F Boyd; Lisa J Martin; Martin Yaffe; Salomon Minkin
Journal:  Breast Cancer Res       Date:  2009-12-18       Impact factor: 6.466

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