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the free encyclopedia
A randomized controlled
trial (RCT) is a form of
clinical trial, or scientific
procedure used in the testing of
the efficacy of medicines or
medical procedures. It is
widely considered the most
reliable form of
scientific evidence because it
is the best known design for
eliminating the variety of
biases that regularly
compromise the validity of medical
research.
Sellers of medicines throughout
the ages have had to convince
their patients that the medicine
works. As science has progressed,
public expectations have risen,
and government health budgets have
become ever tighter, pressure has
grown for a reliable system to do
this. Moreover, the public's
concern for the dangers of medical
interventions has spurred both
legislators and administrators to
provide an evidential basis for
licensing or paying for new
procedures and medications. In
most modern health-care systems
all new
medicines and
surgical procedures therefore
have to undergo trials before
being approved.
Trials are used to establish
average efficacy of a treatment as
well as learn about its most
frequently occurring
side-effects. This is meant to
address the following concerns.
First, effects of a treatment may
be small and therefore
undetectable except when studied
systematically on a large
population. Second, biological
organisms (including
humans) are complex, and do
not react to the same stimulus in
the same way, which makes
inference from single clinical
reports very unreliable and
generally unacceptable as
scientific evidence. Third, some
conditions will spontaneously go
into
remission, with many extant
reports of miraculous cures for no
discernible reason. Finally, it is
well-known and has been proven
that the simple process of
administering the treatment may
have direct psychological effects
on the patient, sometimes very
powerful, what is known as the
placebo effect.
Types of trials
Randomized trials are employed
to test efficacy while avoiding
these factors. Trials may be
open, blind or
double-blind.
Open trial
In an open trial, the
researcher knows the full details
of the treatment, and so does the
patient. These trials are open to
challenge for bias, and they do
nothing to reduce the placebo
effect. However, sometimes they
are unavoidable, particularly in
relation to surgical techniques,
where it may not be possible or
ethical to hide from the patient
which treatment he or she
received.
Blind trials
Single-blind trial
In a single-blind trial, the
researcher knows the details of
the treatment but the patient does
not. Because the patient does not
know which treatment is being
administered (the new treatment or
another treatment) there should be
no placebo effect. In practice,
since the researcher knows, it is
possible for them to treat the
patient differently or to
subconsciously hint to the patient
important treatment-related
details, thus influencing the
outcome of the study.
Double-blind trial
In a
double-blind trial, one
researcher allocates a series of
numbers to 'new treatment' or 'old
treatment'. The second researcher
is told the numbers, but not what
they have been allocated to. Since
the second researcher does not
know, they cannot possibly tell
the patient, directly or
otherwise, and cannot give in to
patient pressure to give them the
new treatment. In this system,
there is also often a more
realistic distribution of sexes
and ages of patients. Therefore
double-blind (or randomized)
trials are preferred, as they tend
to give the most accurate results.
Triple-blind trial
Some randomized controlled
trials are considered
triple-blinded, although the
meaning of this may vary according
to the exact study design. The
most common meaning is that the
subject, researcher and person
administering the treatment (often
a
pharmacist) are blinded to
what is being given. Alternately,
it may mean that the patient,
researcher and
statistician are blinded.
These additional precautions are
often in place with the more
commonly accepted term "double
blind trials", and thus the term
"triple-blinded" is infrequently
used. However, it connotes an
additional layer of security to
prevent undue influence of study
results by anyone directly
involved with the study.
Controlled aspect
The 'controlled' aspect comes
from three main sources. The first
is another member of the research
team, who will typically review
the test to try to remove any
factors which might skew the
results. For example, it is
important to have a test group
which is reasonably balanced for
ages and sexes of the subjects
(unless this is a treatment which
will never be used on a particular
sex or age group). The second
source of control is inherent in
having a 'control' group, that is,
a group which is undergoing the
same routine (seeing a doctor,
taking pills at the same time,
etc.) but is not receiving the
same treatment. This control group
will be receiving either no
treatment (e.g., sugar pills) or
will be receiving the current
standard treatment (if, for
example, it would be unethical not
to treat their ailment at all).
The third source of control is via
peer review and/or review by
government regulators, who will
examine the trial when it is
presented for publication or when
the drug manufacturer applies for
a licence for the drug.
The importance of having a
control group cannot be
overstated. Merely being told that
one is receiving a miraculous cure
can be enough to cure a
patient—even if the pill contains
nothing more than sugar.
Additionally, the procedure itself
can produce ill effects. For
example, in one study on
rabbits where these subjects
were receiving daily injections of
a drug, it was found that they
were developing
cancer. If this was a result
of the treatment, it would
obviously be unsuitable for
testing in humans. Because this
result was reflected equally
between the control and test
groups, the source of the problem
was investigated and it was shown
in this case that the
administration of daily injections
was the cancer risk—not the drug
itself.
The analysis of the trial
results is a great skill in
itself, and pharmaceutical firms
employ groups of
statisticians to try to make
sense of the data. Likewise,
regulators pay keen attention to
the statistics, which can be used
to hide serious deficiencies in
the effectiveness of a treatment.
Outcome-adaptive randomization
For a randomized trial in human
subjects to be ethical, the
investigator must believe before
the trial begins that all
treatments under consideration are
equally desirable. At the end of
the trial, one treatment may be
selected as superior if a
statistically significant
difference was discovered. Between
the beginning and end of the trial
is an ethical grey zone. As
patients are treated, evidence may
accumulate that one treatment is
superior, and yet patients are
still randomized equally between
all treatments until the trial
ends.
Outcome-adaptive randomization
is a variation on traditional
randomization designed to address
the ethical issue raised above.
Randomization probabilities are
adjusted continuously throughout
the trial in response to the data.
The probability of a treatment
being assigned increases as the
probability of that treatment
being superior increases. The
statistical advantages of
randomization are retained, while
on average more patients are
assigned to superior treatments.
Difficulties
A major difficulty in dealing
with trial results comes from
commercial, political and/or
academic pressure. Most trials are
expensive to run, and will be the
result of significant previous
research, which is itself not
cheap. There may be a political
issue at stake (compare
MMR vaccine) or vested
interests (compare
homeopathy). In such cases
there is great pressure to
interpret results in a way which
suits the viewer, and great care
must be taken by researchers to
maintain emphasis on clinical
facts.
Most studies start with a 'null
hypothesis' which is being
tested (usually along the lines of
'Our new treatment x cures
as many patients as existing
treatment y') and an
alternative hypothesis ('x
cures more patients than y').
The analysis at the end will give
a statistical likelihood, based on
the facts, of whether the null
hypothesis can be safely rejected
(saying that the new treatment
does, in fact, result in more
cures). Nevertheless this is only
a statistical likelihood, so false
negatives and false positives are
possible. These are generally set
an acceptable level (e.g., 1%
chance that it was a false
result). However, this risk is
cumulative, so if 200 trials are
done (often the case for
contentious matters) about 2 will
show contrary results. There is a
tendency for these two to be
seized on by those who need that
proof for their point of view.
