Transcript Modivation

Multi-Clinic and Multi-National Trials:
A regulatory perspective
Charles Anello Sc.D.
Deputy Director, Office Of Biostatistics
Office of Pharmacovigelence and Statistical Sciences
Center for Drug Evaluation and Research
[email protected]
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Acknowledgements
I would like to express my appreciation to
Robert T. O’Neill, Satya Dubey, Jim Hung,
Robert Temple and John Lawrence for their
helpful suggestions in the preparation of
this talk.
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Disclaimer
The views expressed are those of the author
and do not necessarily represent those of the
Food and Drug Administration.
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Topics
Motivation
Regulatory Context
Changing Context
Some statistical Issues
Multi-national studies
An example
Conclusions
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Motivation
University Group Diabetes Program
Coronary Drug Project
How did multi-clinic and multi-national
trials become so common?
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Regulatory Context
Kefauver-Harris Amendments to FD &C Act.

The need to establish efficacy based on substantial
evidence
 Adequately powered studies are needed to detect
clinically meaningful drug effects

As the focus shifted to modest effects the need for large
enough studies to establish efficacy led to the increase
use of multi-clinic or multi-investigator trials.
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Changing Context
Format and Content Guidance
ICH E9
Evidence Document
Emergence of a global pharmaceutical
industry and the multi-national Trial
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Format and Content Guidance
Results for individual studies should be
presented
Suggests test for interaction between
treatments and centers
No guidance on how this test is to be
conducted or the significance level to be
used
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Format and Content Guidance
Extreme or opposite results need to be
discussed
Demographic , baseline and results
presented by center
Graphic displays by center on key
characteristics and findings
Special attentions is given to age, gender,
ethnicity (or region).
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Why the emphasis on interaction?
 The review of a clinical trial as several
aspects:
1. Are the treatment groups comparable
2. Are the potential sources of bias that may
account for the findings
3. Is the treatment effect consistent across the
centers
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Why the emphasis on interaction?
The review function as a detective aspect
The review function as a quality control aspect
The goal of the review is to establish efficacy and
safety and provide information to physicians in
the product label about how and for whom the
drug works
If subgroups (e.g., clinics) show different results(
i.e., interaction) this could impact the label
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ICH E9
Suggests multi-clinic trials are needed to
speed up the time needed to conduct trials
Provide a basis for generalization
Stress the need to implement the common
protocol in a similar manner in all clinics
across all regions
Offers advice how to approach the analysis
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ICH E9
Test main effect first , if significant
Test interaction as an exploratory analysis
If there are a large number of centers, it is
less important to consider interaction.
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Evidence Document
When only one multi-clinic trial is available
for establishing substantial evidence of
efficacy and safety
The results need to be statistically very
persuasive
Internally consistent
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Evidence Document
No single site, clinic provides an unusually large
fraction of patients
No single site, clinic is responsible for a
disproportionate favorable effect
Estimated effects are consistent across clinics
Multiple endpoints are consistent
Results highly statistically significant p<<.05 (eg.
.001)
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Lack of consistency in statistical
advice?
In an ANOVA situation the Format and Content
document suggest one tests first for interaction but
doesn’t say how to do it.
ICH E9 suggests one test main effects first only
they are significant does one examine interaction
Evidence document focuses on the need for
internal consistency but leaves open how
consistency is to be established. No advice on
statistical approach
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Looking at Interaction
There is no consistent approach
Some advocate fixed effect models
Some advocate random effect models
Some advocated mixed effect models
And so on.
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Some statistical Issues
Are centers fixed or random
If an ANOVA is used would one use the
type II or type III sums of squares
Other approaches
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Are Centers Fixed or Random?
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Centers fixed or Random
 The decision to call centers fixed or random has
implications for the analysis
Arguments in support of fixed effects:
1. only approach for single center
2. gives precise answer to well defined question
3. only realistic approach with few centers,
4. definition of center is arbitrary
Senn (1998)
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Centers fixed or Random

