1. Changing the paradigm of dose-finding designs
in cancer trials in the UK:
Experiences and lessons learnt from the practical implementation of model-based designs
Dr Christina Yap
Cancer Research UK Clinical Trials Unit
University of Birmingham
Joint ICTMC/SCT 10th May 2017 1

2. Outline Why a change is needed?
Development of Tailored Model-Based Designs
Practical Implementation
Expected and Unexpected Benefits
National Initiatives
From 2012…… 2

3. Rationale of Phase I trials
Trials are typically small (20 – 40 patients)
Three Ethical Criteria
Do not want to undertreat
Do not want to overtreat
Use as few patients as possible (efficiency)
Aim: To obtain the Recommended Phase II dose, RP2D
Monotonic Assumption:
↑ dose  ↑ chance of toxicity and ↑ chance of activity
If assumption is true,
RP2D = Maximum Tolerated Dose (MTD), highest possible dose with an acceptable risk of dose-limiting toxicity (DLT) 3

4. Why a change is needed? 3+3 designs Simple Familiar
Relatively safe (?)
BUT
Inflexible
Inefficient
Unethical
Dose 3
1/3
2/3
Dose 2
0/3
Dose 1
Cohort 1
Cohort 2
Cohort 3
Cohort 4
Cohort 5
Cohort 6

5. Why a change is needed? x x Planned 1 2 3 4 5 6 7 8 9 Time #DLT? #DLT?10 11
Time
#DLT?
#DLT?
What might actually happen

6. Model-Based Designs

7. Continual Reassessment Method (CRM)
Review of 1,235 phase I trials published :
only 1.6% used model-based approaches (Rogatko et al, 2007)
Increasing to only 6.4% by (van Brummelen et al, 2016)
656
Model-based approaches have been neglected since their introduction in the 1990s. They were used in 1.6% of phase I trials published (Rogatko et al, 2007), increasing to only 6.4% by (van Brummelen et al, 2016).
In recent years, investigators/funders show interest for more innovative, adaptive designs. 7

8. Matchpoint (CML): EffTox Wisteria (Head and Neck): Tite-CRM
Featured Trials
Viola (AML): CRM
Matchpoint (CML): EffTox
Wisteria (Head and Neck): Tite-CRM

9. Rule-based Designs Model-based Designs? Clinical Parameters
DLT definition and assessment period
Set of doses
Start dose
Fixed or variable sample size
Target (acceptable) level of DLT
Cohort Size
Clinical Parameters
Model for dose-toxicity curve
Initial guesses of DLT rates
1-stage or 2-stage designs
Estimation approach (Bayesian/Frequentist)
If Bayesian, for a one-parameter model, assume prior distribution of slope parameter
Model Specification Parameters
Skipping of untried doses in escalation or de-escalation? (Yes/No)
Early rules to stop the trial early if
Strong evidence that the lowest dose is too toxic
Strong evidence that the MTD is reached
Practical Considerations
Rule-based Designs
Model-based Designs?

10. Model Specification Parameters
DLT definition and assessment period
Set of doses
Start dose
Fixed or variable sample size
Target (acceptable) level of DLT
Cohort Size
Clinical Parameters
Model for dose-toxicity curve
Initial guesses of DLT rates
1-stage or 2-stage designs
Estimation approach (Bayesian/Frequentist)
For a one-parameter Bayesian model, assume prior distribution of slope parameter
Model Specification Parameters
Skipping of untried doses in escalation or de-escalation? (Yes/No)
Early rules to stop the trial early if
Strong evidence that the lowest dose is too toxic
Strong evidence that the MTD is reached
Practical Considerations

11. Trial Conduct of a model-based approach
Screen Patients
Recruit eligible patients at recommended dose
AE data is collected
Monitors’ visit to sites (Quality Control)
Statistician updates model and produces recommended dose
Safety Committee meeting
- review AE data &
- consider model’s dose choice & recommend next dose
e.g. CRM
636
For each dose update decision 11

12. Continual Reassessment Method (CRM)
Identify dose with target DLT rate e.g. 20%
Assumes a particular shape for dose-toxicity curve
Repeated analysis of all data (DLT outcomes at all tested doses) gathered to date
Estimates probability of DLT at each dose (Bayesian/Frequentist)
Treat next patient/cohort at dose with estimated DLT closest to target level, based on all accumulated data
639 12

