Dense Breast Notification Laws: Impact on Downstream Imaging After Screening Mammography

Abstract

Dense breast tissue is a common finding that decreases the sensitivity of mammography in detecting cancer. Many states have recently enacted dense breast notification (DBN) laws to provide patients with information to help them make better-informed decisions about their health. To test whether DBN legislation affected the probability of screening mammography follow-up by ultrasound and magnetic resonance imaging (MRI), we examined the proportion of times screening mammography was followed by ultrasound or MRI for a series of months pre- and post-legislation. The subjects were women aged 40 to 64 years, covered by private health insurance, undergoing screening mammography from 2007 to 2014. Except for Hawaii, Maryland, and New York, DBN legislation significantly increased the probability of ultrasound follow-up in all states that implemented DBN legislation before December 2014. It also increased the probability of MRI follow-up in California, North Carolina, Pennsylvania, and Texas. The financial and access consequences merit further study.

Keywords

screening mammography dense breast tissue follow-up breast ultrasound breast magnetic resonance imaging state law

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References

Athey

Imbens

G. W.

(2006). Identification and inference in nonlinear difference-in-differences models. Econometrica, 74, 431-497.

Bolan

(2013). Breast density notification drives supplemental screening tests. Applied Radiology: Journal of Practical Medical Imaging and Management, 42(10), 27E-28E.

Boyd

N. F.

Guo

Martin

L. J.

Sun

Stone

Fishell

. . . Yaffe

M. J.

(2007). Mammographic density and the risk and detection of breast cancer. New England Journal of Medicine, 356, 227-236.

Centers for Disease Control and Prevention. (2015). Health United States—Tables—2015 complete list. Retrieved from http://www.cdc.gov/nchs/hus/contents2015.htm#070

Cohen

S. L.

Margolies

L. R.

Schwager

S. J.

Zuckerman

Patel

Szabo

Sonnenblick

(2014). Early discussion of breast density and supplemental breast cancer screening: Is it possible? Breast Journal, 20, 229-234.

Dehkordy

S. F.

Carlos

R. C.

(2013). Dense breast legislation in the United States: State of the states. Journal of the American College of Radiology, 10, 899-902.

Duffy

S. W.

Tabar

Olsen

A. H.

Vitak

Allgood

P. C.

Chen

T. H. H.

. . . Smith

R. A.

(2010). Absolute numbers of lives saved and overdiagnosis in breast cancer screening, from a randomized trial and from the Breast Screening Programme in England. Journal of Medical Screening, 17(1), 25-30.

Gatsonis

(2005). Hierarchical Models in health service research. In Encyclopedia of biostatistics. New York, NY: Wiley.

Haas

J. S.

Kaplan

C. P.

(2015). The divide between breast density notification laws and evidence-based guidelines for breast cancer screening: Legislating practice. JAMA Internal Medicine, 175, 1439-1440.

10.

Harvey

S. C.

Vegesna

Mass

Clarke

Skoufalos

(2014). Understanding patient options, utilization patterns, and burdens associated with breast cancer screening. Journal of Women’s Health, 23(Suppl. 1), S3-S9.

11.

Independent UK Panel on Breast Cancer Screening. (2012). The benefits and harms of breast cancer screening: An independent review. Lancet, 380, 1778-1786.

12.

Kalager

Adami

H.-O.

Bretthauer

Tamimi

R. M.

(2012). Overdiagnosis of invasive breast cancer due to mammography screening: Results from the Norwegian screening program. Annals of Internal Medicine, 156, 491-499.

13.

Kerlikowske

Zhu

Tosteson

A. N. A.

Sprague

B. L.

Tice

J. A.

Lehman

C. D.

, . . . Breast Cancer Surveillance Consortium. (2015). Identifying women with dense breasts at high risk for interval cancer: A cohort study. Annals of Internal Medicine, 162, 673-681.

14.

Kressin

N. R.

Gunn

C. M.

Battaglia

T. A.

(2016). Content, readability, and understandability of dense breast notifications by state. JAMA: Journal of the American Medical Association, 315, 1786-1788.

15.

