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Lessons from the Mammography Wars REPLY

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Abstract

In this article, the authors argue that any intervention produces a continuous gradient of benefit versus harm. Subjective thresholds can vary, even if the data are agreed upon. Should we rely solely on expert panels to make arbitrary judgments, especially in the gray areas?
sounding b oa r d
The new england journal of medicine
n engl j med 363;11 nejm.org september 9, 2010
1076
Lessons from the Mammography Wars
Kerianne H. Quanstrum, M.D., and Rodney A. Hayward, M.D.
People of the same trade seldom meet to-
gether . . . [without] the conversation end-
[ing] in a conspiracy against the public.
— Adam Smith, The Wealth of Nations, 1776
1
The controversy was predictable.
Since 2002, annual mammograms had been
recommended for women 40 years of age or old-
er.
2
Suddenly, an independent, government-fund-
ed panel was suggesting that this schedule might
be too much — that less, in fact, might be better.
Advocates of breast-cancer screening, particu-
larly breast radiologists, immediately took action,
denounci ng the panel’s statement s as government
rationing, suggesting that the panel members had
ignored the medical evidence, and even implying
that the panel members were guilty of a callous
disregard for the life and well-being of women.
As one prominent breast radiologist put it, “Ba-
sically, [the panel] said nothing is good. Just wait
until it breaks through your skin. . . .
3
Speci alt y
societies quickly issued countermanding guide-
lines.
4
In reality, this independent panel, the Preven-
tive Services Task Force, simply recommended t hat
routine screening mammography begin at the age
of 50 years, whereas women bet ween the ages of
40 and 49 years should make individual decisions
with their doctors as to whether their preferences
and risk factors indicate screening at an earlier
age. The panel also recommended that screening
mammograms be performed every other year,
which they suggested would reduce the harms of
mammography by nearly half while maintaining
most of the benef its provided by annual imag-
ing.
5
In short, the panel concluded that we had
previously overestimated the value of mammog-
raphy: that mammography is good, but not that
good; that it is necessary for many women, but
not all; and that it should be performed at some
frequency, but perhaps not every year, for every
woman.
Behind the panel’s conclusions regarding mam-
mography lurks an unwelcome reality that our
profession has often failed to acknowledge. Every
medical intervention no matter how benefi-
cial for some patients will provide continu-
ously diminishing returns as the threshold for in-
tervention is lowered. Mammography is just one
case in point. For women bet ween the ages of 40
and 49 years, the false positive rate is quite high,
and the expected benefits are quite low: more
than 1900 women would need to be invited for
screening mammography in order to prevent just
one death from breast cancer during 11 years of
follow-up, at the direct cost of more than 20,000
visits for breast imaging and approximately 2000
false positive mammograms. Conversely, for
women between the ages of 60 and 69 years, fewer
than 400 women would need to be invited for
screening in order to prevent one breast-cancer
death during 13 years of follow-up, while accruing
approximately 5000 visits and 400 false positive
mammograms.
6
In short, as the risk of breast
cancer increases, the benef its of mammography
increase, whereas the relative harms become pro-
gressively less signif icant.
More generally, the net benefit of all medical
treatments is a continuous function of three fac-
tors: the risk of morbidity or mortalit y if untreat-
ed (Risk
NoRx
), the treatment’s relative risk reduc-
tion (RRR
Rx
), and the treatment’s risk of harm
(Harms
Rx
):
Net Benefit = (RiskNoRx × RRRRx) – (HarmsRx).
As the risk of no treatment (Risk
NoRx
) decreas-
es, the net benefit of treatment will decrease, even
if the treatment’s relative benef it (RRR
Rx
) remains
constant. Indeed, for many interventions, if the
risk of no treatment is low enough (e.g., if we low-
er the threshold for treatment too far or if a pa-
tient’s life expectancy is relatively limited for other
reasons), then the side effects and risks of treat-
ment will dominate, and the treatment will result
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n engl j med 363;11 nejm.org september 9, 2010
1077
sounding board
in net harm.
7-9
Since the risk of no treatment var-
ies dramatically among patients for almost every
disease or condition, even a highly effective inter-
vention will show a gradient of net benefit in a
given population.
