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Journal of Medicine and Philosophy, 0: 1–14, 2012
doi:10.1093/jmp/jhs017
© The Author 2012. Published by Oxford University Press, on behalf of the Journal of Medicine and Philosophy Inc.
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Ethical Issues in Cancer Screening and
Prevention
ANYA PLUTYNSKI*
The University of Utah, Salt Lake City, Utah, USA
*Address correspondence to: Anya Plutynski, PhD, The University of Utah, Salt Lake City,
UT, USA. E-mail: anya.plutynski@philosophy.utah.edu
November 2009’s announcement of the USPSTF’s recommendations
for screening for breast cancer raised a firestorm of objections.
Chief among them were that the panel had insufficiently valued
patients’ lives or allowed cost considerations to influence recommen-
dations. The publicity about the recommendations, however, often
either simplified the actual content of the recommendations or
bypassed significant methodological issues, which a philosophical
examination of both the science behind screening recommendations
and their import reveals. In this article, I discuss two of the leading
ethical considerations at issue in screening recommendations:
respect for patient autonomy and beneficence and then turn to the
most significant methodological issues raised by cancer screening:
the potential biases that may infect a trial of screening effective-
ness, the problem of base rates in communicating risk, and the
trade-offs involved in a judgment of screening effectiveness. These
issues reach more broadly, into the use of “evidence-based” medicine
generally, and have important implications for informed consent.
Keywords: base rate fallacy, cancer screening, risk communication,
trade-off neglect, USPSTF
I. INTRODUCTION
Cancer is the second leading cause of death in the United States. Under-
standably, with so many peoples’ lives affected by this devastating disease,
early detection has become the mantra of many cancer activists. Screening
for disease in asymptomatic individuals has an intuitive appeal. If all cancers
have a linear progression toward morbidity and mortality, then halting the
progress of the disease early seems the best strategy. Many are hopeful that
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more and better screening modalities will be provided to a wider public. If not
all cancers have linear progression (as seems clear, cf. Croswell, Ransohoff,
and Kramer, 2010), more, however, may not always be better. The recent
upset over the USPSTF’s recommendations for screening for breast cancer
brought the intuitive thinking behind early detection into question and raised
a host of ethical issues, besides. The object of this essay will be to examine
the intuitive thinking behind support for frequent screening, consider the
nature of the evidence for the USPSTF’s recommendations, and whether the
recommendations can be made consistently with respect for autonomy and
beneficence. I will argue that the recommendations can and should be
followed consistently with respect for autonomy and beneficence but argue
that safeguards need to be put in place to ensure this.
The USPSTF recommended that women under 50 consult with their clinicians
about whether to have annual screening (US Preventive Services Task Force,
2009). A meta-analysis of multiple clinical trials appeared to show that the
benefit for most women under 50 may be relatively small, and the cost—in
terms of false positives, unnecessary biopsies, and overdiagnosis (unnecessarily
treating cancers that never would have caused illness during that person’s life-
time), is relatively high. For women over 50, they found that biannual screening
may be as effective as annual screening for reducing age-adjusted mortality
(Mandelblatt et al., 2009; Nelson et al., 2009). As might have been predicted by
more savvy publicists, the response was not positive. Many breast cancer activ-
ists, and the American Radiological Association, as well as the American Cancer
Association dismissed the findings. Some argued that the USPSTF was condemn-
ing women to early death. Moving past the outrage, we need to look closely at
both the salient scientific and ethical issues at stake in this heated exchange.
The USPSTF recommended individual women in their forties decide whether
to screen in consultation with clinicians. Why does this create such outrage?
Perhaps some worry that insurance companies will not cover screening
if screening is not standard care for some age group, or that even those
patients at elevated risk (perhaps due to family history) will not seek screening
based on recommendations for the population at large. However legitimate
these concerns, the matter of whether or not most women under 50 should get
screened should depend upon whether the risk to those screened is out-
weighed by the benefit. What is the evidence for the benefits for women in this
age group? We should not simply assume that more screening is better, and that
all screening modalities for all cancers are risk free for all patients. As the
authors of a recent article put it, we should be sure to “protect ourselves from
our intuitions” (Croswell, Ransohoff, and Kramer, 2010). Not all cancers prog-
ress linearly, and some may never cause clinical symptoms—in other words,
preventative screening methods may not always be for the benefit of patients,
for some cancers and in some populations. Although many of us assume that
in the era of modern medicine, no one prescribes either tests or treatments that
do more harm than good, we should make sure to check the evidence.
