How much can we adapt?An EORTC perspective

Saskia Litière

EORTC - Biostatistician

I have no conflicts of interest

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Adaptive designs• What?• Why?• The challenges• Examples

Currently part of EORTC portfolio Currently not (yet) part of EORTC portfolio

• Take home messages

Outline

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“… 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. “

What is an adaptive design?

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• 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

Why use adaptive designs?

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• 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!

The challenges

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• 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…

To name but a few …

Several possible approaches

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Well-known

Less understood

Most of them come down to

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Learn Confirm

One trial

Change H0? Change design parameters?

A few examples

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EORTC 62012 in first line treatment of advanced, high grade STS

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R

Doxorubicin

Doxorubicin + Ifosfamide In

terim

1: P

FS?

Group sequential design

Inte

rim 2

: OS?

Fina

l: O

S?

TRUSTS (EORTC 62091) in advanced or metastatic STS

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R

Trabectedin 1.5 mg/m2 24-h

Doxorubicin 75 mg/m2

Doxo 75 mg/m2

T 3-h or 24-h

Sele

ct th

e be

stPF

S

Phase IIb3 x 40 pts

Phase III2 x 110 pts

Trabectedin 1.3 mg/m2 3-h

PFS?

Seamless phase II/III design

– 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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TRUSTS (EORTC 62091) in advanced or metastatic STS

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Cytel Webinar for East®SurvAdapt, October 28, 2010

2-sided = a5%Power = 90%HR = 0.7

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!

Sample size re-estimation

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Battle Trial – Adaptive randomization

Lee et al.Zhou et al. CT 2008

Prior probability of

each treatment

success given marker

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

Battle Trial – Adaptive randomization

Randomizeusing the weights given by prior prob

• 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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Adaptive randomization

• 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’.

Conclusion

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Stats colleagues at the EORTC, specifically

Acknowledgment

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Laurence Collette Jan Bogaerts Murielle Mauer