高血压英文ppt精品课件assessing surrogacy in

Assessing Surrogacy in CKD* Tom Greene, Ph.D. University of Utah *Joint work with Marshal Joffe, Liang Li, Andrew Levey, and Lesley Stevens Concept of Surrogate Endpoint The most relevant clinical outcome may be difficult to use in an RCT because: measurement is costly or invasive long follow-up required large N required A surrogate endpoint is an alternative outcome that is substituted for the true clinical outcome in an attempt to reduce these difficulties Difficult to Evaluate ESRD in Trials of Early CKD Years from ESRD GFR (ml/min/1.73m 2) ESRD 14 12 10 8 6 4 2 Window for feasible RCTs with renal endpoints 0 100 50 0 Past Problems with Surrogate Endpoints Disease Intervention Surrogate Clinical outcome Arrythmia Encainide,Flecainide* Suppressed arrhythmias Increased mortality CHF Milrinone Improved cardiac output Increased mortality Osteoperosis SodiumFluoride Increased bone mineral density More Fractures Change in GFR from Baseline Ramipril Amlodipine Mean (SE) GFR (ml/min/1.73m 2) -12 - 8 - 4 0 4 8 Follow-up Month 0 6 12 24 36 48 Failures of Mean Change in GFR as Surrogate for Renal Endpoints Follow-up Month HR = 0.51, p 0.001 Amlodipine Ramipril 0 10 20 30 40 0 12 24 36 48 60 Incidence of ESRD or Death Endpoints for Progression of CKD Target Clinical Endpoint: Time-to-ESRD ( Death) Time-to-Event Surrogate Endpoints: 50% reduction in GFR or ESRD ( Death) ? Doubling of serum creatinine (SCR) or ESRD ( Death) ? Slope-Based Surrogate Endpoints Slope of GFR vs. time ? Slope of estimated GFR (from SCR) ? Proteinuria Based Surrogate Endpoints ? Statistical Approaches to Validation of Surrogate Endpoints Individual level association Prentice criterion Molenberghs et al, 2000 2005 Trial-Level Approach Ideal Hypothetical Example Treatment effect on % UP Treatment effect on ESRD (Log RR) Points represent estimated treatment effects in different RCTs Trial-Level Approach Ideal Hypothetical Example Points represent estimated treatment effects in different RCTs Treatment effect on % UP Treatment effect on ESRD (Log RR) UP for new trial Trial-Level Approach Real Example* * Burzykowski, JRSS A, 2004 Incorporation of Trial Level Can Obtain Direct & Indirect Effect In Broader Framework Trial level approach formulated under “causal association framework” just relates treatment effects on T to treatment effects on UP. No need to assume UP is directly on causal pathway. Under intermediate variable model, trial level approach estimates direct and indirect effects associated with UP even in presence of uncontrolled confounders Limits of Trial Level Approach Logic for extrapolation to new studies works best if new study is similar to prior studies (e.g., best for “me-too” studies) Treatment effect on % UPTreatment effect on ESRD (Log RR) UP for new trial Limits of Trial Level Approach Requires significant heterogeneity between studies in “true” treatment effects on UP Requires “effect modification” Opposite of typical situation in meta-analysis Treatment effect on % UPTreatment effect on ESRD (Log RR) UP for new trial Consistent Effects on both UP and Clinical Endpoint Encouraging but Not Convincing from Perspective of Trial-Based Approach Treatment Effect on UP Treatment Effect on T (HR) 0 1 Looking for Heterogeneity Can look for effect modification between and within studies Between interventions: ACE vs. Control CCB vs. Control Low vs. Usual BP Low vs. Usual Protein Immunosuppressive therapies Between patient subgroups Diabetics, Non-diabetics, Transplant recipients Low UP, High UP PKD, Glomerular disease, Hypertensive kidney disease, Interstitial kidney disease Younger, Older Black, white Technical Difficulties for Trial-Level Approach in CKD Huge variation in sample sizes between studies Observed treatment effects on clinical endpoints depend in part of arbitrary study characteristics e.g., distribution of GFR at entry, length of follow-up Variation in measurement of UP Unclear what is best index of UP (e.g., absolute change or % change) CKD-EPI Project Collaboration to analyze large databases of pooled individual-patient data, including most major RCTs of CKD -patients Assess validity of change in proteinuria as a surrogate marker using all three statistical approaches Lesley Stevens to later present very preliminaryresults for ACE/ARB studies Potential Uses of “Validated” Surrogate Endpoints Early phase of development of new interventions Exploratory subgroup analyses Extension of established findings to related patient populations with less severe disease Extension of established findings to related interventions Establish benefit of new interventionsMoreRisky LessRisky Conclusions Use of surrogate endpoints is necessary component of clinical research Statistical formalisms for addressing validity of surrogate endpoints are still developing Two general statistical approaches: Estimate direct & indirect effects under models that attempt to control for all confounding between UP & T Try to take advantage of effect modification to determine if t