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Ethical Issues in Cancer Screening and Prevention 3
Although it is surely correct that clinicians and patients (and insurance
companies) find it easier to follow general recommendations, when screen-
ing will only benefit a minority at greater risk, it seems that individual-based
decision making, rather than universal screening, is a better option. Indeed,
the USPSTF was clear that women should consult individually with physicians;
their recommendations were not “broadly utilitarian,” in the sense of simply
considering costs for insurance companies, but instead, emphasized individual
assessment and weighing of risks, with clinicians. However, individual-based
decision raises another suite of issues about risk communication and deci-
sion making under uncertainty. Some have argued that patients are simply
bad at making choices based on, for example, misunderstanding of the dif-
ferences between absolute versus relative risk (Schwartz and Meslin, 2008).
As Schwartz and Meslin explain, pamphlets encouraging mammography
tend to cite relative over absolute risk as the apparent “risk reduction” will
always look higher described as relative risk. Moreover, they support this
strategy. They explain:
Absolute risk reduction (ARR) is calculated by subtracting the mortality rate in the
screened group from that of the unscreened group. Thus, according to one study,
the ARR of performing mammography regularly for 20 years is 4.9 per 1,000
(or 0.49%), i.e., 14 per 1,000 (1.4%) minus 9.1 per 1,000 (0.91%) (Barrat et al., 2005).
In contrast, Relative Risk Reduction (RRR) is calculated by dividing the decrease in
morbidity or mortality by the baseline rate. Using the same model as above, mam-
mograms performed over 20 years would provide a RRR of 36%, i.e., 4.9 per 1,000
decrease in death from breast cancer divided by the baseline rate (in the unscreened
group) of 14 per 1,000. In this case as in others, the RRR (36%) is a much larger
number than the ARR (0.5%), and so it is not surprising that brochures that aim to
encourage patients to get regular mammograms generally present RRR if numbers
are given at all. (Schwartz and Meslin, 2008, 868)
As mentioned above, the difference apparent reduction of risk for relative
versus absolute risk reduction may be quite stark, particularly when screen-
ing for disease that is not very prevalent. Schwartz and Meslin endorse the
practice of describing relative risk reduction, as opposed to absolute risk
reduction, to patients, to encourage mammography. However, we should
be careful to not slip into paternalism, particularly in “gray areas” where
the risk reduction is small, and the costs of screening may be relatively high
(Quanstrum, 2009). Although a narrow utilitarian or expected utility perspective
might simply attach values to lives saved, and so use any strategy (including
representing risk deceptively, or discounting or hiding cost to patients due
to unnecessary biopsies or overdiagnosis), there are broader issues at stake.
Questions of risk and benefit need to be supplemented by some discussion
of the reasonable variability in values patients attach to different risks, the
norms of clinician-patient relationships, and what respect for autonomy and
informed consent requires. Questions about risk and benefit can be better
answered once we know how sensitive or specific are our screening tools,
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how prevalent the disease, and thus what the risks are of false positives.
However, we also need to assess the values behind general versus individu-
ally tailored recommendations, and arguments for and against individual
consultation with clinicians, versus general recommendations that may benefit
some, but not most patients.
Even the best clinical trials often leave some gray areas where it is not
clear that benefit outweighs cost (Quanstrum and Hayward, 2009). Evidence-
based medicine is surely important, but it cannot always draw a bright clear
line between when universal screening is advisable and when it is not. In
this paper, I will argue, along with Malm (1999), that public health recom-
mendations should be such that the benefit on balance for the patient who
receives a recommendation is greater than the harm.1 By this, I mean that
that benefit for any particular patient is higher than risks of harm, taking into
account the probability that this harm will occur. However, of course, how
risks or benefits are assessed is not merely a matter for science to decide.
Although EBM may give us information that we can use to make judgments
about policy, in some cases, the evidence underdetermines the recommenda-
tions. In just such cases, to make public policy recommendations, absent con-
sideration of the patient’s (a) particular risk, and (b) weighting of preferences,
is unsound.
