Loading in 2 Seconds...
Loading in 2 Seconds...
Review Experience in Evaluating Predictive Biomarkers – Design and Analysis Considerations. Yuan-Li Shen, Dr. P.H. U.S. Food and Drug Administration Center for Drug Evaluation and Research Office of Biostatistics. Acknowledgement. Somesh Chattopadhyay Kun He Rajeshwari Sridhara
Yuan-Li Shen, Dr. P.H.
U.S. Food and Drug Administration
Center for Drug Evaluation and Research
Office of Biostatistics
The views expressed in this talk are those of the author, not of the FDA
- Example of HER-2 for MBC (metastatic breast cancer)
- Example of EGFR for NSCLC (non-small cell lung cancer)
- Example of K-ras for mCRC (metastatic colorectal cancer)
e.g. Hormonal therapy in ER/PR positive breast cancer women;
e.g. Herceptin for HER2+ metastatic breast cancer; Note: HER2–amplified
in 25–30% of all breast cancer patients (Cobleigh et al, 1999)
e.g.Gleevec for KIT+ Gastrointestinal Stromal Tumor (GIST);
e.g. products underdevelopment: BRAF inhibition in melanoma; ALK
inhibition in NSCLC
e.g. K-Ras WT for metastatic colorectal cancer (mCRC)
e.g. EGFR for non-small cell lung cancer (NSCLC) (???)
e.g. EGFR in squamous cell head and neck cancer.
Note: EGFR is overexpressed in 80% of squamous cell carcinoma
(Kumar, et al,2003)
(e.g. relationship between biomarker and treatment; treatment effectiveness)
Requires smaller sample size (relative to all comers design), however…..
DFS results in Herceptin for adjuvant breast cancer trial by HER2 overexpression or amplification
Reference: Herceptin package insert
Potential Analysis Plan:
Issues: May not have enough power for interaction and failure to show interaction does not mean no differential subgroup effect
Issues: more complicated when interim analyses for efficacy and futility will be performed and more endpoints (e.g. PFS, OS) will be involved.
Issues: Overall treatment effect may be driven by one of the Biomarker subgroup; when to perform the event driven analysis
-- Futility analysis
-- Combining Phase II and III data
-- Adaptive signature design :
Stage 1 data will be used to define a biomarker “sensitive” subgroup and the rule will be applied to stage 2 to select a biomarker sensitive subgroup; Analysis will be performed to evaluate treatment effect in overall population and biomarker subgroup selected at stage 2
e.g. HER2+ in Lapatinib+Letrozole trial (studied in all comers;
change analysis population to HER2+; not stratified by HER2 status);
• Working Definition : In completed or post-interim-analysis trial where genomic samples were collected prior to treatment initiation, whether or not full ascertainment, the genomic hypothesis is ‘prospectively specified’ prior to diagnostic assay testing. However, the clinical outcome data without genomic information have already been (partially) collected, unblinded, and analyzed. The genomic data analysis might be arguably ‘prospectively performed, which is a retrospective analysis.
* Wang et al (2006 TPJ) ; Wang, et. al. (2010, Clinical Trials)
Criteria for Consideration
O’Neill, Dec. 2008 ODAC
and should not be used to salvage a failed trial
Issues: type I error, if the primary endpoint from the ITT population is not significant; possible selection bias; imbalance between treatment arms.
and distribution of the baseline characteristics
Phase II dose/biomarker screening
Biomarkers: ER (+,-), PR(+,-), HER2 (IHC/FISH, gene expression, protein microarray), MammaPrint score (higher MP2, other MP1)
– comparative analysis not interpretable
K-ras in EGFR inhibitor for mCRC
e.g. EPIC, OPUS and PACCE
Multicenter, International, Randomized, Double-blind, Placebo-controlled, Phase III – maintenance therapy after platinum-based doublet chemotherapy in patients with advanced or recurrent or metastatic NSCLC
Patients who had CR, PR or SD were randomized to receive Tarceva or placebo using adaptive randomization method (Pocock and Simon, 1975) based on the following stratification factors :
EGFR protein expression, stage of disease, ECOG performance status, chemotherapy regimen, smoking status and region.
