Surrogate Endpoints: The Challenges are Greater than they Seem March 7, 2005 Thomas R. Fleming,...

Surrogate Endpoints: The Challenges are

Greater than they Seem

March 7, 2005

Thomas R. Fleming, Ph.D.Professor and Chair of Biostatistics

University of Washington

NIDDK Workshop:

Surrogate Endpoints

• Criteria for Study Endpoints

• A Correlate does not a Surrogate Make

• Validation of Surrogates

• Controversial Issues with AA

Criteria for Study Endpointsin Clinical Trials

• Measurable/Interpretable

• Sensitive

• Clinically relevant ~ Retinopathy, Nephropathy ~ Major hypoglycemic events: Coma/Seizure

Use of Surrogate Endpoints

Treatment Effects on Surrogate Endpoints eg: ~ Oncology: Tumor Burden Outcomes ~ HIV/AIDS: CD4, Viral Load

~ Cardiovascular Dis: B.P., Cholesterol ~ Type 1 Diabetes: HbA1c , C-Peptide

• Establishes Biological Activity

• But Not Necessarily Clinical Efficacy

Surrogate Endpoints





Surrogate Endpoint:Not in Causal Pathway of Disease Process

Disease Surrogate True Clinical Endpoint Endpoint

Causal Pathway

The Surrogate Endpoint is not in the Causal Pathway of the Disease Process.

Disease

Disease

Biomarker Mother-to-Child e.g., CD4 Trans of HIV

HIV Viral Load

Anti-Islet End-Organ Autoantibodies Diabetic

Complications β-Cell Function

• “Correlates”: Useful for Disease Diagnosis, or Assessing Prognosis and Effect Modification• “Valid Surrogates”: Replacement Endpoints

Surrogate True ClinicalEndpoint Endpoint

Intervention

Disease

True Clinical Endpoint

Surrogate Endpoint

Disease

Intervention

Multiple Pathways of the Disease Process

Surrogate True ClinicalEndpoint Endpoint

Intervention

Disease

End-Organ DiabeticComplications HbA1c

Glycemic Control

Disease

Intervention

Multiple Pathways of the Disease Process

CD4 Cell AIDS Events Count & Death

IL-2

Disease

• IL-2: known > 200 CD4 cell count increase

• Unknown whether IL-2 is increasing the levelof functional CD4 cells

• NIH is sponsoring the evaluation of 6000 patients,followed for >5 years, in SILCAAT and ESPRIT

Time

Surrogate True Clinical Endpoint EndpointDisease

Intervention

Interventions having Mechanisms of Action Independent of the Disease Process

Arrhythmia OverallSuppression SurvivalDisease

Intervention

Interventions having Mechanisms of Action Independent of the Disease Process

Surrogate Endpoints





End Stage Renal Disease

Goal: Normalize Hematocrit Values and reduce Death and MI

Patient Distribution & Percent Deaths by Hematocrit %

27-30 30-33 33-36 36-39 39-42

STANDARD DOSE EPOGEN

60%

45%

30%

15%

0%


High Dose EpogenStandard Dose Epogen

R



27-30 30-33 33-36 36-39 39-42


60%

45%

30%

15%

0%


27-30 30-33 33-36 36-39 39-42


HIGH DOSE EPOGEN

• 30% death RR

for 10 pt in hem.

60%

45%

30%

15%

0%

60%

45%

30%

15%

0%

27-30 30-33 33-36 36-39 39-42


27-30 30-33 33-36 36-39 39-42


HIGH DOSE EPOGEN

• 30% death RR

for 10 pt in hem.

• in hematocrit

60%

45%

30%

15%

0%

60%

45%

30%

15%

0%

27-30 30-33 33-36 36-39 39-42


27-30 30-33 33-36 36-39 39-42


HIGH DOSE EPOGEN

• 30% death RR

for 10 pt in hem.

