How much can we adapt? An EORTC perspective Saskia Litière EORTC - Biostatistician

I have no conflicts of interest 2

Adaptive designs What? Why? The challenges Examples  Currently part of EORTC portfolio  Currently not (yet) part of EORTC portfolio Take home messages Outline 3

“… 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? 4

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? 5

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 6

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 7 Well-known Less understood

Most of them come down to 8 Learn Confirm One trial Change H 0 ? Change design parameters?

A few examples 9

EORTC in first line treatment of advanced, high grade STS 10 R Doxorubicin + Ifosfamide Interim 1: PFS? Group sequential design Interim 2: OS? Final: OS?

TRUSTS (EORTC 62091) in advanced or metastatic STS 11 R Trabectedin 1.5 mg/m 2 24-h Doxorubicin 75 mg/m 2 Doxo 75 mg/m2 T 3-h or 24-h Select the best PFS Phase IIb 3 x 40 pts Phase III 2 x 110 pts Trabectedin 1.3 mg/m 2 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 12 TRUSTS (EORTC 62091) in advanced or metastatic STS

13 Cytel Webinar for East®SurvAdapt, October 28, sided  5% Power = 90% HR = sided  5% 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 14

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 Randomize using 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 17 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+) 18 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 19

Stats colleagues at the EORTC, specifically Acknowledgment 20 Laurence Collette Jan Bogaerts Murielle Mauer