D5 efficacy endpoints in oncology

Geneva Branch
EFFICACY ENDPOINTS IN ONCOLOGY
– IS01
Bruxelles 13-16/10/2013
Angelo Tinazzi
Cytel Inc., Wilmington Del. USA
Succursale de Meyrin – Geneva – Switzerland
angelo.tinazzi@cytel.com

Geneva Branch
Cytel Inc. - Confidential 2
Efficacy Endpoints in Oncology
Disclaimer
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
The information contained in this
presentation is based on personal
research of the author and does not
necessarily represent Cytel Inc..

Geneva Branch
Introduction
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
Oncology Endpoints in Drug Development
Early Phase
Safety and Evidence of Drug Activity
Identification of possible indications
Late Phase
Seeks for Clinical Benefit

Geneva Branch
Introduction
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
Key Requirements for Drugs Approval
Demonstration of efficacy with acceptable safety in
adeguate and well-controlled studies
Benefits/Risks asssessment
 Longer Life
 Better Life (Quality)
 Safety
 Cost
“Clinical Trials Enpoints for the Approval of Cancer Drugs and Biologics”
Guidance for Industry, FDA, May 2007

Geneva Branch
Overall Survival (OS)
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
Definition Time from randomization until death
from any cause
Pros • Measure of direct benefit
• Easy to measure (Unbiased)
Cons • It may require large population and follow-up
• It includes deaths unrelated to cancer
• It may be affected by crossover or subsequent
therapies
Censor • Last date subjects was seen alive
The «Gold» standard for demonstrating clinical benefit

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
History of (FDA) Drugs Approval
‘70: Objective (tumor) Response Rate (ORR)
‘80: More evidence of clinical benefit:
Survival, QoL, Physical functioning, Tumor-
related symptoms
’90: use of Surrogate endpoints predicting
clinical benefits
1992: FDA adopted accelerated drug approval
J. McCain, "The Ongoing Evolution of Endpoints in Oncology," 2010.

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
A surrogate endpoint is an alternative endpoint that if validated
allows inference on the effect of an intervention on a true
endpoint often requiring a shorten observaion period
Surrogate ‘efficacy’ endpoints in oncology aim to replace OS,
the endpoint to ‘predict’
Primary endpoints in randomized controlled
trials of treatments for advanced breast
cancer 2000-2007)
Endpoints used for
basis of oncology drug
approvals
(FDA 1990–2002)

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
The concept of Tumor Response and Progression in Solid Tumors
Standard set of Criteria (RECIST)
 Identification and Classification of Tumor Lesions
 Measurable (Target) vs Non Measurable (Non-Target)
 Periodicity (e.g. CT-Scan every 6 or 8 weeks)
 Response evaluated vs Baseline (baseline assessment prior
to study entry)
 A 30% decrease in the sum of all lesions measurement (mm)
 Progression evaluated vs Nadir (best response prior to current
assessment)
 A 20% increase in the sum of all lesions’ measurements (mm)
 An increase / prgression of any non-target lesion or new lesion identified
after study entry determines also the progression

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
Standard set of Criteria (RECIST) - Cont
 5 Overall Response Criteria
 CR – Complete Response
 PR – Partial Response
 SD – Stable Response
 PD – Progressive Disease
 NE – Not Evaluable
 Best Overall Response as the best response (criteria) assessed since the
subject is on-study (on-treatment)
• P Therasse et al, "New response evaluation criteria in solid tumors: Revised RECIST
guideline (version 1.1)," European Journal of Clinical Oncology, pp. 45: 228-247, 2009.
• MB Mayakuntla, PM Nidamathy, "RECIST and programming challenges," in IASCT, 2012.
• Ji Yu, P Slagle, "Objective tumor response and RECIST criteria in cancer clinical trials," in
MWSUG, 2011.

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
EUROPEAN JOURNAL OF CANCER 45 ( 2009 ) 228 –247
Lesion Baseline Timepoint 1 Timepoint 2 Timepoint 3 Timepoint 4
T1 (mm) 10 10 5 7 10
T2 (mm) 25 15 5 5 5
T3 (mm) 15 15 15 15 20
(Sum of Lesion mm) 50 40 25 27 35
(Response Target Lesions) SD PR PR PD
NT1 NA Stable Stable Stable Stable
New Lesion NA No No No No
PRSD PR PDPRSD PD

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
The concept of Progression and Response
PD
PR
PR
SD
Decrease with
respect to baseline...
…but also increase
with respect to prior
reduction showing
the «re-growth» of
the tumor and
therefore the
possible failure of
the treatment