13. Phase I Acute Myeloid Leukaemia (AML) Trial
Viola:
Phase I Acute Myeloid Leukaemia (AML) Trial
CI: Charlie Craddock
Patient Population:
Patients with AML who relapse after Allogeneic Stem Cell Transplantation
Primary Objective:
Maximum Tolerated Dose (MTD) of combined Lenalidomide and Azacitidine with a target Dose Limiting Toxicity (DLT) probability of 20%
7 dose levels of LEN (Azacitidine fixed)
Sample size: 27 (with possible extension of 3 patients)
Cohort size: 3
Trial Design: Modified CRM
3+3 Design? 13

14. Trial design: EffTox; joint evaluation of efficacy and toxicity
Aim
To determine the most desirable dose of ponatinib in combination with FLAG-IDA that is both tolerable and shows sufficient efficacy
Co-Primary outcomes
Tolerability of the combined treatment defined in terms of dose limiting toxicities (DLT)
Efficacy measured as Complete Cytogenetic Response or Haematological Response
Sample size:
30 patients
No. of doses: 4
Trial design: EffTox; joint evaluation of efficacy
and toxicity
(CI: Mhairi Copland)
643
Dose Level

15. What if ….?
Treatment might give late onset toxicities, e.g. radiotherapy, some molecular targeted agents
DLT observation period might have to be longer
Extended trial suspensions
Long trial duration 1 2 3 4 5 6 7 8 9
Time
#DLT?
#DLT?

16. Extension of CRM: Time-to-event CRM
(Cheung 2000, 2011)
CI: Hisham Mehanna
A dose-finding trial of a Wee-1 inhibitor in combination with chemo-radiotherapy in Head and Neck cancer using time-to-event CRM -

17. Head & Neck Cancer Trial
Patient Population:
High-risk Head and Neck cancer patients after surgery
Background:
Standard care: post-operative chemo-radiotherapy
Improves cure rates but treatment failure rate is 30-40% over 3 years
Treatment related toxicity rate (≥ Grade 3) is expected to be 15%-25% with chemo-radiotherapy
Wee-1 inhibitor is well-tolerated in monotherapy
Strong pre-clinical rationale that Wee-1 inhibitor will enhance chemo-radiation and hence improve local control and survival
Primary Objective:
Maximum Tolerated Dose (MTD) with a target Dose Limiting Toxicity (DLT) probability of 30%
0756 17

18. Design Considerations
Clinical Parameters
4 dose levels of Wee-1 inhibitor (in combination with chemo-radiation at fixed doses)
Target toxicity probability for MTD: 30%
Sample size: up to 21 patients
Cohort size: 3
Dose Level
Initial Guess of DLT -1
12%
0 (Starting Dose)
20% 1
30% 2
40%
Prior MTD 18

19. Clinical Parameters cont.
Treatment Duration: 6 weeks
Two DLT assessment periods: 12 weeks (final); 8 weeks (initial)
POCRT to start within 42 days of surgery
Week 1-2
RT Cisplatin,
Wee-1
Week 3
RT Cisplatin
Week 4-5
RT Cisplatin
Wee-1
Week 6
RT Cisplatin
Week 8
Initial DLT Assessment
Week 12
Final DLT Assessment
Radiotherapy is known to cause delayed toxicities
(2)
(3) Because of the heterogeneous population, we would want to ensure it is safe at a new dose before escalation. Inevaluable patients have to be replaced 19

20. Empiric Model, 𝑭 𝒙,𝜷 = 𝒙 𝐞𝐱𝐩⁡(𝜷)
Model Specification
Model Specification
Dose Toxicity Curve, DTC:
Empiric Model, 𝑭 𝒙,𝜷 = 𝒙 𝐞𝐱𝐩⁡(𝜷)
Estimation Approach: Bayesian (Two-Stage)
Normal Prior for 𝛽 with mean 0 and variance of 0.75 20

21. Trial Specific Considerations
Avoid skipping of untried doses in escalation
Requires 3 evaluable patients at a new dose before escalation
Funding restriction: Trial duration ≤ 2 years
Maximum sample size: 21 patients
Practical considerations:
Monitoring visit before confirmation of DLT (0/1)
Frequent updating more resource intensive!
Stop early once sufficient evidence that MTD is reached? No 21

