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0:00
Hello, my name is Marc Buyse.
I'm the Chief Scientific Officer
of the International
Drug Development Institute
in San Francisco.
And the talk today
will be about biomarkers
and surrogate endpoints
in randomized clinical trials.
0:15
Here is the outline of the talk.
I will first define the notions
that I will discuss today.
First, the prognostic biomarker,
second,
the predictive biomarker,
and third, the topic
that I will spend most time on,
a surrogate biomarker
or surrogate endpoint.
I will then discuss
the statistical validation
of these different
types of biomarkers.
I will provide examples of
surrogate endpoints in oncology.
And again, most of the talk
will be about those examples.
And I will conclude.
0:44
First, let's define
some of the notions
we will discuss
during this talk.
A clinical endpoint
is a characteristic or variable
that reflects
how a patient feels,
functions, or survives.
In cancer, for example,
and most of my examples
will be in advanced forms
of cancer,
survival is the typical
clinical endpoint,
response to treatment
may also be seen
as a clinical endpoint.
Although, the value
of response to treatment
is more arguable
than the value of survival
as an endpoint.
Response to treatment
may or may not be accompanied
with a benefit to the patient.
Disease
or progression-free survival
also are
considered clinical endpoints.
These definitions,
by the way, were provided
by the by Biomarkers Definition
Working Group
about 15 years ago
and they are still in use today.
1:34
A biomarker is a characteristic
that is objectively measured
and evaluated as an indicator
of normal biological processes,
pathogenic processes,
or pharmacologic responses
to a therapeutic intervention.
So the key difference
between a biomarker
and a clinical endpoint
is that a biomarker
may or may not, and usually
is not associated,
with some patient benefit.
Typical examples of biomarkers
are PSA levels
in prostate cancer,
circulating tumor cells
in solid tumors, etc...