Despite this continuous gradient of treatment
benef it versus harm, medical decision making is
necessarily discrete. In the case of any given pa-
tient, we must choose to treat or not treat, to
screen or not screen. In an effort to help us make
these choices, our profession is constantly trying
to elucidate clear thresholds for intervention, such
as the level of glycated hemoglobin or low-densi-
ty lipoprotein cholesterol, age, or standard time
intervals. What we often do not remember is that
these thresholds — for example, an age of 40 ver-
sus 50 years or annual versus biennial routine
mammography — are to some degree subjective
and arbitrar y. After all, scientif ic evidence can only
help us describe the continuum of benefit versus
harm. The assessment of whether the benefit is
great enough to warrant the risk of harm — i.e.,
the decision of where the threshold for interven-
tion should lie — is necessarily a value judgment.
When either side in the mammography wars
claims that the evidence suggests that women
should or should not undergo routine mammog-
raphy starting at the age of 40 years, they are de-
ceiving themselves and the public about what the
evidence can tell us. They are really just making
different value judgments about where to set the
threshold.
Who is right? Who should be making these
judgments?
The obvious answer might seem to be “the in-
dividual patient and her doctor.” But it would be
folly to suggest that every medical decision ought
to be made anew for each patient, with no stan-
dard of care in any case, no guidelines, and no
professional norms. Instead, our profession needs
to start distinguishing between choices that are
clear-cut and those that require individualized
decision making. To this end, for most interven-
tions, rather than seeking a single, universal
threshold for intervention (
Fig. 1A
), we should be
arguing over a minimum of two distinct thresh-
olds: one above which benefit clearly outweighs
the risk of harm, in which c ase clinicians should
recommend a treatment; and one below which
concern about harm clearly dominates, in which
case clinicians should recommend against that
treatment. Between these two thresholds lies a
gray area of indeterminate net benefit, in which
clinicians should defer to an individual patient’s
preferences — including, for example, a woman’s
emotional response to her risk of breast cancer
— in choosing whether to intervene (
Fig. 1B
).
It is just such a gray area into which women
in their 40s are assigned by the new mammog-
raphy guidelines. Of note, there are quantitative
methods available that can assist clinicians in
guiding individual decision making even in these
gray areas.
6-10
In our profession’s apt pursuit of
more systematized care, however, we have gen-
erally preferred to ignore these gray areas alto-
gether. It is easier, after all, to simply lower the
threshold for inter vent ion — to recommend mam-
mography for all women 40 years of age or older
than to rely on individual judgments about
which of these women actually warrant screening.
However, our current approach is more than
just a quest for uniformit y. When a given service
is successfully extended to more people with more
intensity, the profession providing that service
tends to grow in importance and profitability. In
the United States, where medical specialists often
enjoy an exalted status in the minds of the pub-
lic, if experts shout loudly that every woman 40
years of age or older must be screened annually
for breast cancer, then breast cancer must be im-
portant, screening must be a basic human right,
and doctors who provide this service must have
great value and authority.
But what if those experts are basing their rec-
ommendations on more than the interest of pa-
tients alone? In any other industry, we accept the
idea as natural that those providing a service or
BNew Model
ACurrent Model
Net benefitNet harm
Care
discouraged
Care recommended
Substantial
net benefitSmall or uncertain net benefit
Net harm
Care
discouraged
Care
recommended
Discretionary care
Figure 1. Creating a New Risk–Benefit Model that Allows for Individualized
Decision Making.
For most interventions, the current practice of seeking a single, universal
threshold for intervention (Panel A) might be replaced by a model that allows
for individualized decisions about whether to inter vene on the basis of per-
sonal risk factors and preferences (Panel B).
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The
new england journal
of
me dicine
n engl j med 363;11 nejm.org september 9, 2010
1078
product hold their own and their shareholders’
interests as a primary objective. Why have we
failed to acknowledge that the same phenome-
non occurs in health care? Although it is true that
individual medical providers care deeply about
their patients, the guild of health care profession-
als including their specialty societies has
a primary responsibility to promote its members’
interests. Now, self-interest is not in itself a bad
thing; indeed, it is a force for productivity and
eff iciency in a well-functioning market. But it is
a fool’s dream to expect the guild of any service
industry to harness its self-interest and to act ac-
cording to beneficence alone — to compete on
true value when the opportunit y to inf late per-
ceived value is readily available.