Further, we need to also consider the role and limitations of risk commu-
nication. When communicating with a patient about their preferences, we
should make clear when the recommendations are not ‘black and white’;
some women need to receive false positive tests, have unnecessary biopsies,
or be unnecessarily treated on balance to save lives. How often will women
be willing to take the risk of being in the first category to offset the chance
of landing in the latter? Similarly, how many men should receive diagnoses
of “indolent” prostate cancer that may never have presented clinically to
save one life? Arguably, individual patients need to decide for themselves
whether they will be willing to go through the risk of unnecessary post-
screening tests.
Unnecessary tests—test that, by and large, do not benefit the vast majority
of patients, and may harm them—should not be touted as a human right and
a necessity for health and survival. Screening does have downsides, as well
as positive outcomes (see, e.g., Gøtzsche and Nielsen, 2009). Patients should
know that they may be exposed to unnecessary radiation, that false positives
are more likely when a disease is rare, and that in many cases, screening for
early disease is neither always necessary nor beneficial. For instance, many
more prostate cancers are detected and treated today than 30 years ago due
to the promotion and use of PSA tests, and yet it is not clear that quality of
life for the vast majority of men treated for prostate cancer is thereby
improved (Esserman, Shieh, and Thompson, 2009). Since most prostate cancers
are slow growing, such that many men may never have clinical symptoms of
these cancers, and treatment can cause impotence and incontinence, it is not
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Ethical Issues in Cancer Screening and Prevention 5
clear that the vast increase in number of prostate cancers diagnosed benefits
most patients or extended lives.
However, those who administer and profit from these tests and treatments
do benefit. We cannot always assume that makers of mammography and other
technologies are motivated entirely by altruism. There must be oversight of
medical technologies and procedures to ensure that they help and do not
harm patients (Groopman, 2007; Quanstrum and Hayward, 2009). The
following is an overview and discussion of the general principles that should
be put in place for ethical practice of cancer screening and prevention and
a call for areas where we need to be more attentive to the variable biology
of different cancers, as well as the variable values of patients.
II. AUTONOMY
Respect for individual decision making and informed consent are central to
a commitment to patient autonomy and are, of course, required by law for
federal research (National Institutes of Health, 2005). However, respect for au-
tonomy is not simply a matter of giving patients choices; it requires that
they be informed about both risks and benefits of screening, and it requires
recognizing that patients may value risks and benefits differently. PSA tests
should be accompanied with some explanation, for example, of disease
prevalence, morbidity and mortality, test sensitivity and false positive rates,
and side effects of further screening and treatment. As mentioned above, for
many prostate cancers, “catching it early” may not be for the best, at least
in terms of quality of life. Many men die of heart disease, but die with pros-
tate cancer, having never experienced clinical symptoms. A better understand-
ing of the distinct pathology and genetics of more and less aggressive
forms of such cancers is important to assessing the value of such tests. Clini-
cians are understandably frustrated when, even when screening does
appear to have a proven benefit, some patients refuse screening because
they are afraid of medical procedures, do not like being put in the role of a
“patient,” or simply do not trust the evidence. In such cases, clinicians might
provide the patient with more information or better explanations of benefits
and risks of screening. However, they also must recognize that it is not un-
reasonable to value some choices over others; choices to not be screened
may not be due to ignorance but differences in values.
Informing patients about risk and benefit, as many have argued, is not a
straightforward matter. Even those with PhDs in statistics are subject to
heuristics and biases that make it difficult to understand or distinguish between
absolute and relative risk, for instance (Kahneman and Tversky, 1979; Weinstein,
1980; McKenna, 1993; Baron, 2000; Bowling and Ebrahim, 2001). Availability
heuristics and base rate fallacies are problems that plague researchers as well
as the average Joe. Clinicians may be as subject to bias as patients; a clinician
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does not want to think of the possibility that the tests (or treatment) are
either not effective or may even harm their patient unnecessarily.
With this in mind, respect for autonomy requires that those who manufacture
and profit from diagnostic tests actively seek to document and acknowledge
risk of screening tests. Federal regulations should require them to provide
effective ways of communicating such risk to both clinicians and patients.
Ideally, third parties without an interest in misinformation should assess the
science behind such risk/benefit assessments. Most of us assume (correctly)
that an X-ray or even a CT or two is not a serious risk. However, it has become
apparent that such machines may malfunction due to operator errors as well
as improper maintenance. Moreover, a lifetime of tests can add up. Patients
must be made aware that multiple CT scans and X-rays, over time, are not
“risk free.” Risks should be communicated in a way that is user friendly
and transparent, and patients and clinicians should communicate about the
cumulative effects of such tests over a lifetime.
