1. Novel Clinical Trial Designs for Oncology
Richard Simon, D.Sc.
Biometric Research Branch
National Cancer Institute

2. BRB Website http://brb.nci.nih.gov
Powerpoint presentations & reprints
BRB-ArrayTools software
Web based sample size planning

3. How can therapeutics development be successful if tumors contain dozens, hundreds or thousands of mutations, with substantial intra-tumor heterogeneity?
How should we modify our paradigms for clinical development in light of tumor genomic heterogeneity?

4. Success Likely Requires
Inhibiting pathways deregulated by early oncogenic mutations
Using combinations of molecularly targeted drugs
Treating early
Before mutational meltdown
Treating the right tumors with the right drugs

5. Co-development of drugs and companion diagnostics increases the complexity of drug development
It does not make drug development simpler, cheaper and quicker
But it may make development more successful and it has great potential value for patients and for the economics of health care

6. Roadmap for Co-Development of New Drugs with Companion Diagnostics
Develop during phase II a completely specified genomic classifier of the patients likely to benefit from a new drug
Single gene/protein or composite gene expression classifier
Develop an analyticly validated assay (reproducibe and robust) for the classifier
Use the completely specified classifier to design and analyze a phase III clinical trial to evaluate effectiveness of the new treatment with a pre-defined analysis plan.

7. Targeted (Enrichment) Design
Restrict entry to the phase III trial based on the binary predictive classifier

8. Develop Predictor of Response to New Drug
Using phase II data, develop predictor of response to new drug
Patient Predicted Responsive
Patient Predicted Non-Responsive
Off Study
New Drug
Control

9. Applicability of Targeted Design
Primarily for settings where the drug effect is specific, the biology of the target is well understood, and an accurate assay is available
Advantage of design is that the target population is clear and trial clearly must be sized for the test+ patients
With a strong biological basis for the test and a drug with potentially serious toxicity, it may be unacceptable to expose test negative patients to the drug
Analytical validation, biological rationale and phase II data provide basis for regulatory approval of the test, if needed

10. Relative efficiency of targeted design depends on
proportion of patients test positive
effectiveness of new drug (compared to control) for test negative patients
When less than half of patients are test positive and the drug has little or no benefit for test negative patients, the targeted design requires dramatically fewer randomized patients

11. Biomarker Stratified Design
Develop Predictor of
Response to New Rx
Predicted Non-responsive to New Rx
Predicted Responsive
To New Rx
Control
New RX

12. Biomarker Stratified Design
Do not use the diagnostic to restrict eligibility, but to structure a prospective analysis plan
Having a prospective analysis plan for how the test will be used in the analysis and having the trial appropriately sized are essential
The purpose of the study is to evaluate the new treatment overall and for the pre-defined subsets

13. R Simon. Using genomics in clinical trial design, Clinical Cancer Research 14:5984-93, 2008

15. Analysis Plan B (Limited confidence in test)
Compare the new drug to the control overall for all patients ignoring the classifier.
If poverall ≤0.03 claim effectiveness for the eligible population as a whole
Otherwise perform a single subset analysis evaluating the new drug in the classifier + patients
If p+ ≤0.02 claim effectiveness for the classifier + patients.

16. Sample size for Analysis Plan B
To have 90% power for detecting uniform 33% reduction in overall hazard at 3% two-sided level requires 297 events (instead of 263 for similar power at 5% level)
If 25% of patients are positive, then when there are 297 total events there will be approximately 75 events in positive patients
75 events provides 75% power for detecting 50% reduction in hazard at 2% two-sided significance level
By delaying evaluation in test positive patients, 80% power is achieved with 84 events and 90% power with 109 events

17. Does the RCT Need to Be Significant Overall for the Treatment Comparison to Justify the Pre-planned Focused Subset Analysis? No
That requirement has been traditionally used to protect against data dredging. It is inappropriate for focused trials of a treatment with a companion test with a pre-planned subset analysis if the analysis plan protects the overall type I error at 5%. .