It is for this reason that some degree of mar-
ket regulation is necessary, such as truth-in-adver-
tising and antitrust laws. It is only in health care
that we have failed to recognize the need for anal-
ogous protections. It is only in health care, after
all, that the same group that provides a service
also tells us how valuable that service is and how
much of it we need, as when the Society of Breast
Imaging sets the recommendations for mammog-
ra phy.
4
If there is overutilization in health care,
we can be sure that it will continue unabated as
long as those with a vested interest are allowed to
win the public-relations wars by shouting about
“rationing” or “death panels” whenever anyone
suggests that more health care, in fact, may not be
bet ter.
It is time for a change. We must acknowledge
that just as in any other profession or industry,
self-interest is unavoidably at work in health care.
Rather than even acknowledging practice guide-
lines offered by vested experts, we ought to bor-
row from the wisdom of sound governance and
implement a system of checks and balances when
it comes to the interpretation and application of
medical evidence. At the same time, we need to
recognize that these two tasks are distinct. Al-
though the interpretation of medical evidence is
(or ought to be) a scientif ic exercise, the applica-
tion of that evidence, as in guideline formation,
is ultimately a social exercise.
Decisions regarding practice guidelines can,
and certainly should, be informed by evidence. But
they will always require value judgments regard-
ing how much evidence is suff icient to dictate
care, for example, or whether and to what degree
costs should be considered. By separating the pro-
cesses of evidence review and guideline format ion,
fair disagreements about the quality or substance
of the evidence can occur separately from, and be-
fore, disagreements about the implications for
clinical care.
Ideally, we ought to have a system in which
independent panels of generalists, with expertise
in the methods of evidence review and synthesis,
are responsible for objectively synthesizing the
medical evidence around a given question or pro-
cess of care. These independent panels could then
seek input from the relevant clinician groups re-
garding their views concerning the evidence and
where they feel the thresholds for recommended
care versus individualized decision making should
reside. To facilitate impartiality and political vi-
ability, a public–private alliance might be best,
with funding and representation for the indepen-
dent panels coming from government, private
foundations, and provider and payer groups.
Furthermore, unlike one-time or occasional
panels, t h is process of evidence review a nd guid e-
line formation ought to be adequately funded to
allow for regular updates as new evidence be-
comes available. Recent proposals to increase
spending on comparative-effectiveness research
are certainly laudable, but it is unrealistic to think
that an investment in research alone will have a
sizable effect on the practice of medicine without
a concomitant investment in a credible process
for vetting medical evidence and clinical care
guidelines.
The Preventive Services Task Force approaches
the format that we propose here, since the panel
is composed of expert generalists. This panel,
however, tends to interpret t he evidence and write
the recommendations as a single process, creating
the appearance, and perhaps the realit y, of al-
lowing too little input from vested interests and
often conf lating disagreements about the evidence
with disagreements about the recommendations.
Furthermore, as seen in the mammography wars,
the panel’s perceived failure to seek sufficient in-
put from specialty groups was a prominent, and
seemingly effective, argument against the guide-
lines.
11
Even the perception that the process of
guideline formation is closed or does not consid-
er specialists’ opinions can make it easy for those
arguing that more care is better to prey on the
public’s legitimate concern that government and
insurers are out to deny them lifesaving care.
As a profession, we have the potential to play
The New England Journal of Medicine
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Copyright © 2010 Massachusetts Medical Society. All rights reserved.
n engl j med 363;11 nejm.org september 9, 2010
1079
sounding board
a very real role in improving our health care sys-
tem. We can choose t o acknowledge the gray a reas
of medicine and insist that they be ref lected in
clinical-practice guidelines and in performance
measures. And we can work to prevent vested in-
terests from being granted the loudest voices in
hea lt h care — even when those voices bla zon f rom
our own specialty by granting credence to
groups such as the Preventive Services Task Force
that seek to formulate evidence-based guidelines
in an objective way.
Or we can, instead, conduct our own version
of the mammography wars when a prudent ap-
plication of the evidence threatens the profit-
ability and stature of our own specialty.
The opinions expressed in this article are those of the authors
and do not necessarily represent those of the Robert Wood
Johnson Foundation or the University of Michigan.
Disclosure forms provided by the authors are available with
the full text of this article at NEJM.org.
