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This page is maintained by the PhRMA adaptive
design working group ( Alex
Dmitrienko).
Lecture series
Adaptive design lecture series.
January 11, 2008
Testing and estimation in adaptive group
sequential designs with treatment selection presented by Prof.
Martin Posch (Medical University of Vienna) [ Download
slides].
Abstract
Integrating selection and confirmation phases
into a single trial can expedite the development of new treatments.
We consider adaptive group sequential trials to compare several
treatments (or doses) with a control. In an interim analysis one
or more of the considered treatments are selected to be continued
in the further stages. The choice of treatments depends on the
data accumulated so far. This includes typically not solely data
on the primary endpoint but also data on secondary endpoints,
safety data and also data from external sources as, e.g., other
trials running in parallel. Adaptive designs based on combination
tests are efficient tools to implement treatment selection without
compromising the multiple type I error rate (Bauer and Kieser,
1999; Hommel, 2001). A crucial feature of these designs is that
the treatment selection rule need not be specified in advance.
For the sake of credibility, in clinical trials one should, however,
specify the major options for treatment selection in the protocol.
Besides hypotheses testing, we discuss the properties of point
estimates and the construction of confidence intervals for designs
with adaptive treatment selection (Posch et al. 2005).
References
Bauer, P. and Köhne, K. (1994). Evaluation
of experiments with adaptive interim analyses. Biometrics. 50,
1029-1041.
Müller, HH. and Schäfer, H. (2004). A general statistical principle
for changing a design any time during the course of a trial. Statistics
In Medicine. 23, 2497-2508.
Posch M., König F., Branson M., Brannath W. Dunger-Baldauf C.
and Bauer P. (2005). Testing and estimation in flexible group
sequential designs with adaptive treatment selection. Statistics
in Medicine. 24, 3697-714.
Hommel, G. (2001). Adaptive modifications of hypotheses after
an interim analysis. 43, 581-589
February 8, 2008
Supply issues in adaptive clinical trials
presented by Mr. Tom Parke (Tessella) [ Download
slides].
Abstract
Adaptive designs make drug supply during
the trial much harder and if they feel they can't supply your
trial you won't be able to run it. So what are the key issues
for drug supply and how can we address them:
1. There are more treatment arms - how do we supply more doses?
2. Arms may be dropped/introduced or arms may become more/less
likely to be allocated.
3. How do we know how much of each dose we will need make/package?
4. During the trial, how do we know which doses to ship?
March 14, 2008
Adaptive designs for clinical trials:
Insightfully innovative or irrelevantly impractical presented
by Prof. Stuart Pocock (London School of Hygiene and Tropical
Medicine) [ Download
slides].
April 11, 2008
Drug supply for adaptive trials presented
by Dr. Nitin Patel (Co-founder and Chairman, Cytel Inc) [ Download
abstract] [ Download
slides].
June 13, 2008
Interim analyses with multiple primary
endpoints – Application to an HIV vaccine trial presented
by Dr. Devan Mehrotra (Merck) [ Download
slides].
Abstract
Published research on group sequential methods
and adaptive designs has largely focused on clinical trials with
a single primary endpoint. In this presentation, we will discuss
interim analysis strategies when there are two primary endpoints
and the goal is to maximize the number of endpoints for which
statistical significance can be demonstrated in a timely manner
while ensuring control of the overall type I error rate. To illustrate
the key ideas, we will describe an interim analysis strategy that
was developed and implemented for a placebo-controlled HIV vaccine
test-of-concept efficacy trial with dual primary endpoints: HIV
infection status (infected/uninfected) and post-infection HIV
RNA set-point (for those who become HIV infected). The proposed
strategy can be extended to more general settings, including trials
with more than two treatment arms and/or with than two primary
endpoints.
July 11, 2008
Population enrichment within a group sequential
design presented by Dr. Cyrus Mehta (Cytel Inc) [ Download
slides].
Abstract
We present a method for combining group sequential
stopping rules with population enrichment within the framework
of a confirmatory clinical trial. The approach is motivated by
the need for greater efficiency in large cardiology trials where
event rates are low and efficacy gains relative to the current
standard of care are likely to be small. Since such trials typically
involve sample sizes in the thousands, group sequential designs
with early stopping for benefit or futility are commonly adopted.
The chances of success with such trials can be greatly enhanced
if patient eligibility is restricted to a subpopulation, selected
from analysis of interim data that is sensitive to the new treatment.Statistical
methodology for enriching an ongoing group sequential trial in
this manner, possibly accompanied by a data dependent sample size
increase, will be presented. The approach is general and can be
applied to late stage clinical trials in other therapeutic areas
besides cardiology.
August 08, 2008
Sample size recalculation in internal
pilot study designs: A review presented by Prof. Tim Friede
(University of Warwick) [ Download
slides].
Abstract
The adequacy of sample size is important
to clinical trials. In the planning phase of a trial, however,
the investigators are often quite uncertain about the sizes of
parameters which are needed for sample size calculations. A solution
to this problem is mid-course recalculation of the sample size
during the ongoing trial. In internal pilot study designs, nuisance
parameters are estimated on the basis of interim data and the
sample size is adjusted accordingly. This review attempts to give
an overview on the available methods.
September 12, 2008
Comparing adaptive designs and the classical,
group sequential approach to clinical trial design presented
by Prof. Chris Jennison (University of Bath).
Abstract
We shall consider the objectives of adaptive
and group sequential designs and compare these approaches in two
applications. The first case study concerns sample size re-estimation
in response to interim estimates of the treatment effect. Our
conclusion here is that group sequential methods provide an adequate
mechanism to curtail or prolong a study as information accrues
about the primary endpoint. In the second case study we focus
on adaptation of the patient population in response to interim
results and see tangible benefits from the adaptive approach:
moreover, the issues here are beyond the remit of group sequential
tests. The talk will conclude with an attempt to generalise from
these two examples.
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