Manning

M. A.

Duric

Littrup

Bey-Knight

Penner

Albrecht

T. L.

(2013). Knowledge of breast density and awareness of related breast cancer risk. Journal of Cancer Education, 28, 270-274.

16.

Marcus

E. N.

Yepes

(2013). The conundrum of explaining breast density to patients. Cleveland Clinic Journal of Medicine, 80, 761-765.

17.

Moss

(2005). Overdiagnosis and overtreatment of breast cancer: Overdiagnosis in randomised controlled trials of breast cancer screening. Breast Cancer Research, 7, 230-234.

18.

Onega

Beaber

E. F.

Sprague

B. L.

Barlow

W. E.

Haas

J. S.

Tosteson

A. N. A.

. . . Conant

E. F.

(2014). Breast cancer screening in an era of personalized regimens: A conceptual model and National Cancer Institute initiative for risk-based and preference-based approaches at a population level. Cancer, 120, 2955-2964.

19.

O’Neill

S. C.

Leventhal

K. G.

Scarles

Evans

C. N.

Makariou

Pien

. . . Willey

(2014). Mammographic breast density as a risk factor for breast cancer: Awareness in a recently screened clinical sample. Women’s Health Issues, 24, e321-e326.

20.

R Core Team. (2016). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from https://www.R-project.org/

21.

Rosenstock

I. M.

(1974). The health belief model and preventive health behavior. Health Education Monographs, 2, 354-386.

22.

Sanders

L. M.

King

A. B.

Goodman

K. S.

(2016). Impact of the New Jersey breast density law on imaging and intervention volumes and breast cancer diagnosis. Journal of the American College of Radiology, 13, 1189-1194.

23.

SAS Institute Inc. (2012). SAS. Cary, NC: Author.

24.

Saslow

Boetes

Burke

Harms

Leach

M. O.

Lehman

C. D.

. . . Russell

C. A.

(2007). American cancer society guidelines for breast screening with MRI as an adjunct to mammography. CA: A Cancer Journal for Clinicians, 57(2), 75-89.

25.

Shadish

W. R.

Cook

T. D.

Campbell

D. T.

(2001). Experimental and quasi-experimental designs for generalized causal inference (2nd ed.). Boston, MA: Cengage Learning.

26.

Slanetz

P. J.

Freer

P. E.

Birdwell

R. L.

(2015). Breast-density legislation—Practical considerations. New England Journal of Medicine, 372, 593-595.

27.

Sobotka

Hinrichs

(2015). Breast density legislation: Discussion of patient utilization and subsequent direct financial ramifications for insurance providers. Journal of the American College of Radiology, 12, 1011-1015.

28.

Sprague

B. L.

Conant

E. F.

Onega

Garcia

M. P.

Beaber

E. F.

Herschorn

S. D.

. . . Barlow

W. E.

(2016). Variation in mammographic breast density assessments among radiologists in clinical practice: A multicenter observational study. Annals of Internal Medicine, 165, 457-464.

29.

Sprague

B. L.

Gangnon

R. E.

Burt

Trentham-Dietz

Hampton

J. M.

Wellman

R. D.

. . . Miglioretti

D. L.

(2014). Prevalence of mammographically dense breasts in the United States. Journal of the National Cancer Institute, 106(10), dju255.

30.

Sprague

B. L.

Stout

N. K.

Schechter

van Ravesteyn

N. T.

Cevik

Alagoz

. . . Tosteson

A. N.

(2015). Benefits, harms, and cost-effectiveness of supplemental ultrasonography screening for women with dense breasts. Annals of Internal Medicine, 162, 157-166.

31.

Trochim

Donnelly

J. P.

Arora

(2015). Research methods: The essential knowledge base (2nd ed.). Boston, MA: Cengage Learning.

32.

Yeh

V. M.

Schnur

J. B.

Margolies

Montgomery

G. H.

(2015). Dense breast tissue notification: Impact on women’s perceived risk, anxiety, and intentions for future breast cancer screening. Journal of the American College of Radiology, 12, 261-266.

33.

Zackrisson

Andersson

Janzon

Manjer

Garne

J. P.

(2006). Rate of over-diagnosis of breast cancer 15 years after end of Malmö mammographic screening trial: Follow-up study. British Medical Journal, 332, 689-692.

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