From the Robert Wood Johnson Foundation Clinical Scholars
Program (K.H.Q., R.A.H.); the Departments of Surgery (K.H.Q.)
and Internal Medicine (R.A.H.), University of Michigan; and the
Department of Veterans Affairs (VA), VA Health Services Re-
search and Development Center of Excellence, VA Ann Arbor
Healthcare System (R. A.H.) — all in Ann Arbor, MI.
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Importance In 2023, the American Heart Association (AHA) developed the Predicting Risk of Cardiovascular Disease Events (PREVENT) equations to estimate 10-year risk of atherosclerotic cardiovascular disease (ASCVD), as an update to the 2013 pooled cohort equations (PCEs). The PREVENT equations were derived from contemporary cohorts and removed race and added variables for kidney function and statin use. Objective To compare national estimates of 10-year ASCVD risk using the PCEs and PREVENT equations and how these equations affect recommendations for primary prevention statin therapy. Design, Setting, and Participants This cross-sectional study included adults aged 40 to 75 years who participated in the National Health and Nutrition Examination Survey from 2017 to March 2020. Adults were defined as eligible for primary prevention statin use based on the 2019 AHA/American College of Cardiology guideline on the primary prevention of cardiovascular disease. Data were weighted to be nationally representative and were analyzed from December 27, 2023, to January 31, 2024. Main Outcomes and Measures The 10-year ASCVD risk and eligibility for primary prevention statin therapy based on PREVENT and PCE calculations. Results In the weighted sample of 3785 US adults (mean [SD] age, 55.7 [9.7] years; 52.5% women) without known ASCVD, 20.7% reported current statin use. The mean estimated 10-year ASCVD risk was 8.0% (95% CI, 7.6%-8.4%) using the PCEs and 4.3% (95% CI, 4.1%-4.5%) using the PREVENT equations. Across all age, sex, and racial subgroups, compared with the PCEs, the mean estimated 10-year ASCVD risk was lower using the PREVENT equations, with the largest difference for Black adults (10.9% [95% CI, 10.1%-11.7%] vs 5.1% [95% CI 4.7%-5.4%]) and individuals aged 70 to 75 years (22.8% [95% CI, 21.6%-24.1%] vs 10.2% [95% CI, 9.6%-10.8%]). The use of the PREVENT equations instead of the PCEs could reduce the number of adults meeting criteria for primary prevention statin therapy from 45.4 million (95% CI, 40.3 million-50.4 million) to 28.3 million (95% CI, 25.2 million-31.4 million). In other words, 17.3 million (95% CI, 14.8 million-19.7 million) adults recommended statins based on the PCEs would no longer be recommended statins based on PREVENT equations, including 4.1 million (95% CI, 2.8 million-5.5 million) adults currently taking statins. Based on the PREVENT equations, 44.1% (95% CI, 38.6%-49.5%) of adults eligible for primary prevention statin therapy reported currently taking statins, equating to 15.8 million (95% CI, 13.4 million-18.2 million) individuals eligible for primary prevention statins who reported not taking statins. Conclusions and Relevance This cross-sectional study found that use of the PREVENT equations was associated with fewer US adults being eligible for primary prevention statin therapy; however, the majority of adults eligible for receiving such therapy based on PREVENT equations did not report statin use.
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Population screening for early-stage cancer or cancer precursors began in the mid-twentieth century, with the goal of reducing suffering from cancer illness and lengthening average life by preventing cancer deaths. Since the establishment of cancer screening, concerns have emerged that it may be doing considerable harm; despite this, screening practices have remained relatively intractable. This intractability in the face of harm is the central problematic of my analysis. I reinterpret a large study of breast, cervical and prostate cancer screening completed recently by our Australian research group, working across empirical bioethics, public health and social science. I suggest three reasons why cancer screening might persist as it does, and thus reach conclusions about what might be required to make cancer screening systems more responsive to the potential for harm.
