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Ten Years Later
Breast Density Gains Acceptance As Breast
Cancer Risk Factor
By Vicki Brower
This is part of an occasional series that updates
some of the stories reported 10 years ago in the
news section of the Journal.
Breast cancer patients with very dense breasts
who undergo lumpectomy have a greater risk of
recurrence than women with less dense breasts,
according to a new 10-year Canadian study that
appeared in the December 15 issue of Cancer.
Led by Steven Narod, M.D., at the University
of Toronto, the study is the most recent confirmation of the importance of breast density in
the biology of breast cancer. Ten years ago, a
JNCI news story reported that breast density
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had been shown to be a risk factor for breast
cancer, but that there was little agreement on
how to measure density or how it contributed to
risk. Today, many studies later, those questions
remain, but density is more firmly established as
a key risk factor and has been incorporated into
widely used breast cancer risk models.
“During the past decade, about three dozen
studies have demonstrated that breast density
may be the single most important factor for
cancer risk,” said Jack Cuzick, Ph.D., professor of epidemiology at the Wolfson Institute
of Preventive Medicine in London. Scientists
now estimate that dense breasts raise a wom-
an’s risk of cancer sixfold, said Thea Tlsty,
Ph.D., professor of pathology at the University
of California in San Francisco.
Ten more years of research has also affected
clinical practice. Although earlier studies showed
that density was a risk factor along with age,
parity, family history, and hormone use, clinicians have begun to accept it in just the past few
years, because several seminal reports appeared
in mainstream journals, said Celine Vachon,
Ph.D., of the Mayo Clinic in Rochester, Minn.
Researchers first turned their attention to
breast density when J.N. Wolfe of Detroit
noticed an association with cancer in 1976.
Vol. 102, Issue 6 | March 17, 2010
N EWS
Breast density is a phenomenon that shows up on
mammograms because fatty tissue is relatively
translucent to x-rays, whereas epithelial and
stromal cells block x-rays and appear as white
areas. Thus “dense” breast tissue contains less fat
and more epithelial and stromal cells; it also has
more collagen and acini—small, milk-producing
elements in breast lobules. Many researchers
refer to this concept as mammographic density.
Little research occurred, however, until the
1990s. “While the field is now . . . well funded
and populated, till the mid-1990s you could fit
all of us into a phone booth,” said Norman
Boyd, M.D., who studies breast density at the
Ontario Cancer Institute in Toronto.
The Gail model, a widely used tool to assess breast cancer risk, was revised to include
density in 2006. Its creator, Mitchell Gail,
M.D., Ph.D., at the National Cancer Institute,
said that the revised model is available only for
research purposes at present, because it has
not yet been validated in independent data.
There are now other risk models in development incorporating density, some of which
are not easily used by clinicians, said Karla
Kerlikowske, M.D., professor of medicine,
epidemiology, and biostatistics at the University
of California in San Francisco. She and colleagues have developed a model that she said is
easily employed and applicable to many ethnic
groups. It was published in the Annals of
Clinical Acceptance
Internal Medicine in 2008. The ultimate goal is
In 2007 Boyd published research in the New to use risk prediction to stratify women for
England Journal of Medicine topping off three primary and secondary prevention, she said.
decades of study and marking a turning point for
Although density is now part of some risk
wider acceptance of breast density, said Gertrude models, clinicians could be doing more accordMaskarinec, M.D., Ph.D., of the University of ing to Cuzick. “Breast density is definitely
Hawaii in Honolulu. Before that, many clinicians underapplied in risk assessment by clinicians,
thought that mammographic density only masked and patients do not understand its importance
cancer. Boyd’s analysis of three nested case– either,” he said. “Breast density should be taken
control studies with more
into consideration in
than 2,000 women demdetermining how fre“While the field is
onstrated that masking
quently individuals get
couldn’t account for a
mammograms, and if
now. . .well funded and
fivefold-increased risk.
they should receive adpopulated, till the mid-1990s ditional tests such as
Depending on age,
16%–30% of breast
you could fit all of us into a ultrasound, [computed
cancers can be associtomography], or [magated with high density,
netic
resonance
phone booth.”
Boyd said. Family hisimaging].”
tory and known oncogenic genes account for a
One reason for the gap between risk
much smaller proportion of cancer.
research and clinical practice may be that no
Boyd and others have shown that density is widespread accepted “treatment” exists for
highly heritable; is related to tumor size, lymph mammographic density. Some studies show
node status, and invasiveness; and is associated that tamoxifen and possibly raloxifene reduce
with two aggressive breast cancer subtypes, lu- density, along with cancer incidence, but a
minal A and triple negative. Women with causal connection has not been shown yet.
mammographic density have a different cancer
A study led by Cuzick, called IBIS I and
profile, including larger and more interval can- published in JNCI in 2004, showed that tacers, after adjustment for age, hormone use, moxifen reduced density and risk in some
family history, and mode of detection, accord- women within 12–18 months. In an update 4
ing to a study led by Carolyn Nickson of the years later, Cuzick reported that women who
University of Melbourne in Australia, pub- had a moderately elevated risk of breast canlished last year in the Journal of Medical cer and who reduced breast density by 10%
Screening. Steven Cummings, M.D., director of were half as likely to develop cancer as those
the San Francisco Coordinating Center at the on placebo. In contrast, women who had little
California Pacific Medical Center Research or no change in density had a risk about equal
Institute reported last year that adding density to those on placebo.
to risk models improves predictive accuracy.
Other studies of this issue are under way.
(see J. Natl. Cancer Inst. 2009;101:384–98).
“More data is forthcoming that will show
jnci.oxfordjournals.org breast density to be a potential surrogate
marker of therapeutic efficacy of chemoprevention, which will also underscore the clinical
significance of breast density,” Vachon said.
Measuring Density
Perhaps the most important reason that mammographic density research has not gained
greater acceptance by clinicians is the lack of
any standardized, quantitative, and automated
method of density measurement available to
them, Gail said. Radiologists frequently use a
subjective, qualitative tool, BIRADS, which
designates density from 1 to 4, from predominantly fatty to highly dense tissue.
New quantitative methods of measurement are being developed. Many researchers
now use a semiautomated, user-assisted measurement method, Cumulus. Vachon and
collaborator John Hein, Ph.D., of the H. Lee
Moffitt Cancer Center in Tampa, Fla., are
developing a totally automated digitized
system to estimate density. Martin Yaffe,
Ph.D., senior scientist, imaging research at
the Sunnybrook Health Sciences Centre in
Toronto, and Cummings
and Kerlikowske have
developed an automated
software and hardware
system to measure density with volume. Their
system is installed onto
26 digital mammogram
machines around the
country and will be used
Norman Boyd, M.D., D.Sc.
to study 250,000 women
prospectively in a longterm density study, according to Tlsty.
Researchers also question whether it is
better to measure the percentage of dense
area or the absolute dense area. Cuzick and
Jennifer Stone, Ph.D., of the University of
Melbourne in Australia recently found that
percent dense area is associated with many
risk factors but that dense area is not, making
the latter a simpler biomarker for risk prediction modeling. Their results appeared last
year in the American Journal of Epidemiology.
Analyzing parenchymal patterns according
to texture, measuring volume using computed
tomography and tomosynthesis, and calculating collagen and tissue stiffness are other
approaches being studied.
© Oxford University Press 2010. DOI: 10.1093/jnci/djq080
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