22. Using a CRM
If there is no DLT, how would a CRM with cohorts of 3 work?
Recruitment rate: 3 patients/month
12 wks
12 wks
Can we consider a more time-efficient design, but still maintain safety and accuracy?
TITE-CRM?
> 2 years 22

23. Implementation of TITE-CRM
Trial Design: Modified Two-stage Bayesian TITE-CRM
First Stage
An initial dose escalation scheme – cohorts of 3
A waiting window = 8 weeks, minimum length of waiting time between cohorts before an escalation can take place
If no DLT is experienced within the waiting window, we will escalate to next higher dose and this follows for the next cohort and so on
Second stage commences once a DLT is experienced 23

24. Implementation of TITE-CRM cont.
Second Stage
Once a DLT is observed, the second stage of the TITE-CRM design commences and subsequent doses will be obtained via the model which using fully evaluated patients + partially followed-up patients
Original TITE-CRM proposal (Cheung 2000, 2011): Continual recruitment of patients without further suspension 24

25. Trial Specific Modifications
Cohort size = 3 for 2nd stage (logistical)
Stop early for safety:
if P(DLT rate at lowest dose>target+10%|data)>0.65
Allow a waiting period of 8 weeks for initial cohort at each new dose (ensure safety)
Flexibility of waiting period as more data accumulate
Software:
Modification of source codes in dfcrm package in R (Cheung 2015)
Build all the above considerations into the simulations
 How often you update will affect design’s performance 25

26. Expected and Unexpected Benefits
Higher statistical efficiency
Flexibility
Unexpected
Dose error
Delayed outcomes
Incomplete cohorts due to drop-outs
Refinement of outcome measures
Refinement of cohort size
Advantages of Model-based designs are even more pronounced in those settings 26

27. Comments (1) Phase I trials are very resource intensive; operationally
Main limitation of dose-finding is the sample size and the endpoint
The model is used to aid decision making at each dose decision meeting.
Part of an integrated approach where other important factors are taken into account.
Close interaction with clinical investigators and trial managers to produce a bespoke, acceptable design tailored to the needs of the trial is crucial as well as its operation.
Consider how the design is going to be implemented in practice and build that into the simulations

28. Comments (2)
Model-based designs are very flexible (and efficient) and can be easily adapted to suit the specific needs of a trial.
The “optimal” adaptive design might not necessary be one with the best statistical properties
Due to the rigidity of the 3+3 design, extensions to cope with increasingly complex dose-finding trials are often limited or impossible.
It is key to be able to make complex models easy to understand and easy to implement.
“Practical clinical trial designs lie somewhere between the two extremes of oversimplification and unrealistic elaboration” (Yuan, Nguyen and Thall, 2016)
Substantial increase in statistical resources and costs
Funders & Regulatory bodies

29. National Initiatives
MRC Adaptive Designs Working Group of the MRC Network of Hubs for Trials Methodology Research
A quick guide why not to use A+B Designs. _quick_guide_why_not_to_use_AB_designs.pdf (2016)
Featured in Experimental Cancer Medicine Centres (ECMC) ECMC Connect newsletter (June 2016)
Outreach Programme
NIHR Early Phase Group
Collaboration of early phase statisticians and clinicians in academia and pharma
Paper 1: Embracing model-based designs for dose-finding trials (Love et al, in press in British Journal of Cancer)
Paper 2: CRM tutorial paper

30. Changing Landscape

31. Acknowledgements
Statisticians Lucinda Billingham, Kristian Brock, Daniel Slade, Samuel Munoz Vicente, Amanda Kirkham Special thanks: John O’Quigley and Ken Cheung Trials Team Bloodwise Trials Acceleration Programme (led by Shamyla Siddique) CRCTU Early Phase Drug Development Team (led by Laura Llewellyn) Clinicians Charlie Craddock, Hisham Mehanna, Graham Collins, Neil Steven, Mhairi Copland, Mark Drummond Trial Management Groups of all trials mentioned Funders: CRUK and Bloodwise

32. 
Thank You!
A Good Start is Vital ! 32