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Although treating to lipid targets ("treat to target") is widely recommended for coronary artery disease (CAD) prevention, some have advocated administering fixed doses of statins based on a person's estimated net benefit ("tailored treatment"). To examine how a tailored treatment approach to statin therapy compares with a treat-to-target approach. Simulated model of population-level effects of treat-to-target and tailored treatment approaches to statin therapy. Statin trials from 1994 to 2009 and nationally representative CAD risk factor data. U.S. persons aged 30 to 75 years with no history of myocardial infarction. Lifetime effects of 5 years of treatment. Societal and patient. Tailored treatment based on a person's 5-year CAD risk (simvastatin, 40 mg, for 5% to 15% CAD risk and atorvastatin, 40 mg, for CAD risk >15%) versus treat-to-target approaches that escalate statin dose per National Cholesterol Education Program [NCEP] III guidelines (including an intensive approach that advances treatment whenever intensification is optional by NCEP III criteria). Quality-adjusted life-years (QALYs). Compared with the standard NCEP III approach, the intensive NCEP III approach treated 15 million more persons and saved 570,000 more QALYs over 5 years. The tailored strategy treated a similar number of persons, as did the intensive NCEP III approach, but saved 500,000 more QALYs and treated fewer persons with high-dose statins. No circumstances were found in which a treat-to-target approach was preferable to tailored treatment. Model assumptions were based on available clinical data, which included few persons 75 years or older. A tailored treatment strategy prevents more CAD events while treating fewer persons with high-dose statins than low-density lipoprotein cholesterol-based target approaches. Results were robust, even with assumptions favoring a treat-to-target approach. Department of Veteran Affairs Health Services Research & Development Service's Quality Enhancement Research Initiative.
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This systematic review is an update of evidence since the 2002 U.S. Preventive Services Task Force recommendation on breast cancer screening. To determine the effectiveness of mammography screening in decreasing breast cancer mortality among average-risk women aged 40 to 49 years and 70 years or older, the effectiveness of clinical breast examination and breast self-examination, and the harms of screening. Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews (through the fourth quarter of 2008), MEDLINE (January 2001 to December 2008), reference lists, and Web of Science searches for published studies and Breast Cancer Surveillance Consortium for screening mammography data. Randomized, controlled trials with breast cancer mortality outcomes for screening effectiveness, and studies of various designs and multiple data sources for harms. Relevant data were abstracted, and study quality was rated by using established criteria. Mammography screening reduces breast cancer mortality by 15% for women aged 39 to 49 years (relative risk, 0.85 [95% credible interval, 0.75 to 0.96]; 8 trials). Data are lacking for women aged 70 years or older. Radiation exposure from mammography is low. Patient adverse experiences are common and transient and do not affect screening practices. Estimates of overdiagnosis vary from 1% to 10%. Younger women have more false-positive mammography results and additional imaging but fewer biopsies than older women. Trials of clinical breast examination are ongoing; trials for breast self-examination showed no reductions in mortality but increases in benign biopsy results. Limitation: Studies of older women, digital mammography, and magnetic resonance imaging are lacking. Mammography screening reduces breast cancer mortality for women aged 39 to 69 years; data are insufficient for older women. False-positive mammography results and additional imaging are common. No benefit has been shown for clinical breast examination or breast self-examination.
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This statement summarizes the current U.S. Preventive Services Task Force (USPSTF) recommendations on screening for breast cancer and the supporting scientific evidence and updates the 1996 USPSTF recommendations on this topic. The complete USPSTF recommendation and rationale statement on this topic, which includes a brief review of the supporting evidence, is available through the USPSTF Web site (www.preventiveservices.ahrq.gov), the National Guideline Clearinghouse (www.guideline.gov), and in print through the Agency for Healthcare Research and Quality Publications Clearinghouse (telephone, 800-358-9295; e-mail, ahrqpubs@ahrq.gov). The complete information on which this statement is based, including evidence tables and references, is available in the accompanying article in this issue and in the summary of the evidence and systematic evidence review on the Web sites already mentioned. To update its recommendations on screening for breast cancer, the USPSTF reviewed the evidence regarding the effectiveness of mammography, clinical breast examination, and breast self-examination in reducing breast cancer mortality. The USPSTF did not review the evidence regarding genetic screening, surveillance of women with prior breast cancer, or formal evaluation of new screening modalities that have not been studied in the general population. A meta-analysis using a Bayesian random-effects model was conducted for the USPSTF to obtain a summary of relative risk estimates of the effectiveness of screening with mammography, either alone or in combination with clinical breast examination, in reducing breast cancer mortality. Clinical studies that evaluated breast self-examination were included in the review. Sources for estimates cited in this Recommendation and Rationale statement are described in the systematic evidence review on this topic, which is available on the USPSTF Web site (www.preventiveservices.ahrq.gov).
