Literature DB >> 12869401

The detection of change in mammographic density.

J Stone1, A Gunasekara, L J Martin, M Yaffe, S Minkin, N F Boyd.   

Abstract

Mammographic density is associated with risk of breast cancer, and factors that change density may also change risk. There has, however, been little research into how change in serial mammograms is best detected. The purpose of the work described here was to examine the effects of different reading conditions on the detection of change in mammographic features. Mammograms were selected from women who had participated in a randomized controlled trial of screening for breast cancer. We selected two age-matched groups of subjects, one had undergone menopause after entry (n = 202) and another who had not (n = 202). Serial mammograms from these subjects were then measured four times using a computer-assisted method under different conditions: (a) films were randomized; (b) subjects were randomized (i.e., pairs of films from individuals were read one after the other), but the order of films was random and unknown to the reader; (c) subjects were randomized, and the order of films was sequential and known to the reader; and (d) subjects were randomized, and the order of films was random and unknown to the reader, but both films in each pair were read simultaneously on separate computer screens. The mean effect of the menopause on change in the mammographic measures of total, dense and nondense areas, percent density, and the associated variances were then compared. With one exception, all of the randomization and viewing methods confirmed a change in all mammographic measures at menopause and produced very similar overall results, suggesting that mammographic density is a robust measure. Compared with randomization of all films, the method in which subjects were randomized and paired films read one after the other in random and unknown order was associated with a slightly smaller mean difference and achieved a substantial reduction in variability, suggesting that it is the most sensitive method of randomization and viewing for the detection of change.

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Year:  2003        PMID: 12869401

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  16 in total

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Authors:  Carol J Fabian; Bruce F Kimler; Teresa A Phillips; Jennifer L Nydegger; Amy L Kreutzjans; Susan E Carlson; Brandon H Hidaka; Trina Metheny; Carola M Zalles; Gordon B Mills; Kandy R Powers; Debra K Sullivan; Brian K Petroff; Whitney L Hensing; Brooke L Fridley; Stephen D Hursting
Journal:  Cancer Prev Res (Phila)       Date:  2015-08-14

2.  Clinical Trial of Acolbifene in Premenopausal Women at High Risk for Breast Cancer.

Authors:  Carol J Fabian; Bruce F Kimler; Carola M Zalles; Teresa A Phillips; Trina Metheny; Brian K Petroff; Thomas C Havighurst; KyungMann Kim; Howard H Bailey; Brandy M Heckman-Stoddard
Journal:  Cancer Prev Res (Phila)       Date:  2015-09-21

3.  Modulation of Breast Cancer Risk Biomarkers by High-Dose Omega-3 Fatty Acids: Phase II Pilot Study in Premenopausal Women.

Authors:  Carol J Fabian; Bruce F Kimler; Teresa A Phillips; Jessica A Box; Amy L Kreutzjans; Susan E Carlson; Brandon H Hidaka; Trina Metheny; Carola M Zalles; Gordon B Mills; Kandy R Powers; Debra K Sullivan; Brian K Petroff; Whitney L Hensing; Brooke L Fridley; Stephen D Hursting
Journal:  Cancer Prev Res (Phila)       Date:  2015-10

4.  Mammographic breast density and tolerance for short-term postmenopausal hormone therapy suspension.

Authors:  Erin J Aiello Bowles; Melissa L Anderson; Susan D Reed; Katherine M Newton; E Dawn Fitzgibbons; Deborah Seger; Diana S M Buist
Journal:  J Womens Health (Larchmt)       Date:  2010-08       Impact factor: 2.681

5.  Determinants of the reliability of ultrasound tomography sound speed estimates as a surrogate for volumetric breast density.

Authors:  Zeina G Khodr; Mark A Sak; Ruth M Pfeiffer; Nebojsa Duric; Peter Littrup; Lisa Bey-Knight; Haythem Ali; Patricia Vallieres; Mark E Sherman; Gretchen L Gierach
Journal:  Med Phys       Date:  2015-10       Impact factor: 4.071

6.  Mammographic Density Change With Estrogen and Progestin Therapy and Breast Cancer Risk.

Authors:  Celia Byrne; Giske Ursin; Christopher F Martin; Jennifer D Peck; Elodia B Cole; Donglin Zeng; Eunhee Kim; Martin D Yaffe; Norman F Boyd; Gerardo Heiss; Anne McTiernan; Rowan T Chlebowski; Dorothy S Lane; JoAnn E Manson; Jean Wactawski-Wende; Etta D Pisano
Journal:  J Natl Cancer Inst       Date:  2017-09-01       Impact factor: 13.506

7.  An automated approach for estimation of breast density.

Authors:  John J Heine; Michael J Carston; Christopher G Scott; Kathleen R Brandt; Fang-Fang Wu; Vernon Shane Pankratz; Thomas A Sellers; Celine M Vachon
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2008-11       Impact factor: 4.254

8.  Conjugated equine estrogen influence on mammographic density in postmenopausal women in a substudy of the women's health initiative randomized trial.

Authors:  Anne McTiernan; Rowan T Chlebowski; Christopher Martin; Jennifer David Peck; Aaron Aragaki; Etta D Pisano; C Y Wang; Karen C Johnson; Joann E Manson; Robert B Wallace; Mara Z Vitolins; Gerardo Heiss
Journal:  J Clin Oncol       Date:  2009-11-09       Impact factor: 44.544

9.  Mammographic Breast Density and Acculturation: Longitudinal Analysis in Chinese Immigrants.

Authors:  Rebeca Almeida; Carolyn Y Fang; Celia Byrne; Marilyn Tseng
Journal:  J Immigr Minor Health       Date:  2020-10-10

10.  Texture features from mammographic images and risk of breast cancer.

Authors:  Armando Manduca; Michael J Carston; John J Heine; Christopher G Scott; V Shane Pankratz; Kathy R Brandt; Thomas A Sellers; Celine M Vachon; James R Cerhan
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2009-03-03       Impact factor: 4.254

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