"Well, I've observed many patients
receive that drug combination, and
I've never seen any problems with it.
Therefore, this is not a clinically
important drug interaction."
Have you ever heard that response
after you informed a prescriber about a
potential drug-drug interaction involving
one of his or her patients? Several
possibilities may account for this
response, of course. It could be that the
drug interaction truly is not clinically
important, and the prescriber is correct
to ignore it. Or, it could be that the prescriber
is trying to "save face"by minimizing
the importance of the drug
interaction. More likely, however, the
prescriber is coming to an erroneous
conclusion due to inappropriate use of
What Is Inductive Reasoning?
Inductionin the philosophical, not
the metabolic senseis the process of
coming to general conclusions from
repeated observations of a particular
event or thing. Human beings use
inductive reasoning on a regular basis.
For example, if a person drives down a
particular road at rush hour several
times and finds the traffic terrible each
time, the person concludes that this is a
good road to avoid at rush hour.
Reaching that conclusion is inductive
reasoning, and it is a useful tool for making
Likewise, the majority of the "truths"
in medicine and pharmacy are derived
from inductive reasoning. If we as pharmacists
observe that 90% of the
patients with hyperthyroidism have a
particular symptom, we say that the
presence of this symptom constitutes
evidence that supports a diagnosis of
hyperthyroidism. That line of thinking
is inductive reasoning as well.
What Are the Pitfalls of
Inductive reasoning is useful, but it
also can be abused, especially when
people use it to come to firm conclusions
based on a limited number of
observations. More than 250 years after
18th-century Scottish philosopher
David Hume eloquently and convincingly
exposed the limitations of inductive
reasoning, abuse of this method
remains alive and well.
The classic example used to show the
poverty of this approach in achieving
certainty is the experience of Europeans
whofor thousands of yearshad
never seen a swan that was not white.
They assumed that all swans were
white, and they were disabused of this
truism only when black swans were discovered
in Australia. Hume used this
example to show that no number of
observations of white swans would be
large enough to allow one to conclude
with absolute certainty that all swans
Nevertheless, inductive reasoning
can be useful as a guide to making decisions
(as opposed to divining "the
truth") if the number of observations is
high enough. For example, tens of
thousands of people have hiked in the
woods of the Pacific Northwest without
a single confirmed Bigfoot sighting.
With this number of observations, it is
safe to conclude that the risk of
encountering Bigfoot is vanishingly
smallthe inductive nature of the conclusion
Accordingly, it is quite reasonable to
behave as though Bigfoot does not exist.
This belief, however, is nothing close to
proof of Bigfoot's nonexistence. Absence
of proof is not proof of absence.
Using Induction for Drug
So, what do all of these examples have
to do with drug interactions? Most health
professionals apply inductive reasoning
naturally and effortlessly when assessing
the potential danger of particular combinations
of drugs. For most clinically
important drug interactions, however,
the number of observations made by
individual practitioners is simply not sufficient
to make accurate risk assessments.
A good example of this principle
involves the concurrent use of angiotensin-
converting enzyme inhibitors and
potassium-sparing diuretics (Hyperkalemia
Due to Drug Interactions,
Pharmacy Times, January 2004). The
combination can contribute to severe or
fatal hyperkalemia in certain predisposed
patients, but most people obtain benefit
without significant adverse outcomes.
Most prescribers, therefore, do not see
severe hyperkalemia, and thus they conclude
that it is of minimal concern. As a
result, patients continue to be harmed by
a preventable adverse drug interaction.
Another way to look at this problem
is from a statistical standpoint. For an
interaction that caused a serious
adverse outcome in 1 of 1000 patients
exposed to the combination, one
would have to study 3000 patients in
order to have a 95% chance of observing
the event. Thus, for serious drug
interactions that occur rarely, few practitioners
would observe enough
patients to see the adverse outcome.
Inductive reasoning based on personal
clinical experience has serious limitations
as a guide to the clinical importance
of most drug-drug interactions. It
is important, therefore, to consider the
results of published literature in addition
to personal clinical experience
when making decisions about drug
interactions in individual patients.
Drs. Horn and Hansten are both professors
of pharmacy at the University of Washington
School of Pharmacy. For an electronic version
of this article, including references if
any, visit www.hanstenandhorn.com.