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On Surrogate Endpoints in HIV Vaccine Efficacy Trials Steven Self, Peter Gilbert, Michael Hudgens FHCRC/UW FDA/Industry Statistics Workshop, Sept 18-19, 2003 “Statistics: From Theory to Regulatory Acceptance”
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Outline 1.HIV Vaccine Trials: Current Status 2.Clinical Endpoints in Vaccine Trials 3.Endpoints in HIV Vaccine Trials 4.A Simulation Approach 1.Goal 2.Approach 3.Example 5.Conclusions/Discussion
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HIV Vaccine Trials: Current Activity Phase I and II trials (ongoing) 27 trials involving ~1,800 participants 16 different vaccine candidates 10 sponsors Phase III trials 1 completed 1 to be completed in Q4 ’03 1 planned to start in ’04 HVTN trials (Ph I, II) starting by Q3 ’04 9 different vaccine candidates 1,453 participants
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HIV Vaccine Trials: Current Results Immune Responses Measurable cellular response in ~50% No broadly neutralizing Ab in sera, mucosa Non-human Primate Trials Amelioration of disease course but no protection from infection upon challenge Body of NHP literature difficult to assess Efficacy No overall efficacy in 1 completed efficacy trial
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HIV Vaccine Trials: Summary Immune correlate of protection unknown Many candidate vaccines but full range of desired immune responses poorly covered Multiple efficacy trials will be required* Plan for long-term, iterative development program* * Klausner et. al. (2003) Science
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Classical Measure of Vaccine Efficacy VE = % reduction in population incidence or morbidity/mortality rate
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Classical Endpoint for Vaccine Efficacy Clinically significant morbidity and mortality Pathogen specificity Standard of care For treatable infections: –Prevent/delay constellation of signs/symptoms sufficient to trigger treatment initiation (save cost/toxicity assoc with treatment) –Interact w/ treatment to improve risk/benefit profile of vaccine/tmt vs tmt alone
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Measures of Vaccine Efficacy* VE = % reduction in population incidence or morbidity/mortality rate VE S = % reduction in population infection rate VE P = % reduction in rate of morbidity/mortality VE I = % reduction in rate of 2 o transmission * Halloran, Longini, Struchiner
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VE: % Reduction in Transition Intensities Uninfected/ Seronegative Infected/ Seropositive Morbidity/ Mortality VE VE S VE P VE I 2 o Transmission
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Endpoints in HIV Vaccine Efficacy Trials –“Infection” Endpoint (A biomarker-based surrogate) Operationally: presence of Ab and detectable HIV RNA Aligned with one primary objective of HIV vaccine Acceptable by all However captures only one aspect of potential vaccine effects on clinical outcomes
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Endpoints in HIV Vaccine Efficacy Trials “Post-infection” Endpoints: Some Issues Long-term FU required for morbidity/mortality endpoints esp with ARV treatment Complicated dynamical process likely dominated by treatment effects Uncertainty of optimal treatment initiation triggers Variability in treatment initiation Analytics –Key biomarker trajectories “dependently censored” by treatment initiation –Conditional vs unconditional analyses –Combination of analyses
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Post-Infection Endpoints: Current Approach Provide treatment within trial –standardized treatment initiation guidelines (e.g. DHHS, UNAIDS) –standardized treatment monitoring/management Develop complementary array of endpoints to cover key aspects of post-infection outcomes –Early Endpoints - pre-ART –Mid-term Endpoints - peri-ART –Long-term Endpoints - post-ART “Reasonable conservatism” for interpretation of vaccine effects on surrogates
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HIV Vaccine Efficacy Trial Endpoints Uninfected/ Seronegative Infected/ Seropositive Treatment Initiation Morbidity/ Mortality Infection Short-term Endpoints: - Pre-ART VL Mid-term Endpoints: - Composite (VL, tmt init) - Biomarker trajectories (VL, CD4) Long-term Endpoints: - vaccine/tmt effects - CD4 - Morbidity/Mortality
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Definition: First event of ART initiation or virologic failure (VL > X cps/ml) Composite endpoint directly tied to clinical events virologic failure places a subject at risk for progression/transmission starting ART exposes a subject to drug toxicities, resistance, loss of future drug options Assess with standard statistical methods (Kaplan-Meier, Cox regression) A Composite Endpoint
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Surrogate vaccine efficacy parameter: VEVL C (T;X) = percent reduction (vaccine vs. placebo) in the risk of the composite endpoint by T months post infection diagnosis X calibrates the magnitude of virologic control (e.g., X = 1,500 copies/ml) T calibrates the durability of virologic control (e.g., use T 18 months) A Composite Endpoint
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Example Analysis of VEVL C (18;X)
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A Numerical Study*: Goal Provide an approach to facilitate the discussion of how to use surrogate endpoints –specific to trial design –specific to particular surrogate endpoints –accommodate statistical uncertainties –accommodate model uncertainties with desired degree of conservatism * Gilbert et al (2003) JID
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A Numerical Study: Approach adopt empirically-based joint model of biomarker process and clinical outcomes as “true” prediction model* modify model to incorporate degrees of “reasonable conservatism” –proportion vaccine effect explained** (attenuate log RR relating surrogate to clinical outcome by f percent ) –selection bias for conditional analyses*** (attenuate observed vaccine effect on surrogate outcome) RCT simulation to identify minimum observed effects on specific surrogate endpoints that would generate 95% prediction intervals for VE parameters exceeding 40%, say * Albert et al (1998) Stat in Med ** Freedman et al (1992) Stat in Med *** Hudgens et al (2003) Stat in Med; Gilbert et al (2003) Biometrics
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Numerical Study: An Example Question: What inference on VEVL C (18;X) “reasonably” predicts a clinically significant VE P ? Numerical study based on the following predictions: from the MACS * : Predicted(VE P ) = VEVL C (18;X) for X 5,000-10,000 cps/ml * Albert et al (1998) Stat in Med
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The numerical study is based on the following hypothetical trial: Hypothetical Efficacy Trial
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A lower 95% confidence bound for VEVL C (18;X) > 50% predicts VE P > 40% with f = 0.375 Prediction of VE P
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Summary/Conclusions Use of surrogate endpoints in HIV vaccine efficacy trials is question of how not whether A framework is proposed to help interpret observed effects on surrogate endpoints that is –specific to particular trial designs/endpoints –captures relevant aspects of magnitude and durability of effect on surrogates –uses available empirical information relating biomarkers to clinical outcomes –is tunable with respect to degree of conservatism w/r/t use of empirical information –flexible to evolve with development program
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Summary/Conclusions HIV vaccines showing strong and durable effects on post-infection endpoints should be licensed –use of standardized ART guidelines important –use simulation studies to assist in building agreement about defining “sufficiently strong” and “sufficiently durable” –design trials to detect significant levels of either VE S or VEVL C (T;X) –use supporting data on other endpoints Long-term follow-up needed –for assessing VE and VE P directly –better understanding of surrogate endpoints
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