• in hematocrit

• 30% in death RR

60%

45%

30%

15%

0%

60%

45%

30%

15%

0%

27-30 30-33 33-36 36-39 39-42


High Dose EpogenStandard Dose Epogen

R


Besarab et al, NEJM 339:584-590, 1998:“ in incidence of thrombosis of vascular access sites”

How does onevalidate

asurrogate endpoint?

Validation of Surrogate Endpoints

Property of a Valid Surrogate

Effect of the Intervention on the Clinical Endpoint

is reliably predicted by the

Effect of the Intervention on the Surrogate Endpoint

Prentice’s Sufficient Conditions

1. The surrogate endpointmust be correlated with

the clinical outcome

2. The surrogate endpoint must fully capture

the net effect of the intervention on the clinical outcome

Z = 1 : Control ; Z = 0 : InterventionS(t) : Surrogate Endpoint at t

(t | Z) = 0(t) e

(t | Z,S(t) ) = 0(t) eZ + S(t)

Proportion of net intervention effectexplained by the surrogate endpoint:

DeGruttola et al, J Infectious Diseases 175:237-246, 1997

p = 1 -

Meta-analysesare required to explore

the validityof surrogate endpoints

Z = 1 : Control ; Z = 0 : InterventionS(t) : Surrogate Endpoint at t

(t | Z) = 0(t) e

(t | Z,S(t) ) = 0(t) eZ + S(t)

Proportion of net intervention effectexplained by the surrogate endpoint:

DeGruttola et al, J Infectious Diseases 175:237-246, 1997

p = 1 -

HbA1c Major Clinical Glycemic Control Events

• Unintended negative effects

• Alternative beneficial effects

Disease

Intervention

Time

Validation of Surrogate Endpoints

Statistical Meta-analyses of clinical trials data

Clinical Comprehensive understanding of the

~ Causal pathways of the disease process ~ Intervention’s intended and unintended

mechanisms of action

Hazard Ratios for DFS vs Overall Survival

0.5

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3

Disease Free Survival Hazard Ratio

Ove

rall

Su

rviv

al H

azar

d R

atio

Endpoint Hierarchy

• True Clinical Efficacy Measure

• Validated Surrogate Endpoint (Rare)

• Non-validated Surrogate Endpoint that is “reasonably likely to predict clinical benefit”

• Correlate that is solely a measure of Biological Activity

Illustrations of Valid Surrogates

Preventing Mother-to-Child Transmission of HIV when using short course antiretrovirals

~ Prevention of AIDS and Death often occurring within two years

Substantial Sustained Reduction in Blood Pressure when using β-blockers or low dose diuretics

~ Prevention of Fatal and Non-fatal Stroke

Hierarchy for Outcome Measures





Establishing a Level #3 Outcome Measure

• Accurately representing the treatment’s effect on the predominant mechanism through which the disease process induces clinical risks

• Lack of large adverse effects on clinical endpoint not captured by the outcome measure

• Net effect on the clinical endpoint is consistent with what would be predicted by

level of effect on the outcome measure

• Targeted effect on outcome measure sufficiently strong and durable to predict meaningful benefit

Surrogate Endpoints





FDA Oncology Drugs AC: 3/12-13/03

’95-’00: 12 Accelerated Approvals Facts presented to ODAC: Of 12 AA, 8 remain unresolved:

• Average time from AA to Completion of Validation Trial projected to be 10 years

• In one case, sponsor enrolled 8 pts/year

• In 3 cases, Validation Trial indicated minimal treatment benefit


’95-’00: 12 Accelerated Approvals

Disturbing Issues re Validation Trials:• Enrollment difficulties into validation trials

• Cross-ins on the control arm

• Loss of “sense of urgency” by sponsor

• Lack of clear vision for proper process when the validation trial

is not conclusively positive


’95-’00: 12 Accelerated Approvals Facts presented to ODAC: Of 12 AA, 8 remain unresolved:

• Average time from AA to Completion of Validation Trial projected to be 10 years

• In one case, sponsor enrolled 8 pts/year

• In 3 cases, Validation Trial indicated minimal treatment benefit


’95-’00: 12 Accelerated Approvals

Disturbing Issues re Validation Trials:• Enrollment difficulties into validation trials

