Transcript EORTC mission

How much can we adapt?
An EORTC perspective
Saskia Litière
EORTC - Biostatistician
I have no conflicts of interest
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Outline
Adaptive designs
• What?
• Why?
• The challenges
• Examples
 Currently part of EORTC portfolio
 Currently not (yet) part of EORTC portfolio
• Take home messages
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What is an adaptive design?
“… a study that includes a prospectively planned
opportunity for modification of one or more
specified aspects of the study design and
hypotheses based on analysis of data (usually
interim data) from subjects in the study. “
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Why use adaptive designs?
• They aim to make efficient use of patient and
financial resources
• Allow for real-time learning during the course of
a trial
• Relatively flexible: modifications possible in the
course of trial which make the approach more
robust to failure
• The drug development process is streamlined
and optimized
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The challenges
• To control the
operating characteristics
• To control the bias due to the adaptation
 Statistical
 Operational
• To guarantee that the results can
be interpreted and explained!
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Several possible approaches
• Early stopping for futility and/or
efficacy
• Drop treatment arm(s) – also
known as pick the winner
designs
• Biomarker adaptive designs
• Sample size re-estimation
• Adaptive randomization…
Well-known
Less understood
To name but a few …
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Most of them come down to
One trial
Learn
Confirm
Change H0?
Change design parameters?
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A few examples
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Doxorubicin
+ Ifosfamide
Final: OS?
R
Interim 2: OS?
Doxorubicin
Interim 1: PFS?
EORTC 62012 in first line treatment of
advanced, high grade STS
Group sequential design
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TRUSTS (EORTC 62091) in advanced or
metastatic STS
Phase IIb
3 x 40 pts
Phase III
2 x 110 pts
Trabectedin 1.3 mg/m2 3-h
Doxo 75 mg/m2
PFS?
R
Select the best
PFS
Doxorubicin 75 mg/m2
T 3-h or 24-h
Trabectedin 1.5 mg/m2 24-h
Seamless phase II/III design
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TRUSTS (EORTC 62091) in advanced or
metastatic STS
– Both steps are conducted independently and
the results of both steps are combined in the
end in an overall test result
– Shortens time and patient exposure
– Relatively flexible
– Efficient use of patient resources
– Complex design: statistics are difficult to
explain
– Gap in accrual between phase II and phase III
– Logistically challenging
– Difficult in studies with long-term endpoints
» Unless in combination with a short-term endpoint
for the phase II part … another long and complex
story on type I error and correlation
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Sample size re-estimation
2-sided a = 5%
Power = 90%
HR = 0.7
Cytel Webinar for East®SurvAdapt,
October 28, 2010
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Sample size re-estimation
• May increase the risk of running an enlarged
negative trial
• Possibility of second guessing
 A resampling decision can be easily interpreted
as “the treatment is not as efficient as expected”
→ Operational bias? Accrual?
→ May require extensive (expensive) logistics
Protection of study integrity is essential!
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Battle Trial – Adaptive randomization
Lee et al.
Zhou et al. CT 2008
Battle Trial – Adaptive randomization
Prior
probability of
each
treatment
success given
marker
Randomize
using the
weights
given by
prior prob
8-week
outcome
observed
Probabilities of
treatment
success
updated based
on observed
results
Maximizes the chance that the patient receives the
treatment that is most effective for him/her
Adaptive randomization
• Sample size?
• Requires fast dataflow – logistically demanding
especially in large multicenter trials
• Does not work for long-term endpoint.
• Difficult to interpret results beyond estimation
 Comparisons?
 Precision?
• Recruitment patterns can change during the
course of the trial because of deduced
knowledge of randomization probabilities
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Adaptive randomization
• Simulations suggest very similar operational
characteristics may be achieved if applying
classical 2-stage designs with stopping rules
 Korn and Freidlin, JCO 2011
 Yuan and Yin, JCO 2011
• Example of such an alternative: CREATE
(EORTC 90101)
 A Simon 2-stage design is being used to assess
the activity of Crizotinib in each of 6 cohorts of
patients (ALK/MET+)
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Conclusion
• The STBSG EORTC is more adaptive
than you may have thought
• There are challenging times ahead, both for
clinicians as well as statisticians
 Flexible design strategies
 More efficient use of resources
• While the sky seems to be the limit, experience
teaches us to be wary and critical of solutions
presented as ‘miracles’.
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Acknowledgment
Stats colleagues at the EORTC, specifically
Laurence Collette
Jan Bogaerts
Murielle Mauer
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