For example, a patient admitted for a CT scan should be provided a pamphlet
showing exactly how much an excess of a certain number of such scans
will, on average, increase risk for cancer. Expression of risk in the simplest
possible fashion—for example, 1 in 100 individuals who have more than
N CT scans are at elevated risk for cancer to extent x—would be most effec-
tive. Clinicians, unfortunately, are incentivized to offer more tests, and many
do not have accurate knowledge about the risks of such tests, either because
manufacturers play down the risks or because there is simply insufficient
data. Either this incentive structure for clinicians needs to change or inde-
pendent parties need to provide some form of evidence-based regulation of
unnecessary and risky tests.
III. BENIFICENCE
Clinicians and their professional organizations have a vested interest in argu-
ing that their screening and treatment protocols are safe and effective. An
independent third party should watch over such claims and make sure
that the claimed benefits genuinely outweigh the risks. Sometimes this will
involve sponsoring more and better clinical trials. However, epidemiologists
may estimate when and whether a test is more or less effective, even with-
out a clinical trial, if they know how prevalent a disease is and how sensi-
tive and specific the available screening modality.
A general rule of thumb is that if a disease is not very prevalent, false posi-
tives will be relatively common. A simple example of how prevalence, for
instance, is relevant to the effectiveness of screening regimes follows (from
Buys, 2011). Suppose that you have a screening test that has very high speci-
ficity (the probability that a negative test means the disease is absent) and
high sensitivity (the probability that the test will be positive if the disease is
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Ethical Issues in Cancer Screening and Prevention 7
present). Let us say that the test is 95% specific (95% of positive tests are due
to disease) and 95% sensitive (95% of disease is identified). Suppose 10,000
individuals are tested. The performance of the screening test will vary
depending upon whether the disease is common (say, 5% prevalence) or very
uncommon (.05%).
Consider table 1: For the disease with high prevalence, the positive pre-
dictive value of the test (or the proportion of those who test positive who
have the condition) = ½. You can calculate this number yourself by dividing
the number of true positives by the number of true and false positives
(475/950). This means that half of those who screened positive were in fact
diseased. That may seem like a very high false-positive rate, but consider
table 2 for a much less prevalent disease.
Consider table 2: For the disease with lower prevalence, the positive
predictive value of the same test is 1/101. This means that only one out of
101 individuals who screened positive were in fact diseased (see table 2).
Thus, the effectiveness of the very same screening modality is significantly
less for less common diseases. Cancer, on average, is more prevalent in older
populations.
The lesson of this example is fairly simple: when a disease is not very
prevalent (as is the case for most cancers in most persons under 50), even
the most sensitive and specific screening test is not as effective, and may be
more harmful, than not being screened.
What are the costs of a false positive test? Perhaps a few days of worry,
followed up by a relatively noninvasive biopsy, are, some argue, not a serious
problem. However, sometimes, according to a recent report, unnecessary
open biopsies are done when needle aspirated biopsies would be equally
effective and safer (Gutwin et al., 2011). Moreover, for many cancers,
the only recourse after a positive diagnosis is a very serious surgery. For
instance, in the case of ovarian cancer, ovarectomies are not a minor proce-
dure and one with some serious side effects long term. Further, pathologists
are not immune to error. So, positive biopsies, that is, claims of malignancy,
can be in error. How often does this occur? According to some (Moss, 2005;
Table 1. Hypothetical disease no. 1—high prevalence
No. with positive test No. with negative test Totals
Disease 475 25 500
No disease 475 9,025 9,500
Table 2. Hypothetical disease no. 2—low prevalence
No. with positive test No. with negative test Totals
Disease 5 0 5
No disease 500 9,495 9,995
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Paci et al., 2006; Welch and Black, 2010) pathologists may overdiagnose some
cancers as much as one third of the time. Pathologists’ judgments about the
“invasiveness” or “metastatic potential” of a tumor vary; one pathologist’s
atypical ductal hyperplasia, a pathological finding that increases the risk of
subsequent cancer but is not itself cancer, may be another pathologist’s ductal
carcinoma in situ, which may be treated with surgery and radiation therapy.
Although on the side of the clinician, it is better to be “safe than sorry,” it is
not always safer for the patient to undergo ever earlier screening and pos-
sibly unnecessary surgical procedures. The upshot is: patients should be
able to decide what risk they are willing to accept, and not all screening
options are risk free.