1.
2.
3.
In support of the Random effect model
approximate answer to difficult question
affect more general
wider confidence interval
Senn (1998)
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Are Centers Fixed or Random?
There are other opinions
Fleiss(1988) favored fixed effect model with a
test for interaction
Grizzle(1988) questioned the fixed effect
model and preferred the random effect
model
Senn(1993) remained open minded on this
issue
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Are Centers Fixed or Random?
The random effect model incorporates
interaction into the error term.
The fixed effect model allows one to
explore interaction if it exists
Both approaches can be justified at some
level.
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Are Centers Fixed or Randon
 In order to label a product correctly one needs to be sure
the effect is consistent across all relevant subgroups
 From my perspective the fixed effect model seems more
relevant.
 Whereas the random effect model may answer a question
it may answer a different question?
 It may give the right answer to the wrong question.
Kimbell(1965) would have called this a “type III error”
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What is the correct Sums of Squares
in an ANOVA analysis
The choice is between the type II and typeIII SS
for SAS GLM
Many authors support the type II SS which
involves weighting by center size
FDA has been alleged to favor the type III SS
While I can not speak for all FDA I think the
current view within CDER is with those
supporting the type II SS
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Much Discussion about variation
between centers
Is to be expected but difficult to detect
Is it quantitative (i.e., same direction only
magnitude differs) very common
Is it qualitative (i.e., treatment shows benefit in
some centers , Placebo shows benefit in others)
less common
Qualitative interaction is of concern but not found
very often and hard to establish
Peto(1982)
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Expected Center Variation
For fixed sample size as the number of centers
increases so does the chances of reversal
It has been shown that with as few as six centers
there is better than a 50% chance of having at
least one center where the placebo effect would
exceed the treatment effect.
O’Neill et. al.(1998)
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Multi-national Differences
Temple (SCT 2003) discussed the
interpretation of international differences in
clinical trail results
I will focus on a single international trial in
which a subgroup( country or region)
appeared to show a result different from the
overall finding of the study
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Multi-national Multi clinic Trials
MERIT-HF Trial a multi-national trial of
mortality in patients with chronic heart
failure.
When the regions of US versus Europe was
examined by a post hoc analysis differences
were observed although not quite at the
“qualitative difference”
one group showed a benefit another did not.
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MERIT-HF Trial
Metoprolol succinate extended release
(Toprol XL) the MERIT-HF Trial
Placebo controlled, multi-national 3991
patient trial in NYHA Class II_III CHF
,treated added to ACEI, digitalis and other
Rx
Endpoints: all cause mortality and all cause
mortality plus hospitalization
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MERIT-HF Trial
The differences occurred in the mortality
findings. The combined endpoint showed a
consistent finding whereas the mortality
endpoint showed a 50% reduction in the
Non US population compared to a 5%
excess in the US population. With a post
hoc p-value of .003.
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MERIT-HF Trial
The regions were not a pre-specified subset
Approval was not an issue the study showed a
benefit for mortality plus hospitalization
The agency’s internal debate focused on “full
disclosure” this apparent unexplained qualitative
interaction in a component of composite endpoint.
Whether regions matter in this instance is an open
question.
Temple(2003)
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Summary
Multi-clinic trials are an important aspect of drug
development and regulatory review
Multi-clinic multi-national trials are becoming
more important
From a regulatory perspective consistency in
results are important
If interaction occur, they need to be identified and
understood
Interactions may have implications for the product
label and public health
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Summary
 Some statistical tools for dealing with these interaction
exist, but may have limited utility due to low power
 The fixed effect model may be more useful when there are
not to many clinics and the sample sizes are large and
approximately equal size and it is reasonable to assume a
constant effect across the clinics
 The random effect model may be more useful when there
are large number of clinics with few observations per clinic
and one can not address the question of center by treatment
interaction.
 When an ANOVA is appropriate, the type II sums of
squares is often the Sums of squares of choice
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Summary
Quantitative and Qualitative interactions happen
although Qualitative interaction is rare
Observed clinic or regional differences need to be
noted, explained if possible and reported but not
necessarily believed.
The potential for regional differences, may have
implications for study design and the way DSMBs
monitor trials.
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