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
The concept of Progression and Response
PD
PR
PR
SD
data respT;
set SOLD;
by USUBJID VISITNUM;
retain NADIR BASE;
if first.USUBJID then do;
NADIR=.;
BASE=SOLDMM;
end;
PCTBASE=((SOLDMM-BASE)/BASE)*100;
PCTNADIR=((SOLDMM-NADIR)/NADIR)*100;
if SOLDMM=0 then NTRESP=‘CR’;
else if PCTNADIR>20 then NTRESP=‘PD’;
else if abs(PCTBASE)>30 then NTRESP=‘PR’;
else SOLDMM ne . Then NTRESP=‘SD’;
else NTRESP=‘NE’;
output;
NADIR=min(NADIR,SOLDMM);
run;
Timepoint SOL
DMM
BA
SE
PCTB
ASE
NA
DIR
PCTN
ADIR
NTRE
SPT
Baseline 50
Timepoint 1 40 50 -20 50 -20 SD
Timepoint 2 25 50 -50 40 -37.5 PR
Timepoint 3 27 50 -46 25 8 PR
Timepoint 4 35 50 -30 25 40 PD

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
Definition Time from randomization until radiolagical
tumor progression
Pros • Requires smaller sample size
• Not affected by crossover or subsequent
therapies
• Based on objective and quantitative assessment
Cons • Measurement may be subject to bias
• Requires frequent radiologic assessment (e.g.
every 6 weeks) and same or similar among
treatment arms
• In some settings can be difficult to validate
Censor • Last date radiological tumor assessment
Time to Tumor Progression (TTP)

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
Progression Free Survival (PFS)
A variant of TTP where deaths are also counted as events
In some protocols Death as event can be limited if occurred
within ‘xx’ weeks from last tumor assessment (e.g. 12 weeks)
Applicable to study with patients with advanced cancer
Disease Free Survival (DFS)
Same as PFS but it assumes patients are disease-free
at study entry
Applicable to study testing adjuvant therapies with
patients where the disease (cancer) was previously
surgically removed

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
Time to Treatment Failure (TTF)
Time from randomization to discontinuation of
treatment for any reason
TTF not reccomended as regulatory endpoint for
approval; «a regulatory endpoint should clearly
distinguish the efficacy of the drug from toxicity,
patient or physichian withdrwal or patient intolerance»

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
Definition Proportion of patients with tumor size reduction
of a predefined amount and for a minumim time
period. FDA has defined ORR as the sum of
Complete and Partial Responses
Pros • Can be assessed in single-arm studies
• Can be assessed earlier and in smaller studies
• Effect attributable to drug, not natural history
Cons • Not a direct measure of benefit
• Only a subset of patients who benefit
Objective Response Rate (ORR)
Response Duration (DR)
Time from first assessment of CR or PR until date of
progression or last tumor assessment
Applicable only to patients with ORR

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
Efficacy Endpoint – Example 1
Responder
Progressing
RAN SD SD PR CR PD
Response Duration
ORR
OS
PFS TTP
Death /
Alive

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
Efficacy Endpoint – Example 2
Non Responder
Non Progressed
Death
RAN SD SD SD Off TRT
OS
TTP
Death
PFS
TTF

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
Sensitivity Analysis in Tumor Response based endpoint
Use of Per Protocol Population
Include clinical progressions
Different Censoring/Event Date Methods
 Backdating event date when tumor assessment is not performed within the
pre-defined interval
 Censoring at the date of subsequent cancer therapy if occurred before
progression
Use of Independent Review of Tumor Endpoints
 Can minimize bias in readiographic interpretation of the radiological
findings (investigator)
 Often Primary endpoints in non-blinded studies

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
Modified Response / PFS Criteria
e.g. Prostate Cancer according PCWG2 criteria
Where disease progression is defined as the presence of at
least one of the following conditions:
Bone Lesions Progression
Soft-Tissue Lesions Progression (RECIST)
Presence of Skeletal Events
HI Scher, "End Points and Outcomes in Castration-Resistant Prostate Cancer: From Clinical
Trials to Clinical Practice," J Clin Oncol, 2011.

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
Other endpoints: Time to symptom progression (TTSP)
e.g. TTSP in Lung Cancer Trials as per the Lung Cancer
Symptom Scale (LCSS)
Symptomatic progression defined as an increase
(worsening) of the average symptomatic burden index
(ASBI, i.e., the mean of the six major lung cancer
specific symptom scores [fatigue, pain, dyspnoea,
cough, anorexia and hemoptysis])
The worsening is defined as an at least 10% increase
of the scale breadth (i.e., at least 10 mm increase on
the 100 mm scale) from the baseline score.
Hollen PJ, Gralla RJ, Kris MG, et al. Quality of life assessment in individuals
with lung cancer: Testing the lung cancer symptom scale (LCSS). Eur J Cancer.
1993;29A(1):51-8..