Tarceva (Erlotinib) : EGFR tyrosine kinase inhibitor (TKI)
Co-primary hypothesis : PFS in all randomized patients
PFS in EGFR IHC positive subset
Alpha – allocation : 0.03 for PFS in all randomized patients;
0.02 for PFS in EGFR IHC positive subset
Note: Protocol implemented a hierarchy of biomarker ascertainment
-- Change primary population (from ITT to HER2+)
(after 760 patients were randomized)
-- Hierarchical testing
10 : PFS in HER2+
20 : PFS in ITT
10 objective : PFS in HER2+
20 objective : PFS in ITT
HER2 : FISH + or IHC : 3+
Study EGF 3008: Kaplan-Meier Estimate of Investigator-Evaluated PFS
(1) The primary efficacy population was changed from ITT to HER2-positive after 760 patients were randomized, and sample size was increased to 1286 to have adequate HER2-positive patients;
(2) Study was not stratified at randomization by HER2 status;
(3) Demonstration of OS benefit has generally been the standard for consideration of regular approval in first-line setting of breast cancer.
Currently, the OS benefit of Lapatinib has not been demonstrated.
Note: Lapatinib was approved under accelerated approval.
-- if there is no clear biological evidence of the
biomarker subgroup and diagnostic tool can
reliably identify the biomarker subgroup,
biomarker stratified design may be preferred.
in the Setting of Neoadjuvant Chemotherapy; Clinical pharmacology & Therapeutics, vol. 86, No. 1, July 2009
3. B. Johnson and P. Ja¨nne, Selecting Patients for Epidermal Growth Factor Receptor Inhibitor Treatment: A FISH Story or a Tale of Mutations? J. of Clin. Oncology, Vol. 23, No. 28, 2005, 6813-6816
4. V. Kumar, RS Cotran, SL Robbins, et. al, editors: Robbins Basic Pathology. Seventh edition. Saunders,
7. S. J. Mandrekar and D. J. Sargent; Predictive biomarker validation in practice: lessons from real trials; Clinical Trials 2010; 7: 567–573
8. V. Cutsem, I. Lang, et. al., KRAS status and efficacy in the first-line treatment of patients with metastatic colorectal cancer (mCRC) treated with FOLFIRI with or without cetuximab: The CRYSTAL experience., J. Clin Oncol 26, No. 15S (May 20 Supplement), 2008:2
9. R. Simon, S. Wang, Use of genomic signatures in therapeutics development in oncology and other diseases, The Pharmacogenomics Journal 2006; 6, 166–173
10. R. Simon, The use of Genomics in Clinical Trial Design, Clin. Cancer Res., 2008; 14(19), 2008, 5984-5993.
11. R. Simon, S. Paik, D. Hayes, Use of Archived Specimens in Evaluation of Prognostic and Predictive Biomarkers, Commentaries, J. of National Cancer Ins., V. 101, Issue 21, 2009,1446-1452
12. S. Wang, R. O’Neill and H. M. J.Hung, Approaches to evaluation of treatment effect in randomized clinical trials with
genomic subsets, Pharmaceut. Statist. 2007; 6: 227–244
13. S. Wang, R. O’Neill, J. Hung, Statistical considerations in evaluating pharmacogenomics-based clinical effect for confirmatory trials, Clinical Trials 2010; 7: 525–536
14. K-Ras Briefing document from Oncologic Drugs Advisory Committee, 12/16/08: http://www.fda.gov/ohrms/dockets/ac/cder08.html#OncologicDrugs
15. Tarceva Briefing document from Oncologic Drugs Advisory Committee, 12/16/09:http://www.fda.gov/AdvisoryCommittees/CommitteesMeetingMaterials/Drugs/OncologicDrugsAdvisoryCommittee/ucm126185.htm
16. Gleevec labeling: http://www.gleevec.com/prescriptioninformation.jsp?site=PU027801&source=01030&irmasrc=GLIWB0082
17. Herceptin labeling:
18. Lapatinib labeling:
19. G. Amado, M. Wolf, et.al., Wild-Type KRAS Is Required for Panitumumab Efficacy in patients With Metastatic Colorectal Cancer, J. of Clin. Oncology, Vol. 26, No. 10, 2008, 1626-1634
20. A. S. Crystal, and A. T. Shaw, New Targets in Advanced NSCLC: EML4-ALK, Clinical Advances in Hematology & Oncology Volume 9, Issue 3, 2011, 207-214
21. A. Vultur, J. Villanueva and M. Herln, Targeting BRAF in Advanced Melanoma: A First Step toward Manageable Disease Clin Cancer Res April 1, 2011 17:1658