• Cross-ins on the control arm

• Loss of “sense of urgency” by sponsor

• Lack of clear vision for proper process when the validation trial

is not conclusively positive




• Surrogate Endpoint that is “reasonably likely to predict clinical benefit”

• None of the Above: A Correlate that is solely a measure of Biological Activity

Use of Biological Markers

• As “Correlates”… Disease Diagnosis, or assessing

Prognosis or Effect Modification

• In Screening or Proof of Concept Trials… Primary Endpoint

• In Definitive Trials… Supportive Data on Mechanism of Action

NIDDK Workshop

• Surrogate Endpoints

• The Next Step after the Phase 1

Trial

Development Strategies

After Phase 1: What should be the next step?

~ Phase 2

~ Phase 2B (Intermediate Trial)

~ Phase 3

Why Conduct a Phase 2 Trial?

Obtain improved insights:

• Biological Activity: Proof of Concept• Refinements in dose/schedule• Safety• Improving adherence to interventions• Improving quality of trial conduct

- Timely accrual- High quality study implementation- High quality data, including retention

Development Strategies

After Phase 1: What should be the next step?

~ Phase 2

~ Phase 2B (Screening Trial)

~ Phase 3

The Randomized Phase 2B “Screening Trial”

Illustration: Type 1 Diabetes

Primary Endpoint:

Time to Hypoglycemic Events or

End-Organ Diabetic Complications

Targeted Treatment Effect:

33% reduction in progression rate

Screening Trial Design

Phase 3 Trial Design

-33% 0% 33% 44% 67%

FurtherStudies Positive

-17% 0% 17% 33% 50%Positive

An Illustration of the Useof an Intermediate TrialBefore a Definitive Trial

Surgical Adjuvant Therapyof Colorectal Cancer

5-FU + LevamisoleLevamisoleControl

R

SURGICAL ADJUVANT THERAPYOF COLORECTAL CANCER

Surv

i vin

g, %

0 1 2 3 4 5 6

100 -

80 -

60 -

40 -

20 -

0

Years from randomization

NCCTG Trial

5-FU+LEV n=91Levamisole n=85Control n=86



-33% 0% 33% 44% 67%


-17% 0% 17% 33% 50%Positive


Surv

i vin

g, %

0 1 2 3 4 5 6

100 -

80 -

60 -

40 -

20 -

0


NCCTG Trial



Surv

i vin

g, %

0 1 2 3 4 5 6

100 -

80 -

60 -

40 -

20 -

0


NCCTG Trial Cancer Intergroup Trial

0 1 2 3 4 5 6 7 8 9

100 -

80 -

60 -

40 -

20 -

0




Important Observations

• Confirmatory trials of promising results from Intermediate Trials can be performed successfully

• Confirmatory trials- can reveal true positives (eg, 5-FU+Lev)- can reveal true negatives (eg, Levamisole)


Surv

i vin

g, %

0 1 2 3 4 5 6

100 -

80 -

60 -

40 -

20 -

0


NCCTG Trial Cancer Intergroup Trial

0 1 2 3 4 5 6 7 8 9

100 -

80 -

60 -

40 -

20 -

0




RAZT Labor/Delivery/1 wk to I

NVP Single doses to M/I

Illustration of a Screening Trial with “Compelling” Results: HIVNET 012

• 8/99 Results Lancet 1999; 354: 795-802

MCT of HIV N 6-8 wks 14-16 wks

AZT 302 59 (21.3%) 65 (25.1%)

NVP 307 35 (11.9%) 37 (13.1%)

1p = 0.0014 1p = 0.0003



-33% 0% 33% 44% 67%


-17% 0% 17% 33% 50%Positive

Goals in Development of Diabetes Drugs

• Using Biomarkers to achieve a cost-effective research strategy

• Achieving rapid availability of drugs providing improved benefit-to-risk profile

• Achieving reliable as well as timelyevaluation of both efficacy and safety

of new interventions

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