mammograms (PDF)

Jen Brodeur, right, Tufts Medical Center mammographer prepares Yan Ling Zhong of Boston for a digital
mammogram. BIZUAYEHU TESFAYE / AP
APR. 10, 2014 AT 6:00 AM

Are Mammograms Worth It?
By Emily Oster
Filed under Women's Health

A Canadian study published in February reignited the years-long debate over breast
cancer screening methods, arguing fairly strongly against mammography, or the use of
X-rays to detect tumors. The study’s authors say mammograms have no survival benefit
relative to physical breast exams and in fact lead to significant over-diagnosis. In their
words: “The data suggest that the value of mammography screening should be
reassessed.” Predictably, not everyone agreed with them.
The debate over mammograms centers on two questions. First, how many lives are saved
by mammography? Or more specifically, how many tumors are detected early enough
with this technology but would be missed by a physical exam until it was too late?
Second, to what extent do mammograms increase over-diagnosis? Some small tumors
will never be fatal. They will grow so slowly that within a normal lifetime, they will not
cause illness. There is no reason to treat these tumors with chemotherapy or radiation
since there is no survival benefit to doing so, and such treatments are unpleasant and
carry their own risks. Mammograms increase the rate of over-diagnosis since they detect
smaller tumors. The key question is: Do the possible survival benefits outweigh this overdiagnosis risk?
Every year, about 300,000 women are diagnosed with breast cancer and 40,000 die
from it. Among the strongest predictors of survival is early detection: The smaller the
tumor is when it’s identified, the better the woman’s odds of survival. This makes breast
cancer screening — looking for tumors in women who otherwise have no symptoms — a
central component of prevention. The simplest way to screen for tumors is a physical

exam. But such an exam can only identify tumors that are large enough and close enough
to the surface to be palpable. Because of these limitations, starting in the 1960s women
and their doctors turned increasingly to mammograms, which use X-rays to find tumors
at an even earlier stage of development.
The American Cancer Society recommends that women over 40 get a mammogram every
year. Up until 2009, this was also the recommendation of the U.S. Preventive Services
Task Force, an independent panel of experts appointed by the federal Department of
Health and Human Services. But the task force changed its recommendation, saying that
women between the ages of 50 to 74 should get a mammogram every two years. These
conflicting recommendations from national organizations have muddied the waters for
women around an incredibly common procedure — 67 percent of women over 40 have
had a mammogram in the last year.
The recent study only added to this confusion. It was somewhat striking, to me at least,
that it got so much attention, since no one should have been surprised by the results. The
study was based on data from a large randomized controlled trial in Canada, which
began in the 1980s and involved about 90,000 women. Half of the women were
randomly assigned to have more or fewer mammograms.1 The other half engaged in
physical exams only; younger participants were told to conduct yearly self-exams and
older participants were given yearly physical exams by a doctor.
The mammography screening component of the study ran for five years. After that, the
two groups could engage in whatever screening they chose (mammograms, physical
exams, etc). In 1992, the first results from the study were published. After seven years,
there were no differences in breast cancer death rates between the two groups.
In 2000, now 13 years out from the start of the study, more results were published, and
again mammograms had no impact on these women’s deaths rates. It’s important to note
that in this period from 1992 to 2000 the women were not receiving differential breast
care, at least not as part of the study. The study was set up this way in order to answer
the question of whether there were longer-term impacts of short-term screening.
The most recent study extended this follow-up to 25 years and, again, found no impacts.
In my view it would have been surprising — not impossible, but surprising — to see no
impacts 13 years after the study and then suddenly find impacts 25 years later.
Putting all of these results together, things don’t look good for mammography. It would
be a shame to stop with this study, though, since it’s only one of many large randomized

controlled trials of mammography. If we want the entire picture, we need to look at all of
them together.
Most of the work is already done for us by Cochrane Reviews, which published on this
topic in 2013. The Cochrane Reviews are a series of summary documents on a whole host
of medical questions. Their goal is to aggregate information from individual randomized
controlled trials to provide evidence-based guidance on best practices.
In the case of mammograms, the review in question aggregated eight large randomized
trials encompassing more than 600,000 women. All of these trials had a similar
structure to the Canadian trial: They divided women into two groups, and one group
got mammograms with some frequency over a period of several years while the other
group got “usual care.” The researchers then compared breast cancer deaths, diagnoses
and treatments between the two groups.
One of the key advantages of these Cochrane Reviews is that they try to say something
about the quality of each study they cover. In this case, the authors argue that three of
the large trials were well-randomized and unlikely to be biased, and five were less well
randomized and more likely to be biased. What it means to be “sub-optimally
randomized” varies across trials, but to give one example: in a large trial in New York,
which started in the 1960s, more than twice as many people with a history of breast
cancer were excluded from the mammogram group than from the control group. This
suggests more women with previous breast cancer were included in the control group,
thus biasing the conclusions in favor of mammograms.
When we focus on the high-quality trials (the Canadian study is one of these), the
Cochrane Reviews’ authors found those who were screened with mammograms
were only slightly less likely to die from breast cancer in the seven or 13 years following
the trial. This effect was not statistically significant. And, perhaps more important, they
were no less likely to die overall.2
It’s not that mammograms do nothing. Women who were randomized into the
mammography group were much more likely to be diagnosed and treated for breast
cancer — this was true for all the studies. And it starkly illustrates the over-diagnosis
issue. In the control group, some small tumors were not detected or treated, but they
were detected in the mammogram group, hence the higher diagnosis rates in the latter
group. And yet women in the control group were no more likely to die of breast cancer.
This suggests those tumors that were missed were often not fatal.

Taking these results together, some doctors and policymakers have argued for a
significant decrease in the use of mammograms — the argument being that the risks of
over-diagnosis are too large.
Where you fall in this debate depends on whether you believe a mammogram really
has no effect on survival or just that any effects are small — perhaps too small for studies
like these to pick up. It also matters how you decide to trade off number of deaths versus
number of unnecessary treatments. Is it worth one additional death to avoid 10 women
being treated unnecessarily? Twenty women? Clearly, this is not something everyone will
agree on, and there’s a good argument that the choice to get a mammogram should be
left up to women themselves.
In my view, however, this debate ignores a more important question: How can we use
the good information from mammograms without experiencing the risks associated with
over-diagnosis? One of the central assumptions of economics is that more information
cannot generate worse decisions. Mammography clearly provides more information. The
problem is that contrary to our typical economic assumptions, it seems hard for doctors
and patients to ignore this information. Once a tumor is detected, we want to treat it.
It is clear that watchful waiting would sometimes be a better policy. And there’s no
practical reason we can’t have that policy; it’s a common treatment in the case of prostate
cancer. In an ideal world, we could use better data to guide such a policy. What features
of a tumor predict slow growth? Is there a threshold size and location of a tumor that
should dictate treatment? Could more frequent mammography after a tumor is detected
be useful? Rather than throwing away the technology, let’s see if we can better use it.

Footnotes
1. To learn about a mammogram’s impact, this randomization is important since just comparing
women who undergo mammography to those who do not runs into the problem that the kind
of women who choose to have mammograms are different in other ways from those who do
not.
2. In the lower-quality trials, there was a large and significant effect on deaths from breast cancer
but, again, this may have been because of the poor randomization.