Literature DB >> 26290416

Breast cancer screening in the era of density notification legislation: summary of 2014 Massachusetts experience and suggestion of an evidence-based management algorithm by multi-disciplinary expert panel.

Phoebe E Freer1, Priscilla J Slanetz, Jennifer S Haas, Nadine M Tung, Kevin S Hughes, Katrina Armstrong, A Alan Semine, Susan L Troyan, Robyn L Birdwell.   

Abstract

Stemming from breast density notification legislation in Massachusetts effective 2015, we sought to develop a collaborative evidence-based approach to density notification that could be used by practitioners across the state. Our goal was to develop an evidence-based consensus management algorithm to help patients and health care providers follow best practices to implement a coordinated, evidence-based, cost-effective, sustainable practice and to standardize care in recommendations for supplemental screening. We formed the Massachusetts Breast Risk Education and Assessment Task Force (MA-BREAST) a multi-institutional, multi-disciplinary panel of expert radiologists, surgeons, primary care physicians, and oncologists to develop a collaborative approach to density notification legislation. Using evidence-based data from the Institute for Clinical and Economic Review, the Cochrane review, National Comprehensive Cancer Network guidelines, American Cancer Society recommendations, and American College of Radiology appropriateness criteria, the group collaboratively developed an evidence-based best-practices algorithm. The expert consensus algorithm uses breast density as one element in the risk stratification to determine the need for supplemental screening. Women with dense breasts and otherwise low risk (<15% lifetime risk), do not routinely require supplemental screening per the expert consensus. Women of high risk (>20% lifetime) should consider supplemental screening MRI in addition to routine mammography regardless of breast density. We report the development of the multi-disciplinary collaborative approach to density notification. We propose a risk stratification algorithm to assess personal level of risk to determine the need for supplemental screening for an individual woman.

Entities:  

Mesh:

Year:  2015        PMID: 26290416      PMCID: PMC4592317          DOI: 10.1007/s10549-015-3534-9

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  39 in total

1.  Accuracy of assigned BI-RADS breast density category definitions.

Authors:  Brandi T Nicholson; Alexander P LoRusso; Mark Smolkin; Viktor E Bovbjerg; Gina R Petroni; Jennifer A Harvey
Journal:  Acad Radiol       Date:  2006-09       Impact factor: 3.173

2.  Performance benchmarks for screening mammography.

Authors:  Robert D Rosenberg; Bonnie C Yankaskas; Linn A Abraham; Edward A Sickles; Constance D Lehman; Berta M Geller; Patricia A Carney; Karla Kerlikowske; Diana S M Buist; Donald L Weaver; William E Barlow; Rachel Ballard-Barbash
Journal:  Radiology       Date:  2006-10       Impact factor: 11.105

3.  Mammographic density and the risk and detection of breast cancer.

Authors:  Norman F Boyd; Helen Guo; Lisa J Martin; Limei Sun; Jennifer Stone; Eve Fishell; Roberta A Jong; Greg Hislop; Anna Chiarelli; Salomon Minkin; Martin J Yaffe
Journal:  N Engl J Med       Date:  2007-01-18       Impact factor: 91.245

4.  American Cancer Society guidelines for breast screening with MRI as an adjunct to mammography.

Authors:  Debbie Saslow; Carla Boetes; Wylie Burke; Steven Harms; Martin O Leach; Constance D Lehman; Elizabeth Morris; Etta Pisano; Mitchell Schnall; Stephen Sener; Robert A Smith; Ellen Warner; Martin Yaffe; Kimberly S Andrews; Christy A Russell
Journal:  CA Cancer J Clin       Date:  2007 Mar-Apr       Impact factor: 508.702

5.  Diagnostic accuracy of digital versus film mammography: exploratory analysis of selected population subgroups in DMIST.

Authors:  Etta D Pisano; R Edward Hendrick; Martin J Yaffe; Janet K Baum; Suddhasatta Acharyya; Jean B Cormack; Lucy A Hanna; Emily F Conant; Laurie L Fajardo; Lawrence W Bassett; Carl J D'Orsi; Roberta A Jong; Murray Rebner; Anna N A Tosteson; Constantine A Gatsonis
Journal:  Radiology       Date:  2008-02       Impact factor: 11.105

6.  Efficacy of screening mammography among women aged 40 to 49 years and 50 to 69 years: comparison of relative and absolute benefit.