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Description: Update of the 2002 U.S. Preventive Services Task Force (USPSTF) recommendation statement on screening for breast cancer in the general population. Methods: The USPSTF examined the evidence on the efficacy of 5 screening modalities in reducing mortality from breast cancer: film mammography, clinical breast examination, breast self-examination, digital mammography, and magnetic resonance imaging in order to update the 2002 recommendation. To accomplish this update, the USPSTF commissioned 2 studies: 1) a targeted systematic evidence review of 6 selected questions relating to benefits and harms of screening, and 2) a decision analysis that used population modeling techniques to compare the expected health outcomes and resource requirements of starting and ending mammography screening at different ages and using annual versus biennial screening intervals. Recommendations: The USPSTF recommends against routine screening mammography in women aged 40 to 49 years. The decision to start regular, biennial screening mammography before the age of 50 years should be an individual one and take into account patient context, including the patient's values regarding specific benefits and harms. (Grade C recommendation) The USPSTF recommends biennial screening mammography for women between the ages of 50 and 74 years. (Grade B recommendation) The USPSTF concludes that the current evidence is insufficient to assess the additional benefits and harms of screening mammography in women 75 years or older. (I statement) The USPSTF concludes that the current evidence is insufficient to assess the additional benefits and harms of clinical breast examination beyond screening mammography in women 40 years or older. (I statement) The USPSTF recommends against clinicians teaching women how to perform breast self-examination. (Grade D recommendation) The USPSTF concludes that the current evidence is insufficient to assess additional benefits and harms of either digital mammography or magnetic resonance imaging instead of film mammography as screening modalities for breast cancer. (I statement).
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Background: This systematic review is an update of evidence since the 2002 U.S. Preventive Services Task Force recommendation on breast cancer screening. Purpose: To determine the effectiveness of mammography screening in decreasing breast cancer mortality among average-risk women aged 40 to 49 years and 70 years or older, the effectiveness of clinical breast examination and breast self-examination, and the harms of screening. Data sources: Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews (through the fourth quarter of 2008), MEDLINE (January 2001 to December 2008), reference lists, and Web of Science searches for published studies and Breast Cancer Surveillance Consortium for screening mammography data. Study selection: Randomized, controlled trials with breast cancer mortality outcomes for screening effectiveness, and studies of various designs and multiple data sources for harms. Data extraction: Relevant data were abstracted, and study quality was rated by using established criteria. Data synthesis: Mammography screening reduces breast cancer mortality by 15% for women aged 39 to 49 years (relative risk, 0.85 [95% credible interval, 0.75 to 0.96]; 8 trials). Data are lacking for women aged 70 years or older. Radiation exposure from mammography is low. Patient adverse experiences are common and transient and do not affect screening practices. Estimates of overdiagnosis vary from 1% to 10%. Younger women have more false-positive mammography results and additional imaging but fewer biopsies than older women. Trials of clinical breast examination are ongoing; trials for breast self-examination showed no reductions in mortality but increases in benign biopsy results. Limitation: Studies of older women, digital mammography, and magnetic resonance imaging are lacking. Conclusion: Mammography screening reduces breast cancer mortality for women aged 39 to 69 years; data are insufficient for older women. False-positive mammography results and additional imaging are common. No benefit has been shown for clinical breast examination or breast self-examination.
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Background: Although treating to lipid targets ("treat to target") is widely recommended for coronary artery disease (CAD) prevention, some have advocated administering fixed doses of statins based on a person's estimated net benefit ("tailored treatment"). Objective: To examine how a tailored treatment approach to statin therapy compares with a treat-to-target approach. Design: Simulated model of population-level effects of treat-to-target and tailored treatment approaches to statin therapy. Data Sources: Statin trials from 1994 to 2009 and nationally representative CAD risk factor data. Target Population: U.S. persons aged 30 to 75 years with no history of myocardial infarction. Time Horizon: Lifetime effects of 5 years of treatment. Perspective: Societal and patient. Intervention: Tailored treatment based on a person's 5-year CAD risk (simvastatin, 40 mg, for 5% to 15% CAD risk and atorvastatin, 40 mg, for CAD risk >15%) versus treat-to-target approaches that escalate statin dose per National Cholesterol Education Program [NCEP] III guidelines (including an intensive approach that advances treatment whenever intensification is optional by NCEP III criteria). Outcome Measures: Quality-adjusted life-years (QALYs). Results of Base-Case Analysis: Compared with the standard NCEP III approach, the intensive NCEP III approach treated 15 million more persons and saved 570 000 more QALYs over 5 years. The tailored strategy treated a similar number of persons, as did the intensive NCEP III approach, but saved 500 000 more QALYs and treated fewer persons with high-dose statins. Results of Sensitivity Analysis: No circumstances were found in which a treat-to-target approach was preferable to tailored treatment. Limitation: Model assumptions were based on available clinical data, which included few persons 75 years or older. Conclusion: A tailored treatment strategy prevents more CAD events while treating fewer persons with high-dose statins than low-density lipoprotein cholesterol-based target approaches. Results were robust, even with assumptions favoring a treat-to-target approach. Primary Funding Source: Department of Veteran Affairs Health Services Research & Development Service's Quality Enhancement Research Initiative.
