In order to understand the studies and trials
on which our knowledge is based, an understanding of the terminology
Retrospective studies identify patients
suffering from a disease and, through medical interviews and examinations,
attempt to discover which characteristics they have in common. For
example, in the case of coronary disease, the common characteristic
might be male gender or cigarette smoking; these are referred to
as risk factors for coronary disease.
The predictive accuracy of risk factors established
by retrospective studies can be tested by prospective studies.
These identify healthy individuals who possess the proposed risk
factors, then follow them to see if they eventually develop coronary
disease. Both types of studies make no attempt to affect the outcome;
they are purely observational in nature. Probably the best- known,
and certainly the most-often-quoted prospective study in the field
of coronary disease, is the U.S. Department of Health's Framingham
Study, which started in 1949 and is still active (as one of its
principal investigators, Dr. William Kannel has said " It's
a race to see who survives the longest, the investigators or the
In contrast, clinical trials test
the effect on a disease of some form of intervention - either drug,
diet, or even regular exercise. In order to avoid biasing the results
by inadvertently preselecting a group of subjects who might respond
favorably to the intervention, a process known as randomization
is used. Candidates for the trial are randomly allocated, usually
by computer, to either a treatment or nontreatment (control) group.
In the case of a drug clinical trial, the control group is generally
given a placebo, an inert, harmless substance identical in appearance
to the drug. This corrects for the placebo effect, a well-known
medical phenomenon in which some subjects experience a benefit from
any form of treatment merely because they expect one. Since subjects
do not know whether they are taking the active drug or the placebo,
the trial is described as "blind".
When we come to evaluate the results of a
clinical trial, we need to compare the occurrence of a predetermined
measure, called the end-point, in the treated and the control groups;
for instance, the occurrence of death from a heart attack. However,
we have to be sure that any difference in end-points between the
two groups is not due to chance. This is solved by subjecting the
numbers to statistical significance testing. For a trial to show
a statistical significance and a conclusive result, the probability
of any difference in end-point between the treated and the control
subjects happening purely by chance alone must be 5% of less, expressed
as p (probability) = 0.05. A probability of more than 5% (p = 0.06
or greater) means a non-significant or chance result. Obviously
a probability of 1% or one in a hundred (p = 0.01), or of 0.1%,
one in a thousand (p = 0.001) confers upon the difference in end-point
even greater statistical significance, and therefore makes it even
Sometimes a trial may fall just short
of achieving a statistically significant result, possibly because
of methodological problems, e.g. not enough subjects were recruited,
or the time allowed for follow-up was too short. In cases such as
this, if the data from similar trials are available, then we can
resort to a statistical tool known as meta- analysis. Here we pool
all the results and analyze them as if they came from a single trial.
In this way we may be able to detect from a series of "almost
successful" trials an outcome which may be more conclusive.
The use of meta-analysis is rapidly increasing as we come to rely
more and more on clinical trials to prove, or disprove, the value
of various medical treatments.
CCRF would like to thank Dr. T. Kavanagh for his contribution to the Website.
The articles, on the Cardiac Health Foundation of Canada website, are presented with the understanding that the Foundation is providing information only and not rendering medical advise. Please check with your family physician, specialist or health care professional before implementing any of the ideas expressed in these articles.
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