IV. EVIDENCE-BASED MEDICINE
In light of these concerns, there needs to be more and better clinical trials of
screening modalities and other preventative measures. However, even the
best clinical trial is not free of bias. A variety of concerns have been raised
about evidence-based medicine, from concerns about meta-analyses and
their limitations to the variety of limitations of RCTs, randomized clinical trials.
Screening RCTs are subject to a number of systematic biases, and their impli-
cations for decision making under risk and uncertainty are not simple.
To start with some simple examples, consider lead-time bias—when detection
does not on average extend life but only makes patient aware of a diagnosis
earlier. This is likely a confounding factor in many clinical trials of new
screening modalities. More sensitive detection methods mean that cancers
are detected earlier, which leads to higher estimates of time to mortality since
diagnosis. However, if undetectable metastases have occurred prior to the
cancer being detected by the screening test, the cancer may cause death at
the same time as if it had never been detected. Thus, the measure or “end
point” of screening tests should be the “age-adjusted mortality,” rather than
years of survival after diagnosis.
Length bias—the fact that while many indolent (slow growing) cancers
show up on screening exams, but more aggressive cancers tend to show up
between screenings—is a serious problem for some cancers. Length bias leads
to the conclusion that screening and therefore early treatment improves
survival, whereas screening has simply identified less aggressive tumors.
Finally, overdiagnosis bias (the extreme of length bias) is the most damn-
ing problem. It is possible that many people are screened and treated for
cancers that may never have caused clinical symptoms. This is particularly
true in populations of patients over 80, who are more likely to die of other
causes and so may never have suffered any clinical symptoms of a slower
growing cancer. Older adults with significant comorbidities should not be
subject to the toxic effects of cancer treatment unnecessarily.
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Ethical Issues in Cancer Screening and Prevention 9
What the case of overdiagnosis in older populations illustrates is that context
matters. Not all screening tests are best for all patients at all ages, sexes, or
ethnicities. Underrepresented groups should be studied for variability in age
of onset of different cancers, as well as in aggressiveness of different can-
cers. It is well known that African Americans (particularly men) have higher
rates of mortality from cancer. How much of this is because they suffer from
more aggressive cancers and how much of it is due to the fact that African
Americans on average do not have adequate access to screening and/or
treatment? We need to remedy both inadequate access and inadequate or
ill-suited treatment regimens, taking human variability into consideration.
More inclusive and comprehensive RCTs of screening for different cancers
in different ethnic groups may help resolve some of these dilemmas (for a
discussion of the dilemmas of difference, see King, 1992).
In addition to the possible confounding factors of clinical trials, there are
a variety of methodological and broader policy concerns that some raise
about evidence based medicine.
First, a general worry is that EMB will result in a “one-size-fits-all” approach
to setting standards of care. For example, universal screening for a disease
starting at some specific age, when individual assessment of risk may be
more appropriate. Many worry that EBM and policy will reduce the power
of clinicians to make decisions on a case-by-case basis. Moreover, perhaps
clinicians need to have their enthusiasms (occasionally) reined in by the evi-
dence. As the case of open biopsies, reported above, and cases of back
surgery discussed by Groopman (2007) make strikingly clear, the culture of
medicine may be such that clinicians are trained in a practice—a surgical
procedure, screening modality, or treatment—that may or may not have
evidential support of benefit versus other (perhaps less costly) options.
To avoid cases of bias, clinicians may occasionally need to have their practices
and choices “second guessed” by epidemiologists.
Second, some may fear that where EBM points to “low” or “gray areas”
of benefit, third-party insurers may not be willing to pay for screening or
other tests or treatments. This is a legitimate concern, but perhaps this is an
argument for, rather than against, more public and open communication
about exactly when screening is and is not effective. For instance, if a clinician
needs to justify a screening test by giving evidence of increased patient risk,
this may actually reduce unnecessary harm to the vast majority of patients
who would receive little individual benefit from such a test.
Third, a variety of philosophers have raised questions about the “water-
tight” conclusions of RCTs. It is not clear, at least according to Worrall (2002,
2007), that randomized clinical trials are the “final word” on any medical
question (they are famously subject to reversals!), and he raises legitimate
objections to the claim that randomization (necessarily) eliminates all known
and unknown confounders. Further, some (Cartwright, 2010) argue that we
need to be careful of “exporting” the results of RCTs into contexts that are
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significantly different. It is not clear that the results of even the most carefully
conducted RCT at time X in geographical location Y can be exported to
an entirely different location, time, or culture. Medical culture, as well as
patient population, varies by location, university setting, and rural versus
urban areas.
