Download Statistical Challenges in the Validation of Surrogate Endpoints

Surrogate Markers and its role in the
Drug Development Process
Aloka G. Chakravarty, Ph.D.
Director,
Biologics Therapeutics Statistical Staff
[email protected]
The opinions expressed are those of the author and do not necessarily reflect those of the
FDA
Outline
 Definition and motivation
 Biomarkers and Surrogate Endpoints – are
these terms interchangeable?
 Regulatory Issues
 Case Examples
 Conclusion
Surrogate Marker
Working Definition
 A laboratory or physical sign that is used in
therapeutic trials as a substitute for a
clinically meaningful endpoint that is a
direct measure of how a patient feels,
functions, or survives and that is expected
to predict the effect of the therapy
(Temple, 1999)
Regulatory Motivation
 Replace a distal endpoint with a more proximal
one,
– can be measured earlier
– Can be measured more easily or frequently
– Can be measured with higher precision, or less subject
to competing risks
 May be less affected by other treatment modalities
 Reduced sample size requirements ?
 Possibility of faster decision making
Surrogate Endpoints at various phases of
drug development
 Will focus this talk on effect of Surrogate
Endpoints in Phase III clinical trials – a
possible FDA Critical Path Initiative
 Other uses:
– Can be used to integrate data across all phases to build
an evidence base, including validation (Phase II Learn
and Confirm strategy)
– Can be linked with external sources of information - of
disease, of other treatments
– Can be mined for relationships of SEPs to disease,
other markers, patient covariates and treatment as well
as for signs of possible toxicity
Relationship:
Surrogate Endpoint and Disease
 Need to establish strength of relationship of SEP
with the disease, not just a correlation factor
 “A correlate does not a surrogate make” (Fleming)
SEP good
SEP poor
CE good
a
c
a+c
CE poor
b
d
b+d
Total
a+b
c+d
N
 Need high sensitivity SE= a/(a+c) and specificity
SP= d/(b+d)
 Attributable proportion defined as AP=SE/[1-(RR)-1]
should be close to 1, where RR=a(c+d)/[c(a+b)]
Relationship:
Surrogate Endpoint and Treatment
 Evaluate treatment action plans on SEPs, or
identify safety concerns based on SEPs
 Select appropriate metric to characterize treatment
response, the choice depends on biological
considerations as well as statistical
 Rank possibly useful SEPs based on AP
 Use SEPs to study dose response, subgroup of
responders etc.
Biomarker - Definition
 A characteristic that is objectively measured and
evaluated as an indicator of normal biologic or
pathogenic processes or pharmacological
responses to a therapeutic intervention
 Biomarkers can be measurements thought to
be directly related to clinical outcomes
– blood pressure, blood pressure
– total lipids, lipid fractions
– coronary artery occlusion
- RNA viral load
- CD4 count
- tumor size
Biomarker – what to consider
 Effects on Binding
– early effects such as intracellular, membrane or circulating receptor
e.g. binding to ACE of ACE-Is was an early clue that the effects
will be relatively prolonged than their blood level half life
 Effects on activity of an intrinsic or externally induced
molecule
– Effect on an externally induced enzyme, hormone or cytokine is
the effect examined e.g. inhibition of infused isoproterenol as a
measure of beta blockade
 Effect on etiologic agents or anatomical features
– infectious agent
– pathological hallmarks of neurologic disease e.g. arteriosclerotic
plaque structure
Biomarkers & Surrogate Endpoints
- A Conceptual Model
Clinical endpoints
(for Efficacy)
Surrogate
Endpoints
(for Efficacy)
Biomarkers
(for Efficacy)
Establish linkage of
biomarker with
Clinical Endpoint
Biomarkers
(for Toxicity)
Evaluate
Patient Benefit
Conduct provisional
integrated evaluation
Surrogate
Endpoints
(for Toxicity)
Evaluate
Patient Risk
Clinical endpoints
(for Toxicity)
Global
Intervention
Assessment
Biomarkers as Surrogate Endpoints Possible Relationships
Type of
Relationship
Value of the
Biomarker
A. Unreliable
Biomarker of no value
interaction between as a surrogate endpoint
biomarker and the
treatment
intervention
B. The full effect of
the intervention is
observed through
the biomarker
assessment
Biomarker is an ideal
surrogate endpoint
Example
Prostrate-specific
antigen is a useful
biomarker for prostrate
cancer detection but
unreliable as an
indicator of treatment
response.
None known at present
Biomarkers as Surrogate Endpoints Possible Relationships (contd.)
Type of
Relationship
Value of the
Biomarker
Example
C. Intervention affects
the endpoint and
marker independently,
only a proportion of the
treatment effect is
captured by the SEP.
