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analyses that analyze or compensate for them. Typical exceptions include
the following:
Did Not Participate.
Subjects who were eligible and available but did
not participate in the study—this group should be broken down further
into those who were approached but chose not to participate and those
who were not approached. With a mail-in survey for example, we would
distinguish between those whose envelopes were returned “address
unknown” and those who simply did not reply.
Ineligibles.
In some instances, circumstances may not permit deferring
treatment until the subject's eligibility can be determined.
For example, an individual arrives at a study center in critical condition;
the study protocol calls for a series of tests, the results of which may not
be back for several days; but in the opinion of the examining physician,
treatment must begin immediately. The patient is randomized to treat-
ment, and only later is it determined that the patient is ineligible.
The solution is to present two forms of the final analysis: one incorpo-
rating all patients, the other limited to those who were actually eligible.
Withdrawals.
Subjects who enrolled in the study but did not complete
it including both dropouts and noncompliant patients. These patients
might be subdivided further based on the point in the study at which they
dropped out.
At issue is whether such withdrawals were treatment related or not. For
example, the gastrointestinal side effects associated with erythromycin are
such that many patients (including both authors) may refuse to continue
with the drug. Traditional statistical methods are not applicable when
withdrawals are treatment related.
Crossovers.
If the design provided for intent-to-treat, a noncompliant
patient may still continue in the study after being reassigned to an
alternate treatment. Two sets of results should be reported: the first for
all patients who completed the trials (retaining their original treatment
assignments for the purpose of analysis), the second restricted to the
smaller number of patients who persisted in the treatment groups to
which they were originally assigned.
Missing Data.
Missing data is common, expensive, and preventable in
many instances.
The primary endpoint of a recent clinical study of various cardiovascular
techniques was based on the analysis of follow-up angiograms. Although
more than 750 patients were enrolled in the study, only 523 had the
necessary angiograms. Almost one-third of the monies spent on the
trials had been wasted. This result is not atypical. Capaldi and Patterson