Fourth, critics of meta-analyses argue that it is not altogether clear that they
are free of bias (Stegenga, 2011). Bias can enter in at the stage where choice
of studies to include in a meta-analysis is made, either in terms of the effect
measured or inclusion or exclusion on the bases of assessments of quality
and other methodological criteria. Further, different RCTs in different loca-
tions (even though they claim to be measuring the same “effect”) may be
drawing upon different patient populations, may be different in terms of
rates of diagnosis at different institutions and may not have uniform measures
of either cause or effect variable (RWJF, 2010). For example, when looking
into the USPSTF’s meta-analysis of the effectiveness of screening, different
institutions included ductal carcinoma in situ in their “count” of cancer diag-
noses and some used different measure of end point; for example, relative
risk versus hazard ratio.
Finally, meta-analyses do not have policy recommendations “written on
their sleeves.” Even when all the issues surrounding RCTs and meta-analyses
are appropriately addressed, an empirical study will always underdetermine
policy recommendations. For instance, the USPSTF’s recommendations are
based on clinical trials where patients were “invited” to be screened. Of course,
compliance was not perfect. So, a recommendation of universal screening for
individuals based on less than perfect compliance may be doubtful.
Confounders, such as “healthy volunteer” bias, may also contribute such
that only those at less risk are actually seeking opportunities to be screened,
so that the effectiveness of screening may be downplayed. Issues surrounding
compliance require more empirical follow-up. If compliance is imperfect,
some worry that recommendations of less frequent screening may cause
some women to choose not to go at all. However, the opposite may be the
case as well; if women are told that they only need to go every other year,
they may be better able to comply. Empirical data on when and why patients
seek screening might help resolve this issue. Determining how or whether
annual versus biannual recommendations are more likely to be complied
with is surely relevant to determining what should be recommended. Whether
and why patients fail to go for screening seems to be very important to
understand, not simply whether screening itself saves lives.
V. RISK AND PRECAUTION
Apart from the issues surrounding the empirical evidence for and against
screening, there is a further matter of risk communication and decision
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Ethical Issues in Cancer Screening and Prevention 11
making under uncertainty. How should physicians communicate about
screening, particularly when the benefits are small, or uncertain, and may be
outweighed by not insignificant risks? How should patients weigh the risks
and benefits of early screening? Ought one to make general clinical recom-
mendations drawing upon a precautionary principle and what does it mean
to do so? How, if at all, should individual medical decisions be conducted,
as distinct from public health recommendations? Is it necessary for clinicians
to communicate both absolute and relative risk to patients? What are we to
make of the fact that both patients (and clinicians!) are poor at deliberating
on decisions under risk? (see, e.g., Fagerlin et al., 2007; Schwartz, 2009).
As Resnik (2004) and Katz (1984) remind us in this context, we must be
attentive to both the science and values at stake in medical decision making.
The case of screening is not unique in this respect; many medical decisions
are made without complete evidence. Diagnosis and treatment decisions
often are made under time constraints; waiting for all the evidence to come
in might mean that a decision comes too late. Resnik (2004) argues that
where a risk is plausible and serious (e.g., if negative outcomes are irrevers-
ible), precaution is in order. This would seem to argue in favor of screening,
whatever the potential risks of false positives or overdiagnosis. However, as
Resnik remarks, given the sensitivity of the PSA test (and thus the high risk
of false positives), the patient has to make an individual decision about
whether he or she is willing to risk the need for follow up and possible treat-
ment for a disease that was indolent. Precaution is a double-edged sword.
Schwartz and Meslin (2008) argue that providing patients with absolute
rather than relative risk information may cause them to forgo a test or treatment
that may be beneficial. As mentioned above, absolute risk is calculated by sub-
tracting the mortality rate in the screened from the unscreened group. Relative
risk is calculated by dividing the decrease in morbidity or mortality by the base-
line rate. Schwartz and Meslin argue that providing relative risk information is
preferable and warn that absolute risk information can cause individuals to
forgo screening and the benefits thereof. If patients request further information,
they should certainly be provided it (Schwartz and Meslin, 2008).
