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Analyzing Trials with Active Control Arms

Analyzing Trials with Active Control Arms. Non-Inferiority Analyses David Harrington Dana-Farber Cancer Institute. Disclaimers…. No financial support from sponsor Expenses paid by FDA as a member of ODAC

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Analyzing Trials with Active Control Arms

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  1. Analyzing Trials with Active Control Arms Non-Inferiority Analyses David Harrington Dana-Farber Cancer Institute

  2. Disclaimers… • No financial support from sponsor • Expenses paid by FDA as a member of ODAC • Will not discuss in detail or evaluate the analyses in the application, but will use some data for context

  3. Trials in Application

  4. Main Statistical Issue in Analysis of STAR • Application contains non-inferiority (NI) analysis of Raloxifene vs Tamoxifen in STAR trial. • Primary endpoint is invasive breast cancer • Raloxifene is test agent • Tamoxifen is an ‘active control’ • Analysis of active control trials uses information outside of current trial to infer effect of a study drug (raloxifene) vs placebo in absence of a direct comparison • See Rothmann et al. (2003), Temple & Ellenberg (2000), many others… • What questions should be asked about NI analysis?

  5. Tamoxifen vs Placebo: NSABP P1 Trial Subset of 7,998 Women  50 years old Favors Tamoxifen Favors placebo RR = 0.47 (0.33 - 0.66) Interpretation: T reduces the rate of invasive breast cancer incidence on placebo by 53% (confidence interval 34% to 67%) 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Relative Risk for Invasive Br Ca: Tamoxifen / Placebo

  6. Favors Tamoxifen Favors Placebo 2.2 2.6 2.4 2.0 1.6 1.8 0.8 1.0 1.2 1.4 0.6 Tamoxifen vs Placebo: NSABP P1 Trial Subset of Women  50 years old RR = 2.12 (1.52 - 3.03) Interpretation: P increases the rate of invasive breast cancer incidence compared to Tam by 112% (confidence interval 52% to 303%) Relative Risk for Invasive Br Ca: Placebo / Tamoxifen

  7. Potential Designs for Evaluating Raloxifene Raloxifene R A N D O M I Z E STAR designed as superiority trial R vs T 85% power if RR (R/T) < 0.67 95% power if RR (R/T) > 1.56 Tamoxifen Placebo Observed RR = 1.02 Application has non-inferiority analysis of STAR

  8. Tamoxifen vs Placebo: NSABP P1 Trial Subset of Women  50 years old Favors Placebo Favors Tamoxifen RR = 2.12 (1.52 - 3.03) NI margin: 50% of Active control effect retained. 56% increased risk on P RR = 1.56 1.84 1.28 2.2 2.6 2.4 2.0 1.6 1.8 0.8 1.0 1.2 1.4 0.6 Relative Risk for Invasive Br Ca: Placebo / Tamoxifen

  9. 2.2 2.6 2.4 2.0 1.6 1.8 0.8 1.0 1.2 1.4 0.6 Possible Outcomes of Active Control Trials Favors Test Tx Favors Active Control NI margin: 50% of Active control effect retained. 56% increased risk on P Placebo vs Active Control: RR = 2.12, with C.I. Relative Risk: Test Treatment / Active Control

  10. Goal of Active Control (NI) Analysis • How would test treatment compare to placebo, had placebo been present in the trial? • Estimate effect of T compared to active control (C) in current trial (T vs C) • Use data from previous trials to estimate effect of P vs C, along with a margin of error for that effect • Combine these estimates to evaluate putative effect of T vs P • Sometimes done by estimating the range of percent retention of the P vs C effect consistent with data (confidence interval for NI margin) • If T has fewer side effects than active control, T may be useful even if not as effective as C

  11. Most important issue when evaluating NI analyses…extrapolation • NI analyses are based on one or more previous trials and a current trial and use information gained in potentially different settings. • More careful labeling is helpful… • Current trial: T test treatment, C2 active control, P a putative (unobserved) Placebo • Previous trial(s) C1 the same control, P1 the placebo

  12. Assumptions in NI Analysis • T vs C2 well conducted. • P vs C2 = P1 vs C1 if placebo had been present in current trial (assay sensitivity) • P1 vs C1 effect has not changed since prior trials, or any change can be modeled • Uncertainty in P1 vs C1 effect can be estimated • Both within and between trial variability relevant • P1 vs C1 sometimes estimated from meta-analysis of prior trials. • Clinically relevant non-inferiority margin was specified before analysis • Assumptions all used in inference

  13. Some Questions to ask about NI analyses • Is the claim of NI supported by a biological rationale? • Might the effect of Active Control (vs placebo) have been different in current trial? • Changes in administration of agent • Differences in populations using the drug or in endpoint determination • Has long term follow-up changed the thinking of the value of the active control? • Does the analysis use the best available historical data on active control to estimate both treatment effects and uncertainty in the estimate? • Justification for omitted trials…

  14. Questions… • Is an estimated NI margin clinically relevant? Was it specified in advance of the analysis? • Is a reduced therapeutic effect for the test agent balanced by other benefits? • What is the margin of error (confidence interval) in the estimate of possible loss of efficacy? • Are results consistent across related endpoints? • As in all trials, treatment effects measured in NI analyses are estimates of population effects, not predictions of efficacy for individuals • Is there a clear signal to the treating clinician on when to use the active control vs the new treatment?

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