18. Marker Strategy Design
Randomize
Perform test and employ test determined treatment
Standard of care treatment

19. Marker Strategy Design
Randomize
Perform test and employ test determined rx T C

22. Phase III RCT of new regimen T vs control C
Multiple candidate predictive biomarkers or whole genome expression profiling
Prospectively specified classifier development algorithm

23. Apply the algorithm A to the full dataset to develop a classifier function that provides a prediction of whether the new treatment T is better than the control C for a patient with covariate vector x.
e.g. let h(t;x,z) denote a proportional hazards model fit to the data providing estimate of hazard of failure for patient with covariate vector x receiving treatment z (1 for T, 0 for C)

24. e.g. Classify a patient with covariate vector x as likely to benefit from the new treatment if h(t;x,z=1)/h(t;x,z=0) < 0.8
Evaluate the effectiveness of the classifier by imbedding the classification algorithm A into a K-fold cross-validation

26. Phase II Trials for Molecularly Targeted Drugs
The purpose of phase II trials is to decide what phase III trials to do and how to do them
Phase II trials today need to identify the right predictive biomarker for use in phase III and develop an analytically validated assay for it’s measurement
Larger phase II trials are needed to achieve the new objectives

27. Phase II trials should not serve as the basis for medical practice
except in unusual circumstances which we hope become more frequent
The design and analysis of phase II trials can be less restrictive and more exploratory than for phase III trials

28. Phase II trials can be used to exclude clearly unpromising regimens
Can use “conditional surrogate endpoints”
Effect of treatment on a conditional surrogate is necessary but not sufficient for effect on clinical outcome
Phase II trials can be used to screen for large anti-tumor effects in genomically defined sub-populations

29. Single arm phase II trials are efficient and interpretable for
screening single agents for activity in shrinking tumors
for identifying genomically characterized subsets where anti-tumor activity is maximized

30. Progression Delay
Evaluating progression delay is inherently comparative
Rate of tumor progression untreated is often highly variable
Stable disease definitions are frequently not documented as being interpretable as a drug effect

31. Process and/or flow or approaches for determination of phase II trial design recommendations.
Process and/or flow or approaches for determination of phase II trial design recommendations. PRO, patient related outcomes; PFS, progression-free survival.
Seymour L et al. Clin Cancer Res 2010;16:
©2010 by American Association for Cancer Research

32. Number of total events to observe in two-arm randomized phase II trial comparing progression-free survival 1-sided significance.

33. Seamless phase II/III trials
Randomized between 1 or more new regimens and a control arm
Interim analysis based on phase II endpoint for either selecting among new regimens or terminating accrual for futility
Final analysis based on phase III endpoint using all randomized patients

35. Hypothetical randomized trial showing a multi-arm, two-stage design
Parmar, M. K. B. et al. J. Natl. Cancer Inst : ; doi: /jnci/djn267
Copyright restrictions may apply.

37. Marker Based Phase II Design Pusztai, Anderson, Hess (ClinCancerRes 2007)
Two stage design, treat all comers of a given primary site
If the overall number of responders at the end of stage 1 is adequate, then continue and complete trial based on overall analysis
If the overall number of responders at the end of stage 1 is not adequate, then start separate two stage phase II trials for each marker stratum

39. Concurrent 2-Stage Phase II Designs for K Marker Strata
Can use with time to progression endpoint
Can use with early stopping criteria

40. K Arms (Strata) Optimal Two-Stage Phase II Design for each arm α=0
Null response probability
Desirable response probabiliity
Stop early if >r1 responses in n1 patients
Reject drug if >r responses in n patients
Probability of Correct Selection
Probability of Correct Selection p0 p1
r1/n1
r/n
K=2 arms
K=3 arms
.05
.25
0/6
2/23
0.81
0.80
.10
.30
0/7
3/18
0.86
0.82
.20
.40
2/12
7/25
0.87
0.83
.50
5/15
12/32

41. Bayesian Adaptive Design BATTLE Study in NSCLC
Randomized phase II trial with 4 experimental regimens, no control group
Erlotinib, sorafenib, vandetanib, erlotinib+bexarotene
Tumor biopsy at entry, assayed for candidate predictive biomarkers
EGFR mutation or amplification
KRAS or BRAF mutation
VEGFr2 over-expression
Cyclin D1 over-expression
Endpoint is freedom from progression at 8 weeks

42. Bayesian Adaptive Design BATTLE Study in NSCLC
First 97 patients were randomized equally to the 4 arms
Then, the randomization was weighted based on estimated of effectiveness of each regimen for patients in each biomarker stratum

43. Bayesian Adaptive Design BATTLE Study in NSCLC
As data accumulates, for each treament i and marker stratum k the probability that 8 week disease control is > 0.5 is computed
If that probability becomes <0.10 for some treatment i and stratum k, then use of that treatment in that stratum is suspended

44. Bayesian Adaptive Design BATTLE Study in NSCLC
Results not yet published
Approximately 255 patients randomized
Erlotinib performed best against EGFR mutant tumors
Sorafinib performed best against KRAS mutant tumors
Vandetanib performed best against tumors that over-expressed VEGFr2
Erlotinib+bexarotene performed best against tumors that over-expressed cyclin D1

45. Acknowledgement
Boris Freidlin
Abboubakar Maitournam
Wenyu Jiang