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How much can we adapt? An EORTC perspective. Saskia Litière EORTC - Biostatistician. I have no conflicts of interest. 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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how much can we adapt an eortc perspective

How much can we adapt?An EORTC perspective


EORTC - Biostatistician


Adaptive designs

  • What?
  • Why?
  • The challenges
  • Examples
    • Currently part of EORTC portfolio
    • Currently not (yet) part of EORTC portfolio
  • Take home messages
what is an adaptive design
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. “

why use adaptive designs
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
the challenges
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!

several possible approaches
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…

To name but a few …

Less understood

most of them come down to
Most of them come down to

One trial

Change H0?

Change design parameters?

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

Interim 1: PFS?

Interim 2: OS?

Final: OS?



Group sequential design


+ Ifosfamide

trusts eortc 62091 in advanced or metastatic sts
TRUSTS (EORTC 62091) in advanced or metastatic STS

Phase IIb

3 x 40 pts

Phase III

2 x 110 pts

Doxorubicin 75 mg/m2




Doxo 75 mg/m2


Trabectedin 1.3 mg/m2 3-h

T 3-h or 24-h

Trabectedin 1.5 mg/m2 24-h

Seamless phase II/III design

trusts eortc 62091 in advanced or metastatic sts1
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
  • Complexdesign: 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
sample size re estimation
Sample size re-estimation

2-sided a = 5%

Power = 90%

HR = 0.7

Cytel Webinar for East®SurvAdapt,

October 28, 2010

sample size re estimation1
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!

battle trial adaptive randomization
Battle Trial – Adaptive randomization

Lee et al.

Zhou et al. CT 2008

battle trial adaptive randomization1
Battle Trial – Adaptive randomization

Probabilities of treatment success updated based on observed results

Prior probability of each treatment success given marker

Randomizeusing the weights given by prior prob

8-week outcome observed

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
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+)
  • 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’.

Stats colleagues at the EORTC, specifically

Laurence Collette

Jan Bogaerts

Murielle Mauer