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
Quality of Life
Only used in support of primary endpoints
Several ‘validated’ questionnaires available for
different indications
http://groups.eortc.be/qol/eortc-modules

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
Duration of Complete Response in Leukemia
Considered established endpoint of clinical benefit in leukemia
Less infection
Less Bleeding
Less use of blood product support (e.g. transfusion)
D Cheson et al, "Revised Recommendations of the International Working Group for Diagnosis,
Standardization of Response Criteria, Treatment Outcomes, and Reporting Standards for Therapeutic Trials in
Acute Myeloid Leukemia," Journal of Clinical Oncology, pp. Vol 21, No 24: pp 4642-4649, 2003

Geneva Branch
Surrogate Endpoints
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions

Geneva Branch
Regulatory Requirements
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
FDA Clinical Trial Endpoints for the Approval of Cancer
Drugs and Biologics (2007)
General regulatory requirements for efficacy
Detailed description of endpoints and how these can
be used in various clinical settings
 Pros and Cons
 Protocol and SAP design requirements
 Data Collection for Tumor Measurement
 Issue to consider in PFS analysis
 Progression and Censore Date
 How to handle Missing Data
 Lesions evaluation
 Sensitivity Analysis
++ Clinical Trial Endpoints for the Approval of Non-Small Cell Lung Cancer Cancer Drugs and
Biologics, FDA, 2011
Cancer Drug Approval Endpoints
http://www.fda.gov/Drugs/DevelopmentApprovalProcess/DevelopmentResources/CancerDrugs/ucm094586.htm

Geneva Branch
Regulatory Requirements
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
EMA Guideline on the evaluation of anticancer medical
products in man
Guidance on all stages of clinical drug development for
the treatment of malignancies
The current version of the guidance cover also non-
cytotoxic compounds and additional indication for
exploratory studies.
Completed by a set of specific appendices covering
methodologial aspects related
 Methodological Consideration for using Progression Free Survival
(PFS) and Disease Free Survival (DFS) in confirmatory trials
 Confirmatory Studies in Haematological Malignancies
 Condition specific Guidance such as NSCLC, Prostate
The EMA is also planning to provide an additional
appendix for Quality of Life/Patient Reported Outcome.

Geneva Branch
Data Management Issues
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions
Tumor Response
Missing Assessments
Consistent Lesions Reporting
 Type, Site
Assessment of method used
Disappeared Tumor Lesions (0mm)
Consisteny between lesions details (sum of diamaters
for target lesions) and overall response
Independent Review Committee
Keep follow-up up-to-date
CDISC SDTM 3.1.3 Tumor Response Domains
++ • Overcoming Difficulties in Implementing RECIST criteria, PhUSE 2013, G. Ruhnke
• CDISC Journey on Solid Tumor Studies using RECIST 1.1., PhUSE 2013, K. Lee

Geneva Branch
ORR Analysis with proportion and %CI
Analysis
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions

Geneva Branch
Survival Analysis
Unadjusted (Kaplan Meier & Log-Rank Test)
 SAS Proc LIFETEST
Adjusted (Cox proportional hazards regression model)
 SAS Proc PHREG
 Selection of covariates to be used depends on the indication and
treatment setting. E.g. type and/or response to prior therapy
 Examples of other possible covariates
Analysis
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions

Geneva Branch
Survival Analysis
Analysis
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions

Geneva Branch
Subgroup Analysis with Forest Plot
Analyisis
Bursac, Z, "Creating Forest Plots from Pre-computed Data using PROC SGPLOT and Graph Template Language,“
In SAS Global Forum, 2010
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions

Geneva Branch
Analyisis
Tumor Shrinkage with Waterfall Plot
NJ Pandya, "Waterfall Charts in Oncology Trials - Ride the Wave,"
In PharmaSUG, 2012
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Data Management
Analysis
Conclusions

Geneva Branch
Conclusions
Introduction
Overall Survival
Surrogate Endpoints
Regulatory Req.
Analysis
Data Management
Conclusions
Despite its complexity, “stable” standards exist for
efficacy evaluation
Use of efficacy indicators may be different from an
indication to another
Managing, deriving and analyzing efficacy endpoints
in oncology requires a clear understanding of the
disease
The use of efficacy endpoints in drug approval may
change again with the idea of targetting the therapies
based on molecular profiling

Geneva Branch
New Geneva offices – November 2012
Questions

D5 efficacy endpoints in oncology

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