D. Intervention affects
favorably on the marker
but unfavorable on the
well-state and disease
Biomarker has value as
a SEP but explains only
part of the treatment
effect
Most established SEPs
(development of OI
with HIV antivirals and
mortality)
Biomarker is of little
practical use as a SEP
but may have utility in
exploratory studies
PVCs as a biomarker of
fatal arrythmias
following MI (CAST
trials)
Distinction - Biomarkers and
Surrogate endpoints
 Surrogate endpoints are a subset of biomarkers
 Early clue by biomarkers, validation by surrogates
 A biological marker is a candidate for surrogate endpoint if
it is expected to predict clinical benefit (or harm, or lack of
benefit or harm) based on epidemiologic, therapeutic,
pathophysiologic or other scientific evidence
 Need to consider all possible effects
– COX-2 selective NSAIDs treat pain, but cardiovascular
effects?
– TPA establishes blood flow but causes hemorrhage
strokes
Distinction - Biomarkers and
Surrogate endpoints (contd.)
 Surrogate endpoint are primarily endpoints in
therapeutic intervention trials, although sometimes
in natural history or epidemiologic studies
 For a surrogate to be useful, one must specify the
clinical endpoint, class of intervention and
population in which substitution of a biomarker
for clinical endpoint is considered reasonable
Fast track Program
 To facilitate the development and expedite
the review of new drugs that are
– intended to treat serious or life-threatening
conditions
– demonstrate the potential to address unmet
medical conditions
 Granted for a specific indication of a
specific drug/biological product
Scheme to determine Fast Track
No
Not fast
track
Condition serious or
life-threatening?
Yes
Yes Any approved treatment
for the condition?
No
No
Unmet Medical needs?
Yes
Fast track
designation
Accelerated Approval
 21 CFR (314 and 601) Accelerated
Approval Rule, 1992
– Serious or life-threatening illness
– Surrogate or non-ultimate clinical endpoints
– Post-marketing data required to “verify and describe the
drug’s clinical benefit and to resolve remaining
uncertainty as to the relation of the surrogate endpoint
upon which approval was based to clinical benefit, or
the observed clinical benefit to ultimate outcomes.”
Subpart H
 Special section of fast track related to
surrogate endpoints
 Section 112 of the FDAMA of 1997,
Chapter V (21 USC 351)
– provides for definition, designation, and request for such
– … has an effect either on a clinical endpoint or on a surrogate
endpoint that is reasonably likely to predict clinical benefit
– conduct post-approval studies to validate the surrogate endpoint or
otherwise confirm the effect on the clinical endpoint
Regulatory Issues
 Use of SEPs focus on the treatment effect
mediated by a certain pathway, but in reality,
multiple pathways or modalities may exist.
– All anti-hypertensives lower BP but could have
different (better or worse) effects on endpoints (CHF,
renal function, diabetes) because their mechanism of
action are different and multiple
 They have to be comparatively evaluated as well
Four Roles of Surrogate
Endpoints
 Efficient and improved design of trials
 Improved understanding of drug effects
– subgroup differences
-dose &dose interval
– effects over time
-withdrawal effect
– phramaco-dynamic effects
 Efficacy in new settings (e.g. pediatric)
 Support for results of clinical trials
Improve design of Phase II-III
trials
 Effect (magnitude and time course) on an
“etiologic SEP” can help choose dose range and
regimens, titration steps
– for large trials give insight into tolerance, first dose
effects, withdrawal effects that need study
– this is important for “all at once” Phase III studies, seen
substantial efforts to study regimens that would have
had little chance on PK/PD grounds
 Potential role in identifying population more or
less likely to respond (as a baseline covariate)
Better understanding
 Subgroup differences in favorable (or not)
responses
– sensitivity to QT effects in women or group with
inherited QT abnormalities
 potential problems may be avoided (orthostatic
effects, anti-cholinergic effects)
 Better labels (precautions or modified treatment
plan)
 PD interactions
Efficacy in new settings
 Approval is sometimes feasible without new
clinical trials where basic effectiveness is
established and pathophysiology is clear
– ICH E-5 proposes use of PD drug response as a
potential basis for “bridging study” into new regions
– ICH PED guidance discusses PD to bridge adult DR to
pediatric population where disease is similar
 Depends on understanding of the SEP effect to the
clinical effect
Efficacy in new setting
 FDA Guidance: Providing Clinical Evidence of
Effectiveness for Human Drug and Biological
Products
– Efficacy of a different dose, regimen or dosage
form (e.g. post-infarction propranalol)
 Better the understanding of SEP relationship to the
clinical outcome, the better clinical trial design
Case example I - CD4 count as
SEP in HIV trials
 CD4 lymphocyte count widely used and accepted
as a SEP for progression to AIDS
 ZDV approved in 1987 based on 17 weeks
survival
 ddI approved in 1991 based on surrogate endpoint
(CD4) with limited indication (in AZT failures)
 ddC is the first drug approved under accelerated
approval regulation (1992)
 More than 12 other HIV drugs has been approved
under this regulation since then.