Schwartz and Meslin acknowledge that their proposal may raise legitimate
concerns about informed consent and paternalism. There is, arguably, a
principle of “truth in advertising” that clinicians should follow. By way of
analogy, were the NRA to argue that carrying a firearm reduces one’s risk of
dying in a terrorist attack by 50%, one should be skeptical, and not only
because getting statistically significant data to support such a claim would
be nearly impossible. Relative risk reduction can be deceptive, particularly
when the baseline prevalence of some disease is exceedingly low. Clinicians
must be attentive to this and to the fact that there may be more than one
reasonable response to risk. Trade-off neglect, or the failure to acknowledge
and recognize reasonable trade-offs in decision, is a very common failure in
reasoning in such contexts. Different parties value precaution differently and
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may value, for example, more years of life without worry of false positives
over early aggressive treatment. As we have seen from the examples discussed
above, we all (clinicians included) should not assume that our “intuitions” are
always correct; early frequent screening may not always benefit all patients.
Framing risk reduction in relative terms is, arguably, a form of coercion, par-
ticularly when considering cases of gray areas, where one could legitimately
choose one of several options and not be entirely “irrational.” Values differ,
and putting likely trade-offs “on screen” is at least plausibly a moral obligation,
even if putting every possible remote risk on screen for patients is not.
Even clinicians may disagree as to the value of a treatment, procedure, or
screening modality, depending on their knowledge and values. As Quanstrum
argues, radiologists may be overly confident about the benefits of screening
(Quanstrum and Hayward, 2009). Especially where there are gray areas
concerning benefit, clinicians should watch that their own biases do not cause
them to frame the issues so that they gently urge one course of action.
However well meaning, such patterns run the risk of leading to overtreatment
and overdiagnosis, no small risk, particularly for older patients. What is at risk
is not simply worry or fear of cancer, but overtreatment, which is much more
serious, particularly for elderly women and men who may well die from other
causes before even experiencing clinical symptoms of disease.
VI. CONCLUSIONS
Although clinical trials of the effectiveness of screening are important, under-
standing cancer’s basic biology and natural history is as, if not more, important
to both the development of smarter screening modalities and better treatment.
There needs to be more swift progress in understanding the variable prog-
nosis for varieties of “the same” cancers. The assumption that all cancers
progress in a linear fashion at the very same speed toward morbidity and
mortality is no longer reasonable (Zahl et al., 2008; Croswell, Ransohoff,
and Kramer, 2010). Although it is not news that not all breast cancers are
alike, as we learn more about the variety of the major forms of cancer, it ap-
pears that even some very aggressive and uniformly deadly cancers, such as
pancreatic cancer, vary in their genetic profile and prognosis. This variation
could make significant differences in recommendations for both screening
and treatment. Although sequencing the “genome” of these different cancers
promises much, it is also the case that targeted therapies need not await a
complete “genetic diagnosis” of each and every therapy. Some of the best
available targeted therapies were made possible without a complete under-
standing of the genetic bases of the disease—understanding not only the
genetic but also molecular character, epigenetics, and/or developmental
context of different cancers can suggest innovative treatment as well.
Cancer is not one disease, but several. Not all cancers progress in the same
fashion. Some are “indolent”—they never or only at long last produce clinical
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Ethical Issues in Cancer Screening and Prevention 13
symptoms. Such slow-growing cancers may call for a “wait and see” strategy.
With better and more evidence-based pathological information about the
prospective course of different varieties of this disease, as well as the devel-
opment of better, more targeted and less toxic therapies, this may be a case
where less is more.
NOTES
1. As she puts it: “A necessary condition for an ethically justified screening recommendation is that the
test reasonably can be expected to be beneficial on balance for the person taking it. The qualifier ‘on balance’
takes into account the benefits and harms of the tests and outcomes as well as the probabilities that those
benefits and harms will occur. Thus it does not require that a given test be actually beneficial to everyone who
takes it. Such a requirement would be unreasonable since, given the nature of screening, the vast majority of
people screened will not have the disease in question and thus will not be able to benefit from the screening
(except by being told that they do not have a disease that they had no reason to suspect they had in the first
place). Instead, the standard requires only that the size of the benefit, taking into account the probability that
it will occur, outweighs the size of the risks, taking into account the probability that they will occur.
(Thus, an unlikely but great benefit can outweigh a very likely but small harm.) When this is the case, the test
can be said to be good for the recipient, all things considered or ‘beneficial on balance’” (Malm, 1999, p. 27).
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