Authors:  K Kerlikowske
Journal:  J Natl Cancer Inst Monogr       Date:  1997

7.  Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis.

Authors:  Valerie A McCormack; Isabel dos Santos Silva
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2006-06       Impact factor: 4.254

8.  Comparison of breast consistency at palpation with breast density at mammography.

Authors:  W L Boren; T B Hunter; J C Bjelland; K R Hunt
Journal:  Invest Radiol       Date:  1990-09       Impact factor: 6.016

9.  Variability and accuracy in mammographic interpretation using the American College of Radiology Breast Imaging Reporting and Data System.

Authors:  K Kerlikowske; D Grady; J Barclay; S D Frankel; S H Ominsky; E A Sickles; V Ernster
Journal:  J Natl Cancer Inst       Date:  1998-12-02       Impact factor: 13.506

10.  Using clinical factors and mammographic breast density to estimate breast cancer risk: development and validation of a new predictive model.

Authors:  Jeffrey A Tice; Steven R Cummings; Rebecca Smith-Bindman; Laura Ichikawa; William E Barlow; Karla Kerlikowske
Journal:  Ann Intern Med       Date:  2008-03-04       Impact factor: 25.391

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  8 in total

1.  Acceptability of an Interactive Computer-Animated Agent to Promote Patient-Provider Communication About Breast Density: a Mixed Method Pilot Study.

Authors:  Christine Gunn; Ariel Maschke; Timothy Bickmore; Mark Kennedy; Margaret F Hopkins; Michael D C Fishman; Michael K Paasche-Orlow; Erica T Warner
Journal:  J Gen Intern Med       Date:  2020-01-09       Impact factor: 5.128

Review 2.  Risk-based Breast Cancer Screening: Implications of Breast Density.

Authors:  Christoph I Lee; Linda E Chen; Joann G Elmore
Journal:  Med Clin North Am       Date:  2017-07       Impact factor: 5.456

3.  Physician Knowledge, Attitudes, and Practices Regarding Breast Density.

Authors:  Jordonna Brown; Chloe Soukas; Jenny J Lin; Laurie Margolies; Marimer Santiago-Rivas; Lina Jandorf
Journal:  J Womens Health (Larchmt)       Date:  2019-05-07       Impact factor: 2.681

4.  A Qualitative Study of Spanish-Speakers' Experience with Dense Breast Notifications in a Massachusetts Safety-Net Hospital.

Authors:  Christine M Gunn; Amy Fitzpatrick; Sarah Waugh; Michelle Carrera; Nancy R Kressin; Michael K Paasche-Orlow; Tracy A Battaglia
Journal:  J Gen Intern Med       Date:  2018-10-22       Impact factor: 5.128

5.  Primary Care Provider Experience with Breast Density Legislation in Massachusetts.

Authors:  Christine M Gunn; Nancy R Kressin; Kristina Cooper; Cinthya Marturano; Karen M Freund; Tracy A Battaglia
Journal:  J Womens Health (Larchmt)       Date:  2018-01-17       Impact factor: 2.681

6.  The Effect of California's Breast Density Notification Legislation on Breast Cancer Screening.

Authors:  Stephanie Lynn Chau; Amy Alabaster; Karin Luikart; Leslie Manace Brenman; Laurel A Habel
Journal:  J Prim Care Community Health       Date:  2016-10-31

7.  Explaining Breast Density Recommendations: An Introductory Workshop for Breast Health Providers.

Authors:  Rachel S Casas; Ambili Ramachandran; Christine M Gunn; Janice M Weinberg; Kitt Shaffer
Journal:  MedEdPORTAL       Date:  2017-11-21

8.  The Feasibility of Classifying Breast Masses Using a Computer-Assisted Diagnosis (CAD) System Based on Ultrasound Elastography and BI-RADS Lexicon.

Authors:  Eduardo F C Fleury; Ana Claudia Gianini; Karem Marcomini; Vilmar Oliveira
Journal:  Technol Cancer Res Treat       Date:  2018-01-01
  8 in total

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