Accelerated to Traditional Approval:
Time and Endpoints
CD4
ddI
CD4
ddC
DAVG16 of CD4
CD4, HIV, p24
CD4 and HIV RNA
DAVG of HIV, DP
DAVG CD4, DAVG HIV
Change of CD4 and HIV RNA
DAVG CD4 and HIV RNA
DAVG CD4 and HIV RNA
%<400 for HIV at Week 24
%<400 for HIV at Week 16
%<400 for HIV at Week 24
%<400 for HIV at Week 24
1990 1991
1992
1993
1994
d4T
3TC
SQV
RTV
IDV
NVP
NFV
DLV
EFV
ABC
AMP
LPV
1995
1996
1997
1998
1999
2000
2001
DP or 50% drop of CD4
DP
DP or 50% drop of CD4
DP
DP
Change of HIV, CD4; DP
Survival
Time to HIV failure
%<400 for HIV Week 48
Time to HIV failure
Time to HIV failure
Time to HIV failure
Time to HIV failure
Time to HIV failure
Endpoints used in approval of
Anti-HIV Drugs
CD4
Didanosine(ddI)
Dideoxycytidine (ddC)
CD4
DAVG16 of CD4
CD4, HIV, p24
CD4 and HIV RNA
DAVG of HIV, DP
DAVG CD4, DAVG HIV
Change of CD4 and HIV RNA
DAVG CD4 and HIV RNA
DAVG CD4 and HIV RNA
%<400 for HIV at Week 24
%<400 for HIV at Week 16
%<400 for HIV at Week 24
%<400 for HIV at Week 24
1990
1991
1992
1993
1994
stavudine (d4T)
lamivudine (3TC)
Saquinavir mesylate
Ritonavir
Indinavir sulfate
Nevirapine
Nelfanivir mesylate
Delavirdine mesylate
Efavirenz
Abacavir
Amprenavir
Lopinavir
1995
1996
1997
1998
1999
2000
2001
DP or 50% drop of CD4
DP
DP or 50% drop of CD4
DP
DP
Change of HIV, CD4; DP
Survival
Time to HIV failure
%<400 for HIV Week 48
Time to HIV failure
Time to HIV failure
Time to HIV failure
Time to HIV failure
Time to HIV failure
Endpoints used for
Anti-Viral approvals
Accelerated
Time
Endpoint
Change in CD4
< 1995
count or timeaveraged change
of CD4 (DAVG)
1995-1998
HIV RNA load
(change from
baseline, DAVG,
% < threshold)
> 1998
HIV RNA < 400
and/or <50 copies
/ML
Traditional
Time
Endpoint
Clinical
< 1997
progression
> 1997
HIV RNA % <
400 copies /mL
or time to
virologic failure
Approaches to a better surrogate
 Week 16 vs. Week 24 for HIV RNA
– Week 24 will likely be a better predictor of clinical
outcome than Week 16
– FDA usually ask for Week 24 results in accelerated
approval of HIV drugs.
– Data beyond Week 24 are also requested and reviewed
 Based on the predicted value of the surrogate,
compute what kind of efficacy we will need to
reliably predict a significant and meaningful
clinical outcome at the end for traditional approval
Case Example II: CAST trial
 Cardiac Arrhythmia Suppression Trial (CAST)
evaluated effect of encainide, flecainide and
moricizine on survival of patients who had MI and
had >10 premature ventricular beats per hour
 Reduction in ventricular ectopic contraction used
as a SEP for decreased mortality
 Primary endpoint was death or cardiac arrest with
resuscitation, either of which due to arrhythmia.
CAST trial results
 Unexpected results: encainide and flecainide arms
stopped early : 63 patients died in encainide or flecainide
arm compared to 26 in the placebo arm (p=0.0001).
 After continuing the trial with moricizine as the only active
arm (CASTII), there was excess mortality in moricizine
arm alone (17 deaths in 665 patients) as compared to no
therapy or placebo group (3 deaths in 660 patients). This
study had to be terminated early also.
 Points to the fact that surrogate markers may not always be
a good predictor and have to be validated extensively
before being used in a regulatory setting.
Conclusions
 Collection of information on the SEPs should be
encouraged, it provides additional insight into the
mechanism of action
 It can often provide supportive evidence into
reliability of observed association
 When used as auxiliary information, can provide
improvement in trial design
 Need to be cautious about association and
inferences drawn from it