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Cancer prediction models are becoming ubiquitous, yet we generally have no idea whether they do more good than harm. This is because current statistical methods for evaluating prediction models are uninformative as to their clinical value. Prediction models are typically evaluated in terms of discrimination or calibration. However, it is generally unclear how high discrimination needs to be before it is considered "high enough"; similarly, there are no rational guidelines as to the degree of miscalibration that would discount clinical use of a model. Classification tables do present the results of models in more clinically relevant terms, but it is not always clear which of two models is preferable on the basis of a particular classification table, or even whether either model should be used at all. Recent years have seen the development of straightforward decision analytic techniques that evaluate prediction models in terms of their consequences. This depends on the simple approach of weighting true and false positives differently, to reflect that, for example, delaying the diagnosis of a cancer is more harmful than an unnecessary biopsy. Such decision analytic techniques hold the promise of determining whether clinical implementation of prediction models would do more good than harm.
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Screening for breast cancer with mammography has been shown to decrease mortality from breast cancer, and mammography is the mainstay of screening for clinically occult disease. Mammography, however, has well-recognized limitations, and recently, other imaging including ultrasound and magnetic resonance imaging have been used as adjunctive screening tools, mainly for women who may be at increased risk for the development of breast cancer. The Society of Breast Imaging and the Breast Imaging Commission of the ACR are issuing these recommendations to provide guidance to patients and clinicians on the use of imaging to screen for breast cancer. Wherever possible, the recommendations are based on available evidence. Where evidence is lacking, the recommendations are based on consensus opinions of the fellows and executive committee of the Society of Breast Imaging and the members of the Breast Imaging Commission of the ACR.
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Preventive medicine has historically favored reducing a risk factor by a small amount in the entire population rather than by a large amount in high-risk individuals. The use of multivariable risk prediction tools, however, may affect the relative merits of this strategy. This study uses risk factor data from the National Health and Nutrition Examination Survey III to simulate a population of more than 100 million Americans aged thirty or older with no history of CV disease. Three strategies that could affect CV events, CV mortality, and quality-adjusted life years were examined: (1) a population-based strategy that treats all individuals with a low- or moderate-intensity intervention (in which the low-intensity intervention represents a public health campaign with no demonstrable adverse effects), (2) a targeted strategy that treats individuals in the top 25 percent based on a single risk factor (LDL), and (3) a risk-targeted strategy that treats individuals in the top 25 percent based on overall CV risk (as predicted by a multivariable prediction tool). The efficiency of each strategy was compared while varying the intervention's intensity and associated adverse effects, and the accuracy of the risk prediction tool. The LDL-targeted strategy and the low-intensity population-based strategy were comparable for CV events prevented over five years (0.79 million and 0.75 million, respectively), as were the risk-targeted strategy and moderate-intensity population-based strategy (1.56 million and 1.87 million, respectively). The risk-targeted strategy, however, was more efficient than the moderate-intensity population-based strategy (number needed to treat [NNT] 19 vs. 62). Incorporating a small degree of treatment-related adverse effects greatly magnified the relative advantages of the risk-targeted approach over other strategies. Reducing the accuracy of the prediction tool only modestly decreased this greater efficiency. A population-based prevention strategy can be an excellent option if an intervention has almost no adverse effects. But if the intervention has even a small degree of disutility, a targeted approach using multivariable risk prediction can prevent more morbidity and mortality while treating many fewer people.